symptom presentation in myocardial infarction, ambulance … · symptom presentation in myocardial...

Symptom Presentation in Myocardial

Infarction, Ambulance Times and

Prehospital Delay

Linda L. Coventry

RN, DipAppSc, BSc, MS

This thesis is presented for the degree of

Doctor of Philosophy

of The University of Western Australia

School of Population Health

School of Primary, Aboriginal and Rural Health Care

2015

i

Abstract Background

Early prehospital recognition of presenting symptoms of myocardial infarction (MI) is

time-critical because reperfusion and medical therapies improve patient outcomes.

Failure to recognize symptoms of MI may lead to longer delays in both prehospital and

medical care. Some previous studies have identified that women are less likely to

present with chest pain, however, findings from these studies have been inconsistent.

Aims

The aims of this doctoral research were fivefold: (1) to investigate if men and women

present equally with chest pain as a symptom of MI and whether there were sex

differences in other presenting symptoms of MI; (2) to determine if the symptoms

reported during the emergency telephone call, in particular chest pain, and ambulance

response times are the same for men and women with MI; (3) to determine if paramedic

records, compared with hospital medical records, are a reliable source of information

about presenting symptoms of MI and onset-time of symptoms; (4) to compare patient

characteristics from the hospital medical records and patient outcomes for patients

presenting with and without chest pain; and (5) to describe prehospital delay time for

MI patients transported by ambulance and identify patient characteristics and presenting

symptoms which contribute to prehospital delay for MI patients.

Methodology

To address aim 1, a systematic review and meta-analysis were conducted. Aims 2 to 5

were addressed by retrospective cohort studies of patients with an emergency

department (ED) discharge diagnosis of MI, who were transported by ambulance to one

of the seven metropolitan EDs in Perth, between January 2008 and October 2009.

Symptoms of MI were transcribed from audio tapes of the emergency telephone call to

the ambulance service and the text description in the paramedic patient care record

(PCR). To validate the accuracy of the paramedic documentation of presenting

symptoms and symptom onset-time of MI, the patients’ hospital medical records were

reviewed at a single teaching hospital. The following statistical methodologies were

employed: multivariable linear and logistic regression; McNemar tests; kappa and

adjusted kappa statistics, sensitivity, specificity, and positive and negative predictive

values; and Kaplan-Meier curves and Cox regression.

ii

Results

Meta-analysis of 27 studies (1,654,588 patients) showed women with MI had lower

odds (OR 0.63, 95% CI 0.59-0.68) and a lower rate (RR 0.93, 95% CI 0.91-0.95) of

presenting with chest pain than men. Women were significantly more likely to present

with fatigue, neck pain, syncope, nausea, right arm pain, dizziness and jaw pain.

In age-adjusted regression analyses of emergency calls to the ambulance service

(n=1681), women were less likely than men to report chest pain (OR 0.70, 95% CI 0.57-

0.88); and although ambulance times did not differ between men and women with chest

pain, women with chest pain were less likely than men with chest pain to be allocated a

priority 1 (lights and sirens) (OR 0.39, 95% CI 0.18-0.87) ambulance response.

In the comparison of paramedic PCRs with hospital medical records (n=400 pairs of

records), the majority (71.4%) of 21 documented MI symptoms had adjusted Kappa

statistics greater than 0.75, and observed agreement greater than 90%. For the symptom

of chest pain, sensitivity, specificity, positive predictive value and negative predictive

value were all greater than 85%. Where symptom onset-time was recorded in both the

paramedic PCR and the hospital medical record (n=196 pairs of records), it agreed

exactly in 60% of the records, and the times were within 30 minutes in over 80% of the

records.

In the comparison of patient characteristics and survival outcomes for patients who

presented with and without chest pain (n=382), the adjusted odds of presenting without

chest pain were increased for women (OR 1.67, 95% CI 0.99-2.82), and patients aged

70-79 years (OR 4.33, 95% CI 1.50-12.5) and aged over 80 years (OR 7.54, 95% CI

2.81-20.3) compared with patients less than 60 years. The adjusted hazard (median

follow-up time 2.2 years) of presenting without chest pain was not significantly

associated with survival.

For patients with a recorded onset-time (n=829) median delay was 2.2 hours. Decreased

delay was associated with age less than 70 years, presenting with chest pain, and

diaphoresis. Increased delay was associated with being with a primary health care

provider, if the patient was at home, and if the person who called the ambulance was

anyone other than the spouse. For patients with onset-times recorded as word

descriptions (n=174), 37% of patients delayed 1-3 days and 64% of patients described

their symptoms as intermittent and/or of gradual onset.

iii

Conclusions

This doctoral thesis contributes to the evidence about sex differences in symptoms of

MI presentation: women were less likely to present with chest pain and more likely to

present with other symptoms of MI. Women were also less likely to include the

symptom of chest pain in their emergency telephone call to the ambulance service, as

were older patients. Furthermore, it contributes to our knowledge of factors that affect

prehospital delay: older age and presenting without chest pain or diaphoresis were

associated with increased delay. Given that for MI the symptom of chest pain differs

with age, between men and women, and prehospital delay times remain longer than is

recommended, public awareness of symptoms, including education of health

professionals, should be enhanced to reduce time from symptom onset to definitive care.

v

Table of Contents Abstract .............................................................................................................................. i

List of Tables.................................................................................................................. xiii

List of Figures ................................................................................................................. xv

Acknowledgements ....................................................................................................... xvii

Publications and Awards ................................................................................................ xix

Statement of Candidate Contribution ........................................................................... xxiii

List of Abbreviations..................................................................................................... xxv

Chapter 1: Introduction 1

1.1 Background to the Study ..................................................................................... 1

1.2 Context of the Study ........................................................................................... 2

1.2.1 Perth: Geography and Demography ........................................................ 2

1.2.2 The Western Australian Ambulance Service .......................................... 2

1.2.3 The Emergency Call ................................................................................ 3

1.2.4 SJA-WA Communication Officers ......................................................... 4

1.2.5 SJA-WA Paramedics ............................................................................... 4

1.3 Statement of Problem .......................................................................................... 5

1.4 Research Questions ............................................................................................. 6

1.5 Significance of the Study .................................................................................... 6

1.6 Structure of the Thesis ........................................................................................ 7

Chapter 2: Sex Differences in Symptom Presentation in Acute Myocardial

Infarction: A Systematic Review and Meta-analysis 9

2.1 Introduction ......................................................................................................... 9

2.2 Abstract ............................................................................................................... 9

2.2.1 Background ............................................................................................. 9

2.2.2 Methods ................................................................................................... 9

2.2.3 Results ..................................................................................................... 9

2.2.4 Conclusions ........................................................................................... 10

2.2.5 Key Words ............................................................................................ 10

2.3 Background ....................................................................................................... 10

2.4 Methods............................................................................................................. 11

2.4.1 Search Strategy...................................................................................... 11

vi

2.4.2 Inclusion and Exclusion Criteria ........................................................... 12

2.4.3 Quality Assessment ............................................................................... 12

2.4.4 Data Extraction ..................................................................................... 12

2.4.5 Statistical Analysis ................................................................................ 13

2.5 Results ............................................................................................................... 14

2.5.1 Included Studies Characteristics ........................................................... 14

2.5.2 Chest Pain ............................................................................................. 21

2.5.3 Associated Symptoms of AMI .............................................................. 24

2.5.4 Age and Other Adjustments .................................................................. 27

2.5.5 Co-morbidity ......................................................................................... 29

2.5.6 Heterogeneity ........................................................................................ 31

2.5.7 Publication Bias .................................................................................... 31

2.6 Discussion ......................................................................................................... 32

2.7 Limitations of the Review ................................................................................. 33

2.8 Implications for Clinical Practice / Policy ........................................................ 34

2.9 Implications for Future Research ...................................................................... 34

2.10 Conclusion ........................................................................................................ 34

Chapter 3: Methods to Link Data 37

3.1 Introduction ....................................................................................................... 37

3.2 Data Linkage ..................................................................................................... 37

3.3 Data Sources ..................................................................................................... 38

3.3.1 EDIS ...................................................................................................... 38

3.3.2 SJA-WA ................................................................................................ 38

3.3.3 Transcribed Symptoms of MI from the Emergency Telephone Call and

the Paramedic PCR ............................................................................... 39

3.3.4 Mortality Data ....................................................................................... 39

3.3.5 Patient Hospital Medical Record Data .................................................. 39

3.4 The Process of Data Extraction and Merging of the Data ................................ 39

3.5 Data Validation ................................................................................................. 42

3.5.1 Validation of Data Entry of Symptom of MI in the SJA-WA Telephone

call Data ................................................................................................ 42

3.5.2 Validation of the Linked Data Set – EDIS and SJA-WA ..................... 43

3.6 Conclusion ........................................................................................................ 44

Chapter 4: Myocardial Infarction: Sex Differences in Symptoms Reported to

Emergency Dispatch 45

vii

4.1 Introduction ....................................................................................................... 45

4.2 Abstract ............................................................................................................. 45

4.2.1 Background ........................................................................................... 45

4.2.2 Objective ............................................................................................... 45

4.2.3 Methods ................................................................................................. 45

4.2.4 Results ................................................................................................... 46

4.2.5 Conclusion ............................................................................................ 46

4.2.6 Key Words ............................................................................................ 46

4.3 Background ....................................................................................................... 46

4.4 Methods............................................................................................................. 47

4.4.1 Study Setting and Cohort ...................................................................... 47

4.4.2 Statistical Methods ................................................................................ 49

4.5 Results ............................................................................................................... 50

4.5.1 Sex Differences in Chest Pain Reported for Patients with Myocardial

Infarction during the Emergency Telephone Call ................................. 52

4.5.2 Differences in Other Symptoms Reported for Patients with Myocardial

Infarction during the Emergency Telephone Call ................................. 54

4.5.3 Sex Differences in Ambulance Times................................................... 54

4.5.4 Sex Differences in Priority Allocation Total Time from Emergency Call

to Hospital for Each Priority Response ................................................. 57

4.6 Discussion ......................................................................................................... 59

4.6.1 Sex Differences in Chest Pain ............................................................... 59

4.6.2 Sex Differences in Ambulance Times................................................... 60

4.6.3 Sex Differences in Priority Allocation .................................................. 60

4.7 Limitations ........................................................................................................ 61

4.8 Conclusion ........................................................................................................ 62

Chapter 5: Symptoms of Myocardial Infarction: Concordance between Paramedic

and Hospital Records 63

5.1 Introduction ....................................................................................................... 63

5.2 Abstract ............................................................................................................. 63

5.2.1 Background ........................................................................................... 63

5.2.2 Objectives .............................................................................................. 63

5.2.3 Methods ................................................................................................. 64

5.2.4 Results ................................................................................................... 64

5.2.5 Conclusion ............................................................................................ 64

viii

5.2.6 Key Words ............................................................................................ 64

5.3 Background ....................................................................................................... 65

5.4 Methods ............................................................................................................ 66

5.4.1 Setting, Participants and Study Design ................................................. 66

5.4.2 Data Sources ......................................................................................... 66

5.4.3 Data Analysis ........................................................................................ 67

5.5 Results ............................................................................................................... 69

5.5.1 Cohort Characteristics ........................................................................... 69

5.5.2 Symptom Documentation: Paramedic PCR and Hospital Medical

Record ................................................................................................... 69

5.5.3 Chest Pain ............................................................................................. 71

5.5.4 Other Symptoms of MI ......................................................................... 71

5.5.5 Symptom-onset Time: Paramedic PCR and Hospital Medical Record 72

5.6 Discussion ......................................................................................................... 76

5.6.1 Symptom Documentation: Paramedic PCR and Hospital Medical

Record ................................................................................................... 76

5.6.2 Chest Pain ............................................................................................. 77

5.6.3 Other Symptoms of MI ......................................................................... 77

5.6.4 Symptom-onset Time: Paramedic and Medical Record ....................... 77

5.7 Limitations ........................................................................................................ 78

5.8 Conclusions ....................................................................................................... 79

Chapter 6: Characteristics and Outcomes for Myocardial Infarction Patients Who

Present with and without Chest Pain 81

6.1 Introduction ....................................................................................................... 81

6.2 Abstract ............................................................................................................. 81

6.2.1 Background ........................................................................................... 81

6.2.2 Objectives.............................................................................................. 81

6.2.3 Methods ................................................................................................. 81

6.2.4 Results ................................................................................................... 82

6.2.5 Conclusion ............................................................................................ 82

6.2.6 Key Words ............................................................................................ 82

6.3 Introduction ....................................................................................................... 82

6.4 Method .............................................................................................................. 83

6.4.1 Setting and Participants ......................................................................... 83

6.4.2 Study Design and Data Sources ............................................................ 83

ix

6.4.3 Statistical Analysis ................................................................................ 85

6.5 Results ............................................................................................................... 86

6.5.1 Cohort Characteristics ........................................................................... 86

6.5.2 Presenting without Chest Pain .............................................................. 86

6.5.3 Primary PCI or any Cardiac Procedure ................................................. 91

6.5.4 Survival Outcomes ................................................................................ 94

6.6 Discussion ......................................................................................................... 96

6.6.1 Presenting without Chest Pain .............................................................. 96

6.6.2 Primary PCI or any Cardiac Procedure ................................................. 97

6.6.3 Survival Outcomes ................................................................................ 97

6.7 Limitations ........................................................................................................ 98

6.8 Implications for Practice, Research, Policy and Education .............................. 99

6.9 Conclusions ....................................................................................................... 99

Chapter 7: The Effect of Presenting Symptoms and Patient Characteristics on

Prehospital Delay in MI Patients Presenting to ED by Ambulance: A

Cohort Study 101

7.1 Introduction ..................................................................................................... 101

7.2 Abstract ........................................................................................................... 101

7.2.1 Background ......................................................................................... 101

7.2.2 Objectives ............................................................................................ 102

7.2.3 Methods ............................................................................................... 102

7.2.4 Results ................................................................................................. 102

7.2.5 Conclusion .......................................................................................... 102

7.2.6 Key Words .......................................................................................... 102

7.3 Introduction ..................................................................................................... 102

7.4 Methods........................................................................................................... 103

7.4.1 Study Design, Setting and Participants ............................................... 103

7.4.2 Data Sources........................................................................................ 104

7.4.3 Data Analysis ...................................................................................... 104

7.5 Results ............................................................................................................. 105

7.5.1 Characteristics of the Cohort ............................................................... 105

7.5.2 Multivariable Analysis ........................................................................ 110

7.6 Discussion ....................................................................................................... 111

7.7 Strengths and Limitations ............................................................................... 112

7.8 Recommendations for Future Study ............................................................... 113

x

7.9 Conclusions ..................................................................................................... 114

Chapter 8: Discussion 115

8.1 Introduction ..................................................................................................... 115

8.2 Overview of Major Findings ........................................................................... 115

8.3 Strengths of the Study ..................................................................................... 118

8.4 Limitations of the Study ................................................................................. 119

8.5 Implications of Thesis Findings ...................................................................... 121

8.5.1 Implications for Public Health ............................................................ 121

8.5.2 Implications for Professional Practice ............................................... 121

8.6 Areas for Future Research .............................................................................. 122

8.7 Conclusion ...................................................................................................... 123

References 125

Appendices 143

Appendix A: Sex Differences in Symptom Presentation in Acute Myocardial

Infarction: A Systematic Review and Meta-analysis ...................................... 145

Appendix B: Myocardial Infarction: Sex Differences in Symptoms Reported to

Emergency Dispatch ....................................................................................... 161

Appendix C: Symptoms of Myocardial Infarction: Concordance between Paramedic

and Hospital Records ...................................................................................... 171

Appendix D: Characteristics and Outcomes of MI Patients with and without Chest

Pain: A Cohort Study ...................................................................................... 181

Appendix E: The Effect of Presenting Symptoms and Patient Characteristics on

Prehospital Delay in MI Patients Presenting to ED by Ambulance: A Cohort

Study ............................................................................................................... 191

Appendix F: Abstract for Cardiac Society of Australia and New Zealand conference

titled - Sex Differences in Symptom Presentation in Acute Myocardial

Infarction: A Systematic Review and Meta-analysis ...................................... 199

Appendix G: Poster for American Heart Association conference titled - Sex

Differences in Symptoms Reported to Emergency Medical Dispatch in Acute

Myocardial Infarction Patients - Impact on Pre-hospital Delay ..................... 201

Appendix H: Abstract for American Heart Association conference titled - Sex

Differences in Symptoms Reported to Emergency Medical Dispatch in Acute

Myocardial Infarction - Impact on Prehospital Delay .................................... 203

Appendix I: Poster for Paramedics Australasia conference titled - Gender

Differences in Emergency ‘000’ Calls and Ambulance Response for Acute

xi

Myocardial Infarction (AMI) Patients ............................................................ 205

Appendix J: Abstract for Paramedics Australasia Conference titled – Gender

differences in Emergency ‘000’ Calls and Ambulance Response for Acute

Myocardial Infarction (AMI) Patients ............................................................ 207

Appendix K: The University of Western Australia Human Research Ethics

Committee – Ethics Approval ......................................................................... 209

Appendix L: Sir Charles Gairdner Hospital Human Research Ethics Committee –

Ethics Approval .............................................................................................. 211

Appendix M: Reciprocal The University of Western Australia Ethics for Sir Charles

Gairdner Hospital Study ................................................................................. 213

Appendix N: Government of Western Australia Department of Health Human

Research Ethics Committee Conditional Approval ........................................ 215

Appendix O: Government of Western Australia Department of Health Human

Research Ethics Committee Final Approval ................................................... 217

Appendix P: Cohesion – Mysteries of the Heart Continue to Confound our Response

......................................................................................................................... 219

Appendix Q: Australian Doctor - GP Visits Delay Heart Attack Treatment ........... 223

xiii

List of Tables

Table 1: Summary of Characteristics of Included Acute Myocardial

Infarction Studies (ordered alphabetically by the first author)………. 16

Table 2: Newcastle-Ottawa Quality Assessment……………………………… 22

Table 3: Pooled Estimates of the Effect of Sex on Chest Pain and other

Presenting Symptoms in Patients with Acute Myocardial Infarction

(from meta-analyses of individual studies)………………………….. 26

Table 4: Comparison of the Effect of Adjustment for Age and Other

Variables on the Crude Effect Measure in Studies Reporting Sex

Differences in Presenting Symptoms in Patients with Acute

Myocardial Infarction………………………………………………... 28

Table 5: Pooled Estimates of the effect of Sex on Comorbid conditions in

Patients with Acute Myocardial Infarction (from meta-analyses of

individual studies)……………………………………………………. 30

Table 6: Study Flow Chart for Data Extraction and Merging of the Data…….. 40

Table 7: Reasons for Differences between SJA-WA Data and EDIS Data…… 43

Table 8: Sex Differences in the Descriptive Characteristics of the Emergency

Phone Calls for Patients with Myocardial Infarction………………... 52

Table 9: Sex Differences in Symptoms Reported for Patients with Myocardial

Infarction during the Emergency Telephone Call…………………… 53

Table 10: Sex Differences in Ambulance Times for Patients with Myocardial

Infarction who had Chest Pain and those who did not have Chest

Pain…………………………………………………………………... 56

Table 11: Sex Differences in Ambulance Priority Response and Total Time

from Call to Hospital for Patients with Myocardial Infarction who

had Chest Pain and those who did not have Chest Pain……………... 58

Table 12: Formulae to Calculate Statistics……………………………………... 68

Table 13: Prevalence of Symptom Documentation of Myocardial Infarction:

Paramedic PCR and Hospital Medical Record………………………. 71

Table 14: Observed and Chance Agreement, Kappa and PABAK Statistic of

Symptom Documentation of Myocardial Infarction: Paramedic PCR

and Hospital Medical Record………………………………………... 73

Table 15: Sensitivity, Specificity, PPV and NPV of Symptom Documentation

of Myocardial Infarction: Paramedic PCR and Hospital Medical

xiv

Record (hospital medical record was considered the gold standard)... 74

Table 16: Characteristics of Patients with Myocardial Infarction by Clinical

Presentation: No Chest Pain Compared with Chest Pain……………. 89

Table 17: Process of Care and Outcomes of Patients with Myocardial

Infarction by Clinical Presentation: No Chest Pain Compared with

Chest Pain……………………………………………………………. 90

Table 18 Main Symptoms for Patients without Chest Pain………………….. 90

Table 19: Odds Ratio Estimates (from unadjusted and adjusted logistic

regression analyses) of the Associations between Patient

Characteristics and Myocardial Infarction with No Chest Pain……... 92

Table 20: Odds Ratio Estimates from Multiple Logistic Regression Analysis

of the Associations between Patient Characteristics and Having a

Primary PCI or a ‘Cardiac Procedure’……………………………….. 93

Table 21: Hazard Ratio Estimates (from unadjusted and adjusted Cox

regression analyses) for Characteristics Associated with Myocardial

Infarction without Chest Pain………………………………………... 95

Table 22: Characteristics of the Sample (n=829), and Median Prehospital

Delay…………………………………………………………………. 107

Table 23: Multivariable Linear Regression Log Delay Time in Minutes………. 110

Table 24: Categorised Time Intervals from Non-Numeric Symptom Onset-

Times and Relationship with Intermittent or Gradual Onset of

Symptoms (yes/no)…………………………………………………... 111

xv

List of Figures

Figure 1: Flow Diagram of Search Results and Study Selection………………….. 15

Figure 2: Forest Plot of Studies Using OR in Comparing Chest Pain as a

Presenting Symptom of AMI in Women and Men (in alphabetical

order)……………………………………………………………………. 23

Figure 3: Forest Plot of Studies Using RR Comparing Chest Pain as a Presenting

Symptom of AMI in Women and Men (in alphabetical order)…………. 24

Figure 4: Funnel Plot for the Pooled OR of Chest Pain…………………………… 32

Figure 5: Study Flow Diagram……………………………………………………. 51

Figure 6: Boxplot Showing Sex Differences in Times for Each Component of

Prehospital Time for Men and Women (n=1681)………………………. 55


Figure 8: Flow Diagram of Symptom-onset Time: Paramedic PCR and hospital

Medical Record…………………………………………………………. 75

Figure 9: Symptom-onset Time Difference (minutes): Paramedic PCR and

Hospital Medical Record, n = 196………………………………………. 76


Figure 11: Kaplan-Meier Survival Plot for Patients with and without Chest Pain…. 94

Figure 12: Study Flow Diagram…………………………………………………... 106

xvii

Acknowledgements

Completing this study has been a personal journey of learning, facing challenges,

stresses and, importantly, many rewarding experiences. The final thesis would not have

been possible without the support, encouragement and guidance of many people who

were instrumental in assisting me to achieve my goals.

Thanks must go to my supervisory team: Associate Professor Alexandra Bremner,

Professor Judith Finn, Assistant Professor Teresa Williams, and Professor Antonio

Celenza. I wish to extend my sincere gratitude to Alex, without whom this thesis would

not exist. I am forever grateful for your unwavering support and encouragement and I

have benefited from your professionalism, knowledge and wisdom. Judith without your

early guidance and encouragement I would never have commenced this thesis. Your

insight, invaluable suggestions and professional supervision along this journey have

been appreciated. Teresa and Tony thank you for your comments, support, constructive

feedback, and critical review. My sincere thanks go to Professor Ian Jacobs who was

influential especially in the early stages of this thesis. Ian passed away before

completion of this thesis. I recognise Ian’s support and contribution.

This thesis could not have been completed without the support and cooperation of the St

John Ambulance (Western Australian) Service and the Department of Emergency

Medicine of The University of Western Australia. Thanks go to Ms Lorraine Salo and

Dr Nick Gibson for access to data. Nick I appreciate your initial help with syntax and I

now consider you a colleague, a friend, and a mentor. I also acknowledge the financial

support of the National Health and Medical Research Council for the Postgraduate

Research Scholarship and the Nursing and Midwifery office, Department of Health,

Government of Western Australia for the Academic Support Grant. These scholarships

allowed me the privilege of being able to study full-time.

I extend my gratitude to my work colleagues in the Centre for Nursing Research and

Roz Jaworski for their support, rapport, humor, and encouragement throughout the

highs and lows of this rollercoaster ride. To all my friends who stood on the sidelines

cheering me on, I was so grateful you stopped asking when I would finish.

Family support is a vital element in achieving a PhD. I give special thanks to my mum

xviii

and my sister for encouraging me to keep going and assisting me in caring for my young

children. To my amazing Mum, how I valued all your help with house chores, washing,

ironing and school pick-up. To my children Caleb, Sam, and Matthew, most of the time

you probably did not know where or what mummy was doing. The most important

person who has coped with all the emotions of this experience is my partner Steve. His

belief in me never faltered, his patience and willingness to care for our children and run

our home has been a massive sacrifice. Your unwavering support and endless patience

can never be matched by mere words written on this page. I can honestly say I would

never have finished this thesis without you.

xix

Publications and Awards

The following papers published in peer reviewed journals resulted from this study:

1. Coventry LL, Finn J, Bremner AP. Sex differences in symptom presentation in

acute myocardial infarction: A systematic review and meta-analysis. Heart &

Lung. 2011;40:477-491.1

See Appendix A, manuscript reprinted with permission from Elsevier. Available from

http://www.sciencedirect.com/science/article/pii/S0147956311002706

DOI: 10.1016/j.hrtlng.2011.05.001

2. Coventry LL, Bremner AP, Jacobs IG, Finn J. Myocardial Infarction: Sex

differences in symptoms reported to Emergency dispatch. Prehospital

Emergency Care. 2013;17:193-202.2

See Appendix B, manuscript reprinted with permission from Routledge, Taylor &

Francis Group. Available from http://informahealthcare.com

DOI:10.3109/10903127.2012.722175

3. Coventry LL, Bremner AP, Williams TA, Jacobs IG, Finn J. Symptoms of

Myocardial Infarction: Concordance between Paramedic and Hospital Records.

Prehospital Emergency Care. 2014;18:393-401.3

See Appendix C, manuscript reprinted with permission from Routledge, Taylor &

Francis Group. Available from

http://informahealthcare.com.ezproxy.ecu.edu.au/doi/pdf/10.3109/10903127.2014.8910

64 DOI: 10.3109/10903127.2014.891064

4. Coventry LL, Bremner AP, Williams TA, Celenza A, Jacobs IG, Finn J.

Characteristics and outcomes of MI patients with and without chest pain: A

cohort study. Heart, Lung and Circulation. 2015; xx: 1-10.4

See Appendix D, manuscript published with permission from Elsevier. Available from

http://ac.els-cdn.com.qelibresources.health.wa.gov.au/S1443950615000530/1-s2.0-

http://www.sciencedirect.com/science/article/pii/S0147956311002706

http://informahealthcare.com/



http://ac.els-cdn.com.qelibresources.health.wa.gov.au/S1443950615000530/1-s2.0-S1443950615000530-main.pdf?_tid=ab9f368e-ee11-11e4-b56a-00000aacb362&acdnat=1430272219_86a53ba75d68070de88c29c22a101180

xx

S1443950615000530-main.pdf?_tid=ab9f368e-ee11-11e4-b56a-

00000aacb362&acdnat=1430272219_86a53ba75d68070de88c29c22a101180

DOI: 10.1016/j.hlc.2015.01.015

5. Coventry LL, Bremner AP, Williams TA, Celenza A. The effect of presenting

symptoms and patient characteristics on prehospital delay in MI patients

presenting to ED by ambulance: A cohort study. Heart, Lung and Circulation.

2015; xx: 1-8.5

See Appendix E, manuscript published with permission from Elsevier. Available from

http://ac.els-cdn.com.qelibresources.health.wa.gov.au/S144395061500164X/1-s2.0-

S144395061500164X-main.pdf?_tid=a07fe7b6-ee12-11e4-bd6d-

00000aacb362&acdnat=1430272629_1e465cd168275493209f655f3e9729b5

DOI: 10.1016/j.hlc.2015.02.026

Awards and recognition

During this study the student received:

• National Health Medical Research Council Post Graduate PhD Scholarship (30

June 2008 to 28 December 2011),

• Cardiac Society of Australia and New Zealand, Finalist in Best Nursing

Presentation, Perth, Australia. “Sex differences in symptom presentation in acute

myocardial infarction: a systematic review and meta-analysis.” 2011

• Paramedics Australasia, Finalist in Best Poster Award, Sydney, Australia.

“Gender differences in emergency ‘000’ calls and ambulance response for acute

myocardial infarction patients.” 2011

• Young Investigators Award, Sir Charles Gairdner Hospital, Perth Western

Australia. “Sex differences in symptom presentation in acute myocardial

infarction: a systematic review and meta-analysis.” 2011

• Academic Research Grant, The Nursing and Midwifery Office, Western

Australia, 2014



http://ac.els-cdn.com.qelibresources.health.wa.gov.au/S144395061500164X/1-s2.0-S144395061500164X-main.pdf?_tid=a07fe7b6-ee12-11e4-bd6d-00000aacb362&acdnat=1430272629_1e465cd168275493209f655f3e9729b5



xxi

Conference presentations

Oral presentations

Coventry LL, Finn J, Bremner AP. Sex differences in symptom presentation in acute

myocardial infarction: A systematic review and meta-analysis. Population Health

Postgraduate Society, seminar, University of Western Australia, 26 October 2010,

Perth, Western Australia.


myocardial infarction: a systematic review and meta-analysis. Young Investigators

Award, Sir Charles Gairdner Hospital, October 2011, Perth, Western Australia.


myocardial infarction: a systematic review and meta-analysis. Cardiac Society of

Australia and New Zealand Annual Scientific Meeting 2011, 11 August-14 August

2011, Perth, Western Australia.

Abstract 1


myocardial infarction: A systematic review and meta-analysis. Heart, Lung and

Circulation. 2011;20 Suppl 2: S6.

See Appendix F, abstract available from

http://www.sciencedirect.com.qelibresources.health.wa.gov.au/science/article/pii/S1443

950611003556#

Poster presentations

Coventry LL, Jacobs IG, Bremner AP, Finn J. Sex differences in symptoms reported to

emergency medical dispatch in acute myocardial infarction patient – impact on pre-

hospital delay. Population Health Postgraduate Society, seminar, University of Western

Australia, 8 November 2011, Perth, Western Australia.

Coventry LL, Jacobs IG, Bremner AP, Finn J. Sex differences in symptoms reported to

emergency medical dispatch in acute myocardial infarction patient – impact on pre-

hospital delay. Poster Presentation, American Heart Association Scientific Sessions, 12

November -16 November 2011, Orlando, USA.



xxii

See Appendix G

Abstract 2

Coventry LL, Jacobs IG, Finn J. Abstract 12314: Sex differences in symptoms reported

to emergency medical dispatch in acute myocardial – impact on prehospital delay.

Circulation. 2011;124 Suppl 1

See Appendix H, Abstract available from

http://circ.ahajournals.org.qelibresources.health.wa.gov.au/cgi/content/meeting_abstract

/124/21_MeetingAbstracts/A12314?sid=0dbeebda-54e6-4af5-884d-bf4dc4051a24

Coventry LL, Jacobs IG, Bremner AP, Finn J. Gender differences in emergency ‘000’

calls and ambulance response for acute myocardial infarction patients. Paramedics

Australasia, 5 October- 8 October 2011, Sydney, Australia

See Appendix I

Abstract 3

Coventry, L., Finn, J., Jacobs, I. Gender differences in emergency ‘000’ calls and

ambulance response for acute myocardial infarction patients. Australasian Journal of

Paramedicine. 2011:10:34

See Appendix J, Abstract available on page 34 from

http://ro.ecu.edu.au/cgi/viewcontent.cgi?article=1428&context=jephc

http://circ.ahajournals.org.qelibresources.health.wa.gov.au/cgi/content/meeting_abstract/124/21_MeetingAbstracts/A12314?sid=0dbeebda-54e6-4af5-884d-bf4dc4051a24

http://circ.ahajournals.org.qelibresources.health.wa.gov.au/cgi/content/meeting_abstract/124/21_MeetingAbstracts/A12314?sid=0dbeebda-54e6-4af5-884d-bf4dc4051a24

http://ro.ecu.edu.au/cgi/viewcontent.cgi?article=1428&context=jephc

xxiii

Statement of Candidate Contribution

This thesis contains published work and work prepared for publication, some of which

has been co-authored. The bibliographical details of the work, a description and

estimated percentage of the contribution of each author and where it appears in the

thesis are outlined below.

Publication 1

Coventry LL, (70%), Finn J, (15%), Bremner AP (15%). Sex differences in symptom

presentation in acute myocardial infarction: A systematic review and meta-analysis.

Heart & Lung. 2011;40:477-491.1

Linda Coventry conducted the systematic review of the literature, appraised every

article for quality, extracted data from every eligible study, interpreted the results and

drafted the manuscript. Judith Finn contributed to the conception and critically reviewed

the manuscript. Alexandra Bremner provided statistical advice and critically reviewed

the manuscript. This publication represents Chapter 3 of the thesis.

Publication 2

Coventry LL, (70%), Bremner AP, (15%), Jacobs IG, (5%), Finn J. (10%). Myocardial

Infarction: Sex differences in symptoms reported to Emergency dispatch. Prehospital

Emergency Care. 2013;17:193-202.2

Linda Coventry designed the study, collected and analysed the data, interpreted the

results and drafted the manuscript. Alexandra Bremner provided statistical advice and

critically reviewed the manuscript. Ian Jacobs and Judith Finn contributed to the

conception and critically reviewed the manuscript. This publication represents Chapter

4 of the thesis.

Publication 3

Coventry LL, (70%), Bremner AP, (15%), Williams TA, (5%), Jacobs IG, (5%), Finn J.

(5%). Symptoms of Myocardial Infarction: Concordance between Paramedic and

Hospital Records. Prehospital Emergency Care. 2014;18:393-401.3


xxiv


critically reviewed the manuscript. Teresa Williams, Ian Jacobs, and Judith Finn

critically reviewed the manuscript. This publication represents Chapter 5 of the thesis.

Publication 4

Coventry LL, (70%), Bremner AP, (15%), Williams TA, (3%), Celenza A, (3%), Jacobs

IG, (3%), Finn J. (5%). Characteristics and outcomes of MI patients with and without

chest pain: A cohort study. Heart, Lung & Circulation. 2015; xx:1-10.4



critically reviewed the manuscript. Teresa Williams, Antonio Celenza, Ian Jacobs and

Judith Finn critically reviewed the manuscript. This publication represents Chapter 6 of

the thesis.

Publication 5

Coventry LL, (70%), Bremner AP, (20%), Williams TA, (5%), Celenza A, (5%). The

effect of presenting symptoms and patient characteristics on prehospital delay in MI

patients presenting to ED by ambulance: A cohort study. Heart, Lung & Circulation.

2015; xx: 1-8.5



critically reviewed the manuscript. Teresa Williams and Antonio Celenza critically

reviewed the manuscript. This publication represents Chapter 7 of the thesis.

The thesis is my own composition, all sources have been acknowledged and my

contribution is clearly identified in the thesis. For any work in the thesis that has been

co-published with other authors, all authors have given permission for published and

submitted manuscripts to be included as part of this thesis.

The declaration to this effect is signed by my Coordinating Supervisors and myself.

xxv

List of Abbreviations

ABS

Australian Bureau of Statistics

ACC/AHA American College Cardiologist / American Heart Association ACS Acute Coronary Syndrome AMI Acute Myocardial Infarction AOR Adjusted Odds Ratio CABG Coronary Artery Bypass Graft CAD Coronary Artery Disease CI Confidence Interval CT Computerized Tomography CVD Cardiovascular Disease ECG Electrocardiograph ED Emergency Department EDIS Emergency Department Information System EMS Emergency Medical Service FMC First Medical Contact HCP Health Care Provider HR Hazard Ratio HTN Hypertension ICD-10-AM International Classification of Disease, 10th Revision, Australian

Modification IQR Interquartile Range n Number NOS Newcastle Ottawa Scale NPV Negative predictive Value NSTEMI Non ST Segment Elevated Myocardial Infarction MI Myocardial Infarction OR Odds Ratio PCI Percutaneous Coronary Intervention PCR Patient Care Record PPV Positive Predictive Value RFDS Royal Flying Doctor Service RR Rate Ratio SCGH Sir Charles Gairdner Hospital SD Standard Deviation SJA-WA St John Ambulance – Western Australia SPSS Statistical Package for the Social Sciences STEMI ST Segment Elevated Myocardial Infarction TOPAS The Open Patient Admission System UA Unstable Angina UMRN Unit Medical Record Number WA

Western Australia

1

Chapter 1: Introduction

1.1 Background to the Study

Cardiovascular disease is the leading cause of death among women and men in the

world6 and in Australia.7 In Australia, it causes 31%8 of all deaths and is the most

expensive disease, comprising 12% of direct health care expenditure at over $7,605

million.9 One of the most common types of cardiovascular disease is acute coronary

syndrome (ACS). ACS represents a range of conditions including unstable angina, and

myocardial infarction (MI).

The underlying problem of MI in most cases is a condition called atherosclerosis where

abnormal build-up of fat cholesterol and fibre-like substances called plaque line the

arteries. Plaque causes narrowing of the blood vessels of the heart, which limits the

blood supply, a condition called angina.9 MI occurs when plaque ruptures and causes

thrombosis in the lumen of the coronary artery and completely blocks the blood flow to

the heart muscle. If the clot is not treated, some of the heart muscle will die,9 resulting

in a life-threatening situation, in which the patient may experience severe chest pain,

arrhythmias, heart failure or sudden death.9

A person who is having a MI (often referred to as a ‘heart attack’) is commonly

believed to present with a sudden onset of crushing, central chest pain, which causes

them to clutch their chest and collapse.10 This “Hollywood-like” portrayal of a MI does

indeed occur, but not in all cases and possibly less so in older patients and female

patients. Symptoms of MI may also include arm, shoulder, neck, jaw, abdominal and

back pain; shortness of breath; sweating; syncope and collapse; and nausea and

vomiting.

Minimising the time from onset of symptoms to definitive care (coronary artery

revascularisation) has consistently been shown to reduce both patient mortality and

damage to the heart muscle.11-15 Patient delay in recognising the symptoms of MI and

appropriately responding (activating emergency services such as calling “000” for an

ambulance) account for a major component of the delay from symptom onset to

definitive care. International and national public education campaigns16,17 have

attempted to reduce this patient delay by stressing the importance of responding

2

appropriately to chest pain. However, this may not be sufficient, as research has shown

that as many as one in three women and one in four men18 do not experience chest pain

and little is known about the characteristics of MI without chest pain.

The diagnosis of a MI is based on a combination of clinical symptoms,

electrocardiograph changes, elevation of cardiac biomarkers e.g., troponin and creatine

kinase-MB19 and in fatal cases, autopsy findings.20 The Australian Heart Foundation21

recommends, if you have chest pain or other warning signs of a heart attack that are

severe, get worse quickly, or last 10 minutes, you need to get help fast, and make an

emergency telephone call by dialling triple zero (000) immediately. Current Australian

guidelines22 to reduce delay to reperfusion therapy for patients with ST-elevation MI

recommend ambulance triage and early activation of the catheterisation laboratory. In

addition, international guidelines23 recommend emergency medical services perform a

12-lead electrocardiograph at the site of first medical contact and recommend

emergency medical services transport the patient to a percutaneous coronary

intervention capable hospital. The ideal first medical contact-to-device time system goal

should be less than 90 minutes.24

1.2 Context of the Study

1.2.1 Perth: Geography and Demography

The land area of Australia is almost the same as that of the United States (excluding

Alaska) and about 50% greater than the area of Europe (excluding the former Union of

Soviet Socialist Republic).25 Western Australia (WA), the largest state in Australia,

comprises the western third of the continent. In 2014, the population of WA was

estimated at 2.57 million - approximately 11% of Australia’s population.26 Perth, the

capital of WA, contains over three quarters (79%) of the state’s total population.27

1.2.2 The Western Australian Ambulance Service

St John Ambulance WA (SJA-WA) covers the largest area of any single ambulance

service in the world – 2,525,500 square kilometres. SJA-WA is the sole provider of

emergency road ambulance services in WA. During 2012/13, SJA-WA received an

average of 1441 emergency calls per day and dispatched more than 190,000 ambulance

cases in the Perth metropolitan area.28,29

3

During the period of this study (January 2008 to October 2009), SJA-WA provided

emergency ambulance services to the greater Perth metropolitan area that extended from

Two Rocks, 63 km (39 miles) north, to Port Kennedy, 56 km (35 miles) south, and

Wundowie, 71 km (44 miles) east, of the city centre.30 This area had 24 ambulance

centres: 21 were staffed by approximately 500 paramedics and patient transport officers;

and three were staffed by volunteer ambulance officers. The metropolitan fleet consisted

of approximately 90 ambulances and 15 patient transport vehicles.28

SJA-WA, a not-for-profit-organisation, generates funds through the provision of

ambulance services as a ‘user-pays’ organisation. Private health funds provide insurance

against ambulance fees. SJA-WA provides these services under a contract with the

Department for Health, but operates independently. Funding is also provided through

grants from supporters such as Lottery West, and from business activities; for example,

industrial paramedical services and first aid training.28

1.2.3 The Emergency Call

Emergency assistance from the ambulance in Perth is accessed by dialing triple zero

(000). Calls are answered by an operator who asks the caller whether the emergency

requires “police, fire or ambulance.” Calls requesting an ambulance are immediately

transferred to a communications officer at the Ambulance Operation Centre located in

Belmont, Perth. The communications officer asks vital emergency call information and

allocates a priority to the call, as outlined below:

• Priority 1 represents a ‘potential for life to be at risk’ and entails a lights and

sirens ambulance response. Types of calls in this category are for patients with

chest pain and/or shortness of breath, unconscious patients, direct transfers to a

cardiac catheter laboratory, motor vehicle and industrial accidents, and childbirth.

The call is dispatched to the closest available ambulance and the response time to

the scene from the time the call is received by the ambulance service should be

<15 minutes for 90% of cases.

• Priority 2 represents ‘no immediate threat to life’. This category includes calls for

patients who have a medical problem or accident, but there is no immediate threat

to life. The call is dispatched to the most appropriate ambulance, and the response

time to the scene from the time the call is received by the ambulance service

4

should be <25 minutes for 90% of cases.

• Priority 3 includes the Royal Flying Doctor Service (RFDS) transfers and rescue

tasks. Ambulances need to be on time for the RFDS, and the call is dispatched to

the next available ambulance, taking into consideration appropriate paramedic

skill levels. The response time to the scene from the time the call is received by

the ambulance service should be <60 minutes for 90% of cases.

The communications officer takes details of the call using a computer aided dispatch

system which provides comprehensive geographical and incident information.28 The

computer aided dispatch system automatically records the time the call was received;

the time the call was dispatched to the ambulance; and the times the ambulance arrived

on the scene, departed the scene, and arrived at the hospital.

1.2.4 SJA-WA Communication Officers

At the time of the study, SJA-WA communications officers completed a two-week in-

house training course in dispatch and prioritising ambulance calls. The communications

officers were not medically trained and they followed written in-house protocols which

directed them to ask a series of scripted questions to establish location of the incident,

phone number of the caller, chief complaint, and other complaint-specific questions.

The American terminology for SJA-WA ‘communication officer’ is a ‘dispatch officer’

and these terms are used interchangeably in this thesis.

1.2.5 SJA-WA Paramedics

Training to become a SJA-WA paramedic in WA requires completion of a Bachelor of

Science (Paramedical Science) degree and can be accomplished in four years. After

successful completion of the first year of training, students are employed by SJA-WA as

student ambulance officers. During the next two years of training, at SJA-WA and

Curtin University, students work full time and undertake study in specially allocated

blocks or by distance education. On passing all course work and completing the on-road

requirements, the student ambulance officer completes a further 12 month internship

under the guidance of senior paramedics before graduating as a paramedic.28

5

1.3 Statement of Problem

The emergency ambulance is usually the quickest mode of transport to hospital, and

paramedics are equipped to treat life-threatening cardiac arrhythmias if they occur.

Patients base their decision to make an emergency call on the symptoms they

experience, and these symptoms are critical in determining pre-hospital and emergency

department triage.

The research questions addressed in this thesis evolved as the study progressed.

Initially, although previous reviews1,18 of sex differences in symptoms of MI had found

that presenting without chest pain was more common in women than in men, findings

about sex differences in symptoms have been inconsistent and meta-analysis had not

been conducted. Also, no studies were found that investigated sex differences in

symptoms of MI reported during the emergency telephone call to the ambulance

service.

After completing the study of sex differences in symptoms of MI during the emergency

phone call, it was realised that both men and women may not report chest pain as a

symptom of their MI. This finding led to the subsequent research question about what

are the characteristics of presenting without chest pain. However, to answer this

question it was necessary to extract patient comorbidity and reperfusion data from the

hospital medical record. When reviewing the hospital medical record the accuracy of

the paramedic documentation of MI symptoms and symptom onset-time was also

validated. No studies were found in the literature that had investigated the accuracy of

paramedic documentation of MI symptoms.

After validating the accuracy of paramedic documentation and extracting the patient

comorbidity data, the characteristics associated with presenting with and without chest

pain and survival outcomes could be investigated. Studies in the literature reporting

characteristics associated with and without chest pain and survival outcomes have also

been inconsistent.31-33

As there were no recent Australian published studies that investigated the effect of

symptoms and patient characteristics on prehospital delay, the time from symptom-

onset to arrival in the ED, was the focus of the final research question. This information

is important as identification of variables associated with prehospital delay may lead to

6

interventions that succeed in shortening delay time.

Thus, in summary, the statement of problem is that there were no existing published

meta-analyses of sex differences in MI presentation, no studies that reported sex

differences in the emergency telephone call, and no studies that investigated the

accuracy of paramedic documentation of MI symptoms. Furthermore, the findings from

studies that reported patient characteristics and survival outcomes associated with

presenting with and without chest pain were inconsistent, and there were no recent

Australian studies of prehospital delay.

1.4 Research Questions

1. Do men and women equally present with chest pain as a symptom of MI

and are there sex differences in other presenting symptoms of MI?

2. Are the symptoms, in particular chest pain, reported during the emergency

telephone call to SJA-WA and ambulance response times, the same for men

and women with MI?

3. Are paramedic records a reliable source of information about presenting

symptoms of MI and onset-time of symptoms compared with the

documentation in the hospital medical record?

4. Are patient characteristics and patient outcomes (survival and hospital

discharge diagnosis) of patients presenting with and without chest pain the

same?

5. What is the prehospital delay time for MI patients transported by

ambulance, and what are the patient characteristics and presenting

symptoms which contribute to prehospital delay?

1.5 Significance of the Study

Correct recognition of MI symptoms in the prehospital environment is crucial for the

ambulance dispatcher to allocate a priority 1 (lights and sirens) ambulance response.

Early symptom recognition of MI reduces patient delay in seeking treatment, ensures

timely diagnosis and definitive care. Early presentation and coronary revascularisation

have consistently been shown to reduce morbidity and mortality.14,15

Identifying sex differences and other patient characteristics associated with the

7

symptoms of MI, and the patient characteristics associated with prehospital delay, may

better inform future public health campaigns aimed at decreasing delay. This study is

important because time from onset of symptoms of MI to arrival at the hospital

continues to be far too long to achieve optimal benefit from reperfusion therapy in the

majority of cases.

1.6 Structure of the Thesis

The regulations of The University of Western Australia34 provide the option for

candidates for the Degree of Doctor of Philosophy to present their thesis as a series of

manuscripts which have been published in refereed journals, manuscripts that have been

submitted for publication but not yet accepted, or manuscripts that could be submitted.

This thesis is presented as a combination of published manuscripts and supporting text

description. As such, there is some repetition particularly in the Background and the

Methods sections. Also, there are minor variations in abbreviations and the use of

Australian English and American English throughout. An overview of each chapter

follows.

Chapter 2 is the Author’s Original Manuscript published in the Heart & Lung journal,

and it reports the findings of the systematic review and meta-analysis.1 This Chapter

contains the majority of the literature review for the study. The literature that has been

published post publication of this manuscript is updated in Chapter 8.

Although methods are briefly explained in each manuscript, Chapter 3 has been

included to expand on this information and provide an overview of the data sources

used and the linkage of the data. Chapter 4 is the Author’s Original Manuscript,

published in Prehospital Emergency Care journal, which outlines the sex differences in

symptoms reported to ambulance dispatch and ambulance times for patients with MI.2

This retrospective cohort study reviewed the emergency telephone call of all adult

patients with an ED discharge diagnosis of MI transported by SJA-WA to one of seven

Perth metropolitan EDs between January 2008 and October 2009.

Chapter 5 is the Author’s Original Manuscript published in Prehospital Emergency Care

journal. It reports the concordance of the symptoms and symptom-onset time

documented in the paramedic patient care record with those in the hospital medical

8

record for MI patients.3 This study was conducted at a single teaching hospital in Perth,

between January 2008 and October 2009.

Chapter 6 is the Author’s Original Manuscript, published in Heart, Lung and

Circulation, and it reports the characteristics and outcomes of MI patients with and

without chest pain.4 This study was conducted at a single teaching hospital in Perth,

between January 2008 and October 2009.

Chapter 7 is the Author’s Original Manuscript, published in Heart, Lung and

Circulation.5 This study describes the prehospital delay time of all adult patients with an

ED discharge diagnosis of MI transported by SJA-WA to one of seven Perth

metropolitan EDs between January 2008 and October 2009.

In the final chapter, Chapter 8, the major findings of the study are discussed, the

literature published post each publication is reviewed, and limitations of the study are

described. Recommendations for policy, practice and further research are made and

final conclusions are drawn.

9

Chapter 2: Sex Differences in Symptom Presentation in

Acute Myocardial Infarction: A Systematic Review and

Meta-analysis

2.1 Introduction

This chapter is the Author’s Original Manuscript published in Heart & Lung, 2011;

40:477-491 (Appendix A).1 The manuscript reports a systematic review and meta-

analysis of sex differences in symptom presentation of acute MI. The process adhered to

the Meta-analysis of Observational Studies in Epidemiology study guidelines.35 This

chapter aims to answer the first research question posed in Chapter 1, Section 1.4.

1. Do men and women equally present with chest pain as a symptom of MI

and are there sex differences in other presenting symptoms of MI?

This chapter provides most of the literature review for the study. The literature

published after the search was completed in October 2009 has been updated in Chapter

8.

2.2 Abstract

2.2.1 Background

Recognition of sex differences in symptom presentation of acute myocardial infarction

(AMI) is important for timely clinical diagnosis. This review examined whether women

are equally as likely as men to present with chest pain.

2.2.2 Methods

We conducted a systematic review and meta-analysis of English language research

articles published between 1990 and 2009.

2.2.3 Results

Meta-analysis showed women with AMI had lower odds and a lower rate of presenting

with chest pain than men (OR=0.63, 95% CI 0.59, 0.68; RR=0.93, 95% CI 0.91, 0.95).

10

Women were significantly more likely than men to present with fatigue, neck pain,

syncope, nausea, right arm pain, dizziness and jaw pain.

2.2.4 Conclusions

Health campaigns on symptom presentation of AMI should continue to promote chest

pain as the cardinal symptom of AMI, but also reflect a wider spectrum of possible

symptoms and highlight potential differences in symptom presentation between men

and women.

2.2.5 Key Words

Acute myocardial infarction, meta-analysis, sex differences, symptom presentation,

systematic review

2.3 Background

Despite heart disease being the leading cause of death worldwide in older women, there

is a misperception that heart disease is an affliction mainly of men.36 Heart disease is an

umbrella term for a variety of different diseases affecting the heart, including Acute

Coronary Syndrome (ACS). In turn, ACS represents a range of conditions including

unstable angina (UA) and acute myocardial infarction (AMI), commonly called a ‘heart

attack’. In the United States of America in 2006, an estimated 785,000 people had a new

AMI and 470,000 people had a recurrent AMI, and more than 76,000 men and 65,000

women died of an AMI.10

A person who has an AMI is commonly believed to present with a sudden onset of

crushing central sternal pain, with the person clutching his/her chest and collapsing.

This ‘Hollywood-like’ portrayal of AMI onset does indeed occur, but not in all cases

and possibly less so in women.10 It is recognised that the more atypical presentations of

AMI can result in a delay in seeking medical care. Correct recognition of AMI

symptoms by the person experiencing the event and the health care provider is vital,

because time to treatment is crucial in minimising myocardial damage37 and improving

morbidity and mortality outcomes.13-15

Current international16 and national10,17,38 public education campaigns tend to promote

chest pain as the cardinal symptom of an AMI, however, research has shown that fewer

women experience chest pain than men.39,40 Women may not be aware of both typical

11

and atypical heart attack symptoms and often delay in seeking medical care.41,42

Subsequently, women with AMI are more likely than men to be under-diagnosed and

under-treated.41,43-45

A number of reviews of sex differences in symptoms of ACS 18,39,46,47 have been

reported in the literature, albeit with inconsistent findings, perhaps because studies and

reviews combine patients with different diagnoses, for example, patients with AMI, UA

and non-cardiac chest pain. Also, the reviews of AMI symptoms include a number of

studies restricted to patients who presented with chest pain39,47,48 and thereby exclude all

potential AMI patients who presented with other symptoms. Previous reviews searched

a limited range of databases and used broad or heterogeneous inclusion / exclusion

criteria.39,47,48 Our article adds to the body of literature as we have narrowed the patient

population to only include AMI patients, performed a quality assessment of the research

articles, and used sophisticated statistical analysis to calculate odds ratios (ORs) and

risk ratios (RRs).

We conducted a systematic review of published quantitative research studies to compare

the presenting symptoms of men and women with a confirmed diagnosis of AMI. We

sought to address 2 main research questions: 1) Do men and women equally present

with chest pain as a symptom of AMI? 2) Are there sex differences in other presenting

symptoms of AMI?

2.4 Methods

2.4.1 Search Strategy

The search strategy adhered to the Meta-analysis of Observational Studies in

Epidemiology study guidelines35 and was undertaken using MEDLINE, CINAHL,

EMBASE, Cochrane Library, Current Contents and ISI Web of Knowledge. The search

was performed with the aid of a professional librarian using a combination of search

terms, including chest pain OR symptom OR atypical OR emergency medical service

AND gender OR women AND acute myocardial infarction. The search strategy was

adapted for the different databases and all terms were searched with Medical Subject

Headings and as key (text) words. In addition, the references of all retrieved articles

were checked, and other articles that cited the retrieved article were also checked using

citation alert with ISI Web of Knowledge.

12

2.4.2 Inclusion and Exclusion Criteria

We aimed to include all research studies published between January 1990 and October

2009 that were written in English and reported sex differences in presenting symptoms

in patients with a confirmed AMI. The method for confirmation of diagnosis of AMI

could include increased enzyme elevation of creatine kinase or troponin,

electrocardiogram changes or International Classification of Diseases diagnosis codes of

410 or I21, I22. Studies were excluded if they were qualitative, included patients who

presented with chest pain (n=11) and reported only ACS symptoms where it was not

possible to differentiate between AMI and UA (n=12). Studies of patients with UA were

excluded because the operational definition was not made clear in many of these studies

and as such risked increasing heterogeneity further, by the inclusion of “patients with

stable angina.” All selected studies were reviewed in full text by one author (L.L.C.).

2.4.3 Quality Assessment

The selected studies were assessed for quality using the Newcastle–Ottawa Scale (NOS)

for Assessing the Quality of Nonrandomized Studies in Meta-Analysis,49 which is a

quality assessment tool that awards stars based on 3 categories. The first category

allocates stars on the selection of cohort, the second category allocates stars on the

comparability of the study based on design or analyses, and the third category allocates

stars on the assessment of outcome of the study. The NOS was adapted for the purposes

of this review as follows: Representativeness of the cohort was given a half star if it was

somewhat representative, and a full star was given if truly representative of the exposed

cohort; for assessment of outcome, record linkage was considered to be data from

medical records, and self report was considered to be data from interview or

questionnaire. Studies were excluded from the review if they failed to achieve at least 5

of the possible 9 stars.

2.4.4 Data Extraction

The following data were extracted in duplicate (to check accuracy) by one author (LLC)

from the included studies:

• Study design: prospective or retrospective, method of collecting data (medical

record, interview, structured data form), and inclusion / exclusion criteria.

• Study setting, study years and sample size.

• Proportion of men and women with chest pain.

13

• Proportion of men and women with each symptom: fatigue, arm and shoulder

pain, indigestion, epigastric pain, neck pain, syncope, nausea, right arm pain,

abdominal pain, dyspnea, dizziness, jaw pain, palpitations, back pain, sweating,

weakness, vomiting, left shoulder pain, right shoulder pain, headache and left arm

pain.

• Proportion of men and women with comorbidity: angina, congestive heart failure,

hypertension, history of AMI, diabetes, and hypercholesteremia.

• Statistical analysis: adjustment for age or other covariates identified in the

particular study.

2.4.5 Statistical Analysis

Forrest plots were produced to display the effect measures of each study that were

expressed as prevalence, OR and RR with 95% confidence intervals (CIs). The OR is

the ratio of the odds of an event occurring in men to the odds of the event occurring in

women. The RR is the ratio of the probability of the event occurring in women divided

by the probability of the event occurring in men. A ratio of 1 implies the event is

equally likely in both men and women, a ratio of greater than 1 implies the event is

more likely in women and a ratio of less than 1 implies the event is less likely in

women.50 Both ORs and RRs were calculated to highlight the different results. When

the outcome or symptom is common (ie, > 10%-20%), it is recommended to use RR

because the OR is further from 1 compared with the RR.51,52 Statistical meta-analysis

was conducted using RevMan, version 5 for Windows by the Cochrane collaboration,53

and results were pooled using random effects models, which assume the different

studies estimate different yet related effects.51 Heterogeneity measures the variability

among the combined studies; if there is considerable variation in the combined or

pooled results, it may be misleading to report a combined summary measure.51 The chi-

square (χ2) test and I2 statistic were used to assess heterogeneity. The χ2 statistic was

used to test the null hypothesis that there is no heterogeneity, with a p-value of < 0.05

indicating heterogeneity. The I2 statistic describes the variability in effect measurements

that is due to heterogeneity rather than sampling error. The I2 value was interpreted as

follows: Less than 40% might not be important, 30% to 60% may represent moderate

heterogeneity, 50% to 90% may represent substantial heterogeneity and 75% to 100%

represents considerable heterogeneity.51 The pooled result was considered

heterogeneous if the I2 statistic was > 40% and the p-value was < 0.05.

14

Publication bias may occur when studies with non-significant findings are not submitted

by the investigator or are rejected by the editors of the journals.50 When 10 or more

studies were combined, publication bias was assessed using funnel plots and interpreted

by visual inspection.51 Missing data were assumed to be missing at random and

therefore not included in the analysis.51 To consistently compare women with men,

some ORs reported in the original studies were reversed and may have rounding errors.

Crude results were estimated from a figure in one study.40 When calculating the pooled

mean age, only studies that had no age restriction in their inclusion criteria were used. A

narrative review is presented for the studies that adjusted for age and other variables in

their analysis.

2.5 Results

2.5.1 Included Studies Characteristics

Figure 1 summarizes the study selection process that resulted in 27 studies32,40,54-78

being included in the meta-analysis. One study57 was not used in the pooled results for

chest pain because the torso was divided into 9 quadrants and we were unable to

accurately ascertain how chest pain was classified, however, this study57 was used in the

pooled results for the other associated symptoms of AMI (right arm, left arm, neck, and

back). Table 1 summarizes the descriptive data from these studies. Most of the studies

were conducted in the United States and Europe, and all were published between 1990

and 2009 but include study years spanning from 1978 to 2006. The majority of study

designs were cohort (78%) or cross-sectional (15%), and the method of enrolling

participants was mostly prospective (78%). Data were collected via medical record

review (67%) or combined interview / medical record review (15%) and the remaining

15% (5 studies) collected the data via a combination of medical record / questionnaire

(n=1); questionnaire (n=1); combination of questionnaire / interview (n=1); or interview

(n=2). Data were abstracted from tables of most of the studies. For the majority of the

studies (n=20, 77%) chest pain was described as “yes or no” with no other descriptors.

In 4 studies65,70,74,75 (15%) chest pain descriptors used included “pain, discomfort,

pressure, tightness, heaviness, squeezing or crushing.” One study54 used “chest pain or

discomfort” and one study72 used “chest discomfort.

15

AM

I, ac

ute

myo

card

ial i

nfar

ctio

n; A

CS,

acu

te c

oron

ary

synd

rom

e,

NO

S, N

ewca

stle

-Otta

wa

Scal

e; U

A, u

nsta

ble

angi

na

Figu

re 1

: Fl

ow D

iagr

am o

f Sea

rch

Res

ults

and

Stu

dy S

elec

tion

N=3

,906

C

INA

HL

n=26

6

MED

LIN

E n=

620

EMB

ASE

n=90

5

CO

CH

RA

NE

n=14

0

CU

RR

ENT

CO

NTE

NTS

n=85

3

ISI W

EB O

F

KN

OW

LED

GE

n=1,

122

Scre

enin

g

abst

ract

and

title

n=55

n=

51

n=12

n=

8 n=

6

n=10

All

reta

ined

stud

ies

Dup

licat

es, n

=131

n=17

3

n=30

4

n=18

4

n=27

Elig

ible

for

furth

er re

view

Fo

und

by re

fere

nce

track

ing

and

cita

tion

aler

t, n=

11

Excl

uded

, n=1

53

• N

o A

MI s

ympt

oms,

n=76

• N

o se

x di

ffer

ence

s rep

orte

d, n

=20

• R

evie

w a

rticl

e, n

=18

• A

CS

sym

ptom

s, un

able

to d

iffer

entia

te

betw

een

AM

I and

UA

, n=1

2

• C

hest

pai

n on

ly p

atie

nts,

n=11

• R

epea

t stu

dy, n

=5

• O

ther

, n=1

1

Excl

uded

, n=4

Few

er th

an 5

/9 st

ars o

n

Qua

lity

Ass

essm

ent (

NO

S)

Elig

ible

for

full

text

revi

ew

Incl

uded

in

revi

ew

16

Tabl

e 1:

Su

mm

ary

of C

hara

cter

istic

s of I

nclu

ded

Acu

te M

yoca

rdia

l Inf

arct

ion

Stud

ies (

orde

red

alph

abet

ical

ly b

y th

e fir

st a

utho

r)

Stud

y C

ount

ry

Stud

y D

esig

n / m

etho

d of

en

rolli

ng

part

icip

ants

Met

hod

of

Col

lect

ing

Dat

a

Stud

y Y

ears

Sam

ple

Size

•

N

• M

en

• W

omen

Mea

n A

ge

(yea

rs)

• M

en

• W

omen

Age

/ O

ther

A

djus

tmen

t fo

r sy

mpt

om

pres

enta

tion

by se

x

Incl

usio

n E

xclu

sion

Ber

g

54

Swed

en

Pr

ospe

ctiv

e C

onse

cutiv

e M

edic

al

reco

rd

2001

–

2004

22

5 M

=173

W

=52

M=5

9.3

W

=61.

2 A

ge

25-7

4 ye

ars,

1st ti

me

AM

I

Cul

ic

55

Cro

atia

Pros

pect

ive

St

ruct

ured

da

ta fo

rm

and

Med

ical

re

cord

1990

–

1995

1,

996

M

=1,3

95

W=6

01

M=5

7 W

=63

Age

/ ris

k fa

ctor

s and

ca

rdia

c en

zym

e le

vel

1st ti

me

AM

I U

nabl

e to

ans

wer

qu

estio

ns,

Prev

ious

infa

rct

Dor

sch

56

U

K

Pros

pect

ive

Con

secu

tive

Med

ical

R

ecor

d Se

pt –

N

ov

1995

2,08

2 M

=1,2

66

W=8

16

1st e

vent

AM

I D

eath

Ever

ts

57

Swed

en

Pros

pect

ive

Con

secu

tive

Stru

ctur

ed

data

form

an

d M

edic

al

reco

rd

45

5

M=3

32

W=1

23

Ove

rall

65.4

D

eath

, phy

sica

l in

capa

city

, lac

k of

pa

in, c

ogni

tive

limita

tion,

and

oth

er

lang

uage

Fi

ebac

h

58

USA

R

etro

spec

tive

M

edic

al

reco

rd

1978

-19

82

1,12

2 M

=790

W

=332

M=5

8 W

=63

30

– 7

4 ye

ars

AM

I fol

low

ing

surg

ery

or tr

aum

a

Gol

dber

g 40

USA

R

etro

spec

tive

Med

ical

re

cord

1986

an

d 19

88

1,36

0 M

=810

W

=550

M=6

4.7

W=7

2.1

Age

/ m

edic

al

hist

ory,

&

sele

cted

AM

I ch

arac

teris

tics

A

MI f

ollo

win

g su

rger

y

17

Stud

y C

ount

ry

Stud

y D

esig

n / m

etho

d of

en

rolli

ng

part

icip

ants

Met

hod

of

Col

lect

ing

Dat

a

Stud

y Y

ears

Sam

ple

Size

•

N

• M

en

• W

omen

Mea

n A

ge

(yea

rs)

• M

en

• W

omen

Age

/ O

ther

A

djus

tmen

t fo

r sy

mpt

om

pres

enta

tion

by se

x

Incl

usio

n E

xclu

sion

Gol

dste

in 59

USA

Pr

ospe

ctiv

e

Inte

rvie

w

and

Med

ical

R

ecor

d

12-5

2 m

onth

fo

llow

-up

, ce

nsor

da

te

June

30

1987

2,46

4

M=1

,966

W

=498

25 –

75

year

s B

rady

card

ia,

sym

ptom

atic

hy

pote

nsio

n, o

r co

mpl

icat

ing

dise

ases

, med

icat

ed

with

cal

cium

cha

nnel

bl

ocke

rs, n

eede

d ca

rdia

c su

rger

y, in

tra-

oper

ativ

e A

MI,

maj

or

psyc

hiat

ric d

isor

der,

impa

ired

cons

ciou

snes

s, ch

roni

c na

rcot

ic u

se

or a

lcoh

olis

m

Gra

ce60

Can

ada

Pr

ospe

ctiv

e C

onse

cutiv

e Su

rvey

and

M

edic

al

Rec

ord

48

2

M=3

47

W=1

35

M=5

9.2

W=6

6.3

Illne

ss se

verit

y,

conf

usio

n, lo

w

Engl

ish

prof

icie

ncy,

un

cons

ciou

s, re

fusa

l H

endr

icks

61

USA

Pr

ospe

ctiv

e C

onse

cutiv

e M

edic

al

reco

rd

1996

27

0 M

=187

W

=83

M=6

1 W

=66

Her

litz62

Sw

eden

R

etro

spec

tive

Med

ical

re

cord

D

ec

1998

–

Feb

1999

130

M=8

5 W

=45

all t

rans

porte

d by

am

bula

nce

with

AC

S

Hira

kaw

a 32

Japa

n

Pros

pect

ive

Con

secu

tive

Med

ical

R

ecor

d 20

01 -

2003

2,

221

M=1

,712

W

=509

18

Stud

y C

ount

ry

Stud

y D

esig

n / m

etho

d of

en

rolli

ng

part

icip

ants

Met

hod

of

Col

lect

ing

Dat

a

Stud

y Y

ears

Sam

ple

Size

•

N

• M

en

• W

omen

Mea

n A

ge

(yea

rs)

• M

en

• W

omen

Age

/ O

ther

A

djus

tmen

t fo

r sy

mpt

om

pres

enta

tion

by se

x

Incl

usio

n E

xclu

sion

Isak

sson

63

Sw

eden

Pros

pect

ive

C

onse

cutiv

e

Med

ical

R

ecor

d 19

89 –

2003

6,

542

M=5

,072

W

=1,4

70

M=5

5.6

W=5

6.6

1985

-200

0 on

ly 2

5-64

yea

rs, 2

000-

2003

on

ly 2

5-74

yea

rs,

both

1st a

nd re

curr

ent

even

ts a

re in

clud

ed

Dea

th o

r in

card

iac

arre

st, n

o tim

e va

riabl

e co

ded

Kos

uge64

Japa

n

Pros

pect

ive

Con

secu

tive

Inte

rvie

w

& C

hart

revi

ew

2001

- 20

04

457

M=3

51

W=1

06

M=6

2 W

=72

ST

EMI o

nly

Car

diog

enic

shoc

k,

dem

entia

, ear

ly d

eath

, ot

her c

ondi

tions

pr

eclu

ding

the

asse

ssm

ent o

f pai

n

Lovl

ien65

N

orw

ay

Pros

pect

ive

Con

secu

tive

Que

stio

nna

ire

Med

ical

R

ecor

ds

2003

–

2004

53

3

M=3

84

W=1

49

M=5

8.5

W

=61.

2

Age

<76

year

s 1st

AM

I A

lread

y ho

spita

lised

pa

tient

s

Lusi

ani66

Italy

Ret

rosp

ectiv

e C

onse

cutiv

e

Med

ical

R

ecor

ds

1989

- 19

91

94

M=6

0 W

=34

Ove

rall

68.5

Mar

tin67

USA

Pros

pect

ive

.

Inte

rvie

w

and

ques

tionn

aire

14-

mon

th

perio

d

157

M

=109

W

=48

M=6

0.1

W=6

1.1

Una

ble

to re

call

the

deci

sion

to se

ek

med

ical

car

e,

diso

rient

ated

or

unab

le to

spea

k En

glis

h, w

ere

with

out

acce

ss to

a p

hone

M

ayna

rd 68

U

SA

Pros

pect

ive

Med

ical

re

cord

19

93

7 mon

th

perio

d

895

M=5

73

W=3

22

M=6

3 W

=69

30

yea

rs

Tr

aum

a, su

rgic

al

emer

genc

y, o

r cle

ar

non-

card

iac

caus

e,

trans

ferr

ed fr

om

anot

her h

ospi

tal

19

Stud

y C

ount

ry

Stud

y D

esig

n / m

etho

d of

en

rolli

ng

part

icip

ants

Met

hod

of

Col

lect

ing

Dat

a

Stud

y Y

ears

Sam

ple

Size

•

N

• M

en

• W

omen

Mea

n A

ge

(yea

rs)

• M

en

• W

omen

Age

/ O

ther

A

djus

tmen

t fo

r sy

mpt

om

pres

enta

tion

by se

x

Incl

usio

n E

xclu

sion

Miln

er69

USA

Pros

pect

ive

Con

secu

tive

Med

ical

R

ecor

d 19

97

and

1999

2,07

3 M

=1,1

92

W=8

81

Div

ided

in

to a

ge

grou

ps

Age

Mor

gan70

U

SA

Pr

ospe

ctiv

e

Inte

rvie

w

2001

- 20

02

98

M=6

2 W

=36

M=6

1

W=6

5

Sym

ptom

s beg

an o

ut

of h

ospi

tal,

curr

ent

in-p

atie

nt

Paul

71

USA

Pros

pect

ive

Med

ical

re

cord

1991

-19

92

561

M=3

83

W=1

78

M=6

4 W

=70

Penq

ue72

U

SA

Pros

pect

ive

Con

veni

ence

Inte

rvie

w

and

Med

ical

re

cord

12 –

m

onth

pe

riod

98

M=4

7 W

=51

M=5

6 W

=61

21 +

yea

rs, E

nglis

h sp

eaki

ng, a

dmitt

ed

via

ED, p

hysi

cian

’s

offic

e or

tran

sfer

fr

om ru

ral h

ospi

tal

with

in 6

hrs

of A

MI

Sudd

en c

ardi

ac d

eath

Sric

haiv

eth

73

Thai

land

Pros

pect

ive

Con

secu

tive

Med

ical

re

cord

20

02 –

20

05

3,83

6

M=2

,613

W

=1,2

23

M=5

9.7

W=6

7.5

ST

EMI o

nly

Sum

mer

s 74

USA

R

etro

spec

tive

Con

secu

tive

Med

ical

re

cord

3

year

pe

riod

166

M=8

1 W

=85

In

suff

icie

nt

info

rmat

ion

to

dete

rmin

e an

ear

ly

ches

t pai

n de

scrip

tion

Then

75

Can

ada

R

etro

spec

tive

:

Med

ical

re

cord

and

In

terv

iew

qu

estio

nna

ire

15

3 M

=105

W

=48

Div

ided

in

to a

ge

grou

ps

35

+ ye

ars,

Engl

ish

spea

king

, 1st ti

me

AM

I

Tran

sfer

red

from

an

othe

r hos

pita

l

Tuns

tall-

Pedo

e76

Scot

land

Pr

ospe

ctiv

e C

onse

cutiv

e M

edic

al

Rec

ords

19

85-

1991

5,

542

M=3

,991

W

=1,5

51

M=5

5.5

W=5

7

25-6

4 ye

ars

20

Stud

y C

ount

ry

Stud

y D

esig

n / m

etho

d of

en

rolli

ng

part

icip

ants

Met

hod

of

Col

lect

ing

Dat

a

Stud

y Y

ears

Sam

ple

Size

•

N

• M

en

• W

omen

Mea

n A

ge

(yea

rs)

• M

en

• W

omen

Age

/ O

ther

A

djus

tmen

t fo

r sy

mpt

om

pres

enta

tion

by se

x

Incl

usio

n E

xclu

sion

Vac

carin

o 77

USA

Pros

pect

ive

Con

secu

tive

Med

ical

re

cord

ab

stra

ctio

n

1994

–

2006

91

6,38

0 M

=

555,

965

W=

362,

415

A

MI s

econ

dary

to

surg

ery,

hyp

oten

sion

or

oth

er e

vent

s afte

r ho

spita

lisat

ion,

tra

nsfe

rred

from

an

othe

r hos

pita

l W

illic

h78

Ger

man

y

Pros

pect

ive

Con

secu

tive

Inte

rvie

w

1,

082

M

=804

W

=278

61

M, m

en; W

, wom

en; A

MI,

acut

e m

yoca

rdia

l inf

arct

ion;

AC

S, a

cute

cor

onar

y sy

ndro

me;

STE

MI,

ST-s

egm

ent e

leva

tion

myo

card

ial i

nfar

ctio

n; E

D, e

mer

genc

y de

partm

ent

.

21

The mean age varied from 57 to 72.1 years for women and from 55.5 to 64.7 years for

men, and sample sizes varied from 94 to > 900,000 participants. Inclusion criteria for

some of the studies involved age restrictions and limits to first-time AMI. Exclusion

criteria for some of the studies included AMI after trauma or surgery, death, impaired

cognition, and illness severity. Only 5 studies40,54,55,65,69 adjusted for age in the analysis

of the effect of sex on symptoms, and of these 3 studies40,55,69 also adjusted for other

factors. The results of the NOS quality assessment ranged from 5.5 to nine stars and are

presented in Table 2. The majority of the studies were allocated 7 of the possible 9 stars.

Four studies79-82 were excluded because they did not meet either of the quality criteria

for both representativeness of the cohort (eg, convenient sample and / or small sample

size) and methodology used for assessing the outcome (eg, interview 3 to 5 days after

AMI).

2.5.2 Chest Pain

Of the 26 studies used in the meta-analysis, 13 found that women with AMI had

significantly lower odds than men of experiencing chest pain. Figure 2 summarizes the

results from each study and the pooled OR. Overall, the pooled OR from the meta-

analysis indicated that women with AMI had lower odds of presenting with chest pain

than men (OR=0.63; 95% CI 0.59, 0.68). The I2 value was 34% suggesting an

acceptable level of heterogeneity between studies. The sample size of the studies ranged

from 94 to 916,380, with the largest study77 contributing approximately 20% of the

weight of the pooled effect. Given concerns about the potential for this study to

dominate the results, we re-ran the analysis excluding the study and found that the

pooled OR changed minimally (OR=0.62; 95% CI 0.58, 0.66).

When analyzing RRs for the 26 studies, 11 indicated that women with AMI were

significantly less likely than men to present with chest pain. Figure 3 summarizes the

results from each study and the pooled RR. Overall, the pooled RR from the meta-

analysis indicated that women with AMI had a lower rate of presenting with chest pain

than men (RR=0.93; 95% CI 0.91, 0.95); however, the I2 value of 87% suggests this

result must be interpreted with care due to heterogeneity.

22

Table 2: Newcastle-Ottawa Quality Assessment

Study

Newcastle – Ottawa Quality Assessment Scale Total Score - maximum 9 stars

Selection - maximum 4 stars

Comparability - maximum 2 stars

Outcome - maximum 3 stars

Berg54 8 Culic55 8 ½ Dorsch56 7 Everts57 6 Fiebach58 6 ½ Goldberg40 9 Goldstein59 7 Grace60 6 Hendricks61 6 ½ Herlitz62 6 Hirakawa32 7 Isaksson 63 7 Kosuge64 6 ½ Lovlien65 6 ½ Lusiani66 6 Martin67 5 ½ Maynard68 7 Milner69 8 Morgan70 5 ½ Paul71 6 Penque72 6 Srichaiveth73 7 Summers74 6 ½ Then75 6 ½ Tunstall-Pedoe76 7 Vaccarino77 7 Willich78 6

http://commons.wikimedia.org/wiki/File:Full_Star_Blue












http://commons.wikimedia.org/wiki/File:Half_Star_Blue








































































































































































































23

Figure 2: Forest Plot of Studies Using OR in Comparing Chest Pain as a Presenting

Symptom of AMI in Women and Men (in alphabetical order)

OR, odds ratio; M-H, Mantel-Haenszel; CI, confidence interval

Study or SubgroupBerg 2009Culic 2002Dorsch 2001Fiebach 1990Goldberg 1998Goldstein 1995Grace 2003Hendricks 1999Herlitz 2002Hirakawa 2006Isaksson 2008Kosuge 2006Lovlien 2006aLuisiani 1994Martin 2004Maynard 1996Milner 2004Morgan 2005Paul 1995Penque 1998Srichaiveth 2007Summers 2001Then 2001Tunstall-Pedoe 1996Vaccarino 2009Willich 1993

Total (95% CI)Total eventsHeterogeneity: Tau² = 0.01; Chi² = 37.89, df = 25 (P = 0.05); I² = 34%Test for overall effect: Z = 12.41 (P < 0.00001)

Events46

479586279418470

876936

3831188

94128

2042

270476

28119

481079

4636

1053249751

247

257478

Total52

601816332550498135

8345

5091385

106149

3448

322881

36178

511223

8548

1297362415

278

372157

Events164

12221075

703688

1879238160

7413864377

310353

4491

516822

53290

462435

4980

2730426886

740

447411

Total173

13951266

790810

1966347187

8517124846

351383

60109573

119262

38347

261381

1053237

553965804

577542

Weight0.4%5.6%7.0%3.2%5.1%2.4%2.6%1.0%0.5%6.3%8.8%1.1%1.4%0.6%0.5%2.7%8.6%0.5%2.9%0.1%6.4%1.3%0.8%9.3%

18.8%2.2%

100.0%

M-H, Random, 95% CI0.42 [0.14, 1.24]0.56 [0.43, 0.72]0.45 [0.36, 0.56]0.65 [0.45, 0.94]0.56 [0.43, 0.74]0.78 [0.50, 1.20]0.83 [0.55, 1.26]0.83 [0.41, 1.68]0.59 [0.23, 1.56]0.71 [0.57, 0.90]0.65 [0.54, 0.77]1.04 [0.52, 2.05]0.52 [0.29, 0.94]0.52 [0.21, 1.27]1.38 [0.51, 3.74]0.57 [0.38, 0.86]0.53 [0.44, 0.63]0.59 [0.21, 1.71]0.65 [0.44, 0.96]0.35 [0.03, 3.47]0.55 [0.43, 0.69]0.77 [0.42, 1.43]0.94 [0.42, 2.07]0.80 [0.68, 0.95]0.66 [0.65, 0.67]0.69 [0.44, 1.08]

0.63 [0.59, 0.68]

Women Men Odds Ratio Odds RatioM-H, Random, 95% CI

0.01 0.1 1 10 100Women Men

24

Figure 3: Forest Plot of Studies Using RR Comparing Chest Pain as a Presenting

Symptom of AMI in Women and Men (in alphabetical order)

RR, rate ratio; M-H, Mantel-Haenszel; CI, confidence interval

The pooled result of the meta-analysis showed women with AMI had lower odds and a

lower rate of presentation with chest pain than men. Two previous reviews of the

literature39,47 have shown that women present with significantly less chest pain than men

in 2 of 8 studies and a third review48 showed that women present with less chest pain

than men in 3 of 8 studies; no studies found more chest pain in women. A possible

limitation of previous reviews is they included studies of patients who presented with

only chest pain and thus excluded all other potential AMI patients who presented with

other symptoms. Also, by combining the results of all the studies in a meta-analysis, we

are able to give a more precise estimate of sex differences in chest pain.

2.5.3 Associated Symptoms of AMI

Table 3 summarizes the pooled results of the meta-analyses of studies reporting sex

differences in other presenting symptoms of AMI. As shown, compared with men,

women had significantly higher odds and rates of presentation with fatigue, neck pain,

Study or SubgroupBerg 2009Culic 2002Dorsch 2001Fiebach 1990Goldberg 1998Goldstein 1995Grace 2003Hendricks 1999Herlitz 2002Hirakawa 2006Isaksson 2008Kosuge 2006Lovlien 2006aLuisiani 1994Martin 2004Maynard 1996Milner 2004Morgan 2005Paul 1995Penque 1998Srichaiveth 2007Summers 2001Then 2001Tunstall-Pedoe 1996Vaccarino 2009Willich 1993

Total (95% CI)Total eventsHeterogeneity: Tau² = 0.00; Chi² = 196.05, df = 25 (P < 0.00001); I² = 87%Test for overall effect: Z = 6.05 (P < 0.00001)

Events46

479586279418470

876936

3831188

94128

2042

270476

28119

481079

4636

1053249751

247

257478

Total52

601816332550498135

8345

5091385

106149

3448

322881

36178

511223

8548

1297362415

278

372157

Events164

12221075

703688

1879238160

7413864377

310353

4491

516822

53290

462435

4980

2730426886

740

447411

Total173

13951266

790810

1966347187

8517124846

351383

60109573

119262

38347

261381

1053237

553965804

577542

Weight2.9%5.4%5.2%5.0%4.9%6.2%1.9%2.6%1.5%4.9%6.2%3.9%4.1%0.5%2.1%4.9%4.1%1.1%2.5%3.8%6.3%0.7%1.2%6.0%6.6%5.3%

100.0%

M-H, Random, 95% CI0.93 [0.84, 1.04]0.91 [0.87, 0.95]0.85 [0.81, 0.89]0.94 [0.90, 1.00]0.89 [0.85, 0.95]0.99 [0.96, 1.01]0.94 [0.81, 1.09]0.97 [0.87, 1.09]0.92 [0.78, 1.09]0.93 [0.88, 0.98]0.95 [0.93, 0.97]1.00 [0.93, 1.09]0.93 [0.87, 1.00]0.80 [0.58, 1.10]1.05 [0.92, 1.20]0.93 [0.88, 0.98]0.78 [0.73, 0.84]0.91 [0.74, 1.11]0.88 [0.78, 0.99]0.96 [0.89, 1.04]0.95 [0.93, 0.97]0.89 [0.69, 1.16]0.98 [0.81, 1.20]0.96 [0.93, 0.99]0.89 [0.89, 0.90]0.97 [0.92, 1.01]

0.93 [0.91, 0.95]

Women Men Risk Ratio Risk RatioM-H, Random, 95% CI

0.01 0.1 1 10 100Women Men

25

nausea, syncope, right arm pain, dizziness and jaw pain. In meta-analyses with a higher

degree of heterogeneity (I2>40%, see table 3), there were significantly higher odds and

rates of women presenting with palpitations, back pain, dyspnea, vomiting and left arm

pain; and lower odds and rate of presenting with sweating.

We found women were more likely than men to experience fatigue (RR 1.19; 95% CI

1.06, 1.33), and 2 previous reviews39,48 showed significantly greater fatigue in women in

2 of 3 and 1 of 2 studies. We found women were more likely than men to experience

neck pain (RR 1.54; 95% CI 1.38, 1.73). Two reviews,39,48 also found women were

more likely than men to experience neck pain in 3 of 5 studies. We found women were

more likely than men to experience syncope (RR 1.37; 95% CI 1.11, 1.70). One

review48 found no significant difference between sexes in 6 studies and one review39

found significant differences in 1 of 3 studies.

We found that women were more likely than men to experience nausea (RR 1.42; 95%

CI, 1.35, 1.51). Two reviews39,47 combined the symptoms of nausea and vomiting, thus

not enabling comparison. The third review48 found women were more likely than men

to experience nausea in 5 of 8 studies. We found women were more likely than men to

experience right arm pain (RR 1.20; 95% CI 1.07, 1.33). One review48 found a

significant difference between sexes in only 1 of 3 studies. We found women were more

likely than men to experience dizziness (RR1.22; 95% CI 1.02, 1.46). Two reviews39,48

found significant differences in 1 of 4 and 1 of 6 studies. We found women were more

likely than men to experience jaw pain (RR 1.39; 95% CI 1.01, 1.92). Three

reviews39,47,48 found significantly greater jaw pain in women in 1 of 3, 1 of 5, and 2 of 4

studies.

26

Tabl

e 3:

Po

oled

Est

imat

es o

f the

Eff

ect o

f Sex

on

Che

st P

ain

and

othe

r Pre

sent

ing

Sym

ptom

s in

Patie

nts w

ith A

cute

Myo

card

ial I

nfar

ctio

n

(fro

m m

eta-

anal

yses

of i

ndiv

idua

l stu

dies

)

Stud

ies i

nclu

ded

in

the

met

a-an

alys

is

Sym

ptom

W

omen

No.

of

eve

nts

(%)

Men

No.

of

even

ts (%

) Po

oled

Odd

s Rat

io

(95%

CI)

W:M

Het

erog

enei

ty

Pool

ed R

isk

Rat

io

(95%

CI)

W:M

Het

erog

enei

ty

Chi

2 p -

valu

e I2 %

C

hi2 p

- va

lue

I2 %

32,4

0,54

-56,

58-7

8 C

hest

Pai

n 25

7,47

8 (6

9)

447,

411

(77)

0.

63 (0

.59-

0.68

)*

0.05

34

0.

93 (0

.91-

0.9

5)*

0.00

001

87

54,6

0,62

,65,

67,7

0,72

Fa

tigue

22

7 (4

4)

412

(34)

1.

43 (1

.14-

1.80

)*

0.64

0

1.19

(1.0

6-1.

33) *

0

.48

0 54

,67,

70

Arm

& sh

ould

er p

ain

86 (6

3)

196

(57)

1.

31 (0

.87-

1.97

) 0.

75

0 1.

11 (0

.95-

1.31

) 0

.73

0 60

,70,

72

Indi

gest

ion

62 (2

8)

109

(2)

1.13

(0.8

9-1.

65)

0.57

0

1.08

(0.8

3-1.

40)

0.5

3 0

40,5

5,62

,64

Epig

astri

c Pa

in

128

(10)

32

4 (1

2)

0.82

(0.6

6-1.

03)

0.86

0

0.84

(0.6

9-1.

02)

0.8

7 0

40,5

4,55

,57,

72,7

8 N

eck

pain

37

6 (2

3)

566

(16)

1.

74 (1

.49-

2.04

)*

0.40

2

1.54

(1.3

8-1.

73) *

0

.56

0 40

,54,

55,6

0,62

,64,

65,6

8,72

,78

Nau

sea

1,09

7 (4

8)

1,70

6 (3

4)

1.83

(1.6

2-2.

07)*

0.

25

21

1.42

(1.3

5-1.

51) *

0

.43

1 40

,60,

62,6

5,68

,70,

76

Sync

ope

170

(61)

25

9 (4

) 1.

41 (1

.11-

1.78

)*

0.33

13

1.

37 (1

.11-

1.70

) *

0.35

11

40

,55,

57,6

4,65

R

ight

arm

pai

n 49

9 (3

3)

925

(60)

1.

32 (1

.11-

1.57

)*

0.27

23

1.

20 (1

.07-

1.33

) *

0.32

16

54

,60,

65,6

7,68

,70,

78

Abd

omin

al p

ain

153

(15)

32

6 (1

3)

1.23

(0.9

3-1.

62)

0.20

30

1.

18 (0

.96-

1.46

) 0.

23

26

54,5

5,60

,65,

68,7

0,72

D

izzi

ness

24

5 (1

8)

432

(14)

1.

31 (1

.02-

1.67

)*

0.15

37

1.

22 (1

.02-

1.46

) *

0.15

37

40

,54,

55,6

4,67

,72

Jaw

pai

n 14

0 (1

0)

196

(7)

1.45

(1.0

2-2.

05)*

0.

14

40

1.39

(1.0

1-1.

92) *

0.

12

43

54,6

2,65

,72

Palp

itatio

ns

79 (2

6)

92 (1

3)

2.05

(1.0

8-3.

89)*

0.

12

49

1.75

(1.0

3-2.

96) *

0.

11

50

40,5

4,55

,64,

65,6

7,72

B

ack

pain

28

9 (1

8)

322

(10)

2.

19 (1

.66-

2.89

)*

0.06

50

1.

89 (1

.51-

2.35

) *

0.06

51

40

,54,

55,6

0,64

,65,

67,7

0,78

Sw

eatin

g 96

4 (4

9)

2,58

3 (5

8)

0.78

(0.6

4-0.

94)*

0.

02

57

0.90

(0.8

3-0.

97) *

0.

03

53

55,6

0,72

W

eakn

ess

367

(47)

81

6 (4

6)

1.13

(0.7

8-1.

65)

0.08

60

1.

07 (0

.88-

1.30

) 0.

07

62

40,5

4,55

,60,

62,6

4,65

,67,

68,7

0,

72,7

3,78

D

yspn

ea

1,64

3 (4

6)

2,67

4 (3

4)

1.58

(1.4

0-1.

77)*

0.

12

33

1.26

(1.1

5-1.

37) *

0.

0005

66

54,5

5,60

,62,

64,6

8,78

V

omiti

ng

342

(22)

52

7 (1

4)

1.88

(1.3

9-2.

55)*

0.

007

66

1.69

(1.3

1-2.

18) *

0.

005

67

40,5

5,64

Le

ft sh

ould

er p

ain

353

(28)

75

4 (2

9)

1.16

(0.8

1-1.

66)

0.05

67

1.

14 (0

.85-

1.52

) 0.

04

69

40,5

5,64

R

ight

shou

lder

pai

n

250

(20)

57

8 (2

3)

0.92

(0.7

7-1.

09)

0.01

77

0.

94 (0

.83-

1.07

) 0.

02

75

55,6

5,70

H

eada

che

102

(13)

14

4 (8

) 1.

34 (0

.61-

2.97

) 0.

002

84

1.31

(0.6

5-2.

67)

0.00

05

87

40,5

5,57

,64,

65

Left

arm

pai

n 77

1 (5

0)

1,44

9 (4

4)

1.70

(1.1

0-2.

64)*

0.

0000

1 88

1.

36 (1

.05-

1.77

) *

0.00

001

91

CI,

conf

iden

ce in

terv

al; M

, men

; W, w

omen

. *S

igni

fican

ce d

iffer

ence

27

2.5.4 Age and Other Adjustments

Across all studies, the pooled mean age of patients with AMI showed women were

older than men by a mean of 6.58 years (95% CI 5.42, 7.74, I2 69%). Table 4

summarizes the modification of effect sizes of the relationship between sex and AMI

symptoms with adjustment for age and other variables in the individual studies. For the

symptom of chest pain, the crude OR became nonsignificant after adjustment for age

and other variable(s) in 2 of 5 studies.40,69 The age-stratified study69 shows that

differences between men and women in chest pain presentation vary between older and

younger age groups.

In the majority of studies, adjusting for age and other variables made little difference to

the statistical significance or magnitude of the effect of sex on the other associated

symptoms of AMI. Non-significant crude ORs became significant after adjustment for

age or other variables for symptoms of dizziness65 and jaw pain.40 Significant crude

ORs became non-significant for the symptoms of sweating40 and left arm pain.65 For the

symptom of dyspnea, a significant OR became non-significant after age adjustment in

one study,40 and a non-significant OR became significant after age adjustment in

another study.65 Overall, the effect of adjustment for age and other variables was

equivocal for all of the other symptoms of AMI.

We found women who had an AMI were on average 6.58 years (95% CI 5.42, 7.74)

older than men. This finding is similar to that of Canto et al,18 who found that women

were approximately ten years older on average than men at the time of their initial

myocardial infarction.

Previous reviews18,39,47,48 have suggested that sex differences may decrease after

controlling for age and comorbidity. Our review is the first to compare sex differences

in symptoms of AMI after adjusting for age and other variables. We could only find five

studies40,54,55,65,69 that adjusted for age and other variables and that met our selection

criteria. The age-stratified study69 showed differences between men and women in chest

pain presentation in the “young” (<65) and the “old” (>75) but not the middle-age group

(65-74). The reason for this is not immediately obvious, and the authors69 did not offer

an explanation. Our results suggest that adjusting for age does not make a significant

difference to the direction or magnitude of effect measures of sex differences for the

majority of AMI symptoms.

28

Table 4: Comparison of the Effect of Adjustment for Age and Other Variables on the

Crude Effect Measure in Studies Reporting Sex Differences in Presenting

Symptoms in Patients with Acute Myocardial Infarction

Symptom Author Crude OR (95% CI) W:M

Age (years) Adjusted OR (95% CI) W:M

Other variable AOR (‡ items adjusted for in footnotes) (95% CI) W:M

Chest Pain Berg 54 0.42 (0.14-1.25) 0.42 (0.16-1.52) Culic55 0.56 (0.43-0.72) 0.62 (0.48-0.80) Goldberg40 0.56 (0.43-0.74) 0.86 (0.65-1.15)* 0.80 (0.59-1.09)* Lovlien65 0.81 (0.54-1.23) 0.84 (0.55-1.28) Milner69 0.53 (0.44-0.63) <65, 0.64 (0.42-0.97)

65-74, 0.85 (0.57-1.25)* ≥75, 0.65 (0.50-0.85)

Age < 65 RR 0.98 (0.93-1.06)* Age >=75 RR 0.92 (0.87-0.99)

Fatigue Berg54 1.89 (0.94-3.80) 1.84 (0.91-3.72) Lovlien65 1.36 (0.93-2.00) 1.43 (0.97-2.11)

Epigastric Pain

Culic55 0.80 (0.61-1.05) 0.95 (0.73-1.23) Goldberg40 0.85 (0.56-1.28) 0.88 (0.52-1.47) 0.91 (0.53-1.54)

Neck pain Berg54 1.18 (0.57-2.44) 1.19 (0.57-2.45) Culic55 1.75 (1.33-2.27) 1.56 (1.19-2.04) Goldberg40 1.47 (1.05-2.04) 1.75 (1.19-2.56) 1.92 (1.28-2.86)

Nausea Berg54 2.79 (1.48-5.27) 2.78 (1.47-5.25) Culic55 1.96 (1.61-2.38) 1.61 (1.33-1.96) Goldberg40 1.42 (1.13-1.78) 1.61 (1.28-2.08) 1.72 (1.33-2.22) Lovlien65 2.14 (1.45-3.16) 2.38 (1.59-3.56)

R arm pain Culic55 1.35 (1.11-1.64) 1.33 (1.09-1.61) Goldberg40 1.06 (0.80-1.40) 1.28 (0.94-1.75) 1.28 (0.93-1.78) Lovlien65 1.41 (0.94-2.13 1.52 (1.0-2.32)

Dyspnea Berg54 1.42 (0.73-2.75) 1.41 (0.73-2.75) Culic55 1.78 (1.49-2.17) 1.52 (1.23-1.82) Goldberg40 1.34 (1.07-1.67) 1.25 (0.99-1.56) * 1.16 (0.92-1.49) * Lovlien65 1.47 (1.00-2.16) 1.63 (1.1-2.42) †

Dizziness Berg54 2.58 (1.03-6.43) 2.60 (1.04-6.50) Culic55 1.41 (0.97-2.04) 1.22 (0.84-1.75) Lovlien65 1.32 (0.89-1.95) 1.54 (1.03-2.32) †

Jaw pain Berg54 0.82 (0.26-2.56) 0.80 (0.25-2.51) Culic55 1.72 (1.20-2.5) 1.47 (1.04-2.08) Goldberg40 1.27 (0.87-1.86) 1.89 (1.19-2.94) † 2.0 (1.23- 3.22) †

Back Pain Berg54 4.34 (2.17-8.69) 4.29 (2.14-8.62) Culic55 2.13 (1.54-3.12) 1.64 (1.16-2.27) Goldberg40 1.98 (1.44-2.71) 2.44 (1.69-3.57) 2.63 (1.78 – 3.85) Lovlien65 1.91 (1.2-3.02) 1.8 (1.12-2.89)

Sweating Berg54 0.71 (0.37-1.35) 0.75 (0.39-1.45) Culic55 0.62 (0.52-0.76) 0.73 (0.60-0.88) Goldberg40 0.72 (0.58-0.90) 0.79 (0.63-1.00)* 0.79 (0.62-1.00)* Lovlien65 1.08 (0.74-1.59) 1.28 (0.87-1.92)

Vomiting Berg54 2.09 (0.78-5.61) 2.06 (0.76-5.58) Culic55 1.25 (0.98-1.59) 1.14 (0.89-1.45)

L arm pain Culic55 1.28 (1.03-1.56) 1.32 (1.06-1.61) Goldberg40 1.01 (0.80-1.27) 1.22 (0.95-1.56) 1.20 (0.93-1.56) Lovlien65 3.79 (2.54-5.67) 1.34 (0.9-1.98)†

29

Abbreviations: OR: Odds Ratio; CI: Confidence Interval; W: Women; M: Men; AOR: Adjusted Odds Ratio; HTN: Hypertension; AMI: Acute Myocardial Infarction; RR: Risk Ratio; CHD: Coronary Heart Disease. * Significant crude ORs that becomes non-significant † Non-significant crude ORs that becomes significant ‡ Adjusted for age, angina, diabetes, hypertension, AMI characteristics40, Adjusted for age, risk factors, and cardiac enzyme levels55, Adjusted for age, history of heart failure, coronary heart disease, pulmonary disease, diabetes, hypertension and obesity69

2.5.5 Co-morbidity

Table 5 summarizes the pooled results from meta-analyses of individual studies

reporting the association between sex and various comorbid conditions in patients with

AMI. As shown, compared with men, women had statistically significantly higher odds

and rates of prior congestive heart failure. Other statistically significant differences

found, albeit within meta-analyses with a higher degree of heterogeneity between

studies, increased odds and rates of women with histories of hypertension and diabetes,

and a decreased odds and rate of previous AMI.

Women were more likely than men to have had a history of congestive heart failure (RR

1.64; 95% CI 1.44, 1.88). This finding is similar to that of Canto et al,18 who found on

average women were more likely to have a history of heart failure.

30

Tabl

e 5:

Po

oled

Est

imat

es o

f the

eff

ect o

f Sex

on

Com

orbi

d co

nditi

ons i

n Pa

tient

s with

Acu

te M

yoca

rdia

l Inf

arct

ion

(fro

m m

eta-

anal

yses

of

indi

vidu

al st

udie

s)

Stud

ies i

nclu

ded

in

the

met

a-an

alys

is

Cha

ract

erist

ic

Wom

en

No.

of

Eve

nts

(%)

Men

No.

of

Eve

nts

(%)

Pool

ed O

dds R

atio

(9

5% C

I) W

:M

Het

erog

enei

ty

Pool

ed R

isk

Rat

io

(95%

CI)

W

:M

Het

erog

enei

ty

Chi

2 p-

valu

e I2 %

C

hi2 p

- va

lue

I2 %

64,6

5,68

,76

Ang

ina

854

(40)

2,

096

(40)

1.

02 (0

.92-

1.13

) 0.

48

0 1.

01 (0

.95-

1.08

) 0.

44

0 58

,60,

61,6

7,69

,71

Con

gest

ive

Hea

rt Fa

ilure

35

4 (2

2)

348

(12)

1.

74 (1

.39-

2.20

)*

0.28

20

1.

64 (1

.44-

1.88

)*

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31

2.5.6 Heterogeneity

Most of the meta-analyses performed had a p-value ≥ 0.05 for the chi-square test of

heterogeneity, and approximately half of the meta-analyses performed had an I2≤40%;

thus, heterogeneity is not likely to be a concern. However, in the following meta-

analyses of sex differences, there was a moderate to substantial51 level of heterogeneity

(I2>40%): symptoms of chest pain (RR), palpitations, back pain, sweating, weakness,

dyspnea, vomiting, left and right shoulder pain, headache and arm pain, and the co-

morbid conditions: a history of hypertension, previous AMI, diabetes and

hypercholesteremia.

In our review, we did not combine groups of patients with the diagnoses of AMI and

UA, nor were studies of patients with only chest pain included. The RR for the

symptom of chest pain and both the OR and RR for some other symptoms of AMI and

co-morbidities that showed a moderate to substantial level of heterogeneity must be

interpreted with care because there is considerable variation in the combined or pooled

results, and it may be misleading to report a combined summary measure. Heterogeneity

may be due to the studies’ different geographical locations, study designs, data-

collection methods, sample selection, and inclusion and exclusion criteria.

The discrepancy in heterogeneity between the effect measures (OR and RR) was largest

for the symptoms of chest pain and dyspnea. We could not determine the reason for the

heterogeneity associated with the RR for chest pain (I2 87% and RR 0.93; 95% CI 0.91,

0.95), but by removing 3 studies28, 34, 37, the I2 was reduced to 29%, with an RR of 0.95

(95% CI 0.94, 0.96). For the symptom of dyspnea, removing 2 studies,38, 39 which unlike

the other studies only included patients with ST-segment elevation myocardial

infarction, reduced I2 from 66% to 39% and changed the RR from 1.26 (95% CI 1.15,

1.37) to 1.23 (95% CI 1.14, 1.33).

2.5.7 Publication Bias

Funnel plots were used to assess for publication bias when 10 or more studies were

combined. The plots all appeared symmetrical, suggesting that publication bias was not

a major concern. Figure 4 displays the funnel plot for the pooled OR of chest pain.

32

2.6 Discussion

Our systematic review updates previous reviews on sex differences in symptom

presentation of AMI with the inclusion of additional studies, a more precise inclusion

criterion, and a wider search strategy. In particular, this review has added to the Canto et

al,18 study of symptom presentation in ACS because we only reviewed studies with

confirmed AMI. The present review is the first to conduct meta-analyses of sex

differences in chest-pain and other symptoms of AMI, and thus helps to quantify

differences in AMI presentation between men and women.

There is debate within the literature about whether OR and RR is the better effect

measure to use.83,84 Because this issue is beyond the scope of this article, we have

presented both effect measures so that our results are as informative as possible. The

majority of studies in this meta-analysis used chi-square tests of proportions to analyze

sex differences in symptom presentation of AMI, 5 studies40,54,55,65,69 presented ORs and

1 study69 presented RRs.

Figure 4: Funnel Plot for the Pooled OR of Chest Pain

Abbreviations: SE(log[OR]): Standard Error (logarithm[Odds Ratio])

Previous systematic reviews did not pool results or perform meta-analyses, so we could

not compare our pooled results. However, we did compare our pooled results with the

0.01 0.1 1 10 100

0

0.5

1

1.5

2OR

SE(log[OR])

33

findings of the individual studies that comprise the previous systematic reviews. Only

statistically significant results were presented. Also, we explored the effect of

adjustment for age and other comorbidities on the magnitude and direction of the

association between sex and AMI symptom.

2.7 Limitations of the Review

Our systematic review and meta-analyses were conducted by one investigator (LLC)

who reviewed the literature and extracted the data. However, the search strategy,

inclusion/exclusion criteria, data to be extracted, and analysis were based on a

consensus approach among all 3 authors, and any uncertainty about whether to include

an article or not was resolved through discussion. It was also beyond the scope of this

article to discuss the instruments used to collect the data for the individual studies and to

discuss symptom assessment strategies. A recent review85 did conduct subgroup

analyses to identify whether symptom assessment strategies (medical record review,

self-reports, or mixed methods) were associated with different symptom reports, and

found for most symptoms, the measurement strategy had no effect on the outcome.

Limitations outside of the control of the review authors included the following. Many of

the studies in our review did not include infarct location or type of infarction. In some

studies, data were abstracted from medical records, which may have led to under-

reporting of patients’ presenting symptoms, whereas other studies used questionnaires

and interviews to collect descriptions of symptoms retrospectively and are thus subject

to recall bias. It was also not possible to distinguish the chief symptom from other

associated symptoms in any study. Furthermore, the lack of a standardized data-

collection instrument has resulted in other reviews and individual studies combining

symptoms, for example arm and shoulder pain, jaw and neck pain, nausea and vomiting,

which make comparison between studies difficult. In addition, many studies had age

restrictions and excluded patients > 75 years. This is an important limitation because

women with AMI are generally older than men. One study did not report numeric data,

and crude results were estimated from tables and figures. Finally, only a small number

of studies (n=5) adjusted for age and other comorbidities, and inconsistencies between

studies in adjusting for these variables made comparison between studies invalid.

34

2.8 Implications for Clinical Practice / Policy

Our systematic review and meta-analysis examine symptom difference between men

and women with confirmed AMI and challenges the stereotypic Hollywood depiction of

a heart attack as a dramatic onset of chest pain and collapse. In particular, we have

shown that women with AMI are typically older than men, more likely to have a history

of CHF, significantly less likely to present with chest pain, and more likely than men to

present with fatigue, neck pain, syncope, right arm pain, dizziness and jaw pain.

International and national public health campaigns need to inform women of the wider

spectrum of possible symptoms of AMI and highlight the possible differences in

symptom presentation between men and women. We recommend current and future

health care providers are educated about sex differences in presentation of symptoms of

AMI. Likewise, primary and secondary care clinicians need to explain the possible

variation in AMI symptom presentation to their at-risk patients, to assist them in

recognition of a medical emergency requiring prompt response. In addition, emergency

care personnel (pre-hospital and emergency department clinicians) need to appreciate

that just because a patient does not have central sternal crushing chest pain, this does not

exclude the possibility of an AMI.

2.9 Implications for Future Research

Future research into sex differences in AMI presentation ideally should be prospective

to increase reporting accuracy and use a standardized symptom presentation checklist,

with the chief symptom of AMI distinguished from associated symptoms. Also, because

symptoms of AMI often occur in clusters, further research is needed to define clusters

of symptoms and sex differences in their presentation. We recommend future studies

adjust for age and test for age-sex interactions and, if possible, adjust for comorbidity or

risk factors in a standardized way to allow for comparisons between studies.

2.10 Conclusion

The results of this review indicate there are sex differences in the symptoms of AMI.

Women are significantly less likely than men to present with chest pain. Women are

much more likely than men to present with fatigue, neck pain, syncope, right arm pain,

dizziness, and jaw pain. We recommend current and future health care providers are

35

educated about sex differences in the presentation of symptoms of AMI. In addition, we

recommend that current international and national health campaigns on symptom

presentation of AMI continue to promote chest pain as the cardinal symptom of AMI

but also reflect a wider spectrum of possible symptoms of AMI and highlight the

possible differences in symptom presentation between men and women.

37

Chapter 3: Methods to Link Data

3.1 Introduction

The systematic review and meta-analysis described in Chapter 2 provide important

information to answer the first research question posed in Chapter 1, Section 1.4. It was

necessary to merge data from a number of sources to address the four remaining

research questions. All four of these research questions used data from the Emergency

Department Information System and SJA-WA data. In addition, the second research

question used the transcribed symptoms of MI from the emergency telephone call. The

third research question used data from the patient hospital medical record. The fourth

research question used data from the patient hospital medical record and mortality data.

The fifth research question used data from the transcribed symptoms of MI from the

paramedic patient care record. In this chapter, the term ‘linked data’ is defined, the data

sources are described, and the merging of the data and checking procedures that were

used are explained.

3.2 Data Linkage

In 1946, Dunn introduced the concept of record linkage and proposed the idea that each

person create a “Book of Life”, which begins with birth, ends in death and includes

records of important health and social events.86 Data linkage is defined as “the bringing

together, from two or more different sources, of data that relate to the same individual,

family, place or event.”87

The benefits of linking health records for research purposes have been described

previously.88,89 Linked data is used in epidemiology, utilization and outcome of health

services, aetiologic research and disease surveillance.89 Throughout the world there are

a number of population-based data linkage systems; for example, the Manitoba

Population Health Information System,90 Oxford Record Linkage Study,91 Scottish

Record Linkage System,92 Rochester Epidemiology Project,93 the Centre for Health

Services and Policy Research in British Columbia,94 and the Western Australian Data

Linkage System.89

The process of data linkage consists of five practical steps: data preparation, blocking or

38

sorting files or records in the same order of the unique identifier, matching records,

storage and, finally, merging the linked data.95 A unique identifier is a unique value

assigned to an individual such as a Medical Record Number or an ambulance case

number. Partial identifiers are not completely unique and may include a person’s name,

date of birth or street address.95

Data preparation describes the data sources used. The data used in the thesis include the

Emergency Department Information System (EDIS), SJA-WA data, the transcribed

symptoms of MI from the emergency telephone call and the paramedic PCR, Mortality

data, and the data from the patient’s hospital medical record.

3.3 Data Sources

3.3.1 EDIS

The EDIS contains data on ED activity in WA’s public hospitals and includes all patient

presentations, transfers and discharges, and has patient time-tracking information. The

principal clinical diagnosis is a mandatory data field which is entered into the EDIS by

clinical staff on patient discharge from the ED. The clinical diagnosis is electronically

mapped to the International Statistical Classification of Diseases and Related Problems,

10th Revision, Australian Modification (ICD-10-AM) codes.96

3.3.2 SJA-WA

The SJA-WA data is a computerised record of all cases attended by metropolitan

ambulances in WA. The database includes data from the paramedic patient care record

(PCR) and the computer aided dispatch (CAD) system. Once the call is assigned to an

ambulance, a ‘case number’ for that event is generated. The SJA-WA data includes

patient demographics, clinical problem codes and problem urgency assessed by

paramedics, clinical management provided by paramedics, priority to scene and event

times from the CAD. The CAD event times include the time the call was received; the

time the call was dispatched to the ambulance; and the times that the ambulance arrived

on scene, departed the scene, and arrived at the hospital. The PCR is also scanned and

stored in the SJA-WA database.

39

3.3.3 Transcribed Symptoms of MI from the Emergency Telephone Call and the

Paramedic PCR

The symptoms of MI handwritten by the paramedic on the PCR and the symptoms of

MI from the emergency telephone call were transcribed verbatim. The process of how

this occurred is outlined below in Section 3.4.

3.3.4 Mortality Data

The Mortality data contains all deaths registered in WA by the Registry of Births,

Deaths and Marriages. The Births, Deaths and Marriage Registration Act 1998 require

that a person’s death is registered within 14 days of the date of death. The data that are

extracted from the death certificate completed by the attending physician include date of

death, cause of death (text and ICD-coded by the Australian Bureau of Statistics (ABS)

and place of death (for example, hospital or residential address).

3.3.5 Patient Hospital Medical Record Data

The symptoms of MI, symptom-onset time, type of MI (ST segment elevated MI

[STEMI] / Non STEMI), presence of comorbid conditions (e.g. diabetes, hypertension,

heart failure), and whether or not the patient had a percutaneous coronary intervention

were extracted from the patient medical record at a single hospital.

3.4 The Process of Data Extraction and Merging of the Data

Table 6 outlines the process of data extraction and merging of the data. All ED

presentations in the Perth metropolitan area from 1 January 2008 to 31 October 2009

with a principal ED discharge code related to MI (i.e. I21) in adults over the age of 18

years were extracted from the EDIS and saved in SPSS (IBM Corp. Released 2011.

IBM SPSS Statistics for Windows, Armonk, NY: IBM Corp) by the The University of

Western Australia Emergency Medicine Assistant Professor Nick Gibson. The patients

who were transported by ambulance to ED were identified from the EDIS ‘transport

variable’ and saved in an Excel file by Linda Coventry (LC).

In WA there is no common matching variable such as a unique patient identification

number. The public hospitals share an 8-character alpha-numeric medical record

number but SJA-WA has its own numeric case number. The variable ‘ambulance

record’ in the EDIS and the variable ‘case number’ in the SJA-WA data are, in theory,

40

the same number; i.e., the ‘case number’ and ‘ambulance record’ entries for each patient

admission to ED should be identical. However, the EDIS variable ‘case number’ is

often missing, so it was necessary to identify the correct ‘case number’ at SJA-WA. To

link the data from the EDIS with the SJA-WA data, it was necessary to confirm that

these entries were correct. The checking and matching processes were undertaken at

SJA-WA ambulance operation centre in Belmont (by LC).

Table 6: Study Flow Chart for Data Extraction and Merging of the Data

EDIS • 2009 • EDIS data: All patients with a confirmed discharge diagnosis of MI were

extracted from EDIS and saved to a SPSS file (by Assistant Professor Nick Gibson)

• All patients transported by ambulance (‘transport variable’) were extracted and saved to an Excel file by Linda Coventry (LC)

Note: The EDIS variable ‘ambulance record’ and the SJA-WA variable ‘case number’ are the same number. However, the EDIS variable is often missing, so it was necessary to identify the correct number at SJA-WA Belmont.

SJA-WA Belmont • The excel file was transferred to SJA-WA Belmont • Using SJA-WA intranet and the call-card inquiry, missing ‘ambulance record’

numbers were found and added to the EDIS data Xcel file (by LC) - A new study number was created for all patients - The emergency telephone recordings were retrieved and saved as a wave sound

file (by LC) - In 2008 the phone recordings were saved to disc - In 2009 the phone recordings were saved electronically • The pdfs of the paper PCR were retrieved and saved (by LC) The Excel file, the emergency telephone recording wave file, and the pdfs of the

paper PCR were transferred to Emergency Medicine (EM) at Sir Charles Gairdner Hospital (SCGH) (by Professor Ian Jacobs)

EM SCGH • Symptoms of MI data: - Using the new ‘study number’ as the identifier, the symptoms of MI from the

telephone recordings were transcribed into a string variable in a SPSS data base - The symptoms of MI from the PCR were transcribed into a different string

variable in the same SPSS data base (by LC) • SJA-WA data: Using the SJA-WA variable ‘case number’ the SJA-WA data

was extracted (by Ms Lorraine Salo, SJA-WA Data Manager) Linkage of EDIS data to SJA-WA data

• In the EDIS data the variable ‘ambulance record’ was copied and renamed ‘case number’ (by LC)

• The EDIS data and the SJA-WA data were sorted by ‘case number’ and merged by (by LC)

Linkage of EDIS / SJA-WA data to Symptoms of MI data

• The EDIS / SJA-WA data and the Symptoms of MI data were sorted by ‘study number’ and merged by (by LC)

DATA AVAILABLE FOR PAPERS 2 & 5 Note: Paper 5 was completed later as it was first necessary to validate the

symptoms of MI and symptom-onset time between the paramedic PCR & the hospital medical record (Paper 3)

Linkage of EDIS data / SJA-WA data / Symptoms of MI data to Mortality data

• 2012 • The EDIS data / SJA-WA data / Symptoms of MI data to Mortality data

were linked using Linkagewiz software (by Assistant Professor Nick Gibson)

EDIS data / SJA- • The SPSS File was saved and cut-down to include only patients who arrived at

41

WA data / Symptoms of MI data / Mortality data to patients hospital medical record

SCGH (by LC) • The patients hospital medical record were found in the medical record

department at SCGH (by LC) • Symptoms of MI, type of MI, symptom onset-time, presence of comorbid

conditions, and percutaneous coronary intervention data were extracted and entered into the SPSS data base (by LC)

DATA AVAILABLE FOR PAPERS 3 & 4

The checking and matching process occurred using the SJA-WA intranet, where a query

was submitted using the ‘call card enquiry’. The EDIS patient details (surname and

transport date) were submitted and a list was generated of all patients with similar letters

in their surname who had been transported on that date. The ED patient was matched to

their SJA-WA ‘case number’ by assessing agreement on a combination of surname,

home address, ambulance booking date, and hospital destination. A new ‘study number’

was created for each patient to enable removal of the ‘case number’ and ‘ambulance

record’, and other data such as patient name, address and date of birth, which could be

used to identify patients.

After identification of the ambulance ‘case number’, the paper PCR and, the emergency

telephone call recordings were retrieved. Two systems were in place to record the

emergency telephone calls during the study period. In the first system used in 2008, the

emergency telephone call was identified by inserting a disk that contained recordings of

all calls received during the specified time period. The correct emergency telephone call

was identified by matching a combination of surname, pickup address, and phone

number. The emergency telephone call was then saved as wave sound file. In the second

system used in 2009, the emergency telephone calls were saved electronically. The

emergency telephone call was identified and saved as a wave sound file.

The Excel file, the emergency telephone recording wave sound files, and the electronic

copies (PDFs) of the paper PCR were transferred securely to The University of Western

Australia Department of Emergency Medicine at SCGH by Professor Ian Jacobs.

The symptoms of MI described on the emergency telephone call were transcribed

verbatim into a string variable in SPSS (IBM Corp. Released 2011. IBM SPSS Statistics

for Windows, Armonk, NY: IBM Corp) at SCGH (by LC). No identifying information

was transcribed, such as name or contact details. Additional information collected from

the telephone call included sex of the caller, relationship of the caller to the patient, and

location of the call. The symptoms of MI and symptom onset-time from the paramedic

42

PCR were transcribed into a different string variable in the same SPSS file (by LC).

The SJA-WA data was extracted using the variable ‘case number’ by Ms Lorraine Salo

the SJA-WA data manager at SCGH. To link the EDIS to SJA-WA data, the variable

‘ambulance record’ in EDIS was copied and renamed ‘case number’. Files were sorted

by ‘case number’ and merged. To link the merged EDIS and SJA-WA data sets to the

transcribed symptom of MI from the telephone call and PCR, the files were sorted by

‘study number’ and merged.

In 2012 the data set (EDIS / SJA-WA / telephone and PCR data) was linked to mortality

data97 by Assistant Professor Dr Nick Gibson using Linkagewiz.98 The rationale for

linking the data later was to extend the censor date (to 1 September 2011) and assess

survival. Probabilistic matching99 was used to link the data, and three basic steps were

followed: blocking of records that have a potential relationship; matching to determine

if records within a block were likely to be related; and linking matched records. The

Linkagewiz program uses an iterative approach to mathematically link databases by

comparing data fields in two files with surname, first given name, and initial for second

given name, date of birth, sex, and address as the principal matching fields. Clerical

checking of additional information was undertaken (by LC) for possible matches of

uncertain links; i.e., those that fall within a ‘grey area’ between definite matches and

definite non-matches. There is a degree of uncertainty in probabilistic data linkage,

therefore the challenge is to minimise the number of bad links (false positives) without

increasing the number of missed true links (false negatives). Clerical checking found an

additional seven patients who were in both the EDIS / SJA-WA / telephone and PCR

data set and the death data.

3.5 Data Validation

3.5.1 Validation of Data Entry of Symptom of MI in the SJA-WA Telephone call

Data

To validate the accuracy of the data entry of the symptoms of MI, a random sample of

the emergency telephone calls were checked (by LC). Using the random case selection

function of SPSS, a sample of 200 (10%) cases was selected from the data. The

symptoms of MI contained in the transcribed phone call file were checked for accuracy

43

by comparing them with the original wave sound file. Of the 200 cases, 197 phone call

transcripts matched the original wave sound file resulting in a 98.5% accuracy of data

entry. There were 317 symptoms of MI reported for the 200 cases. Of these, 314 were

the same as those recorded in the original wave sound file, i.e. 99.0% accuracy of data

entry.

3.5.2 Validation of the Linked Data Set – EDIS and SJA-WA

The linked data have been sourced from the EDIS, SJA-WA data, the emergency

telephone and PCR data. Before analysis could commence, it was necessary to validate

and ensure data integrity of the linkage. Patient surname, date of birth, and gender were

compared between the data sets to validate the linkage of the data from the EDIS to

SJA-WA data, and reasons for the differences are summarized in Table 7.

Table 7: Reasons for Differences between SJA-WA Data and EDIS Data

Surname

n (%) Date of birth

n (%) Gender n (%)

Incorrect entry into SJA-WA data 37 (49.2) 11 (61.1)

No PCR, unable to compare 3 (4.0) 5 (27.8)

Missing data on PCR 16 (11.7) 1 (1.3) 2 (11.1)

PCR and SJA-WA data match, but different to EDIS 3 (2.2) 35 (46.0)

Incorrect spelling 116 (84.7)

Totals 137 (100) 76 (100) 18 (100)

For the variable ‘surname’, there were 137 differences within the data sets. Reasons for

differences were incorrect spelling of the surname (n=116), no surname on the PCR

(n=16), and different surname in the data sets (n=3). All (n=135) of these differences

were reconciled via matching either home address, date of birth, or date and time of

arrival at a hospital. In two cases the merge was incorrect: in one case the ambulance

case number was incorrect, and in the other case the patient surname was incorrect.

These two cases were removed from the merged data set. In summary, the integrity

check of the merged data was 2072/2074 cases; i.e. 99.9% correct.

Seventy-six differences were found for ‘date of birth’ within the data sets. Reasons for

differences’ were incorrect data entry into SJA-WA data (n=37); PCR date of birth

matched SJA-WA data date of birth, but was different from EDIS date of birth (n=35);

44

no PCR, therefore unable to compare date of birth (n=3); and missing date of birth on

the PCR (n=1). All of these differences in date of birth were reconciled via matching

patients’ surnames and home addresses.

There were 18 differences in ‘gender’ within the data sets. Reasons for differences were

incorrect data entry into the SJA-WA data (n=11); no PCR, therefore unable to compare

(n=5); and missing data on PCR (n=2). All of these differences in gender were

reconciled via matching surnames and home addresses.

As correct age is vital to ensure that age adjustment is accurate in regression analysis we

also checked for age differences. When there were discrepancies between the date of

birth entered in the EDIS and the SJA-WA data, we assumed that the EDIS record was

correct. After validation of the data integrity all the identifiable patient details,

‘ambulance record’ and ‘case number’ were removed from the data set.

3.6 Conclusion

This chapter has defined the term ‘linked data’, and described the data sources, the data

extraction and the merging of the data and the validation procedures that were followed.

This information supplements the methodology included in Chapters 4, 5, 6, and 7. The

next chapters address the remaining research questions listed in Chapter 1, Section 1.4.

45

Chapter 4: Myocardial Infarction: Sex Differences in

Symptoms Reported to Emergency Dispatch

4.1 Introduction

This chapter is the Author’s Original Manuscript published in Prehospital Emergency

Care Journal, 2013; 17:193-202.2 This manuscript examines the symptoms of MI

reported during the emergency telephone call and the ambulance times for all patients

who presented to one of the seven Perth metropolitan hospital EDs over a 22 month

period. The symptoms of MI were extracted from the transcribed emergency telephone

call. This phase of the study aimed to answer the second research question posed in

Chapter 1, Section 1.4:

Are the symptoms, in particular chest pain, reported during the emergency

telephone call to SJA-WA and ambulance response times, the same for men

and women with MI?

To answer this question it was necessary to link the EDIS, SJA-WA data, and the

emergency telephone data. The detailed explanation of this data linkage in Chapter 3

expands on the brief description in this manuscript.

4.2 Abstract

4.2.1 Background

Emergency management of myocardial infarction (MI) is time critical, because

improved patient outcomes are associated with reduced time from symptom onset to

definitive care. Previous studies have identified that women are less likely to present

with chest pain.

4.2.2 Objective

We sought to measure the effect of sex on symptoms reported to the ambulance dispatch

and ambulance times for MI patients.

4.2.3 Methods

The Western Australia Emergency Department Information System (EDIS) was used to

46

identify patients with emergency department (ED) diagnoses of MI (ST-segment

elevation MI and non-ST-segment elevated MI) who arrived by ambulance between

January 1 2008 and October 31 2009. Their emergency telephone calls to the ambulance

service were transcribed to identify presenting symptoms. Ambulance data were used to

examine ambulance times. Sex differences were analysed using descriptive and age-

adjusted regression analysis.

4.2.4 Results

Of 3,329 MI patients who presented to Perth EDs, 2,100 (63.1%) arrived by ambulance.

After pre-defined exclusions, 1,681 emergency calls were analysed. Women (n=621,

36.9%) were older than men (p<0.001) and even after age-adjustment were less likely to

report chest pain (Odds Ratio [OR]=0.70; 95% Confidence Interval [CI] 0.57, 0.88).

After age-adjustment, ambulance times did not differ between male and female patients

with chest pain. Women with chest pain were less likely than men to be allocated a

‘priority 1’ (lights and sirens) ambulance response (Men 98.3% vs. Women 95.5%;

OR=0.39; 95% CI 0.18, 0.87).

4.2.5 Conclusion

Ambulance dispatch officers (and paramedics) need to be aware of potential sex

differences in MI presentation in order to ensure appropriate ambulance response.

4.2.6 Key Words

Emergency medical services; myocardial infarction; symptoms; sex differences;

emergency medical dispatch

4.3 Background

Current guidelines100,101 recommend prompt activation of the emergency medical

service (EMS) if a person is experiencing symptoms suggestive of a myocardial

infarction (MI). The emergency ambulance is usually the quickest mode of transport to

hospital, especially in urban areas. In addition, paramedics are trained to initiate

treatment and equipped to treat life threatening cardiac arrhythmias should they occur.

The time from onset of MI symptoms to treatment in a hospital influences survival, and

47

rapid reperfusion of an obstructed coronary artery is associated with reduced

mortality.102 Additionally, current Australian and American College of Cardiology and

American Heart Association (ACC/AHA) guidelines for the treatment of ST-segment

elevation myocardial infarction (STEMI) recommend the time from first medical

contact to percutaneous coronary intervention (PCI) to be as-soon-as-possible103 or less

than 90 minutes,19,24 with suggestions that EMS to PCI time should be less than 90

minutes as well.24,104 Many studies have investigated reasons for underuse of emergency

ambulances105,106 and delay in seeking treatment107,108 in MI patients. Research has

shown that pre-hospital median delays range from 84 to over 400 minutes.107

However, no studies were found that have investigated symptoms of MI reported during

the telephone call to emergency dispatch as a possible source of delay. Correct

recognition of symptoms of a MI is crucial for the ambulance dispatcher to allocate a

“priority 1” (lights and sirens) ambulance response. Most ambulance dispatch systems

are primed to rapidly respond to mention of chest pain as a symptom, but not all MI

patients experience chest pain as a symptom.109 Previous studies have identified that

women are less likely to present with chest pain1,18 and have prolonged prehospital

delays.107,110 Our primary aim was to compare symptoms, in particular chest pain,

reported during the emergency telephone call for men and women with MI. We also

compared the relationship between symptoms reported and ambulance responses in men

and women, with adjustment for age.

4.4 Methods

4.4.1 Study Setting and Cohort

This retrospective cohort study reviewed emergency telephone calls of all adult patients

with an emergency department (ED) discharge diagnosis of MI transported by St John

Ambulance (SJA) in Western Australia (WA) to one of the seven Perth metropolitan

EDs between January 1, 2008 and October 31, 2009. The Perth metropolitan area covers

an area over 5,000 square kilometers111 and has a population of 1.7 million, with 9.2%

aged ≥ 65 years and 3% aged ≥ 75 years.112 Two and a half per cent of the population

are indigenous (Aboriginal and Torres Strait Islander), with the overseas born

population largely of Asian (23%) and European (19%) descent.112 SJA-WA is the

single provider of prehospital emergency care and transport for WA and is staffed by

48

paramedics who attend over 200,000 calls per year.28 In WA (as for the whole of

Australia) the emergency telephone number is “triple zero” (0-0-0).28 Calls are

answered by an operator who asks whether the emergency requires “police, fire or

ambulance”. Calls requesting ‘ambulance’ are immediately transferred to the

Ambulance Operations Centre located at SJA-WA headquarters in Perth. All telephone

calls are recorded and stored permanently.

At the time of the study SJA-WA ambulance dispatch operators completed a two- week

in-house course in dispatch and prioritizing ambulances. The dispatch operators were

not medically trained. The dispatch operator followed a written in-house protocol asking

a series of scripted questions that establish location of the incident, phone number of the

caller, chief complaint, and other complaint-specific questions. A computer-aided

dispatch (CAD) System automatically records the time the call was received, the time

the call was dispatched to the ambulance, and the time the ambulance arrived on scene,

departed the scene, and arrived at the hospital. A priority is allocated to each call:

“Priority 1” (lights and sirens) response represents an emergency, “Priority 2” response

represents an urgent call, and “Priority 3” response represents a non-urgent call.28

Priority responses were assigned by the dispatch operator based on a list of predefined

conditions for each priority level, e.g. “chest pain” was allocated as a priority 1. Priority

allocation from scene to hospital is determined by the paramedic, based on patient’s

clinical status. During the study period, current practice of paramedics did not include

acquisition of a 12-lead electrocardiogram or direct transfer to a percutaneous coronary

intervention laboratory.

All adult patients with an ED discharge diagnosis of MI (STEMI and non-STEMI) who

were transported to ED by SJA-WA during the study period were identified from the

Perth Emergency Department Information System (EDIS). EDIS is a real-time patient-

tracking system containing utilization and patient disposition data for each ED in

Perth.113 The principal clinical diagnosis is a mandatory field entered by clinical staff on

patient discharge from the ED. The clinical diagnosis is electronically mapped to the

International Classification of Diseases and Related Problems, 10th Revision,

Australian Modification (ICD-10-AM) codes.96

Patient details identified from EDIS were used to retrieve the emergency phone call

made to SJA-WA, which was saved as a “.wav” file. Patient symptoms, as described by

49

the caller, were transcribed verbatim by one author (LLC). To assess transcription

accuracy a random sample of 200 phone calls were reviewed by the same author (LLC).

Of the 200 phone calls, 197 were accurate indicating 98.5% data-entry accuracy. Initial

lists of possible symptoms of MI were created from an extensive literature search and

clinical expertise, with additional symptoms added as required from the telephone

transcripts. Symptoms were coded “yes” if stated in the telephone call or “no” if

declared absent or not stated. Multiple symptoms for individual patients were possible.

Additional information pertaining to the call was collected, including sex of the caller

and their relationship to the patient, and location of the call.

The SJA-WA patient database contains computerised records of all cases attended by

ambulances in WA from the CAD system and the paramedic-completed patient care

record (PCR), which includes dispatch priority, clinical problem codes, and clinical

management. The EDIS data were linked to the SJA-WA database, together with the

transcribed symptoms from the emergency phone call to SJA. Only the index hospital

admission was included for patients who subsequently transferred to a second hospital.

Patients were excluded if they arrived by private transport, Royal Flying Doctor

Service, helicopter, or other voluntary transport services.

4.4.2 Statistical Methods

Data were presented as frequencies with percentages, or means ± standard deviations.

Ambulance times were described using means, standard deviations, medians and inter-

quartile ranges. Comparisons of baseline characteristics between men and women were

performed using chi-square tests for categorical variables, the Mann-Whitney test for

medians, and Student’s t tests for continuous variables.

For each symptom of MI, logistic regression was used to estimate the odds ratio (OR)

and its 95% confidence interval (CI) for the symptom being reported by women

compared with men. Models were subsequently adjusted for age (as a continuous

variable) and age-sex interaction was tested. For the symptom “chest pain”, a stratified

analysis that dichotomised age into < 70 years and ≥70 years, with men aged <70 years

as the comparison group was also conducted. Age 70 years was selected as the cutoff

based on previous research demonstrating that presentation with chest pain is less

common in individuals over 70 years of age.114,115

50

Linear regression was used to model sex differences in ambulance times for patients

with chest pain and patients without chest pain. Because model residuals were skewed,

time intervals were log transformed. Beta coefficients (and 95% CIs) that estimate the

difference in mean log time were reported. For patients with chest pain and patients

without chest pain logistic regression was used to compare the odds of women being

dispatched as a priority 1 ambulance response with those of men. Both linear and

logistic regression modeling included adjustment for age (as a continuous variable) and

testing for age-sex interaction.

All statistical analyses were performed in PASW Release Version 17.0 (IBM SPSS Inc.,

2008, Chicago, IL, www.spss.com). Two-sided p-values <0.05 were considered

significant. Ethics approval was obtained for this study from the University of Western

Australia, number RA/4/1/2428. See Appendix K.

4.5 Results

During the study period, January 2008 to October 2009, of the 3,329 (women, n = 1115;

men, n = 2214) patients who were discharged from a Perth ED with a diagnosis of MI,

63.1% (women, n = 759; men, n = 1341) arrived by ambulance. More women (68%)

than men (60%) arrived by ambulance (p<0.001). Following exclusions, as detailed in

Figure 5, 1,681 emergency telephone calls to SJA-WA were analyzed. Of these, 621

(36.9%) were for female patients.

Women were older than men (mean age 77.6 vs. 69.1 years, p<0.001). Differences in

the relationship of caller to patient and the location of patient at time of the emergency

call were found between men and women (Table 8).

51

Figure 5: Study Flow Diagram

EDIS Data

EDIS, Emergency Department Information System; MI, Myocardial Infarction; RFDS, Royal Flying Doctor Service; SJA-WA, St John Ambulance-Western Australia; PCR, Patient Care Record; ED, Emergency Department

EDIS confirmed discharge diagnosis of MI (Jan 1, 2008 to Oct 31, 2009)

n=3,329

Excluded 1,229 • private transport (n=1,155) • RFDS transfer (n=47) • other (n=20) • helicopter (n=5) • police (n=1) • voluntary transport (n=1)

Arrived by

ambulance

n=2,100

Excluded 26

• no SJA ambulance record

(transferred by another

transport service)

Excluded 32

• transferred to a second

hospital, counted at first

hospital

SJA-WA records

n=2,040

Excluded 198

No emergency call

• RFDS transfer (n=64)

• hospital transfer (n=18)

• ambulance flagged down (n=2)

• missing, error in recording

system (n=114)

SJA telephone

calls n=1,842

Excluded 161

• ED nurse call. Patient

used own transport to

first hospital and then

transferred to second

hospital (n=155)

• dispatcher call back, no

symptom information

(n=6)

Telephone calls

analysed

n=1,681

Men=1,060

Women=621

Integrity check of merged

EDIS data to SJA data

2072/2074 = 99.9% merge

Excluded 2

• wrong PCR (n=1)

• correct PCR but

wrong patient (n=1)

n=2,072

n=2,074

SJA-WA

Data

Telephone

Transcripts

52

Table 8: Sex Differences in the Descriptive Characteristics of the Emergency Phone

Calls for Patients with Myocardial Infarction

Characteristic Men (patients)

n=1060 Women (patients)

n=621 p-value

Mean Age, years (± SD), years 69.1 (14.4) 77.6 (12.8) <0.001* Duration of Phone Call - median (IQR), seconds

80.4 (67.8, 123.3) 79.2 (65.4, 123.6) 0.13

Sex of Caller, n (%) Male Female

322 (30.3) 738 (69.7)

179 (28.8) 442 (71.2)

0.50

Relation of Caller to Patient Self Spouse Family / Friend Professional† Other Bystander Unsure

129 (12.2) 294 (27.7) 226 (21.3) 321 (30.3)

13 (1.2) 27 (2.6) 50 (4.7)

59 (9.5)

48 (7.7) 204 (32.8) 252 (40.6)

8 (1.3) 11 (1.8) 39 (6.3)

0.09

<0.001* <0.001* <0.001*

0.91 0.30 0.17

Location of Patient at time of emergency call Home Relative / Friend / Work Medical Centre Nursing home‡ Other Unsure

714 (67.4) 53 (5.0)

127 (12.0) 89 (8.4) 61 (5.7) 16 (1.5)

403 (64.9) 17 (2.7) 46 (7.4)

133 (21.4) 19 (3.1)

3 (0.5)

0.18 0.02*

0.002* <0.001* <0.001*

0.68

Data are expressed as n (%) unless otherwise specified. *Statistical significant difference. †Includes health professional, medical receptionist and security personnel. ‡ Includes residential care facilities. IQR = inter-quartile range; SD = standard deviation.

4.5.1 Sex Differences in Chest Pain Reported for Patients with Myocardial

Infarction during the Emergency Telephone Call

As shown in Table 9, women were less likely than men to report chest pain (54% vs.

69%; OR=0.54; 95% CI 0.44, 0.67; p<0.001), even after age adjustment (OR=0.70;

95% CI 0.57, 0.88; p=0.002). There was no significant interaction between sex and age

(p=0.10); however, in age-stratified analysis, men aged ≥70 years (OR=0.48; 95% CI

0.37, 0.63; p<0.001) and women aged ≥70 years (OR=0.28; 95% CI 0.22, 0.37;

p<0.001) were less likely to have reported chest pain when compared with men aged <

70 years.

53

Tabl

e 9:

Se

x D

iffer

ence

s in

Sym

ptom

s Rep

orte

d fo

r Pat

ient

s with

Myo

card

ial I

nfar

ctio

n du

ring

the

Emer

genc

y Te

leph

one

Cal

l

Sym

ptom

*

Wom

en

n= 6

21

n (%

)

Men

n=

1,06

0

n (%

)

Una

djus

ted

OR

(9

5% C

I)

p-V

alue

A

ge-A

djus

ted

OR

(9

5% C

I)

p-V

alue

Che

st p

ain

33

8 (5

4.4)

72

8 (6

8.7)

0.

54 (0

.44,

0.6

7)

<0.0

01†

0.70

(0.5

7, 0

.88)

0.

002†

Le

ft ar

m p

ain

90 (9

.7)

105

(9.9

) 0.

97 (0

.70,

1.3

6)

0.87

1.

26 (0

.89,

1.8

0)

0.19

R

ight

arm

pai

n 40

(6.4

) 11

4 (1

0.8)

0.

57 (0

.39,

0.8

3)

0.00

3†

0.70

(0.4

8, 1

.04)

0.

08

Jaw

/ th

roat

/ ne

ck p

ain

26 (4

.2)

39 (3

.7)

1.14

(0.6

9, 1

.90)

0.

60

1.39

(0.8

2, 2

.37)

0.

22

Swea

tines

s or c

lam

min

ess

51 (8

.2)

136

(12.

8)

0.61

(0.4

3, 0

.85)

0.

004†

0.

71 (0

.50,

1.0

1)

0.06

Sh

ortn

ess o

f bre

ath

176

(28.

3)

273

(25.

8)

1.14

(0.9

1, 1

.42)

0.

25

1.05

(0.8

4, 1

.33)

0.

66

Abd

omin

al /

epig

astri

c pa

in

19 (3

.0)

24 (2

.3)

1.38

(0.7

6, 2

.50)

0.

29

1.02

(0.5

5, 1

.91)

0.

94

Nau

sea

31 (5

.0)

43 (4

.0)

1.24

(0.7

8, 1

.99)

0.

37

1.35

(0.8

2, 2

.22)

0.

23

Vom

iting

46

(7.4

) 52

(4.9

) 1.

55 (1

.03,

2.3

4)

0.04

† 1.

57 (1

.02,

2.4

1)

0.04

† Sy

ncop

e / c

olla

pse

/ unc

onsc

ious

54

(8.7

) 67

(6.3

) 1.

35 (0

.93,

1.9

2)

0.11

1.

42 (0

.96,

2.1

0)

0.08

W

eakn

ess

34 (5

.5)

28 (2

.6)

2.14

(1.2

8, 3

.56)

0.

004†

1.

62 (0

.95,

2.7

5)

0.08

B

ack

pain

28

(4.5

) 30

(2.8

) 1.

62 (0

.96,

2.7

4)

0.07

1.

62 (0

.93,

2.8

1)

0.09

U

nwel

lnes

s 42

(6.7

) 47

(4.4

) 1.

56 (1

.02,

2.4

0)

0.04

† 1.

28 (0

.82,

2.0

0)

0.29

Fa

ll 51

(8.2

) 37

(3.5

) 2.

47 (1

.60,

3.8

2)

<0.0

01†

1.40

(0.8

9, 2

.21)

0.

15

Con

fusi

on

26 (4

.2)

20 (1

.9)

2.27

(1.2

6, 4

.11)

0.

007*

1.

59 (0

.86,

2.9

4)

0.14

*Mul

tiple

sym

ptom

s pos

sibl

e.

† O

R si

gnifi

cant

ly d

iffer

ent f

rom

1.

CI =

con

fiden

ce in

terv

al; O

R =

odd

s rat

io (m

en a

s ref

eren

ce g

roup

).

54

4.5.2 Differences in Other Symptoms Reported for Patients with Myocardial

Infarction during the Emergency Telephone Call

As shown in Table 9, women were more likely than men to present with vomiting (7.4%

vs. 4.9%; OR=1.55; 95% CI 1.03, 2.34; p=0.04), even after age adjustment (OR=1.57;

95% CI 1.02, 2.41; p=0.04). Greater odds of vomiting in women persisted in subgroup

analyses of chest pain only patients, but not in patients who did not report chest pain.

In a subgroup analysis of patients who did not report chest pain there were no

statistically significant differences between other reported symptoms. The most

common symptoms in this subgroup included shortness of breath (38% women vs. 32%

men); a fall (17% women vs. 11% men); syncope, collapse or unconsciousness (17%

women vs. 18% men); feeling unwell (11% women vs. 8% men); weakness (9% women

vs. 7% men); confusion (8% women vs. 5% men); and vomiting (8% women vs. 8%

men).

4.5.3 Sex Differences in Ambulance Times

As shown in Figure 6, compared with men, women had statistically significantly longer

median on-scene time (19 vs. 17.7 minutes; p<0.001) and call to hospital time (48 vs.

46.5 minutes; p=0.009). The greatest component of pre-hospital time for both men and

women was on-scene time.

As shown in Table 10, there were no sex differences in any component of ambulance

times, except for on-scene time for the subgroup of MI patients with chest pain. The

mean on-scene time for women was 1 minute longer than it was for men (p=0.001), but

after age-adjustment, mean on-scene time did not differ by sex.

55

Figure 6: Boxplot Showing Sex Differences in Times for Each Component of

Prehospital Time for Men and Women (n=1681)

*Statistically significant difference, the Mann-Whitney test was used to examine differences in prehospital time. Box encloses the middle 50% of times (the IQR); the horizontal line marks the median. ⁰Outlier, value is between 1.5 and 3 IQR (box lengths) from the end of the box. Extreme outlier; value is more than 3 IQR from the end of the box. Data on one extreme outlier not shown, ‘Scene to hospital’ (180 minutes) and ‘Call to hospital’ (220 minutes).

56

Tabl

e 10

: Sex

Diff

eren

ces i

n A

mbu

lanc

e Ti

mes

for P

atie

nts w

ith M

yoca

rdia

l Inf

arct

ion

who

had

Che

st P

ain

and

thos

e w

ho d

id n

ot h

ave

Che

st

Pain

PA

TIE

NT

S W

ITH

CH

EST

PA

IN

Men

(n=7

29) W

omen

(n=3

37)

PAT

IEN

TS

WIT

HO

UT

CH

EST

PA

IN

Men

(n=3

31) W

omen

(n=2

84)

Am

bula

nce

Tim

e In

terv

al

Tim

e (m

inut

es)

Una

djus

ted

Bet

a C

oeff

icie

nt*

(95%

CI)

p-

Val

ue

Age

-adj

uste

d B

eta

Coe

ffic

ient

* (9

5% C

I)

p-V

alue

Tim

e (m

inut

es)

Una

djus

ted

Bet

a C

oeff

icie

nt*

(9

5% C

I)

p-V

alue

Age

-adj

uste

d B

eta

Coe

ffic

ient

* (9

5% C

I)

p-V

alue

M

ean

(±SD

) M

edia

n (I

QR

) M

ean

(±SD

) M

edia

n (I

QR

)

Cal

l to

on-s

cene

M

en

Wom

en

11

.8(8

.7)

11.2

(6.5

)

10

.1(7

.5, 1

3.2)

10

.0(7

.6, 1

2.6)

-0

.02(

-0.0

8, 0

.04)

0.

52

-0

.02(

-0.0

8, 0

.05)

0.

60

16

.7(1

3.3)

16

.8 (1

2.8)

12

.8(8

.8, 1

9.8)

12

.5(9

.1, 2

0.0)

0.

02(-

0.08

, 0.1

2)

0.67

-0

.04(

-0.1

4, 0

.06)

0.

44

On-

scen

e

Men

W

omen

18

.1(7

.2)

19.1

(5.9

)

17

.3(1

3.4,

22.

4)

18.7

(14.

9, 2

2.6)

0.

09(0

.03,

0.1

4)

0.00

1†

0.

04(-

0.02

, 0.0

9)

0.18

20

.4(9

.3)

21.1

(9.4

)

18

.8(1

4.3,

24.

8)

19.7

(14.

8, 2

6.2)

0.

04(-

0.05

,0.1

2)

0.40

-0

.02(

-0.1

0, 0

.07)

0.

74

On-

scen

e to

ho

spita

l M

en

Wom

en

17

.6(1

0.2)

17

.7(9

.5)

16

.0(1

0.8,

22.

6)

15.7

(11.

3, 2

2.9)

0.

01(-

0.07

, 0.0

8)

0.80

0.

02(-

0.06

, 0.1

0)

0.66

16

.7(1

2.6)

17

.2(9

.1)

14

.9(9

.8, 2

1.1)

15

.3(1

1.1,

21.

7)

0.

10(-

0.01

, 0.1

9)

0.06

0.

09(-

0.02

, 0.1

9)

0.10

C

all t

o ho

spita

l M

en

Wom

en

47

.6(1

6.6)

48

.0(1

3.6)

45

.4(3

7.3,

54.

3)

46.5

(38.

8, 5

6.1)

0.

02(-

0.02

, 0.0

6)

0.29

0.

01(-

0.04

, 0.0

5)

0.79

53

.8(2

1.2)

55

.1(2

0.0)

50

.1(3

9.7,

64.6

) 49

.8(4

2.1,

64.

4)

0.

04(-

0.02

, 0.1

0)

0.20

-0

.01(

-0.0

6,0.

06)

0.92

*Am

bula

nce

times

are

log

trans

form

ed.

† B

eta-

coe

ffici

ent s

igni

fican

tly d

iffer

ent f

rom

0 (m

en a

s ref

eren

ce g

roup

). C

I = c

onfid

ence

inte

rval

; IQ

R =

inte

r-qu

artil

e ra

nge;

SD

= st

anda

rd d

evia

tion.

57

4.5.4 Sex Differences in Priority Allocation Total Time from Emergency Call to

Hospital for Each Priority Response

As shown in Table 11, women with chest pain were less likely than men to be allocated

a priority 1 ambulance response after age-adjustment (98.3% vs. 95.5%; OR=0.39; 95%

CI 0.18, 0.87; p=0.02). Also shown in Table 11, there were no sex differences in total

time from emergency call to hospital for each priority response for patients with and

without chest pain. However, there was an increase in total call-to-hospital time for both

men and women who were allocated a priority 2 or 3 response compared with a priority

1 response.

58

Tabl

e 11

: Sex

Diff

eren

ces i

n A

mbu

lanc

e Pr

iorit

y R

espo

nse

and

Tota

l Tim

e fr

om C

all t

o H

ospi

tal f

or P

atie

nts w

ith M

yoca

rdia

l Inf

arct

ion

who

had

Che

st P

ain

and

thos

e w

ho d

id n

ot h

ave

Che

st P

ain

PA

TIE

NT

S W

ITH

CH

EST

PA

IN

Men

(n=7

29) W

omen

(n=3

37)

PAT

IEN

TS

WIT

HO

UT

CH

EST

PA

IN

Men

(n=3

31) W

omen

(n=2

84)

Prio

rity

Res

pons

e N

o. o

f ev

ents

n

(%)

Age

-adj

uste

d O

R

(95%

CI)

p-

valu

e

Tot

al ti

me

Cal

l to

Hos

pita

l T

ime

(min

utes

) N

o. o

f ev

ents

n

(%)

Age

-adj

uste

d O

R

(95%

CI)

p-

valu

e

Tot

al ti

me

Cal

l to

Hos

pita

l T

ime

(min

utes

)

Mea

n (S

D)

Med

ian

(IQ

R)

Mea

n (S

D)

Med

ian

(IQ

R)

Prio

rity

1

Men

W

omen

717

(98.

3)

322

(95.

5)

0.

39 (0

.18,

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59

4.6 Discussion

To our knowledge, this is the first study to analyze sex differences in symptoms

reported during the emergency telephone calls for (ED confirmed) MI patients. Even

after age-adjustment women were much less likely than men to report chest pain.

Additionally, women were less likely than men to have a priority 1 ambulance response.

Also, the median total time from emergency call to hospital for men and women who

were allocated a priority 2 or 3 ambulance response was longer. Finally, less than two-

thirds of MI patients utilized EMS for transport to the hospital. Other studies that have

examined emergency telephone calls either have not focused on confirmed MI cases or

have not investigated sex differences. We believe these findings add to the literature on

MI patients transported by EMS and offer an opportunity to improve care by stimulation

awareness of potential sex differences in MI presentation.

4.6.1 Sex Differences in Chest Pain

The reasons why women with MI experience less chest pain and are more likely to

report vomiting than men are not entirely understood. Numerous studies have examined

sex differences in symptom presentation of MI, but most have abstracted data from

medical records or interviewed patients after MI. Recent studies1,116 found that women

were less likely than men to experience chest pain. Men and women with MI may have

different locations of obstructing lesions,117,118 and women have been reported to have

less obstructive coronary disease at angiography.119-121 This may lead to different

combinations of sympathetic and vagal stimulation, resulting in differences in the

reporting of pain and vomiting.122,123 Also, it is well known that women with MI are

older1,119,122 and have more co-morbid conditions such as diabetes,1,119,122

hypertension1,77,119 and heart failure,1,77,119 and these conditions have been associated

with MI without pain.64,122,124

For patients who did not report chest pain, there were no sex differences in the

symptoms reported, possibly due to insufficient statistical power due to small numbers.

The most common non-chest pain symptoms for both men and women were shortness

of breath, a fall, or collapse, syncope or unconsciousness. These symptoms are similar

to those found in a study109 from a large multi-centre prospective trial of patients

presenting to ED with suspected acute coronary syndrome but without chest pain. The

two most common symptoms at presentation in this study were shortness of breath and

60

syncope.109

4.6.2 Sex Differences in Ambulance Times

Although on-scene time and total ambulance time intervals were statistically

significantly longer in women compared with men, this is unlikely to be clinically

significant. Other studies analysing ambulance times have found the longest component

of pre-hospital time is on-scene time.125-127

Only one study126 reported sex differences in ambulance times and found women were

delivered to hospital 2.3 minutes slower on average than men.

4.6.3 Sex Differences in Priority Allocation

For patients with chest pain, even after age adjustment, women were less likely than

men to be allocated a ‘priority 1’ ambulance response Other studies have found women

with MI were less likely than men to be allocated an Advanced Life Support ambulance

(76% vs. 92%)128 or a ‘priority 1’ ambulance (67% vs. 81%).62 As to be expected

irrespective of chest pain status we have shown both men and women with MI who

were not allocated a ‘priority 1’ ambulance response had longer median total time from

emergency call to hospital. Further research is required to investigate strategies to better

identify patients who do not present with classic MI symptoms, otherwise they are

unlikely to be allocated to a high priority response and thus will have increased delay to

definitive treatment.

On closer analysis of specific phone calls, the reason why some of the patients with

chest pain were not allocated a priority 1 ambulance response was they were not

experiencing chest pain at time of the emergency call. Some had experienced chest pain,

they had taken sublingual nitrate, and their chest pain had resolved. Several had

experienced chest pain earlier and had consulted their general practitioner, who had

identified changes on the electrocardiogram or a positive test for troponin. While

telephone dispatchers were instructed to ask whether the patient was experiencing chest

pain at time of the call, some dispatchers allocated a priority 2 response to patients if

their chest pain had resolved, contrary to existing SJA-WA policy. Even though

allocating a priority 2 response was incorrect, after these 19 calls were removed from

the analysis, we found no difference in ‘priority 1’ response between men and women.

61

Recently, SJA-WA has introduced dispatch protocols (Medical Priority Dispatch

System129 – Version 12 AUE-std) with specific scripted dispatcher-asked questions,

which ensures that all patients who have had chest pain are allocated a priority 1

response.

Finally, this study found a persistent underuse of emergency ambulance for the whole

cohort (63%), with significantly more women (68%) than men (60%) using an

ambulance. This finding is comparable to the 53% to 70% of MI patients transported by

emergency ambulances in other studies.105,106 Also, consistent with other studies,

women were more often transported by ambulance than men, possibly a reflection of the

fact women tended to be older.106,130 Nonetheless, reasons that more than 35% of all MI

patients in Perth chose not to call an ambulance is of concern and warrants further

exploration. It is recommended that all patients experiencing symptoms of an MI call

the emergency ambulance.100,101

4.7 Limitations

The strength of our study is that it is a population-based cohort of patients with ED-

confirmed MI (STEMI / non-STEMI), drawn from all public hospital EDs in the Perth

metropolitan area. Whilst we are confident in sex differences found in the MI patients

experiencing chest pain, some caution is required in the interpretation of sex differences

in other symptoms, including vomiting. It is important to note that the ambulance

dispatch officer did not attempt to elicit the full spectrum of symptoms experienced by

the patient. If chest pain was mentioned, the need for a priority 1 response was

established and further questioning about other symptoms was unlikely. As such,

patients without chest pain were likely to report more of the other symptoms.

Also, SJA-WA had no formalised or routine call taker quality assurance program

undertaken during the study period. Variations may have been caused by different

subjective interpretations of the symptoms reported between dispatch operators. We

also need to highlight the caller was often not a first party caller (i.e., self) and the

majority of calls were from a second- or third-party caller. In three other studies,131-133

first-party callers comprise 5 – 11%; as such, we would suggest our data is similar. The

relationship of the caller to the patient and the location of the patient at the time of the

emergency call were also different for male and female patients.

Another limitation is that we did not include MI patients for whom an ambulance was

62

called but who were pronounced dead by the paramedics and not taken to an ED.

Although unlikely, it is possible that such patients may have reported a different pattern

of symptoms. Also, the ambulance record (n=26) and the emergency telephone call

(n=198) were missing for a number of patients and could not be analyzed.

We were also unable to identify patient co-morbid conditions or location of the

obstructed coronary artery that may be associated with atypical symptom presentation

of MI. However, our primary research question was to determine sex differences in

symptoms (particularly chest pain) during the emergency telephone call in MI patients

and examine the effect of such differences on ambulance response.

4.8 Conclusion

During the emergency telephone call for an ambulance, women with an ED-confirmed

diagnosis of MI were less likely than men to report chest pain as a symptom. Women

with chest pain were also less likely to be allocated a priority 1 ambulance response.

Overall, ambulance times did not differ between men and women, although women had

a marginally longer on-scene time. Ambulance dispatch officers and paramedics need to

be aware of the potential sex differences in MI presentation, in order to ensure

appropriate ambulance response.

63

Chapter 5: Symptoms of Myocardial Infarction: Concordance

between Paramedic and Hospital Records

5.1 Introduction

This chapter is the Author’s Original Manuscript published in Prehospital Emergency

Care Journal, 2013; 18:393-401.3 This manuscript examines the accuracy of the

paramedic patient care record (PCR) at a single hospital. The symptoms of MI were

extracted from the paramedic PCR and the hospital medical record. The next phase of

the study aims to answer the third research question posed in Chapter 1, Section 1.4:

Are paramedic records a reliable source of information about presenting

symptoms of MI and onset-time of symptoms compared with the

documentation in the hospital medical record?

This phase of the study was important as it validated the accuracy of the paramedic

documentation that was used to answer the remaining research questions. To answer

this question it was necessary to link the EDIS data, SJA-WA data, PCR data, and

hospital medical record data. The detailed explanation of this data linkage in Chapter 3

expands on the brief description in this manuscript.

5.2 Abstract

5.2.1 Background

To further reduce time to definitive therapy for acute myocardial infarction (MI)

patients, the focus of research needs to be on better understanding prehospital delay in

recognition and response to symptoms. Paramedic clinical records can serve as a

convenient source of data for such studies, but their accuracy needs to be established.

5.2.2 Objectives

This study aimed to determine the concordance of the symptoms and symptom-onset

time recorded in the paramedic patient care record (PCR) with those recorded in the

hospital medical record for MI patients.

64

5.2.3 Methods

A retrospective review of paramedic and hospital medical records was undertaken

between January 1, 2008 and October 31, 2009 for all patients with an emergency

department (ED) discharge diagnosis of MI at a single teaching hospital in Perth,

Western Australia. The symptoms of MI and onset times documented in the paramedic

PCR were compared with those recorded in the hospital medical record, which was

considered the “gold standard.” The study assessed differences in documentation using

McNemar’s tests, and concordance was described by kappa and adjusted kappa

statistics, sensitivity, specificity, positive, and negative predictive value (PPV, NPV).

5.2.4 Results

Of 810 patients with an ED discharge diagnosis of MI, 584 (71%) patients arrived by

ambulance and 509 patients had a paramedic PCR. After exclusions, 400 patients had

both paramedic PCR and hospital medical records available for review. Of 21

documented MI symptoms, the majority (71.4%) had adjusted Kappa statistics greater

than 0.75, and observed agreement greater than 90%. For the symptom of chest pain,

sensitivity, specificity, PPV and NPV were all over 85%. Where recorded in both

records (n = 196, 49%) the symptom-onset time agreed exactly for 118 (60.2%) records,

differed by 1-15 minutes for 24 (12.2%) records, and differed by 16-30 minutes for 22

(11.2%) records.

5.2.5 Conclusion

Our study demonstrated that documentation of the common symptoms of MI and

symptom-onset time was similar between the paramedic and hospital records, justifying

the use of paramedic PCRs as a source of data for research in prehospital MI patient

delay. Further research is required to investigate why symptom-onset time was not

routinely documented for all patients with chest pain.

5.2.6 Key Words

Myocardial infarction; symptoms; documentation; concordance; onset-time

65

5.3 Background

Over the last two decades there has been considerable success in reducing the delay

between hospital arrival and definitive therapy for acute myocardial infarction patients

(MI), i.e., the so-called ‘door-to-needle’ or ‘door-to-balloon’ time.134 The focus on MI

research has moved from door-to-balloon, to emergency medical service (EMS)-to-

balloon, to first medical contact-to-balloon, and may even progress to ‘symptom onset’-

to-balloon times. Previous research has demonstrated paramedics can reliably interpret

prehospital electrocardiograms,135,136 activate the cardiac catheter laboratory, and

decrease EMS-to-balloon time137-140 and first medical contact-to-balloon time.138

However, the prehospital delay between MI symptom onset and arrival at hospital still

remains problematic.141-143 In the prehospital environment, correct identification of the

symptoms of MI is crucial to ensure activation of the appropriate prehospital protocol,

thus minimizing time to the commencement of appropriate care. Symptom-onset time is

particularly important for patients experiencing MI because shorter time between

symptom onset and revascularisation has been shown to reduce mortality.102

Moreover, an increasing volume of emergency medical services research relies on the

accuracy of prehospital patient care records (PCRs), which are usually completed by

paramedics. A prehospital study144 of a cohort of patients with chest pain reported

documentation of history and physical characteristics varied considerably among four

ambulance services – with as few as 51% of records reporting the symptom-onset time.

A major criticism of relying on PCRs as the source of data for prehospital research is

they may not be complete or accurate. For example, documentation of vital parameters

is often poor or incomplete.145,146

While a number of studies that have examined concordance of diagnosis (diagnostic

accuracy) by comparing paramedics’ diagnoses with those documented in hospital

medical records,147-161 only a limited number of studies that have investigated

concordance of documentation of symptoms between the paramedic PCRs and the

hospital medical records.148,156 Two studies have investigated paramedic documentation

of symptoms involving patients with stroke and documentation of facial and arm

weakness and slurred speech and both showed good agreement between paramedic and

physician assessment.148,156 We did not find any studies in the literature that compared

66

paramedic documentation symptoms of MI and symptom-onset time with the hospital

medical record. Our study aimed to establish whether paramedic records are a reliable

source of information about presenting symptoms in patients with MI. We measured

concordance of symptom documentation in the prehospital PCR and hospital medical

records, and compared the documentation of symptom-onset time.

5.4 Methods

5.4.1 Setting, Participants and Study Design

Perth is the capital city of Western Australia (WA). It has a population of 1.7 million,

with 12% over 65 years.112 St John Ambulance Western Australia (SJA-WA) is the

single provider of prehospital emergency care in WA and is staffed by paramedics,

whose training consists of a 3-year bachelor of paramedic science degree program.28 Sir

Charles Gairdner Hospital (SCGH) is a metropolitan tertiary referral centre.

This study is a retrospective review of prospectively collected paramedic PCR and

hospital medical record documentation. The cohort (n=810) was identified from a

previous study2 and included all adult patients who were discharged from SCGH

emergency department (ED) with a diagnosis of MI between January 1, 2008 and

October 31, 2009. Of these, 584 patients arrived by SJA-WA ambulance. Of the 509

SJA-WA patient records 400 patients had pairs of paramedic PCRs and hospital medical

records available for review. The hospital medical record included the ED record and

also the initial admission records to the ward, as some patients bypassed ED and were

transferred directly to the cardiac catheter laboratory. Only information on presenting

symptoms was extracted. Ethics approval (with waiver of patient consent) was obtained

for this study from The University of Western Australia (RA/4/1/2428) and from the

SCGH Human Research Ethics Committee (# 2012-146). See Appendix K and L.

5.4.2 Data Sources

The Emergency Department Information System (EDIS),113 a patient-tracking system

containing patient demographic and disposition data, was used to identify patients for

this study. The principal clinical diagnosis is a mandatory field entered by clinical staff

on patient discharge from the ED. It is electronically mapped to the International

Statistical Classification of Diseases and Related Problems, 10th Revision, Australian

67

Modification (ICD-10-AM) codes.96 All adult patients discharged from the SCGH ED

with a discharge diagnosis of MI, code I21.9 (including both ST segment elevated MI

and Non ST segment elevated MI) were identified from EDIS.

In a previous study,2 EDIS data were linked to the SJA-WA database, which contains

data from the emergency call recorded by the SJA-WA Ambulance Operations Centre

using a computer-aided dispatch system and clinical data collected by the paramedics on

a paper based PCR.28 Only index patient ED presentations were included, i.e., the first

ED presentation during the study period for patients with more than one ED

presentation to SCGH. Patients were excluded if we could not locate their emergency

telephone call, if they transferred from another hospital or were transferred to another

hospital. For this study additional data on the symptoms of MI and their onset times

were extracted from the patient’s paramedic-completed prehospital PCR and the

hospital medical record. The data were extracted by one author (LLC), who entered the

data into a SPSS database (IBM SPSS Inc., 2008, Chicago, IL; www.spss.com).

A random sample of 10% of the records was reviewed by the same author (LLC) to

assess transcription accuracy: 5% were hospital medical records and 5% were

paramedic PCRs. Overall, data were collected on 486 comparisons with 99.4% data-

entry accuracy.

5.4.3 Data Analysis

Data are summarised as frequencies (number and percentage) and means. For this study,

the symptom of chest pain was operationally defined to include right-sided chest pain,

central chest pain, left-sided chest pain, chest tightness and chest heaviness. For each

symptom, McNemar’s test was used to determine whether the documented proportions

with the symptom differed between the hospital medical record and the paramedic PCR.

A p-value less than 0.05 indicates that the proportions in the two records differ

significantly.

Kappa statistics and their 95% confidence intervals (CIs) were used to quantify

agreement in documentation of symptoms of MI between the hospital medical records

and the paramedic PCRs. Observed and chance agreement probabilities are also

reported. See Table 12 for details of how statistics were calculated.162,163 A few

http://www.spss.com/

68

studies164,165 have reported that the Kappa statistic is not always satisfactory for

assessing agreement and recommend that bias and prevalence be taken into account

when the magnitude of one or both of their indices is close to one. We have therefore

also calculated bias and prevalence indices and the Prevalence Adjusted Bias Adjusted

Kappa (referred to as adjusted Kappa).164 Kappa (and adjusted Kappa) values of less

than 0.40 represent poor agreement, 0.40 to 0.75 represents fair to good agreement, and

over 0.75 represents excellent agreement.166

Table 12: Formulae to Calculate Statistics

Symptom documented in PCR

Symptom documented in hospital medical record

Yes No Total

Yes A B B1=A+B No C D B2=C+D Total A1=A+C A2=B+D N Sensitivity = A / A1 Specificity = D/ A2 Positive predictive value = A / B1 Negative predictive value = D/ B2 Observed agreement = A + D / N Chance agreement = (A1 x B1 + A2 x B2) / N2

We have reported documentation concordance as sensitivity, specificity, positive

predictive value (PPV) and negative predictive value (NPV), with 95% CIs calculated

using the modified Wald method recommended by Agresti and Coull.167 We have

assumed that the hospital medical record documentation of symptoms of MI was the

‘gold standard.’ Sensitivity represents the proportion of patients with the hospital

medical record documented symptom that are also documented to have the symptom in

the paramedic PCR. Specificity represents the proportion of patients without a hospital

medical record documented symptom that also do not have the symptom documented by

the paramedic PCRs. The PPV is the proportion of patients with a paramedic PCR

documented symptom also identified in the hospital medical record, and the NPV is the

proportion of patients for whom a specific symptom is not recorded in the paramedic

PCR and not identified in the hospital medical record.

Differences (in minutes) between the documented symptom-onset times were calculated

by subtracting the paramedic PCR time from the hospital medical record time and

grouped as follows: 0, ±(1-15), ±(16-30), ±(31-60), ≤-61 and ≥61 minutes.

69

5.5 Results

5.5.1 Cohort Characteristics

Of the 810 patients discharged from SCGH ED with a diagnosis of MI between January

2008 and October 2009, 584 (71%) arrived by ambulance. Following exclusions,

detailed in Figure 7, 422 patients were identified. Paramedic PCR and hospital medical

records were located for 400 (95%) of these patients. Men (n = 243, 61%) were younger

than women (mean age 71.5 vs. 77.2 years).

5.5.2 Symptom Documentation: Paramedic PCR and Hospital Medical Record

Prevalence of the symptoms of MI that were documented in the hospital medical

records and the paramedic PCRs are presented in Table 13. For the majority of

symptoms there was no significant difference between the hospital medical records and

paramedic PCRs in the proportion of patients documented to have the symptom;

exceptions were left shoulder pain (8.5% hospital medical records vs. 4.3% PCR), and

fatigue and lethargy (3% hospital medical records vs. 6% PCR).

70


EDIS = Emergency Department Information System; MI = myocardial infarction; PCR = patient care record; SJA-WA = St John Ambulance-Western Australia.

EDIS confirmed discharge diagnosis of MI (Jan 1, 2008 to Oct 31 2009)

n = 810

Arrived by ambulance

n = 584

Excluded, n = 75

• Missing (Industrial action, n = 37)

• Missing (No PCR, n = 38)

SJA-WA PCR

n = 509

Excluded, n = 87

• No emergency phone call, n = 37

• Transfer from other hospital, n = 33

• Not Index admission, n = 10

• Transfer to other hospital, n = 7

Patients admitted

n = 422

Excluded, n = 22

• Unable to locate hospital record

Hospital record review

n = 400

Men = 243

Women = 157

71

Table 13: Prevalence of Symptom Documentation of Myocardial Infarction: Paramedic

PCR and Hospital Medical Record

Symptom Paramedic PCR n (%)

Hospital Medical Record, n (%) P-value

Chest Pain 290 (72.5) 294 (73.3) 0.58 Shortness of breath 201 (50.3) 211 (52.6) 0.38 Sweaty or clammy 132 (33.0) 121 (30.3) 0.29 Nausea 105 (26.3) 98 (24.4) 0.54 Left arm pain 104 (26.0) 90 (22.4) 0.09 Jaw, throat or neck pain 53 (13.3) 57 (14.3) 0.66 Right arm pain 46 (11.5) 40 (10.0) 0.40 Dizziness 42 (10.5) 40 (10.0) 0.88 Vomiting 36 (9.0) 35 (8.8) >0.99 Syncope, collapse, unconscious 31 (7.8) 35 (8.8) 0.45 Left shoulder pain 17 (4.3) 34 (8.5) <0.01* Back pain 33 (8.3) 29 (7.3) 0.60 Abdominal / epigastric pain 29 (7.3) 24 (6.0) 0.40 Unwell 15 (3.8) 21 (5.3) 0.33 Confusion 15 (3.8) 20 (5.0) 0.31 Right shoulder pain 12 (3.0) 20 (5.0) 0.10 Fall 19 (4.8) 17 (4.3) 0.69 Weakness 17 (4.3) 16 (4.0) >0.99 Fatigue, lethargy 24 (6.0) 12 (3.0) 0.02* Belching, indigestion, heartburn 13 (3.3) 6 (1.5) 0.14 Headache 6 (1.5) 3 (0.8) 0.45

PCR=Patient Care Record; *statistically significant difference; McNemar’s Test was used to examine the difference in symptom documentation between the paramedic PCR and hospital medical record.

5.5.3 Chest Pain

Chest pain was the most common symptom of MI documented in the paramedic PCR

(72%) and hospital medical record (73.3%). The observed agreement was 94%, Kappa

was 0.84 and adjusted Kappa was 0.87. Sensitivity, specificity, PPV, and NPV were 94,

88, 96 and 85% respectively.

5.5.4 Other Symptoms of MI

Kappa and adjusted Kappa statistics for agreement between the hospital medical record

and paramedic PCR documentation for each symptom of MI are presented in Table 14.

Although bias had little effect in this study, the prevalence index was high for most

symptoms and justified use of the adjusted Kappa. The majority of symptoms of MI

(n=17, 81%) had adjusted Kappa statistics greater than 0.75, indicating excellent

agreement between the hospital medical record and paramedic PCR. Four symptoms

(19%), including shortness of breath, sweating, nausea and left arm pain, had adjusted

Kappa statistics between 0.40 and 0.75, indicating fair to good agreement.166

72

The sensitivity, specificity, PPV, NPV comparing documentation of symptoms of MI

between the hospital medical record and paramedic PCR (assuming the hospital medical

record is the gold standard) are presented in Table 15. For the majority of the

symptoms, specificity and NPV were greater than 90%. Shortness of breath had the

lowest values of 75% and 71% respectively, but all were greater than 70%. Sensitivity

and PPV varied as symptom prevalence reduced.

5.5.5 Symptom-onset Time: Paramedic PCR and Hospital Medical Record

The flow diagram of symptom-onset time is presented in Figure 8. In the hospital

medical record, patients with chest pain (n = 294, 74%) had a documented symptom-

onset time in 235 (80%) records. In the paramedic PCR, patients with chest pain (n =

290, 72%) had a documented symptom-onset time in 195 (67%) records. Overall,

hospital medical records had 275 (68.8%) documented symptom-onset times and

paramedic PCRs had 226 (56%). Symptom-onset time was available from both the

hospital medical record and the paramedic PCR for only 196 (49%) of the cohort.

Documented symptom-onset times of MI in the paramedic PCR and hospital medical

records are presented in Figure 9. Symptom-onset time agreed exactly for 118 (60.2%)

records, differed by 1-15 minutes for 24 (12.2%) records, and differed by 16-30 minutes

for 22 (11.2%) records. Eight (4.0%) records reported times that differed between 31 to

60 minutes. Twenty four (12.2%) records reported symptom-onset times that differed by

more than 60 minutes.

73

Tabl

e 14

: Obs

erve

d an

d C

hanc

e A

gree

men

t, K

appa

and

PA

BA

K S

tatis

tic o

f Sym

ptom

Doc

umen

tatio

n of

Myo

card

ial I

nfar

ctio

n: P

aram

edic

PC

R

and

Hos

pita

l Med

ical

Rec

ord

Sym

ptom

O

bser

ved

Agr

eem

ent

%

Cha

nce

Agr

eem

ent

%

Bia

s In

dex*

Pr

eval

ence

In

dex†

K

appa

(9

5%C

I)

Adj

uste

d K

appa

Che

st p

ain

93.5

60

.6

-0.0

1 0.

46

0.84

(0.7

7, 0

.90)

0.

87

Shor

tnes

s of b

reat

h 74

.0

50.0

-0

.02

0.03

0.

48 (0

.39,

0.5

7)

0.48

Sw

eaty

77

.8

56.7

0.

03

-0.3

7 0.

49 (0

.39,

0.5

8)

0.56

N

ause

a 76

.2

62.1

0.

02

-0.4

9 0.

37 (0

.27,

0.4

8)

0.52

Le

ft ar

m p

ain

85.5

63

.2

0.04

-0

.52

0.61

(0.5

1, 0

.70)

0.

71

Jaw

, thr

oat o

r nec

k pa

in

88.0

76

.3

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1 -0

.72

0.49

(0.3

7, 0

.62)

0.

76

Rig

ht a

rm p

ain

91.0

80

.8

0.02

-0

.78

0.53

(0.4

0, 0

.67)

0.

82

Diz

zine

ss

89.0

81

.6

0.00

-0

.80

0.40

(0.2

6, 0

.54)

0.

78

Vom

iting

92

.8

83.8

0.

00

-0.8

2 0.

55 (0

.41,

0.7

0)

0.86

Sy

ncop

e, c

olla

pse

or u

ncon

scio

us

96.0

84

.8

-0.0

1 -0

.84

0.74

(0.6

1, 0

.86)

0.

92

Left

shou

lder

pai

n 93

.2

88.0

-0

.04

-0.8

7 0.

44(0

.25,

0.6

3)

0.86

B

ack

pain

92

.0

85.7

0.

01

-0.8

4 0.

44 (0

.28,

0.6

0 0.

84

Abd

omin

al o

r epi

gast

ric p

ain

94.2

87

.6

0.01

-0

.87

0.54

(0.3

7, 0

.70)

0.

88

Unw

ell

93.5

91

.4

-0.0

2 -0

.91

0.24

(0.0

5, 0

.44)

0.

87

Con

fusi

on

94.2

91

.6

-0.0

1 -0

.91

0.31

(0.1

0, 0

.52)

0.

88

Rig

ht sh

ould

er p

ain

95.5

92

.3

-0.0

2 -0

.92

0.42

(0.2

3, 0

.60)

0.

91

Fall

98.5

91

.4

0.00

-0

.91

0.83

(0.6

9, 0

.96)

0.

97

Wea

knes

s 94

.2

92.1

0.

00

-0.9

2 0.

27 (0

.06,

0.4

8)

0.88

Fa

tigue

or l

etha

rgy

94.0

91

.4

0.03

-0

.91

0.31

(0.1

0, 0

.51)

0.

88

Bel

chin

g, in

dige

stio

n or

hea

rtbur

n 95

.8

95.3

0.

02

-0.9

5 0.

09 (0

.10,

0.2

8)

0.92

H

eada

che

98.2

97

.8

0.01

-0

.98

0.21

(0.0

2, 0

.40)

0.

96

PCR

= Pa

tient

Car

e R

ecor

d; C

I = c

onfid

ence

inte

rval

*T

he b

ias i

ndex

is th

e di

ffer

ence

in p

ropo

rtion

s of “

yes”

bet

wee

n th

e pa

ram

edic

PC

R a

nd h

ospi

tal m

edic

al re

cord

; it h

as a

min

imum

of -

1 an

d m

axim

um o

f 1.

†The

pre

vale

nce

inde

x (P

I) is

the

diff

eren

ce in

pre

vale

nce

of “

yes”

and

“no

”, p

reva

lenc

e be

ing

calc

ulat

ed a

s mea

ns fo

r par

amed

ic P

CR

and

hos

pita

l med

ical

reco

rd.

PI h

as a

min

imum

of -

1 an

d m

axim

um o

f 1 a

nd is

0 w

hen

the

mea

n pr

eval

ence

of “

yes”

is 5

0%

.

74

Tabl

e 15

: Sen

sitiv

ity, S

peci

ficity

, PPV

and

NPV

of S

ympt

om D

ocum

enta

tion

of M

yoca

rdia

l Inf

arct

ion:

Par

amed

ic P

CR

and

Hos

pita

l Med

ical

Rec

ord

(hos

pita

l med

ical

reco

rd w

as c

onsi

dere

d th

e go

ld st

anda

rd)

Sym

ptom

Se

nsiti

vity

(%)

(95%

CI)

Sp

ecifi

city

(%)

(95%

CI)

PP

V (%

) (9

5% C

I)

NPV

(%)

(95%

CI)

Che

st p

ain

94 (9

1, 9

6)

88 (8

2, 9

4)

96 (9

3, 9

8)

85 (7

8, 9

2)

Shor

tnes

s of b

reat

h 73

(66,

79)

75

(68,

81)

76

(70,

82)

71

(65,

77)

Sw

eaty

67

(59,

76)

82

(77,

86)

62

(54,

70)

85

(81,

89

Nau

sea

55 (4

5, 6

5)

83 (7

8, 8

7)

51 (4

2, 6

1)

85 (8

0, 8

9)

Left

arm

pai

n 74

(66,

84)

88

(84,

92)

65

(56,

74)

92

(89,

95)

Ja

w, t

hroa

t or n

eck

pain

54

(41,

67)

93

(90,

96)

58

(45,

71)

92

(89,

95)

R

ight

arm

pai

n 61

(46,

76)

94

(91,

96)

54

(40,

68)

95

(93,

98)

D

izzi

ness

48

(32,

63)

93

(90,

96)

46

(31,

61)

94

(91,

96)

V

omiti

ng

60 (4

3, 7

5)

95 (9

3, 9

8)

58 (4

1, 7

4)

96 (9

4, 9

8)

Sync

ope,

col

laps

e, &

unc

onsc

ious

69

(54,

86)

98

(96,

99)

77

(62,

92)

97

(95,

99)

Le

ft sh

ould

er p

ain

37 (2

0, 5

3)

98 (9

7, 1

00)

67 (4

4, 8

9)

94 (9

1, 9

6)

Bac

k pa

in

52 (3

3, 7

0)

95 (9

2, 9

7)

46 (2

9, 6

3)

96 (9

4, 9

8)

Abd

omin

al &

epi

gast

ric p

ain

61 (4

1, 8

0)

96 (9

4, 9

8)

52 (3

3, 7

0)

97 (9

5, 9

9)

Unw

ell

28 (9

, 47)

97

(95,

99)

37

(12,

61)

95

(93,

98)

C

onfu

sion

33

(13,

54)

97

(96,

99)

42

(17,

67)

96

(94,

98)

R

ight

shou

lder

pai

n 38

(16,

59)

98

(97,

100

) 56

(28,

84)

96

(94,

98)

Fa

ll 81

(62,

100

) 98

(97,

98)

74

(54,

94)

99

(98,

100

) W

eakn

ess

35 (1

2, 5

8)

96 (9

4, 9

8)

33 (1

1, 5

6)

97 (9

5, 9

8)

Fatig

ue &

leth

argy

50

(22,

78)

95

(93,

97)

29

(10,

47)

98

(96,

99)

B

elch

ing,

indi

gest

ion

& h

eartb

urn

30 (0

, 67)

96

(95,

98)

18

(0, 3

8)

98 (9

7, 1

00)

Hea

dach

e 43

(0, 9

0)

98 (9

7, 1

00)

30 (0

, 67)

99

(98,

100

)

CI =

con

fiden

ce in

terv

al; P

PV =

pos

itive

pre

dict

ive

valu

e; N

PV =

neg

ativ

e pr

edic

tive

valu

e

75

Figure 8: Flow Diagram of Symptom-onset Time: Paramedic PCR and hospital

Medical Record

Hospital medical record Paramedic PCR

Patients with Chest pain Patients with Chest pain

Yes, n = 294 (73.5%) No, n = 106 (26.5%) Yes, n = 290 (72.5%) No, n = 110

(27.5%)

Documented Symptom-onset time Documented Symptom-onset time

Yes, n = 235 (79.9%) Yes, n = 40 (37.7%) Yes, n = 195 (67%) Yes, n = 31

(11.3%)

Hospital medical record Paramedic PCR

n = 275 (68.8%) n = 226 (56%)

Both hospital medical record and paramedic PCR symptom-onset

n = 196 (49%) Missing, n = 204 (51%)

Hospital medical symptom-onset only,

n = 79 (38.7%)

Paramedic PCR symptom-onset only,

n = 30 (14.7%)

No symptom-onset for both hospital

medical and paramedic PCR,

n = 95 (46.6%)

76

Figure 9: Symptom-onset Time Difference (minutes): Paramedic PCR and Hospital

Medical Record, n = 196

5.6 Discussion

5.6.1 Symptom Documentation: Paramedic PCR and Hospital Medical Record

While other studies148,156 have investigated documentation of symptoms for stroke

patients between paramedic and hospital medical records, to our knowledge, this is the

first study to analyse the documentation of symptoms for MI patients. Accurate

prehospital documentation of the symptoms of MI on the paramedic PCR is essential for

the ED to ensure time critical revascularisation treatment from a medico-legal

standpoint and as a data source for research. We found the concordance of paramedic

PCR documentation of the symptom of chest pain was excellent, and for all but two

other symptoms there were no differences in the proportions of patients documented to

have the symptom. Overall the measure of agreement between the two records was

excellent and we observed a trend for higher specificity than sensitivity.

77

5.6.2 Chest Pain

For the symptom of chest pain in this study, the sensitivity, specificity, PPV, NPV

values are all above 85%, the observed agreement is 94%, and Kappa and adjusted

Kappa indicate excellent agreement. Statistically these results are impressive; however,

clinically we were concerned that the sensitivity and PPV were 94% and 96%. Further

examination of PCRs revealed that the paramedics were unable to obtain the

information because the patient had collapsed or was unconscious (n = 5), the patient

did not speak English (n = 1), or the paramedic described the pain as “epigastric” (n =

3). The actual anatomic location of “chest” and “epigastric” pain is very similar, despite

different connotations about the underlying pathology.

5.6.3 Other Symptoms of MI

Observed agreement in documentation of the majority of the symptoms of MI between

the two records is high (most > 88%) and the adjusted Kappa reflects excellent

agreement. A study156 that investigated identification of facial and arm weakness and

speech disturbance reported observed agreement of 78% for facial weakness, 98% for

arm weakness and 89% for speech disturbance, and Kappa scores of 0.49, 0.77, and

0.69 respectively. Our study has similar Kappa values, but the adjusted Kappa values

that take symptom prevalence into account indicate excellent inter-observer agreement

between the paramedic PCRs and the hospital medical records.

Our study has a wide range of values for PPV and sensitivity. The most likely reason for

this is that low prevalence of a symptom decreases PPV, and 13 symptoms had less than

10% prevalence. Specificity, which represents the proportion of patients without a

hospital medical record-documented symptom that also do not have the symptom

documented by the paramedic PCRs, tended to be higher than sensitivity, which

represents the proportion of patients with the hospital medical record documented

symptom that are also documented to have the symptom in the paramedic PCR.

5.6.4 Symptom-onset Time: Paramedic and Medical Record

Our study also identified the low rate of documentation of the symptom-onset time of

MI in both the paramedic PCR and the hospital medical record. Other studies107,144,168-

172 have reported missing data on onset times for 9% to 73% of occasions. Further

78

examination of the PCRs for the patients with chest pain who did not have a

documented date and symptom-onset time (n = 95) revealed that onset was missing with

no reason (n = 33); onset was described as either “gradual,” “intermittent,” or over the

last 1-7 days (n = 33); onset time was described as “sudden onset” (n = 9), “awoke with

chest pain” (n = 4), “collapsed” (n = 4), or “patient picked up from doctor’s surgery” (n

= 11); and in one case because the patient was confused. The paramedics may have

presumed that “sudden onset,” “awoke with chest pain,” and “collapsed” meant that the

onset time was similar to their arrival / patient pick up time.

It was concerning that there was no obvious reason why symptom-onset time was not

documented for 33 (11%) of the patients who had chest pain. Documentation of the

symptom-onset time is extremely important as it guides medical decisions and treatment

options. We found that when symptom-onset was documented, the time in the

paramedic PCR was consistently similar to the time in the hospital medical record for

the majority of records.

Our findings add to the growing body of EMS MI evidence and suggest paramedics

accurately identify chest pain and symptom-onset time. Future studies should include

paramedic ‘symptom onset’-to-balloon times.

5.7 Limitations

Our study has several limitations. The data from this study were collected at a single

hospital, which may limit the generalizability of the results. However, the cohort size

was substantial and there is no reason to suspect that hospital medical documentation of

symptoms of MI would differ in other similar tertiary-level metropolitan hospitals.

Furthermore, SJA-WA is the single provider of prehospital emergency care for all

hospitals in WA and at the time of the study patients with chest pain were transported to

the closest tertiary hospital.

The study is a retrospective review of prospectively collected paramedic PCR and

hospital medical record documentation. A standardised data collection instrument was

not used to document symptoms in the paramedic PCR or hospital medical record and

the patient may not have been asked about all the symptoms of MI, for example,

weakness and fatigue. The patient may not have remembered all of their symptoms, and

79

there may have been progression or change of symptoms from the time the paramedic

assessed the patient to the time the patient was assessed in hospital.

We assumed the hospital medical record of the symptom documentation and onset time

was the gold standard and this may not be the case. Some of the presenting symptoms of

MI may not have been considered relevant and, consequently, not documented by

medical staff. In particular, for paramedics the presence of chest pain alone is sufficient

to trigger a “priority one” (lights and siren) response and the need for a full enumeration

of all symptoms may not be deemed essential. It was also assumed that the ED

discharge diagnosis of MI was accurate and there is a possibility that further in-patient

assessment may have resulted in an alternative final diagnosis.

5.8 Conclusions

Our study showed good to excellent concordance in the reporting of the symptoms

between the paramedic PCR and the hospital medical record among patients with an ED

diagnosis of MI. Symptom-onset time agreed exactly for 60% of the records and for

over 80% of the records the times were within 30 minutes. Although our results are not

necessarily applicable to other emergency medical systems, our findings support the

utility of prehospital PCRs as an acceptable means of obtaining data for the

investigation of prehospital delay in MI patients. Further investigation is required to

understand why symptom-onset time is not routinely documented for patients with chest

pain.

81

Chapter 6: Characteristics and Outcomes for Myocardial

Infarction Patients Who Present with and without Chest Pain

6.1 Introduction

This chapter is the Author’s Original Manuscript that has been published in Heart, Lung

and Circulation.4 This manuscript examines the patient characteristics and survival

outcomes of those who present with and without chest pain at a single hospital. The

symptoms of MI for this study were extracted from the hospital medical record. This

phase of the study aimed to answer the fourth research question posed in Chapter 1,

Section 1.4:

Are patient characteristics and patient outcomes (survival and hospital

discharge diagnosis) of patients presenting with and without chest pain the

same?

To answer this question it was necessary to link the EDIS, SJA-WA data, and hospital

medical record data. The detailed explanation of this data linkage in Chapter 3 expands

on the brief description in the manuscript.

6.2 Abstract

6.2.1 Background

There are conflicting data on patient characteristics and outcomes of myocardial

infarction (MI) patients presenting with and without the symptom of chest pain.

6.2.2 Objectives

Compare the characteristics and survival of patients stratified by the symptom chest

pain.

6.2.3 Methods

This retrospective cohort study identified patients with an emergency department

discharge diagnosis of MI, who arrived by ambulance at a teaching hospital in Perth,

Western Australia, between January 2008 to October 2009. The cohort was linked to

82

hospital data and the state-based death register; clinical data were extracted by medical

record review. Patient characteristics were compared using logistic regression models

and survival analysis using Kaplan-Meier curves and Cox regression models.

6.2.4 Results

Of 382 patients, 26% presented without chest pain. The odds of presenting without

chest pain were increased if aged 80+ (OR 7.54; 95%CI 2.81-20.3) and aged 70-79

years (OR 4.33; 95% CI 1.50-12.5), and female (OR 1.67; 95%CI 0.99-2.82). The

adjusted hazard (median follow-up time 2.2 years) of presenting without chest pain was

not significantly associated with survival (HR 1.03; 95%CI 0.71-1.48).

6.2.5 Conclusion

Characteristics differed between patients with and without chest pain. However, the

symptom of chest pain was not associated with survival.

6.2.6 Key Words

Myocardial infarction, symptoms, atypical presentation, patient outcomes, survival

6.3 Introduction

Early symptom recognition of myocardial infarction (MI) is vital to reduce patient delay

in seeking treatment, ensure timely diagnosis and receive definitive care. Early

presentation and coronary revascularisation have consistently been shown to reduce

both mortality and morbidity.14,15 Although the hallmark symptom of MI is chest pain, a

recent literature review1 of symptom presentation in MI found that as many as one in

three women and one in four men did not experience chest pain. Other studies have

reported similar findings.18,31,116

Patients base their decision to seek medical care on the symptoms they experience, and

these symptoms are critical in determining appropriate pre-hospital and emergency

department triage.2,116 Patients and health professionals are less likely to recognise MI

when it occurs without chest pain.31,173 This causes patients to delay seeking medical

treatment,114 and health professionals may treat the patient less aggressively.174 Studies

have shown that MI patients without chest pain are less likely to receive evidence based

83

medical therapies and invasive cardiac procedures.31,56,174 In addition, the absence of

chest pain is associated with increased mortality.33,175

Understanding the demographic and clinical characteristics of patients who have a MI

without chest pain may help facilitate earlier detection and appropriate medical

treatment within the first 24 hours. The aim of this cohort study were to (1) compare

patient characteristics and (2) outcomes (survival and discharge diagnosis) of

emergency department (ED) diagnosed MI patients presenting with and without chest

pain.

6.4 Method

6.4.1 Setting and Participants

Perth is the capital city of Western Australia (WA) and 12% of the population of 2.29

million are over 65 years old.112 Sir Charles Gairdner Hospital (SCGH), one of three

adult tertiary referral hospitals in Perth, has over 53,000 ED presentations annually

(Celenza 2014 personal communication). The cohort was identified from a previous

study2 and included all adult patients who arrived by ambulance at SCGH between 1

January, 2008 and 31 October, 2009 and had an ED discharge diagnosis of MI. Only the

first ED presentation during the study period was included for patients with more than

one ED presentation at SCGH. Patients were excluded if they were transferred to or

from another hospital.

6.4.2 Study Design and Data Sources

A retrospective cohort study of prospectively collected data was examined by data

linkage and medical chart review. The data sources used in this study were (1)

Emergency Department Information System (EDIS), (2) St John Ambulance Western

Australia (SJA-WA), (3) WA Death Register, (4) The Open Patient Admission System

(TOPAS), and (5) medical chart review. EDIS,113 an ED patient-tracking system that

contains patient demographic and disposition data, was used to identify all adult patients

discharged from the SCGH ED between 1 January, 2008 and 31 October, 2009 with a

discharge diagnosis of MI, the International Statistical Classification of Diseases and

Related Problems, 10th Revision, Australian Modification96 code I21.9 (including both

STEMI [ST segment elevated MI] and NSTEMI [Non STEMI]). These data were linked

84

to the SJA-WA database,28 which contains data from the emergency call and clinical

data collected by the paramedics to form the study cohort, which was then linked to the

WA Death Register97 by probabilistic matching using Linkagewiz.98 Patients were

assumed to be alive at 1 September 2011 if there was no record of their death. Hospital

discharge diagnoses and procedure codes for the study cohort were extracted from

TOPAS,176 which contains records of all patient admissions, transfers and discharges.

The data extracted from the patient hospital medical record by one of the authors (L.C.)

included whether or not the patient presented with the symptom chest pain and other

presenting symptoms of MI. The symptom of chest pain was operationally defined to

include right-sided chest pain, central chest pain, left-sided chest pain, chest tightness

and chest heaviness. Other data extracted included the type of MI (STEMI / NSTEMI),

presence of co-morbid conditions (e.g. diabetes, hypertension, heart failure) and

whether or not patients had a primary percutaneous coronary intervention (PCI). Data

extraction accuracy has been previously reported3: in summary, a random sample of

10% of the records was reviewed by the same author (LC) and data-entry accuracy was

99.4%.

Two processes of care variables were considered in this study: ‘Primary PCI’ and any

‘cardiac procedure’. Primary PCI data were extracted from medical record review. A

Primary PCI is an emergency protocol, and a patient with a ST segment elevated MI,

during the study period was given aspirin, clopidogrel, and heparin 5000 units

intravenously in ED and rapidly transferred to the cardiac catheter laboratory for

immediate angiogram and PCI if required.

‘Cardiac procedure’ data were extracted from TOPAS discharge data. The ‘cardiac

procedure’ could have occurred anytime during the patient’s hospital stay. These data

were categorised into five groups: (1) no cardiac procedure, (2) angiogram only, (3) PCI

(with angiogram), (4) coronary artery bypass surgery (CABG) (with angiogram ± PCI),

and (5) computerised tomography (CT) angiography. A binary variable ‘cardiac

procedure’ was created by grouping angiogram, PCI, CABG and CT angiography

(categories 2-5) as ‘yes’, and no cardiac procedure as ‘no’. Patients who were first

treated under the Primary PCI protocol in ED were also included in either category 2, 3,

or 4 of the ‘cardiac procedure’ variable.

Outcome variables were hospital discharge diagnostic category and survival status at 1

85

September 2011. Hospital discharge diagnoses were categorised by the ICD-10-AM

codes: (1) MI (I21), (2) unstable angina (I20.0), (3) angina (I20.8, I20.9), (4) chest pain

(R07.3, R07.4), (5) other cardiac diagnoses, and (6) non-cardiac diagnoses. A binary

variable ‘hospital discharge diagnosis’ was created such that the first category, MI, was

‘yes’ and the remaining categories, unstable angina, angina, chest pain, other cardiac

diagnoses, and non-cardiac diagnoses (categories 2-6) were grouped as ‘no’.

Ethics approval (with waiver of patient consent) was obtained for this study from The

University of Western Australia (RA/4/1/2428, RA/4/1/2567) and from the SCGH

Human Research Ethics Committee (# 2012-146). See Appendix K, L, N and O.

6.4.3 Statistical Analysis

Data were stratified by presence or absence of chest pain on presentation and

summarised as frequencies (numbers and percentages) or means and standard deviations

(SDs). Differences between patient groups with and without chest pain were assessed by

χ2 tests or Fisher’s exact tests for categorical variables and t tests for continuous

variables.

Logistic regression was used to determine the odds of not experiencing chest pain

associated with specified patient characteristics. Characteristics considered included the

following: demographics (age, age-squared, sex, age-sex interaction); medical history

(diabetes, hypertension, dyslipidaemia, family history of coronary artery disease [CAD],

angina, previous MI, CAD, heart failure, previous PCI, previous CABG, and stroke);

and type of MI (STEMI or NSTEMI); and hospital discharge diagnosis (MI, Other).

Characteristics associated with the presence/absence of chest pain were initially tested

in unadjusted models. Age-squared was significantly associated with chest pain

indicating that the relationship between age and chest pain was not linear. For ease of

interpretation of its curved relationship with the log odds of chest pain, age was

categorised into decades in subsequent analyses. All characteristics with p<0.20 in

unadjusted analysis were included in the adjusted model. This model was simplified in a

stepwise fashion by removing the characteristic with the highest p-value and refitting

the model until only characteristics with p-values <0.10 were retained. As a final check,

all excluded characteristics were retested one at a time in this adjusted logistic model.

Logistic regression was also used to determine whether chest pain was associated with

86

processes of care: Primary PCI, or any cardiac procedure. Models were adjusted for

chest pain, age group, sex, type of MI, and hospital discharge diagnosis type, family

history of CAD, and previous stroke, heart failure, and angina; and analyses were

conducted as above. A post hoc sample size calculation was conducted using

methodology described by Peduzzi et al.177

Kaplan-Meier curves were produced, and the log rank test was applied to determine

whether chest pain was associated with survival. The effect of chest pain on survival

was also modelled in separate unadjusted and adjusted Cox regression models with data

stratified by (1) Primary PCI and (2) any cardiac procedure. Hazard ratios (HR)

compare patients who present without chest pain to those who present with chest pain.

All statistical analyses were performed with IBM SPSS Statistics Version 20.0 (IBM

Corp. Released 2011. IBM SPSS Statistics for Windows, Version 20.0 Armonk, NY:

IBM Corp) and statistical significance was set at 5%.

6.5 Results

6.5.1 Cohort Characteristics

Of the 810 patients discharged from SCGH ED with a diagnosis of MI between January

2008 and October 2009, 584 (71%) arrived by ambulance. Following exclusions, 382

patients remained (see Figure 10). Of these, 99 (25.9%) patients presented without chest

pain.

6.5.2 Presenting without Chest Pain

Patient characteristics are shown in Table 16. Patients without chest pain were more

likely to be older (mean age 82.3 years vs. 70.8 years), female, have had a previous

stroke; and have had a NSTEMI. Patients with chest pain were more likely to have a

family history of CAD.

Patient processes of care and outcomes are shown in Table 17. In unadjusted analyses

patients who presented without chest pain were less likely to have a Primary PCI, an

angiogram, a PCI during hospital admission, a hospital discharge diagnosis of MI, and

were less likely to survive the first 24 hours, 30-days, 1-year, and 2-years than patients

who presented with chest pain.

87

The mean recorded number of symptoms for patients with chest pain was 3.3 (SD 1.6)

and for patients without chest pain was 2.0 (SD 1.1). The main presenting symptoms for

the patients without chest pain are shown in Table 18. The most common symptom was

shortness of breath (44.4%); followed by syncope, collapse or unconsciousness

(22.2%); confusion (18.1%); a fall (14.1%); nausea (13.1%); and dizziness (12.1%).

88




n = 584

EDIS confirmed discharge diagnosis of MI (Jan 1, 2008 to Oct 31 2009)

n = 810

Excluded, n = 75

• Missing (SJA-WA industrial action, n = 37)

• Missing (No PCR, n = 38)

SJA-WA PCR

n = 509 Excluded, n = 87

• No emergency phone call, n = 37

• Transfer from other hospital, n = 33

• Not Index admission, n = 10

• Transfer to other hospital, n = 7

Patients admitted to ED

n = 422

Excluded:

• Unable to locate hospital record, n = 22

• Transferred to private hospital, n = 14

• Discharged to nursing home, n = 2

• Discharged home, n = 2

Hospital record review

n = 382

Men = 233

Women = 149

89

Table 16: Characteristics of Patients with Myocardial Infarction by Clinical

Presentation: No Chest Pain Compared with Chest Pain

Variable No Chest Pain (n = 99)

Chest Pain (n = 283) P Value*

Demographic and baseline characteristics, Age, mean (SD), y

82.3 (11.5)

70.8 (14.0)

<0.001

Age groups, n (%) ≥80 years 70 to 79 years 60 to 69 years ≤59 years

68 (68.7) 22 (22.2)

4 (4.0) 5 (5.1)

96 (33.9) 61 (21.6) 62 (21.9) 64 (22.6)

<0.001

Women 51 (51.5) 98 (34.6) 0.003 Coronary heart disease risk factors, n (%) Diabetes

27 (27.3)

70 (24.7)

0.62

Hypertension 62 (62.6) 176 (62.2) 0.94 Dyslipidemia 34 (34.3) 117 (41.3) 0.22 Family history of CAD 4 (4.0) 58 (20.5) <0.001 Previous angina 1 (1.0) 12 (4.2) 0.20 Previous MI 21 (21.2) 58 (20.5) 0.88 Previous CAD 40 (40.4) 106 (37.5) 0.60 Previous heart failure 18 (18.2) 31 (11.0) 0.06 Previous PCI 7 (4.1) 17 (6.0) 0.71 Previous CABG 11 (11.1) 22 (7.8) 0.31 Previous stroke 18 (18.2) 23 (8.1) 0.005 Type of MI, n (%) STEMI NSTEMI Missing

15 (15.2) 64 (64.6) 20 (20.2)

110 (38.9) 139 (49.1) 34 (12.0)

<0.001

* p value from independent t-test, χ2 test or Fisher Exact Test CABG = coronary artery bypass graft; CAD = coronary artery disease; MI = myocardial infarction; NSTEMI = non ST segment elevated myocardial infarction; PCI = percutaneous coronary intervention; SD = standard deviation; STEMI = ST segment elevated myocardial infarction; y = years.

90

Table 17: Process of Care and Outcomes of Patients with Myocardial Infarction by

Clinical Presentation: No Chest Pain Compared with Chest Pain

Variable No Chest Pain (n = 99)

Chest Pain (n = 283) P Value*

Primary PCI, n (%) 5 (5.1) 96 (33.9) <0.001

Hospital cardiac procedure, n (%) No cardiac procedure Angiogram only PCI (including angiogram) CABG (including angiogram, ±PCI) CT Angiography only

88 (88.9)

2 (2.0) 8 (8.1) 0 (0.0) 1 (1.0)

125 (44.2) 37 (13.1)

113 (39.9) 6 (2.1) 2 (0.7)

<0.001 0.001

<0.001 0.35 0.60

Hospital discharge diagnosis (ICD-10-AM code) Myocardial infarction (I21) Unstable angina (I20.0) Stable angina (I20.8, I20.9) Chest pain (R07.3, R07.4) Other cardiac diagnoses Non-cardiac diagnoses

51 (51.5)

4 (4.0) 1 (1.0) 2 (2.0) 7 (7.1)

34 (34.3)

227 (80.2)

9 (3.2) 13 (4.6) 14 (4.9) 12 (4.2) 8 (2.8)

<0.001

0.75 0.13 0.26 0.26

<0.001

Mortality, n (%) ≤ 24 hours ≤ 30 days ≤ 1 year ≤ 2 years

6 (6.1)

18 (18.2) 37 (37.4) 44 (44.4)

4 (1.4)

17 (6.0) 50 (17.7) 72 (25.4)

0.02

<0.001 <0.001 <0.001

* p value from χ2 test or Fisher Exact Test PCI = percutaneous coronary intervention; CABG = coronary artery bypass graft; CT = computerized tomography; ICD-10-AM = International Statistical Classification of Diseases and Related Problems, 10th Revision, Australian Modification.

Table 18 Main Symptoms for Patients without Chest Pain

Symptom* Percent of total (n=99)

Shortness of breath 44.4 Syncope, collapse or unconscious 22.2 Confusion 18.2 Fall 14.1 Nausea 13.1 Dizziness 12.1 Abdomen or epigastric pain 11.1 Unwell 11.1 Fatigue or lethargy 10.1 Weakness 10.1 Vomiting 9.1 Sweaty & clammy 7.1 Left arm pain 5.1 Jaw, throat or neck pain 4.1 Back pain 3.0

*Multiple symptoms possible

91

Odds ratio estimates from logistic regression analyses of the associations between

patient characteristics and MI without chest pain are presented in Table 19. The adjusted

model estimated that the odds of not experiencing chest pain were 7.54 (95% CI, 2.81-

20.3) times higher in patients aged 80 years or more, and 4.33 (95%CI, 1.50-12.5) times

higher in patients aged 70 to 79 years compared with patients under 60 years of age, and

the odds of women not experiencing chest pain were 1.67 (95% CI, 0.99-2.82) times

higher than those of men. Compared with patients who had an MI hospital discharge

diagnosis, the odds of not experiencing chest pain were 3.43 (95% CI, 2.01-5.85) times

higher for patients who had other hospital discharge diagnoses.

6.5.3 Primary PCI or any Cardiac Procedure

In adjusted analyses, for patients presenting without chest pain, the odds of not having a

Primary PCI were 81% lower (OR 0.19; 95% CI, 0.05-0.75), and the odds of not having

any cardiac procedure were 78% lower (OR 0.22; 95% CI, 0.08-0.51) compared with

patients with chest pain (see Table 20).

The post hoc calculation of minimum sample size for a logistic regression model with 7

covariates indicated that 269 patients were required from a population in which the

proportion with chest pain was 0.26.

92

Tabl

e 19

: Odd

s Rat

io E

stim

ates

(fro

m u

nadj

uste

d an

d ad

just

ed lo

gist

ic re

gres

sion

ana

lyse

s) o

f the

Ass

ocia

tions

betw

een

Patie

nt C

hara

cter

istic

s and

Myo

card

ial I

nfar

ctio

n w

ith N

o C

hest

Pai

n

Una

djus

ted

mod

els

Adj

uste

d m

odel

s

OR

95

% C

I P

valu

e O

R

95%

CI

P va

lue

Age

gro

ups,

≥80

year

s

70 to

79

year

s

60 to

69

year

s

<60

year

s Fe

mal

e se

x Ty

pe o

f MI (

STEM

I, N

STEM

I)

Fam

ily h

isto

ry o

f CA

D

Prev

ious

Stro

ke

H

eart

failu

re

A

ngin

a H

ospi

tal d

isch

arge

dia

gnos

is (M

I, ot

her)

9.

07

4.62

0.

83

1.00

2.

01

3.38

0.

16

2.

51

1.80

0.

23

3.82

3.

47-2

3.7

1.64

-13.

0 0.

21-3

.22

1.

26-3

.19

1.82

-6.2

5 0.

06-0

.46

1.

29-4

.89

0.96

-3.4

0 0.

03-1

.80

2.34

, 6.2

3

<0.0

01

<0.0

01

0.00

4 0.

78

0.

003

<0.0

01

0.00

1 0.

007

0.07

0.

16

<0.0

01

7.

54

4.33

0.

71

1.00

1.

67

0.

17

3.43

2.

81-2

0.3

1.50

-12.

5 0.

18-2

.84

0.

99-2

.82

0.

02-1

.38

2.01

-5.8

5

<0.0

01

<0.0

01

0.00

7 0.

63

0.

05

0.

10

<0.0

01

CA

D =

cor

onar

y ar

tery

dis

ease

; CI =

con

fiden

ce in

terv

al; M

I = m

yoca

rdia

l inf

arct

ion;

NST

EMI =

non

ST

segm

ent e

leva

ted

myo

card

ial i

nfar

ctio

n; O

R =

odd

s rat

io;

STEM

I = S

T se

gmen

t ele

vate

d m

yoca

rdia

l inf

arct

ion.

M

odel

adj

uste

d fo

r: ch

est p

ain,

age

gro

ups,

sex,

type

of M

I, fa

mily

his

tory

of C

AD

, pre

viou

s stro

ke, h

eart

failu

re &

ang

ina,

and

hos

pita

l dis

char

ge d

iagn

osis

.

93

Tabl

e 20

: Odd

s Rat

io E

stim

ates

from

Mul

tiple

Log

istic

Reg

ress

ion

Ana

lysi

s of t

he A

ssoc

iatio

ns b

etw

een

Patie

nt C

hara

cter

istic

s and

Hav

ing

a Pr

imar

y PC

I or a

‘Car

diac

Pro

cedu

re’

A

djus

ted

mod

el fo

r Prim

ary

PCI

Adj

uste

d m

odel

for c

ardi

ac

proc

edur

e

OR

95

% C

I P

valu

e O

R

95%

CI

P va

lue

No

ches

t pai

n A

ge g

roup

s,

≥8

0 ye

ars

70

to 7

9 ye

ars

60

to 6

9 ye

ars

<6

0 ye

ars

Type

of M

I (ST

EMI v

s. N

STEM

I)

Fam

ily h

isto

ry o

f CA

D

Prev

ious

hea

rt fa

ilure

H

ospi

tal d

isch

arge

dia

gnos

is (M

I, ot

her)

0.19

0.13

0.

93

2.10

1.

00

0.00

3 0.

61

0.05

-0.7

5

0.04

-0.4

6 0.

24-3

.68

0.44

-9.9

9

<0.0

01-0

.01

0.

08-4

.89

0.02

<0

.001

0.

001

0.92

0.

35

<0

.001

0.64

0.22

0.06

0.

64

0.74

1.

00

0.09

2.

36

0.24

0.

21

0.08

-0.5

1

0.02

-0.1

8 0.

21-1

.95

0.23

-2.4

2

0.04

-0.1

9 0.

92-6

.11

0.06

-0.9

7 0.

07-0

.66

0.00

2 <0

.001

<0

.001

0.

43

0.62

<0.0

01

0.08

0.

04

0.00

8

CA

D =

cor

onar

y ar

tery

dis

ease

; CI =

con

fiden

ce in

terv

al; M

I = m

yoca

rdia

l inf

arct

ion;

NST

EMI =

non

ST

segm

ent e

leva

ted

myo

card

ial i

nfar

ctio

n; O

R =

odd

s rat

io;

STEM

I = S

T se

gmen

t ele

vate

d m

yoca

rdia

l inf

arct

ion.

M

odel

adj

uste

d fo

r: ch

est p

ain,

age

gro

ups,

sex,

type

of M

I, fa

mily

his

tory

of C

AD

, pre

viou

s stro

ke, h

eart

failu

re &

ang

ina

and

hosp

ital d

isch

arge

dia

gnos

is

94

6.5.4 Survival Outcomes

The cohort of patients with an ED discharge diagnosis of MI were followed up for a

median time of 2.2 years (IQR 1.8-2.8 years, range 0-3.75 years). The log rank test for

equality of survival curves indicated patients who presented without chest pain had

significantly poorer survival than those who presented with chest pain. See Figure 11.

Figure 11: Kaplan-Meier Survival Plot for Patients with and without Chest Pain

In the multivariable Cox regression model, chest pain was not associated with survival

(HR 1.00; 95% CI, 0.69-1.46) (see Table 21). When data were stratified by Primary

PCI, chest pain was not associated with survival (No Primary PCI: HR 1.10; 95% CI,

0.75-1.61, and Yes Primary PCI: HR 0.74; 95% CI, 0.08-7.40). When data were

stratified by cardiac procedure, chest pain was not associated with survival (No ‘cardiac

procedure: HR 1.26; 95% CI, 0.86-1.85, and Yes ‘cardiac procedure’: HR 1.04; 95% CI,

0.18-5.98).

95

Tabl

e 21

: Haz

ard

Rat

io E

stim

ates

(fro

m u

nadj

uste

d an

d ad

just

ed C

ox re

gres

sion

ana

lyse

s) fo

r Cha

ract

eris

tics

Ass

ocia

ted

with

Myo

card

ial I

nfar

ctio

n w

ithou

t Che

st P

ain

U

nadj

uste

d m

odel

A

djus

ted

mod

el

H

R

95%

CI

p va

lue

HR

95

% C

I p

valu

e

No

Che

st p

ain

Age

gro

ups

≥8

0 ye

ars

70

to 7

9 ye

ars

60

to 6

9 ye

ars

<6

0 ye

ars

Fem

ale

sex

Type

of M

I (ST

EMI v

s. N

STEM

I)

Fam

ily h

isto

ry o

f CA

D

Prev

ious

Stro

ke

H

eart

failu

re

A

ngin

a H

ospi

tal d

isch

arge

dia

gnos

is (M

I, ot

her)

2.16

11.9

5.

52

0.80

1.

00

1.28

3.

00

0.16

2.02

3.

93

0.62

1.

70

1.52

-3.0

8

4.84

-29.

3 2.

13-1

4.3

0.22

-3.0

0

0.90

-1.8

0 1.

88-4

.80

0.06

-0.3

9

1.28

-3.2

0 2.

65-5

.81

0.20

-1.9

4 1.

20-2

.43

<0.0

01

<0.0

01

<0.0

01

<0.0

01

0.74

0.17

<0

.001

<0

.001

0.00

3 <0

.001

0.

41

0.00

3

1.00

7.49

3.

69

0.64

1.

00

0.

37

2.

29

1.

14

0.69

-1.4

6

2.95

-19.

0 1.

40-9

.74

0.17

-2.4

0

0.15

-0.9

4

1.53

-3.4

1

0.79

-1.6

5

0.99

<0

.001

<0

.001

0.

008

0.51

1.

00

0.

04

<0

.001

0.47

HR

= h

azar

d ra

tio; C

I = c

onfid

ence

inte

rval

; STE

MI =

ST

segm

ent e

leva

ted

myo

card

ial i

nfar

ctio

n; N

STEM

I = n

on S

TEM

I; C

AD

= c

oron

ary

arte

ry d

isea

se.

Mod

el a

djus

ted

for:

ches

t pai

n, a

ge g

roup

s, se

x, ty

pe o

f MI,

fam

ily h

isto

ry o

f CA

D, p

revi

ous s

troke

, hea

rt fa

ilure

& a

ngin

a an

d ho

spita

l dis

char

ge d

iagn

osis

.

96

6.6 Discussion

Some previous reviews 1,18 of sex differences in symptoms of MI found that presenting

without chest pain was more common in women than in men. However, findings from

other studies have been inconsistent: perhaps due to combining patients with different

diagnoses 39,46,47 (e.g. MI, unstable angina, and chest pain); or being restricted to

patients who presented with chest pain, or were within a particular age range; many

have small sample sizes; and many did not adjust for age, gender, interactions, and

comorbidity. 1,18

The major finding of this study were that MI without chest pain is common, and it is

associated with being over 70 years, and being female. Furthermore, presenting

with/without chest pain was not associated with survival after adjustment for covariates.

6.6.1 Presenting without Chest Pain

We found 26% of our MI cohort presented without chest pain, this is similar to other

large studies 1,18,31,116 whom also report 25% to 35% of patients present without chest

pain. This study demonstrates there are clear differences in demographic and clinical

characteristics between MI patients with and without chest pain. Our findings are

consistent with those in the literature that identify the following characteristics of MI

without chest pain include older age, 31,56,109,114,174 and female sex. 31,56,122 The reasons

why older patients experience MI without chest pain is not clearly understood. Possible

explanations include older patients may have more comorbidities, decreased pain

perception, or have cognitive changes (e.g. dementia). 178 Comorbid conditions of

diabetes, hypertension, and heart failure have been associated with MI without chest

pain. 178 The reason why women experience MI without chest pain is also not clearly

understood. Women have been reported to have less obstructive coronary disease at

angiography 120,121 and may have different locations of obstructing lesions. 117 This may

lead to different combinations of sympathetic and vagal stimulation, resulting in

differences in the reporting of pain. 123 Women with MI are also older and may also

have more comorbid conditions. 123 Another reason why older people and/or women

have less chest pain may be the way they express or report their symptoms. Some

studies179,180 have reported women use different language than men when describing

their symptoms of MI.

97

We also found differences in ED discharge diagnosis and hospital discharge diagnoses

between MI patients presenting with and without chest pain. This is not unexpected as

highly sensitive troponin assays can detect elevated troponin in the absence of MI. 181 If

a patient in ED has an elevated troponin they are more likely to have an ED discharge

diagnosis of MI. However, other clinical conditions (e.g. heart failure and renal failure)

may be associated with elevated cardiac troponin levels. 181 Further investigations

during the patient’s hospitalisation may result in a different hospital discharge

diagnosis.

6.6.2 Primary PCI or any Cardiac Procedure

We found patients were less likely to have a Primary PCI if they presented without

chest pain, consistent with the existing literature. 32,116,122,175 The Primary PCI activation

criteria at SCGH includes symptom onset less than 12 hours, electrocardiogram (ECG)

evidence of STEMI, less than 80 years, ongoing pain, and that the patient is mobile and

independent. However, clinicians are informed that the activation criteria are not

absolute and that patients who have typical ECG changes and other clinical features of

MI (e.g. shortness of breath, hypotension, malignant arrhythmias) should also be

considered for activation. This occurred in our study for five patients who presented

without chest pain and had a Primary PCI. Their symptoms included; collapse and

cardiac arrest prior to hospital arrival (n=2), severe shortness of breath (n=1), abdominal

pain and vomiting (n=1), and back pain radiating to left arm (n=1).

We also found patients were less likely to have a cardiac procedure during their

hospitalisation if they presented without chest pain. These findings are also consistent

with the literature, patients without chest pain are less likely to undergo an angiogram 31,32,56,173 and PCI 31,116,173 during hospital admission.

6.6.3 Survival Outcomes

Like others, we found that MI without chest pain was associated with decreased survival

in unadjusted analyses. 31-33,56,109,122,173-175 However, after multivariable adjustment we

did not find MI without chest pain was associated with survival. Two other studies 32,182

had similar results. One study, 32 only examined in-hospital survival. The other

longitudinal cohort study, 182 had a median follow-up of 5.4 years, however the

inclusion criteria to identify individuals with unrecognised MI was self-report and the

potential for recall bias was a limitation in this study. In contrast, many studies

98

31,33,56,109,122,173,174 after multivariable adjustment have found MI without chest pain to be

associated with poor survival. Our study only had a median follow-up of 2.2 years. The

loss to follow-up is expected to be low because of low emigration rates in WA, and

deaths out of the state have been shown to be less than 2%. 183 It is possible that, with

longer follow-up, significant differences in survival between patients with and without

chest pain may have emerged.

Identifying the symptoms of MI other than chest pain is vital for successful

management and timely treatment for patients who present atypically. The dominant

‘other’ presenting symptoms were shortness of breath; collapse, syncope or

unconsciousness; confusion; a fall; nausea; and dizziness. These findings are similar to

other studies, 56,114,173 which also found shortness of breath and collapse were the most

common presentation symptoms of MI without chest pain. However, these ‘symptoms’

are not specific to MI and can reflect a wide spectrum of patient conditions; which

poses a challenge for prehospital triage and triage in the ED.184

6.7 Limitations

Our study has several limitations. Data from this study were collected at a single

hospital and only included patients who arrived by ambulance which may limit the

generalisability of the results. There is no reason to suspect that hospital medical

documentation of symptoms of MI would differ in other similar tertiary-level

metropolitan hospitals. However, patients who did not arrive by ambulance may present

with a different symptom profile. Although, accuracy of data abstraction from the

medical notes was over 99%, 3 this was a retrospective cohort study and the available

data depends on the quality of the information recorded in the medical record. Our

sample size was small and we may have been unable to detect significant differences in

other patient characteristics (e.g. diabetes and hypertension) because of insufficient

statistical power. We also acknowledge ‘type of MI’ had missing data and the logistic

and Cox regression modelling excluded the missing data. Additionally, of all the

patients with an ED discharge diagnosis of MI, only 73% had a hospital discharge

diagnosis of MI. We decided a priori to include all patients with an ED discharge

diagnosis of MI, as during their ED admission and initially on the ward they were

managed as patients with suspected MI. We have also adjusted for type of hospital

discharge diagnosis in all of our models.

99

6.8 Implications for Practice, Research, Policy and Education

The current study supports the need to be able to better identify the high risk patient

who presents without chest pain. Using a standardised symptom assessment /

questionnaire to identify other symptoms of MI may assist in early identification of such

patients. Future studies should focus on ways to identify these high risk patients and

optimise their care. This is particularly important as our population continues to age,

and with women living longer than men, it is likely that patients without chest pain will

make up an increasing proportion of those having a MI.

Implications for policy include health campaigns that reflect a wide spectrum of

symptoms of MI and highlight possible differences in symptom presentation between

men and women. Advice not to exclude a diagnosis of MI in the absence of chest pain,

particularly in older patients and females, should be incorporated in the education of

professionals, including paramedics, General Practitioners, nursing and medical

personnel and those who give health advice and answer emergency telephone lines.

6.9 Conclusions

We compared the clinical and demographic characteristics and survival outcomes of

patients transported by ambulance with an ED discharge diagnosis of MI who presented

with and without chest pain. Older age and female sex were associated with presenting

without chest pain. After adjustment, we found no differences in survival between

patients who presented with and without chest pain.

101

Chapter 7: The Effect of Presenting Symptoms and Patient

Characteristics on Prehospital Delay in MI Patients

Presenting to ED by Ambulance: A Cohort Study

7.1 Introduction

This chapter is the Author’s Original Manuscript that has been published in Heart,

Lung, and Circulation.5 This manuscript describes prehospital delay times and the

presenting symptoms of MI that contribute to delay for all patients who presented to one

of the seven hospitals over a 22 month period. The symptoms of MI were extracted

from the paramedic patient care record (PCR). This final phase of the study aimed to

answer the fifth research question posed in Chapter 1, Section 1.4:

What is the prehospital delay time for MI patients transported by



There were only 10 studies185-194 of prehospital delay that were published in Australia.

The inclusion criteria for these studies differed, in that some studies included only

patients who presented with chest pain,191,194 while others included patients admitted to

a coronary care unit,185,186 or patients with acute coronary syndrome.188,189,192 Of the

acute coronary syndrome studies, two188,192 reported prehospital delay in MI patients;

one188 combined Australian and New Zealand patients, and the other192 had only 15

patients with MI. The three studies187,190,193 that included patients with MI were all

conducted before 1999 and at this time, different criteria were used to define MI.20

There was only one Australian study187 published in 1995 that examined symptom

presentation and delay time. The lack of recent published Australian literature on

prehospital delay contributed to the motivation to answer this final question.

7.2 Abstract

7.2.1 Background

Despite extensive literature on prehospital delay, there is little recent information about

prehospital delay time for Australian patients with myocardial infarction (MI).

102

7.2.2 Objectives

The aims of this study were to: (1) describe prehospital delay time for Western

Australian patients with MI; (2) identify variables and presenting symptoms of MI

which contribute to the delay.

7.2.3 Methods

This retrospective cohort study identified patients with an emergency department (ED)

discharge diagnosis of MI, transported by ambulance to one of the seven metropolitan

EDs in Perth, Australia between January 2008 and October 2009. Prehospital delay

times were analysed using univariable and multivariable linear regression models. Non-

numeric (word descriptions) of delay time were categorised.

7.2.4 Results

Of 1,633 patients, symptom onset-time was available for 1,003. For the 829 patients

with a numeric onset-time, median delay was 2.2 hours; decreased delay was associated

with age <70 years, presenting with chest pain, and diaphoresis. Increased delay was

associated with being with a primary health care provider, and if the patient was at

home and if the person who called the ambulance was anyone other than the spouse. Of

the 174 patients with non-numeric onset-times, 37% patients delayed 1-3 days and 110

(64.0%) patients described their symptoms as intermittent and/or of gradual onset.

7.2.5 Conclusion

Given that prehospital delay times remains longer than is optimal, public awareness of

MI symptoms should be enhanced in order to decrease prehospital delay.

7.2.6 Key Words

Myocardial infarction, prehospital delay, symptom presentation, emergency

7.3 Introduction

Over 49,000 patients per year have a myocardial infarction (MI) in Australia - about

135 per day - and nearly 40% of these events are fatal.195 Reperfusion therapy of an

103

obstructed coronary artery decreases myocardial damage and is vital in decreasing

mortality and morbidity; however, this intervention is time-critical and delays decrease

its efficacy.11,12

There has been considerable success in decreasing hospital delay times for MI patients

(i.e. door-to-treatment),196 but reducing prehospital delay, i.e. the total amount of time

taken by patients to present at the emergency department (ED) following acute

symptom onset, has been less successful.107,188 Australian studies185-194 on prehospital

delay report median prehospital delays of 1.2 to 6.4 hours. Internationally, overall

duration of prehospital delay has remained relatively unchanged over the last two

decades,107,169,188 and public educational campaigns185,197 and targeted education and

counselling141,197 have had little success in reducing prehospital delay.

Identification of variables associated with prehospital delay may lead to interventions

that succeed in shortening delay time. With the exception of increased delay time

associated with contacting a primary health care provider (HCP)80,107,198 and being alone

or at home107,199 at symptom onset, consistent factors that influence delay have not

emerged. There is an abundance of research focussing on prehospital delay but, of the

six studies80,187,198-201 that have investigated the effect of MI symptoms on delay time,

only one187 from 1995 specifically investigates Australian patients with MI, so an

update is timely. The aims of this study were to: (1) describe prehospital delay time in

Western Australian patients with an ED discharge diagnosis of MI who were

transported by ambulance; and (2) identify patient characteristics and presenting

symptoms of MI which contribute to this delay.

7.4 Methods

7.4.1 Study Design, Setting and Participants

A secondary analysis was performed on data originally collected for a study that

examined sex differences in symptoms of MI reported to ambulance dispatch.2 This

retrospective cohort study reviewed prospectively collected paramedic patient care

records (PCRs) and the emergency telephone calls of all adult patients with an ED

discharge diagnosis of MI transported by St John Ambulance Western Australia (SJA-

WA) to one of the seven Perth metropolitan public EDs between January 1, 2008 and

October 31, 2009. The Perth metropolitan area is over 5000 square kilometres and has a

104

population of 1.7 million.111 SJA-WA is the single provider of emergency road

ambulance for WA and is staffed by paramedics. Ethical approval was obtained for this

study from The University of Western Australia (RA/4/1/2428). See Appendix K.

7.4.2 Data Sources

Two databases were linked: the Emergency Department Information System113 (EDIS)

and the SJA-WA database. EDIS, an ED patient-tracking system containing patient

demographic and disposition data, was used to identify all adult patients with an ED

discharge diagnosis of MI during the study period. The SJA-WA patient database

contains records of all cases attended by ambulances in WA and the paper-based,

paramedic-completed PCRs. Data from the emergency phone call to SJA-WA was

retrieved and transcribed. Data collected included patient characteristics, time variables

and symptoms on presentation.

Symptoms reported on presentation and symptom onset-times were extracted from the

paramedics’ PCRs. If the onset-time was not available from the paramedic’s PCR, the

emergency phone call transcript was searched. Presenting symptoms of MI included:

chest pain; left arm; right arm; jaw, throat and neck pain; diaphoresis; shortness of

breath; abdominal or epigastric pain; nausea; vomiting; syncope, collapse or

unconscious; dizziness; weakness; fatigue; back pain; and a fall. Chest pain was

operationally defined to include right-sided, left-sided, and central chest pain, chest

tightness, and chest heaviness. Individual patients could experience multiple symptoms.

Additional information pertaining to the emergency phone call was collected, including

the day of the week (weekday or weekend), time of the day (0600-1159, 1200-1759,

1800-2359, 000-0559), the relationship of the caller to the patient and the patient’s

location. ‘Other location’ included sporting venues, shopping centres, hotels, education

centres, and the side of the road. Hospital arrival time was obtained from the EDIS.

7.4.3 Data Analysis

For patients with numeric symptom onset-times (e.g. 1-Jan 2008 15:30), prehospital

delay time was calculated by subtracting their ED arrival time from their symptom

onset-time. As delay times were skewed, they were described using medians and

interquartile ranges (IQR) and log transformed for further analyses. Each variable was

initially tested for association with delay time in a univariable linear regression model.

Multivariable linear regression was used to determine variables independently

105

associated with prehospital delay time. The initial multivariable model, which included

the variables listed in Table 22, was simplified in a stepwise fashion by removing the

variable with the least significant p-value and refitting the model until only variables

with p-values <0.10 were retained. As a final check, all excluded variables were retested

one at a time in the final multivariable model. Exponential beta coefficients [exp(B)]

and 95% confidence intervals (CIs) were reported. These values correspond to changes

in the ratio of the expected geometric means of the original delay time. Data were

analysed using SPSS version 22 (IBM Corp. Released 2011. IBM SPSS Statistics for

Windows, Version 22.0 Armonk, NY: IBM Corp) and significance was set at 0.05.

Non-numeric symptom onset-times (e.g. yesterday, three days ago, last week), were

categorised by two members of the research team (LC & AB). To enhance credibility

and auditability, data were categorised independently, categories were confirmed, and

disagreements were resolved by discussion until consensus was reached. Categories

included: ≤1 hour; >1 to 6 hours; >6 hours to 1 day; >1 day to 3 days; >3 days to 1

week; >1 week to 2 months. Categories were dichotomised (yes/no) if presenting

symptoms were intermittent and/or had a gradual onset.

7.5 Results

7.5.1 Characteristics of the Cohort

During the study period, January 2008 to October 2009, of the 3,329 patients who were

discharged from a Perth ED with a diagnosis of MI, 1,633 patients arrived by

ambulance (see Figure 12). Patients who were missing a symptom onset-time (n=630,

38.6%) were older (mean age 73.8 vs.70.8 years, p<0.001), and less likely to present

with chest pain (46.8% vs.73.7%. p<0.001). Of the 1,003 patients with prehospital delay

time available, 829 patients had a numeric symptom onset-time documented in the PCR

or the telephone transcript. The median prehospital delay time was 2.2 hours (IQR 1.3-

5.4; range 0.5-73.8), and 11.7% (n=97) of patients arrived in the ED within 1 hour of

symptom onset. Patients with a non-numeric symptom onset-time (n= 174, 17.3%) were

older (74.3 vs.70.1 years, p<0.001), less likely to present with chest pain (55.2%

vs.77.6%, p<001) and more likely to be women (44.3% vs.35.0%, p=0.02) than those

with numeric onset-times.

106



As shown in Table 22, patients with longer delay times were more likely to be older,

female, have had a fall, have a symptom onset-time between 1200-1759 hours, be at a

primary HCP or a nursing home, and if the patient was at home and the person who

called the ambulance was anyone other than the spouse. Patients with shorter delay

times were more likely to present with symptoms of chest pain, diaphoresis, and nausea.

EDIS confirmed discharge diagnosis of MI (Jan 1, 2008 to Oct 31, 2009)

n = 3,329


n = 2,100 Excluded, n = 419

• Transferred to a second hospital, included at first hospital (n = 32)

• Missing (No PCR, n = 28) • No emergency telephone call (n = 198) • ED nurse call. Patient used own transport to first

hospital and then transferred to second hospital (n = 161)

SJA-WA PCR & emergency telephone call

n = 1,681

Excluded, n = 48 • Not first admission

Index patients n = 1,633

Excluded, n = 630 • No delay time (n = 453) • No PCR due to industrial action (n = 117) • Missing PCR (n = 60)

Delay time n = 1,003

Date time variable for delay time n = 829

Men, n = 539 Women, n = 290

Descriptive words for delay time n = 174

Men, n = 97 Women, n = 77

107

Tabl

e 22

: Cha

ract

eris

tics o

f the

Sam

ple

(n=8

29),

and

Med

ian

Preh

ospi

tal D

elay

Var

iabl

e

n (%

) Pr

ehos

pita

l Del

ay

(Hou

rs)

Med

ian

(IQ

R)

Uni

varia

ble

linea

r reg

ress

ion

Exp(

B) (

95%

CI)

p-v

alue

Age

≥80

year

s

70 to

79

year

s

60 to

69

year

s

<60

year

s G

ende

r (M

ale=

0, F

emal

e=1)

Mal

e

Fem

ale

Pres

entin

g sy

mpt

oms r

epor

ted

(No=

0, Y

es=1

)

Che

st p

ain

Yes

N

o

Left

arm

pai

n

Y

es

No

R

ight

arm

pai

n

Y

es

No

Ja

w, t

hroa

t or n

eck

pain

Y

es

No

D

iaph

ores

is

Yes

N

o

Shor

t of b

reat

h

Y

es

No

257

(31.

0)

194

(23.

4 17

3 (2

0.9)

20

5 (2

4.7)

53

9 (6

5.0)

29

0 (3

5.0)

64

3 (7

7.6)

18

6 (2

2.4)

10

3 (1

2.4)

72

6 (8

7.6)

10

3 (1

2.4)

72

6 (8

7.6)

40

(4.8

) 78

9 (9

5.2)

11

4 (1

3.8)

71

5 (8

6.2)

38

7 (4

6.7)

44

2 (5

3.3)

3.0

(1.6

, 6.6

) 2.

4 (1

.4, 5

.4)

1.9

(1.2

, 4.5

) 1.

8 (1

.1, 3

.8)

2.0

(1.3

, 4.9

) 2.

6 (1

.5, 6

.0)

2.1

(1.3

, 4.8

) 2.

7 (1

.4, 7

.5)

1.9

(1.3

, 4.3

) 2.

2 (1

.3, 5

.6)

2.4

(1.4

, 6.3

) 2.

2 (1

.3, 5

.4)

2.0

(1.2

, 7.0

) 2.

2 (1

.3, 5

.4)

1.6

(1.2

, 2.8

) 2.

4 (1

.4, 5

.9)

2.1

(1.3

, 5.5

) 2.

2 (1

.3, 5

.4)

1.47

1.

23

1.09

1.

00

1.15

0.

80

0.89

1.

10

0.98

0.

63

1.02

(1.2

4, 1

.74)

(1

.03,

1.4

7)

(0.9

0, 1

.31)

(1

.00,

1.3

1)

(0.6

8, 0

.92)

(0

.74,

1.0

8)

(0.9

0, 1

.33)

(0

.73,

1.3

2)

(0.5

3, 0

.76)

0.

90-1

.16

<0.0

01

<0.0

01

0.02

0.

37

0.04

0.

003

0.25

0.

35

0.89

<0

.001

0.

79

108

Var

iabl

e

n (%

) Pr

ehos

pita

l Del

ay

(Hou

rs)

Med

ian

(IQ

R)

Uni

varia

ble

linea

r reg

ress

ion

Exp(

B) (

95%

CI)

p-v

alue

Abd

omin

al o

r epi

gast

ric p

ain

Yes

N

o N

ause

a

Y

es

No

V

omiti

ng

Yes

N

o Sy

ncop

e, c

olla

pse

or u

ncon

scio

us

Yes

N

o

Diz

zine

ss

Yes

N

o

Wea

knes

s

Y

es

No

Fa

tigue

Y

es

No

B

ack

pain

Y

es

No

Fa

ll

Y

es

No

Day

of t

he w

eek

(Wee

kday

=0, W

eeke

nd=1

)

Wee

kday

Wee

kend

18 (2

.2)

811

(97.

8)

280

(33.

8)

549

(66.

2)

108

(13.

0)

721

(87.

0)

28 (3

.4)

801

(96.

6)

77 (9

.3)

752

(90.

7)

27 (3

.3)

802

(96.

7)

27 (3

.3)

802

(96.

7)

92 (1

1.1)

73

7 (8

8.9)

15

(1.8

) 81

4 (9

8.2)

60

0 (7

2.4)

22

9 (2

7.6)

2.7

(1.4

, 5.2

) 2.

2 (1

.3, 5

.4)

2.1

(1.3

, 4.1

) 2.

3 (1

.3, 5

.9)

2.1

(1.4

, 4.6

) 2.

2 (1

.3, 5

.5)

2.9

(1.5

, 4.6

) 2.

2 (1

.3, 5

.4)

1.9

(1.4

, 4.4

) 2.

2 (1

.3, 5

.4)

2.6

(1.6

, 10.

0)

2.2

(1.3

, 5.4

) 3.

8 (1

.6, 6

.4)

2.2

(1.3

, 5.4

) 2.

2 (1

.4, 6

.5)

2.2

(1.3

, 5.4

) 4.

6 (2

.1, 1

0.0)

2.

2 (1

.3, 5

.4)

2.2

(1.3

, 5.5

) 2.

1 (1

.4, 5

.3)

1.05

0.

86

0.91

1.

24

0.88

1.

38

1.23

1.

12

1.64

1.

01

0.68

-1.6

2 (0

.75,

0.9

8)

(0.7

6, 1

.10)

(0

.87,

1.7

6)

(0.7

1, 1

.10)

(0

.97,

1.9

7)

(0.8

6, 1

.76)

(0

.92,

1.3

8)

(1.0

2, 2

.64)

(0

.87,

1.1

6)

0.83

0.

03

0.34

0.

23

0.27

0.

08

0.26

0.

25

0.04

0.

92

109

Var

iabl

e

n (%

) Pr

ehos

pita

l Del

ay

(Hou

rs)

Med

ian

(IQ

R)

Uni

varia

ble

linea

r reg

ress

ion

Exp(

B) (

95%

CI)

p-v

alue

Tim

e of

Day

0600

-115

9

1200

-175

9

1800

-235

9

0000

-055

9

Loca

tion

of p

atie

nt ±

who

cal

led

the

ambu

lanc

e

Hom

e &

spou

se c

alle

d

Hom

e &

Fam

ily/fr

iend

/nei

ghbo

r/wor

k co

lleag

ue c

alle

d

Hom

e &

a p

rofe

ssio

nal c

alle

d

Hom

e &

the

patie

nt c

alle

d

Hom

e &

not

sure

who

cal

led

Fam

ily/fr

iend

/nei

ghbo

r/or w

ork

plac

e

Prim

ary

HC

P

Nur

sing

hom

e

O

ther

loca

tion

277

(33.

4)

192

(23.

2)

189

(22.

8)

171

(20.

6)

200

(24.

1)

171

(20.

6)

98 (1

1.8)

10

3 (1

2.4)

37

(4.5

) 30

(3.6

) 80

(9.7

) 58

(7.0

) 52

(6.3

)

2.4

(1.4

, 5.6

) 2.

4 (1

.3, 8

.1)

1.9

(1.2

, 4.7

) 2.

2 (1

.2, 4

.2)

1.7

(1.1

, 3.5

) 2.

6 (1

.4, 5

.7)

3.0

(1.6

, 7.0

) 2.

2 (1

.3, 5

.2)

2.6

(1.4

, 6.6

) 1.

3 (1

.0, 1

.9)

5.1

(2.4

, 11.

6)

2.7

(1.5

,5.1

) 1.

3 (1

.0, 2

.8)

1.18

1.

29

1.06

1.

00

1.25

1.

77

2.14

1.

54

1.77

1.

21

3.16

1.

77

1.00

(0.9

9, 1

.41)

(1

.07,

1.5

6)

(0.8

7, 1

.28)

(0

.95,

1.6

4)

(1.3

5, 2

.34)

(1

.59,

2.8

8)

(1.1

5, 2

.07)

(1

.22,

2.5

7)

(0.8

1, 1

.81)

(2

.32,

4.3

0)

(1.2

7, 2

.47)

0.04

0.06

0.

009

0.56

<0

.001

0.11

<0.0

01

<0.0

01

0.00

4 0.

003

0.35

<0

.001

0.

001

110

7.5.2 Multivariable Analysis

Results of the multivariable linear regression analysis are presented in Table 23. Delay

times were 17% (95% CI, 4-28%) shorter if presenting with chest pain and 28% (95%

CI, 15-40%) shorter if presenting with diaphoresis. Delay times compared with being

<60 years, were 38% (95% CI, 16-64%) longer if ≥80 years, and 20% (95% CI, 1-43%)

longer if 70-79 years. Delay times compared with being at some other location, were

195% (95% CI, 119-299%) longer if with a primary HCP, and if the patient was at

home, delay times were 91% (95% CI, 42-156%) longer if a professional called the

ambulance, 54% (95% CI, 7-121%) longer if not sure who called, 51% (95% CI, 15-

99%) longer if the person who called was a family, friend, neighbour or work colleague,

and 42% (95% CI, 6-89%) longer if the patient called the ambulance.

Table 23: Multivariable Linear Regression Log Delay Time in Minutes

Variables Multivariable linear regression Exp(B) 95% CI p-value

Age (Years) ≥80 years 70 to 79 years 60 to 69 years <60 years

1.38 1.20 1.05 1.00

(1.16, 1.64) (1.01, 1.43) (0.88, 1.25)

0.001

<0.001 0.04 0.57

Presenting symptoms reported (No=0, Yes=1) Chest pain Right arm pain Diaphoresis

0.83 1.20 0.72

(0.72, 0.96) (1.00, 1.44) (0.60, 0.85)

0.01 0.05 <0.001

Location of patient ± who called the ambulance Home & spouse called Home & Family/friend/neighbor/work colleague called Home & a professional called Home & the patient called Home & not sure who called Family/friend/neighbor/or work place Primary HCP Nursing home Other location

1.20 1.51 1.91 1.42 1.54 1.22 2.95 1.38 1.00

(0.93, 1.57) (1.15, 1.99) (1.42, 2.56) (1.06, 1.89) (1.07, 2.21) (0.82, 1.79) (2.19, 3.99) (0.98, 1.93)

<0.001 0.17 0.003 <0.001 0.02 0.02 0.32 <0.001 0.06

Of patients with non-numeric prehospital delay times, most (n=65, 37%) delayed

between 1 to 3 days from symptom onset (see Table 24), and 110 (64%) had

documented statements of ‘intermittent’ (n=97) and/or ‘gradual onset’ (n=77) of

symptoms over a period of time. Descriptions of symptom onset-times included “pain

started after lunch”, “has had chest pain all day”, “3-day history of fatigue and malaise”,

“has had pain in jaw intermittently for a few days”, “complaining of left shoulder pain

111

and left arm pain for past 6-days”, and “experiencing chest pain 3 to 4 times per week

for the past 2 months.”

Table 24: Categorised Time Intervals from Non-Numeric Symptom Onset-Times and

Relationship with Intermittent or Gradual Onset of Symptoms (yes/no)

7.6 Discussion

Prehospital time is the most important component of total delay for MI patients, and

delay to definitive treatment is associated with increased mortality and morbidity.11,12

Median prehospital delay in our study was 2.2 hours which is comparable to other

international studies.107,188 Only 11.7% (n=97) of patients arrived in the ED within the

accepted window of 1 hour needed for the greatest benefit to be gained from reperfusion

therapy.11

Our findings were similar to other studies in that older age107,169 was associated with

increased prehospital delay. Patients ≥80 years delayed a median of 1.2 hours longer

than patients <60 years. Several studies have suggested this may be because older

patients report atypical symptoms compared with younger patients.107 Symptom

presentation was also important. Similar to other studies, decreased delay was

associated with patients presenting with diaphoresis80,187,200 and chest pain.169,199-201

Twenty per cent of patients did not have a documented numeric onset-time and had

words describing their onset-time. Of these patients, almost two thirds had documented

‘intermittent’ and/or ‘gradual onset’ of symptoms. Two other studies198,202 have reported

the intermittent and gradual nature of symptom onset as an important factor associated

with delay. This is a key finding as the pain from myocardial ischaemia can come and

go, and can be temporarily relieved by rest and vasodilators. These data reinforce the

importance of symptom presentation in relation to delay in seeking medical treatment.

Category Intermittent or gradual onset

of symptoms n (%) Total Yes No

≤1 hour 0 (0.0) 5 (100.0) 5 >1 hour to 6 hours 3 (33.3) 6 (66.7) 9 >6 hours to 1 day 30 (52.6) 26 (45.6) 57 >1 day to 3 days 48 (73.8) 17 (26.2) 65 >3 days to 1 week 15 (75.0) 5 (25.0) 20 >1 week to 2 months 14 (87.5) 2 (12.5) 16 Missing 2 Total 174

112

Symptom identification alone may not be sufficient to motivate a patient to seek

medical attention. We found the role of family members, friends, and co-workers in

assisting the patient to make the decision to call the ambulance important. In this study,

if the patient was at home and if the person who called was anyone other than the

spouse, there was an increased delay. We also found that if a ‘professional’ initiated the

phone call from the patient’s home there was an increased delay. A ‘professional’ in this

study included a health monitoring company, a locum doctor, security personnel at a

low care facility, or Health Direct. Health Direct is a government funded, free 24 hour,

7 day a week, health advice line answered by registered nurses. All of these

‘professionals’ relied on the patient to contact them in the first instance. We cannot

assume the patients were alone at symptom onset, however, many studies107,199 have

found that patients who were alone at time of symptom onset were more likely to delay

seeking medical treatment. Also similar to previous studies, consulting a primary

HCP80,198 was associated with increased delay. The median delay for these patients was

5.1 hours.

It is of concern that only 63.1% (n=2100) of patients arrived by ambulance in this study.

The risk of sudden cardiac death within the first hour of symptoms is much increased.197

Paramedics are trained and equipped to recognise and treat life-threatening cardiac

arrhythmias should they occur and the ambulance is usually the quickest mode of

transport to hospital.

7.7 Strengths and Limitations

This study has several strengths, including its population-based design that captured all

public ED MI discharge diagnoses in Perth’s metropolitan area over a 22-month period.

However, several limitations need to be considered. Information about prehospital delay

was abstracted from the paramedic’s PCR or the emergency telephone call transcript.

We do not know if the delay time was the same for patients who did not arrive by

ambulance, but calling the ambulance is known to be associated with a shorter delay

time.169,192 Over a third of patients had missing data on delay time. Although rates of

missing delay time in this study did not differ from another study,107 the rates differed

by age, sex, and whether or not the patient presented with chest pain; therefore our

findings should be interpreted with caution. Nonetheless there were 1003 patients for

whom we had onset-time in this study. One of the challenges in conducting a

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retrospective cohort study is the reliance on the accuracy of reported symptom presence

and onset-time. Paramedic and medical record documentation of symptom presence and

onset-time has been reported in a prior study.3 In brief, agreement between the two

records for symptom presence was excellent, and symptom onset-time agreed exactly

for 60% of the records and times were within 30 minutes for over 80% of the records.

While we adjusted for a number of demographics, symptom presentation, location, and

time factors, we did not have information on other factors that may have influenced

delay, such as patient comorbidity, psychosocial, cognitive, and situational factors.

7.8 Recommendations for Future Study

Although rapid treatment after symptom onset of MI is associated with better outcomes,

most patients did not reach the hospital within the optimal time frame. Future research

needs to incorporate patient interviews into research designs that will assist in

understanding how individuals interpret their symptoms, and how they make the

decision to seek medical attention.

Our findings suggest that future interventions should not only target education in high-

risk populations, but also older adults, and patients who present without chest pain.

Many of the patients were with someone at symptom onset; therefore, including family

members, friends and co-workers in education programmes is crucial. Education must

include not only common symptoms of MI, but the atypical, intermittent, and

progressive nature of some symptoms, and it is essential to emphasize the urgency of

immediate emergency transport by ambulance. Information should be disseminated

face-to-face at patients’ bedsides, as written information on ward corridor walls, and on

electronic screens in outpatient areas. Public education media campaigns in the

community should include articles in the newspaper, on the radio, and television

programmes.

Another aspect that requires further investigation is the role of the primary HCP. The

primary HCP called the ambulance for 10% (n=166) of the patients in our cohort.

Further research is required to investigate how the primary HCP establishes their office

routines to care for patients with suspected MI. It would be valuable to know the

incidence of calls to primary HCPs involving symptoms suggestive of MI, and the

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patient characteristics of those who did not require ED evaluation and treatment and

were successfully managed by their primary HCP.

7.9 Conclusions

This population-based study found the delay to hospital after symptom onset exceeded

the recommended one hour.11 Shorter delay was associated with presenting with the

symptoms of chest pain and diaphoresis, and longer delay was associated with older

age, calling a primary HCP, and the patient’s relationship with the person who called

the ambulance. Given that delay times continue to be prolonged, public awareness of

MI symptoms and the need to seek help early should be enhanced, in order to decrease

prehospital delay and improve MI survival.

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Chapter 8: Discussion

8.1 Introduction

This doctoral research comprised a systematic review and meta-analysis, and analyses

that used linked data, to answer research questions pertaining to symptom presentation

in MI, ambulance times, survival, and prehospital delay. In this chapter the major results

are summarised and compared with the results of other studies published after the

manuscripts in Chapters 2, 4, 5, 6 and 7 were published. This chapter also describes the

strengths and limitations of the research, with reference to its implications and

recommendations for policy, practice, and future research.

Since the manuscripts in this thesis were accepted for publication there have been

further studies published on sex differences in symptom presentation of MI, and

ambulance times. No recent studies were found that related to the paramedic patient

care record (PCR) and the hospital medical record concordance of symptoms of MI,

survival differences between patients presenting with and without chest pain; or studies

that report the patient characteristics and presenting symptoms which contribute to

prehospital delay.

8.2 Overview of Major Findings

The research questions posed in Chapter 1, Section 1.4 are repeated here with the

answers suggested by the statistical analyses of the data available for this PhD research

and the published literature to date.

1. Do men and women equally present with chest pain as a symptom of

MI and are there sex differences in other presenting symptoms of MI?

The study described in “Sex differences in symptom presentation in acute myocardial

infarction: a systematic review and meta-analysis” (Chapter 2) found that women with

MI had lower odds and a lower rate of presenting with chest pain than men. Women

were significantly more likely to present with fatigue, neck pain, syncope, nausea, right

arm pain, dizziness, and jaw pain.

116

Three studies203-205 that investigated sex differences in symptom presentation of MI and

one meta-analysis206 have been published after completion of the literature search (in

October 2009) for the manuscript in Chapter 2. Two of these studies203,204 found that

women were less likely than men to present with chest pain, supporting the results of

this thesis. The other study205 which found no sex differences for the symptom of chest

pain only included patients aged 25 to 74 years. But as reported in “Myocardial

infarction: sex differences in symptoms reported to emergency dispatch” (Chapter 4)2

the mean age of women who had a MI was 77.6 years compared with 69.1 years for

men, so the upper limit of 74 years in the Kirchberger205 study may have excluded some

women who had a MI.

With regard to other symptoms of MI, one study205 had similar findings in that women

were more likely than men to experience nausea, jaw pain, and dizziness; and the other

study203 found women were more likely to experience neck pain. In addition to these

symptoms, the “Sex differences in symptom presentation in acute myocardial infarction:

a systematic review and meta-analysis” (Chapter 2) found women were more likely than

men to experience left arm pain, vomiting, dyspnoea, and back pain. However, the

manuscript in Chapter 2 reported moderate to substantial heterogeneity for these

additional symptoms and suggested it may be misleading to report a combined summary

measure. One study205 had similar findings in that women were more likely than men to

experience left arm pain, vomiting, dyspnoea, and two studies203,205 found women were

more likely than men to experience back pain.

The meta-analysis206 had similar findings to those reported in Chapter 2, but reported

effect sizes (standardised risk differences) rather than odds and rate ratios. Although

men were more likely than women to report chest pain and diaphoresis; the effect size

for each symptom was small. In order of decreasing effect size, women were

significantly more likely than men to report loss of appetite, back pain, palpitations,

nausea and vomiting, neck pain, jaw pain, fatigue, dyspnoea, dizziness, and right arm

pain.

2. Are the symptoms, in particular chest pain, reported during the

emergency telephone call to SJA-WA, and ambulance response times,

the same for men and women with MI?

117

The study described in “Myocardial infarction: sex differences in symptoms reported to

emergency dispatch” (Chapter 4) found that women were less likely than men to report

chest pain and were more likely to present with vomiting. It also found that ambulance

response times did not differ between men and women with chest pain. However,

women with chest pain were less likely than men with chest pain to be allocated a

priority 1 (lights and sirens) ambulance response.

Two studies that examined symptom presentation to emergency dispatch207 and

ambulance times207,208 have been published recently. One study207 found men and

women were similar with regard to presenting symptoms when they called emergency

dispatch. A possible reason for this differing from the results in “Myocardial infarction:

sex differences in symptoms reported to emergency dispatch” (Chapter 4) is that this

study only included patients with a STEMI, and patients who have a STEMI are more

likely to present with chest pain.

Irrespective of presenting with similar symptoms, Melberg 207 also found women with

STEMI were given a lower priority ambulance response. They concluded emergency

dispatch may have difficulty in reaching action decisions with women and, as men and

women presented similarly, there was a possibility of gender-specific bias in ambulance

priority response. Another study208 reviewed ambulance times in a cohort of patients

who had a prehospital electrocardiogram and presented with chest pain. They found a

significant difference of 2 to 4 minutes between men and women with regard to

ambulance scene time and total scene to hospital time. Additionally, they stated that in

the case of women with STEMI this could translate into a possible increase of 0.25% to

1.6% in mortality.

3. Are paramedic records a reliable source of information about

presenting symptoms of MI and onset-time of symptoms compared

with the documentation in the hospital medical record?

The study described in “Symptoms of myocardial infarction: concordance between

paramedic and hospital records” (Chapter 5) demonstrated that documentation of the

common symptoms of MI and symptom-onset time were similar between the paramedic

and hospital records. This phase of the study was important as it validated the accuracy

of the paramedic documentation which was used to answer the final research questions.

This study justified the use of paramedic PCRs as a source of data for research in

118

prehospital MI and patient delay. No further studies have been found post acceptance of

the Chapter 5 manuscript.

4. Are patient characteristics and patient outcomes (survival and

hospital discharge diagnosis) of patients presenting with and without

chest pain the same?

The study described in “Characteristics and outcomes of MI patients with and without

chest pain: a cohort study” (Chapter 6) found that characteristics differed between

patients with and without chest pain. The odds of presenting without chest pain were

increased for patients who were over 70 years of age and for women. However,

presenting with the symptom of chest pain was not associated with survival. Since this

manuscript has been published no further studies of MI patient characteristics and

outcomes of patients presenting with and without chest pain have been found.

5. What is the prehospital delay time for MI patients transported by



The study described in “The effect of presenting symptoms and patient characteristics

on prehospital delay in MI patients presenting to emergency department by ambulance:

a cohort study” (Chapter 7) found that median delay was 2.2 hours and decreased delay

was associated with age <70 years, presenting with chest pain, and diaphoresis.

Increased delay was associated with being with a primary health care provider, if the

patient was at home, and if the person who called the ambulance was anyone other than

their spouse. Many patients described their symptoms as intermittent and/or of gradual

onset. Since this manuscript has been published no further studies of MI patient

characteristics and presenting symptoms which contribute to prehospital delay have

been found.

8.3 Strengths of the Study

The strengths of the systematic review (Chapter 2) are that the application of an updated

search strategy enabled all additional studies up to September 2009 to be considered for

inclusion, study inclusion criteria were precise, and a quality assessment of each study

119

was conducted. This review was the first to conduct meta-analyses of sex differences in

chest pain and other symptoms of MI and quantify the differences in MI presentation

between men and women.

The strength of the retrospective cohort studies, presented in Chapters 4, 5, 6 and 7, are

that they analysed data from a population-based cohort of patients with ED-confirmed

MI, drawn from all public hospitals EDs in the Perth metropolitan area over a 22-month

period. Furthermore, SJA-WA covers the largest area of any single ambulance service

in the world and is the single provider of emergency road ambulance for WA. SJA-WA

data are ideal for epidemiological research for a number of reasons: almost three

quarters of WA’s population resides in Perth; the state’s population is relatively stable;

and there is an absence of border drift with adjoining state ambulance services due to

the natural barrier afforded by inland Australia.

To our knowledge, Chapter 4 is the first study to analyse symptoms of MI reported

during the emergency phone call for ED confirmed MI patients, and Chapter 5 is the

first study to analyse the concordance between documentation of symptoms of MI

between the paramedic and hospital records.

A further strength of this thesis present the use of three different data sources for the

same patient cohort. These independent sources are the transcribed emergency

telephone call (Chapter 4), the documentation from the paramedic PCR (Chapter 5 & 7),

and the documentation from the hospital medical record (Chapter 5 & 6). As the three

sources all showed women and older age were associated with presenting without chest

pain, we are confident that the findings are sound.

8.4 Limitations of the Study

Several limitations need to be acknowledged when considering the results presented in

this thesis. The systematic review and meta-analyses (Chapter 2) were conducted by one

investigator (the candidate, LC), who reviewed the literature, and extracted and

analysed the data. However, the search strategy, inclusion / exclusion criteria, data to be

extracted, and analyses were based on consensus among all three authors, and any

uncertainties were resolved through discussion. Other potential limitations of the

systematic review include reporting bias,209 in that the data were abstracted from the

120

medical records, which may have led to under-reporting of patients’ presenting

symptoms; and recall bias209 in data from the studies that used questionnaires and

interviews to collect symptoms of MI.

A limitation of the retrospective cohort studies (Chapters 4 to 7) is that they only

included patients with an ED-confirmed diagnosis of MI and the patient may not have

had a hospital discharge diagnosis of MI. In the study that compared characteristics and

outcomes for patients who presented with and without chest pain (Chapter 6), 27% of

the patients with an ED discharge diagnosis of MI did not have a hospital discharge

diagnosis of MI. Although, this discrepancy could not be ascertained for the cohorts in

Chapter 4, 5, and 7, we would assume similar results. In addition, the cohorts only

included patients who arrived by ambulance, and comprised 63% of the patients with an

ED-confirmed diagnosis of MI. When reviewing the results of this study, it must be

considered that patients who did not arrive by ambulance may present with a different

symptom profile.

One of the challenges of conducting a retrospective cohort study of MI symptoms

(Chapters 5, 6, and 7) is the reliance on the accuracy of the documented symptoms.

Some of the patient’s presenting symptoms of MI may not have been considered

relevant and, consequently, they were not documented by paramedics or medical staff.

It is also important to highlight that ambulance dispatch officers do not attempt to elicit

the full range of symptoms experienced by the patient. Once chest pain is mentioned,

the need for a priority 1 response is established, and any further questioning about

symptoms is unlikely.

The data for the manuscripts in Chapter 5 and 6 were collected at a single hospital,

which may limit the generalizability of the results. However, there is no reason to

suspect that hospital medical documentation of symptoms of MI would differ in other

similar tertiary-level metropolitan hospitals. The sample size for the manuscript in

Chapter 5 was small, thus the lack of significant differences in some patient

characteristics (e.g. diabetes and hypertension) may have been due to insufficient

statistical power.

121

8.5 Implications of Thesis Findings

8.5.1 Implications for Public Health

Overall duration of prehospital delay has remained relatively unchanged over the last

two decades,107,169,188,210 and public educational campaigns185,197 and targeted education

and counselling141,197 have had little success in reducing prehospital delay. This doctoral

thesis supports both men and women, and older patients may present atypically or

without chest pain. Implications for policy include health campaigns that educate the

public that the spectrum of symptoms of MI is wide. A snippet of some of the findings

from this thesis will be reported in the Edith Cowan University magazine Cohesion (see

Appendix P). This story discusses some of the major findings: the key message for the

public is that both men and women, and older patients may not experience chest pain as

a symptom of a heart attack. If they do experience symptoms of heart attack they should

call an ambulance immediately.

To educate the public a multi-media approach should be adopted that includes

advertising in magazines, newspapers, and in radio and television programmes.

Information should be disseminated face-to-face at patients’ bedsides, as written

information on ward corridor walls, and on electronic screens in outpatient areas. Social

media and social network sites are evolving and should be utilised to educate the public

about the symptoms of MI. An example of a web page is Her Heart211 produced by

Professor Linda Worral-Carter and this web page discusses heart disease in women,

including, signs and symptoms of heart attack, know your risk, and how to change your

lifestyle. Web pages, health campaigns and education are particularly important as our

population continues to age, and with women living longer than men, it is likely that

patients without chest pain will make up an increasing proportion of those having a MI.

8.5.2 Implications for Professional Practice

The systematic review and meta-analyses challenge the stereotypical Hollywood

depiction of a MI as a dramatic onset of chest pain and collapse. In addition, the

retrospective cohort studies show that women and older persons are less likely to

experience chest pain as a symptom of their MI (Chapters 2, 4, and 6). Prehospital and

emergency department clinicians need to understand that just because a patient does not

have central sternal crushing chest pain, this does not exclude the possibility of an MI.

122

The education of professionals; including paramedics, General Practitioners, nursing

and medical personnel and those who give health advice and answer emergency

telephone lines; needs to emphasise that MI can occur without chest pain and that there

are other atypical symptoms that should be considered. Education should include the

intermittent and progressive nature of symptoms, and it is essential to emphasize the

urgency of immediate emergency transport to hospital by ambulance.

Another snippet of some of the findings from this thesis has been reported in the

Australian Doctor magazine (see Appendix Q). This story discusses that patients with

MI who initially visit their GP too an average of five hours to reach ED. The also story

also reiterates the importance of going to hospital immediately.

8.6 Areas for Future Research

This thesis has contributed to our knowledge about the symptoms of MI, the emergency

telephone call and ambulance times, characteristics associated with MI with and without

chest pain, and characteristics associated with prehospital delay; however, further

research questions remain. Future research into symptoms of MI presentation should be

prospective to increase reporting accuracy, and it should use a standardised symptom

checklist, as recently recommended by Canto and colleagues.212 A standard symptom

checklist would allow for comparative analyses between published studies and

adjustment for differences in age, sex, race, comorbidity, and type of MI (STEMI /

NSTEMI).

This research found a persistent underuse of the emergency ambulance with only 63%

of patients with an ED discharge diagnosis of MI calling an ambulance. The reasons

why 37% of patients in Perth chose not to call an ambulance warrant further

exploration. Current Australian guidelines213 recommend that if you experience the

warning signs of a heart attack for 10 minutes, if they are severe or get progressively

worse, make an emergency telephone call by dialing triple zero (000) immediately and

ask for an ambulance.

It was found that 80% of patients with an ED discharge diagnosis of MI who called an

ambulance were allocated a priority 1 ambulance response (Chapter 4). Those patients

123

who were allocated a priority 2 or 3 response had longer median time from emergency

call to hospital arrival. The other symptoms of MI (e.g. shortness of breath, collapse,

confusion, nausea etc.) are not specific and can reflect a wide spectrum of conditions

and thus pose challenges to ambulance dispatch officers and triage in the ED. Further

research is required to investigate strategies that better identify patients who do not

present with classic MI symptoms; otherwise, they are unlikely to be allocated to a

high-priority response or ED triage category and will consequently have increased delay

to definitive treatment.

Although rapid treatment after symptom onset of MI is associated with better outcomes,

most patients did not reach the hospital within the optimal time frame of 60 minutes.

Future research needs to incorporate patient interviews into research designs that will

assist in understanding how individuals interpret their symptoms, and how they make

the decision to seek medical attention. Research should not only target high-risk

populations, but also older adults, and patients who present without chest pain.

Additionally, many patients were with someone at symptom onset, therefore including

family members, friends and co-workers in future interventional studies may assist in

decreasing delay times.

Another aspect that requires further investigation is the role of the primary health care

provider. The primary health care provider called the ambulance for 10% (n=166) of the

patients in our cohort. It would be valuable to know the incidence of visits to primary

health care providers that involved patients with symptoms suggestive of MI, and the

patient characteristics of those who did not require ED evaluation and treatment and

were successfully managed by their primary health care provider.

8.7 Conclusion

This doctoral thesis contributes to the evidence about sex differences and symptoms of

MI presentation. The meta-analysis demonstrated women were less likely than men to

present with chest pain as a symptom of MI and women were more likely to present

with fatigue, neck pain, syncope, right arm pain, dizziness, and jaw pain. This is the first

study to quantify the differences in MI presentation between men and women by meta-

analyses. The retrospective cohort studies demonstrated women were also less likely to

present with chest pain in their emergency telephone call to the ambulance service, as

124

were older patients.

This research demonstrated good to excellent concordance in the reporting of the

symptoms of MI between the paramedic and the hospital medical record. These findings

support the use of prehospital paramedic documentation as an acceptable means of

obtaining data for research purposes.

It was also found that the delay to hospital after symptom onset for WA patients

exceeded recommended time frames. Shorter delay was associated with the symptoms

of chest pain and diaphoresis, and longer delay was associated with older age, calling a

primary health care provider, and the patient’s relationship with the person who called

the ambulance.

Given that for MI, the symptom of chest pain differs with age, as well as between men

and women, and prehospital delay times remain longer than recommended, public

awareness of symptoms and health professionals’ education about symptoms should be

enhanced to reduce time from symptom onset to definitive care.

125

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Appendices

145

Appendix A: Sex Differences in Symptom Presentation in Acute

Myocardial Infarction: A Systematic Review and Meta-analysis

160

Appendices B & C removed due to copyright restrictions.

Coventry, L. L., Bremner, A., Jacobs, I., & Finn, J. (2013). Myocardial infarction: Sex differences in symptoms reported to emergency dispatch. Prehospital Emergency Care, 17(2), 193-202. 10.3109/10903127.2012.722175

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181

Appendix D: Characteristics and Outcomes of MI Patients with and

without Chest Pain: A Cohort Study

191

Appendix E: The Effect of Presenting Symptoms and Patient

Characteristics on Prehospital Delay in MI Patients Presenting

to ED by Ambulance: A Cohort Study

199

Appendix F: Abstract for Cardiac Society of Australia and New

Zealand conference titled - Sex Differences in Symptom

Presentation in Acute Myocardial Infarction: A Systematic

Review and Meta-analysis

Abstract 1

201

Appendix G: Poster for American Heart Association conference titled -

Sex Differences in Symptoms Reported to Emergency Medical

Dispatch in Acute Myocardial Infarction Patients - Impact on

Pre-hospital Delay

203

Appendix H: Abstract for American Heart Association conference

titled - Sex Differences in Symptoms Reported to Emergency

Medical Dispatch in Acute Myocardial Infarction - Impact on

Prehospital Delay

Abstract 2

205

Appendix I: Poster for Paramedics Australasia conference titled -

Gender Differences in Emergency ‘000’ Calls and Ambulance

Response for Acute Myocardial Infarction (AMI) Patients

207

Appendix J: Abstract for Paramedics Australasia Conference titled –

Gender differences in Emergency ‘000’ Calls and Ambulance

Response for Acute Myocardial Infarction (AMI) Patients

209

Appendix K: The University of Western Australia Human Research

Ethics Committee – Ethics Approval

211

Appendix L: Sir Charles Gairdner Hospital Human Research Ethics

Committee – Ethics Approval

213

Appendix M: Reciprocal The University of Western Australia Ethics

for Sir Charles Gairdner Hospital Study

215

Appendix N: Government of Western Australia Department of Health

Human Research Ethics Committee Conditional Approval

217

Appendix O: Government of Western Australia Department of Health

Human Research Ethics Committee Final Approval

219

Appendix P: Cohesion – Mysteries of the Heart Continue to Confound

our Response

MYSTERIES OF THE HEART CONTINUE TO CONFOUND OUR RESPONSE

The standard Hollywood representation of a heart attack, like many dramatisations of

life-threatening events, over-simplifies what is in reality a complex and variable medical

emergency that is only slowly yielding its secrets to medical researchers.

ECU Research Fellow Linda Coventry, in a series of investigative papers that together

make up her PhD thesis, has explored the events that precede presentation by men and

women at major public hospitals who are subsequently diagnosed as having suffered a

myocardial infarction (MI), or heart attack.

“Some of the research findings in this area are really quite surprising,” she says. “For

example, about a third of the women and a quarter of the men who are diagnosed with

MI, having arrived at hospital in an ambulance, have not experienced any chest pain.

“Typically, the absence of this diagnostic signal is more prevalent among people in the

70 and 80-year age groups, and as the population ages we need to be aware that the

incidence of easily-recognised warning signals may decrease.

“Health and para-medical professionals will be on the lookout for other symptoms, such

as shortness of breath, sweating, or collapse, but education about when an ambulance

needs to be called should be brought to the entire adult population.”

The firm rule about a suspected heart attack is that an ambulance should be called

immediately to take the patient to hospital. This is time-critical: the patient should

arrive at hospital less than 60 minutes after first symptoms of a heart attack, so that he

or she can be admitted, and taken to the catheterisation laboratory for a coronary

angiography within 90 minutes.

“The cohort that I studied had an average delay time of 2.2 hours, and these were

patients who arrived by ambulance,” Linda says. “Many people who feel unwell, but

who don’t have chest pain or the period of chest pain has stopped, may make an

appointment with their GP.

220

“Once they get a consultation they are likely to be sent for a blood test, and when the

results show that a heart attack has occurred the doctor will ring them and tell them to

call an ambulance. About 10% of my cohort first went to their GP, and their median

time delay in hospital presentation was 5½ hours.”

Unlike some other studies, Linda’s research did not show any difference in the mortality

rates of those presenting with chest pain, compared with those who did not. “Most of

the big studies show that if you present without chest pain, you are less likely to

survive,” she says.

“The difference in my results was possibly because I had a smaller cohort, or there

could have been other factors at play. I started with 3,030 patients diagnosed with MI,

but my study only investigated the ones who arrived at hospital by ambulance.

“This was 63% of the total group, and that in itself is cause for concern. The remainder

were driven to hospital, took public transport or in some cases took the very dangerous

option of driving themselves.

“Some of the case notes for those who delayed going to hospital make quite worrying

reading. Patients have reported symptoms such as ‘had pain in jaw intermittently for a

few days’, and ‘left shoulder pain and left arm pain for the past six days’, and ‘chest

pain three to four time per week for the past two months’.

“This poses challenges for health care professionals,” Linda says. “We need further

research to investigate strategies to better identify the high risk patients who present

without chest pain.

“We should take account of the fact that as our population ages, a greater proportion of

those who have had an MI may present without chest pain. In an older population you

have more co-morbid diseases, such as diabetes, that may mask the pain associated with

heart attack.

“We should also be aware that if there isn’t a spouse or partner present in the household,

and the decision to call an ambulance is made by someone else such as a neighbour or

non-resident relative, there may be greater delay. This most likely is because the person

delays informing someone of their symptoms.

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“In terms of policy, education campaigns should also take account of the fact that older

people, and particularly older women, are less likely to have chest pain and that there

are other symptoms to look for,” Linda says.

[Do you know the symptoms of a heart attack? The Heart Foundation provides valuable

information at www.heartattackfacts.org.au ]

Written by Brian Wills-Johnson

http://www.heartattackfacts.org.au/

223

Appendix Q: Australian Doctor - GP Visits Delay Heart Attack

Treatment

symptom presentation in myocardial infarction, ambulance … · symptom presentation in myocardial...

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