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Resuscitation (2008) 79, 4145

a v a i l a b l e a t w w w . s c i e n c e d i r e c t . c o m

j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / r e s u s c i t a t i o n

CLINICAL PAPER

Do risk factors for chronic coronary heart disease

help diagnose acute myocardial infarction in the

Emergency Department?

Richard Body , Garry McDowell, Simon Carley, Kevin Mackway-Jones

Emergency Medicine Research Group, Research Office, Emergency Department, Manchester Royal Infirmary, Oxford Road,

Manchester M13 9WL, United Kingdom

Received 29 November 2007; received in revised form 15 April 2008; accepted 8 June 2008

KEYWORDS

Myocardial infarction;Acute coronarysyndromes;Diagnosis;EmergencyDepartment

Summary

Background: Hypertension, hyperlipidaemia, diabetes mellitus, tobacco smoking and a family

history of premature coronary artery disease are known to be risk factors for the development

of coronary artery disease. We sought to determine whether these traditional risk factors aid

the diagnosis of acute myocardial infarction (AMI) in the Emergency Department (ED).

Methods: We performed a prospective diagnostic cohort study within the ED at Manchester

Royal Infirmary, a university-affiliated teaching hospital with an annual ED census of approxi-mately 145,000 patients. We recruited 804 patients who had presented to the ED with suspected

cardiac chest pain. All patients had the presence or absence of traditional cardiac risk fac-

tors documented at the time of presentation using a custom-designed clinical report form. All

patients subsequently underwent 12-h troponin T testing to provide a robust gold standard for

the diagnosis of AMI according to revised World Health Organisation criteria.

Results: The absence of any traditional cardiac risk factors carried a negative likelihood ratio of

0.61 for the diagnosis of AMI. 12.2% of patients with no cardiac risk factors had AMI, compared

with 21.3% of patients with four or five risk factors. The area under the receiver-operating

characteristic curve was 0.49.

Conclusions: Traditional cardiac risk factors are not helpful for the confirmation or exclusion

of AMI within the ED. Future Emergency Medicine research should focus on those clinical and

diagnostic features that are likely to alter during the acute phase of illness.

2008 Elsevier Ireland Ltd. All rights reserved.

A Spanish translated version of the summary of this article appears as Appendix in the online version atdoi:10.1016/j.resuscitation.2008.06.009. Corresponding author. Tel.: +44 7880 712 929; fax: +44 1612 766 925.

E-mail address: rbody@doctors.org.uk (R. Body).

0300-9572/$ see front matter 2008 Elsevier Ireland Ltd. All rights reserved.doi:10.1016/j.resuscitation.2008.06.009

http://dx.doi.org/10.1016/j.resuscitation.2008.06.009mailto:rbody@doctors.org.ukhttp://dx.doi.org/10.1016/j.resuscitation.2008.06.009http://dx.doi.org/10.1016/j.resuscitation.2008.06.009mailto:rbody@doctors.org.ukhttp://dx.doi.org/10.1016/j.resuscitation.2008.06.009

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42 R. Body et al.

Background

The Framingham Heart Study played a vital role in iden-tifying important risk factors for the development ofcoronary heart disease.1 These included hypertension,2,3

hyperlipidaemia,2,4 tobacco smoking,36 diabetesmellitus79 and a family history of premature coronaryartery disease.10 While it is apparent that each of these

risk factors predisposes an individual to the developmentof coronary heart disease, the precise role of these riskfactors in confirming or excluding acute myocardial infarc-tion (AMI) among undifferentiated patients who present tothe Emergency Department (ED) with suspected cardiacchest pain is not clear. Despite this many clinicians feelthat a cardiac history is incomplete unless their presenceor absence has been documented.

We aimed to evaluate the usefulness of the presence orabsence of each of the five traditional cardiac risk factorsin diagnosing or excluding AMI within the ED.

Methods

Study design and setting

This is a substudy of the Early Vascular Markers ofAcute Coronary Syndromes (EVaMACS) study, a single-centreprospective diagnostic cohort study. The study was approvedby the Local Research Ethics Committee. All patients pro-vided written informed consent. We recruited patients atManchester Royal Infirmary, a university-affiliated teachinghospital. The annual ED census is approximately 145,000(comprising approximately 39,000 cases triaged to Majorsincluding the Resuscitation Room and treatment cubicles,43,000 minor injuries, 19,000 ophthalmological emergen-

cies, 24,000 primary care emergencies (patients who areseen by a general (family) practitioner or equivalent),13,000 presentations to the Walk in Centre (patients withminor complaints who are seen by a nurse practitioner) and7000 others).

Selection of participants

Consecutive patients aged over 25 years presenting to theED with chest pain occurring within the past 24 h that thetreating physician suspected to be cardiac in origin wereeligible for inclusion. Patients were excluded if they hadanother medical condition mandating hospital admission,

renal failure needing dialysis, significant chest trauma withsuspicion of myocardial contusion, if they were pregnant,did not speak English, were prisoners or if follow-up wouldbe impossible.

Data collection and processing

Clinical data was recorded by the initial treating physicianat the time of ED presentation using a custom-designedclinical report form. The presence or absence of each car-diac risk factor was recorded using tick boxes. If no boxeswere ticked, the data was considered to be missing. Patientswere considered to have a history of hypertension, hyperlip-

idaemia or diabetes mellitus if they reported that they hadthe condition or that they were taking medication for thecondition. Patients were considered to have a positive fam-ily history if they reported that a first degree relative hadischaemic heart disease at 65 years of age. Patients wereconsidered to be smokers if they reported current tobaccosmoking or tobacco smoking within the past 6 weeks.

All patients had blood taken for troponin T testing 12 h

after onset of their most significant symptoms (Roche Diag-nostics, diagnostic cut-off 0.035 ng/ml). Any patient whohad been discharged without an appropriately timed tro-ponin test was recalled or visited the following day forvenepuncture. All patients were followed up 6 monthsafter presentation. At that time the patients outcome waschecked by examining the National Health Strategic Trac-ing Service (NSTS) database for mortality data and hospitalrecords for clinic letters, investigation reports and details ofhospital admissions and/or ED attendances. Patients werethen interviewed by telephone. If no contact could beestablished with the patient, their general practitioner wascontacted.

Outcome measures

The primary outcome was a diagnosis of acute myocardialinfarction (AMI), defined according to recent American HeartAssociation and European Society of Cardiology guidelines.11

Patients fulfilled the diagnosis of AMI if they had a troponinT elevation 0.035ng/ml (i.e. above the 99th percentileof the upper reference limit with a co-efficient of varia-tion 10%) with at least one of the following: symptoms ofischaemia, ECG evidence of AMI (acute ischaemic changes ordevelopment of pathological Q waves) or imaging evidenceof new loss of viable myocardium. If any patient should havedied before troponin testing, diagnosis was to be assignedaccording to post-mortem findings.12

The principal outcomes at 6-month follow up weredeath, AMI (excluding the index event) and urgent coronaryrevascularisation. Coronary revascularisation included thedetection of a new angiographic coronary stenosis of 50%where revascularisation could not be achieved, as reportedby the patients interventional cardiologist.

Statistical methods

To assess for clinical utility sensitivities, specificities andlikelihood ratios were calculated. Receiver-operating char-acteristic curves were created from the sensitivities andspecificities obtained when using 0, 1, 2, 3, 4 and 5 risk fac-tors as cut-offs. Logistic regression was used to determinewhether each individual risk factor helped to predict thediagnosis of AMI. Odds ratios with 95% confidence intervalsare reported. All statistical analyses were performed usingSPSS version 12.0. Score confidence intervals, calculatedusing accepted methodology, are reported.13

Results

804 patients were recruited to the study between Jan-uary 2006 and February 2007. Eight patients were excluded

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Risk factors and myocardial infarction 43

Table 1 Baseline characteristics according to diagnosis (AMI, met diagnostic criteria for acute myocardial infarction; non-AMI,

did not meet diagnostic criteria for acute myocardial infarction)

Variable Total (N = 796) AMI (N = 148) Non-AMI (N =648)

Age in years (S.D.) 58.9 (14.2) 63.1 (13.2) 57.9 (14.3)

Men (%) 481 (60.4) 104 (70.3) 377 (58.2)

Previous angina (%) 258 (32.4) 35 (23.6) 223 (34.4)

Previous myocardial infarction (%) 194 (24.4) 32 (21.6) 163 (25.2)

Hypertension (%) 399 (50.1) 73 (49.3) 326 (50.3)

Hyperlipidaemia (%) 379 (47.6) 57 (38.5) 322 (49.7)

Diabetes mellitus (%) 141 (17.7) 23 (15.5) 118 (18.2)

Smoking (%) 247 (31.0) 69 (46.6) 178 (27.5)

Family history (%) 379 (47.6) 63 (42.6) 316 (48.8)

Number of risk factors (%)

0 90 (11.3) 11 (7.4) 79 (12.2)

1 212 (26.6) 51 (34.5) 171 (24.8)

2 237 (29.8) 45 (30.4) 192 (29.6)

3 177 (22.2) 24 (16.2) 153 (23.6)

4 or 5 80 (10.1) 17 (11.0) 63 (9.8)

Grade of attending physician (%)

Senior House Officer 71 (8.9) 13 (8.8) 58 (9.0)Registrar 724 (91.0) 135 (91.2) 589 (90.9)

Consultant 1 (0.1) 0 1 (0.2)

because they were found to meet pre-defined exclusioncriteria, meaning that 796 patients were suitable for finalanalysis. 148 (18.6%) patients had AMI. There was no miss-ing data regarding the presence or absence of cardiac riskfactors in any patient. All patients underwent troponin Ttesting 12 h after the onset of their most significant symp-toms. No patients were lost to follow up at 6 months. Table 1shows the baseline characteristics of the included patientsstratified by the presence of AMI.

The incidence of AMI according to the number of risk fac-tors present is demonstrated in Figure 1. There was no trendtowards increasing incidence of AMI with increasing numberof risk factors. The receiver-operating characteristic (ROC)curve demonstrating the value of cardiac risk factors for thediagnosis of AMI is shown in Figure 2. The area under the ROCcurve was 0.49 (95% confidence intervals 0.440.54). Whentested against the null hypothesis that the true area underthe curve is 0.50 this yielded a p-value of 0.59, suggesting

Figure 1 Incidence of AMI according to risk factor burden.

that cardiac risk factor burden is not useful in the diagnosisor exclusion of AMI. The sensitivities, specificities and likeli-hood ratios at each cut-off are demonstrated in Table 2. Theabsence of any cardiac risk factors carried a negative like-lihood ratio of 0.61 for the diagnosis of AMI, a sensitivity of92.6% (95% confidence intervals 87.295.8%) and a negativepredictive value of 87.8% (79.493.0%).

The results of the logistic regression analysis are shown inTable 3. Only smoking carried significant positive predictive

Figure 2 Receiver-operating characteristic curve for risk fac-

tors and acute myocardial infarction.

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44 R. Body et al.

Table 2 Sensitivities, specificities and predictive values for each risk factor burden cut-off for diagnosis of AMI

Number of risk factors Sensitivity, % (95% CI) Specificity, % (95% CI) LR+ LR

1 92.6 (87.295.8) 12.2 (9.914.9) 1.05 0.61

2 58.1 (50.165.8) 37.0 (33.440.8) 0.92 1.12

3 27.7 (21.335.4) 66.7 (62.970.2) 0.83 1.08

4 11.5 (7.317.6) 90.3 (87.892.3) 1.18 0.98

CI: confidence intervals.

value for the diagnosis of AMI. Interestingly, the presence ofhyperlipidaemia was a weak negative predictor of AMI. Asonly one cardiac risk factor was a significant positive pre-dictor on univariate analysis a multivariate analysis was notundertaken.

The incidence of adverse events at 6-month follow up isdemonstrated in Table 4. With increasing number of risk fac-tors there was a weak trend towards increasing incidenceof death or AMI and a stronger trend towards increasingincidence of death, AMI or urgent revascularisation.

Discussion

Our results indicate that traditional cardiac risk factors donot assist in the diagnosis or exclusion of AMI within theED. Of the five traditional risk factors only smoking was asignificant positive predictor of the diagnosis of AMI. Whilethe absence of any cardiac risk factors has slight negativepredictive value, a likelihood ratio of 0.61 means that in ourpopulation with a 18.6% incidence of AMI (a similar incidenceto other similar studies14) the post-test probability of AMI isshifted only to 12.2%. Further, the presence at least fourof the five traditional cardiac risk factors does not help toconfirm a diagnosis of AMI, as the post-test probability is

shifted only as far as 21.3%.While we found that the number of traditional risk fac-

tors did not correlate with the incidence of AMI, we diddemonstrate a correlation with the incidence of death, AMIor urgent coronary revascularisation within 6 months. Thus,it may be that while cardiac risk factors are useful for pre-dicting prognosis with regard to coronary heart disease, theydo little to tell us what is actually happening now.

Interestingly we found that the presence of hyperlipi-daemia carried weak but statistically significant negativepredictive value for the diagnosis of AMI. This may be astatistical anomaly. However, there may be a rational expla-nation for this observation. Patients who have been told thatthey have hyperlipidaemia may have a heightened aware-ness of their cardiac risk and therefore more likely to attend

Table 3 Logistic regression analyses of risk factors for diag-

nosis of AMI (univariate)

Variable Odds ratio (95% CI) p-Value

Hyperlipidaemia 0.63 (0.440.91) 0.014

Hypertension 0.96 (0.671.37) 0.829

Diabetes mellitus 0.83 (0.511.35) 0.443

Smoking 2.31 (1.603.23)

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Risk factors and myocardial infarction 45

Table 4 Risk factors and incidence of adverse events at 6-month follow up

Number of risk factors

0 1 2 3 4 or 5

Death/AMI, number (%) 3(3.3) 10 (4.7) 8 (3.4) 11 (6.2) 5 (6.9)

Death/AMI/UR, number (%) 14(15.6) 44 (20.8) 54 (22.8) 41 (23.2) 27 (33.8)

Abbreviations: AMI, acute myocardial infarction; UR, urgent coronary.

ence of at least three risk factors was associated with arelative risk of 2.13 for death, AMI or coronary revascular-isation within 30 days.18 These findings are also consistentwith our results. While cardiac risk factors are not helpfulin the diagnosis of AMI they may help to identify popula-tions who are at higher risk of events in the near future. It isalso possible that the presence of risk factors increases theprobability that patients will undergo diagnostic coronaryangiography and thus a revascularisation procedure.

There is now a growing amount of evidence to supportthe theory that traditional cardiac risk factors are unhelpful

in the ED diagnosis or exclusion of AMI. Risk factor burdendoes not alter the post-test probability of AMI to an extentthat approaches clinical significance. These results shouldbe considered by practitioners, policy makers and guidelinedevelopers to ensure that the presence or absence of cardiacrisk factors does not influence the decision to investigatepatients with possible cardiac chest pain.

Conclusions

Risk factors for chronic coronary heart disease are not clin-ically helpful in the diagnosis or exclusion of AMI in the EDsetting. Future Emergency Medicine research should focusupon factors that are likely to alter during the acute phase

of illness.

Conflict of interest

The authors confirm that they have no conflicts of interestto declare with regard to this study.

Acknowledgements

The authors would like to acknowledge the contribution ofDr. Jamie Ferguson, who assisted with patient recruitmentand follow up and research administration. We would alsolike to acknowledge the assistance given by all of the nursingand medical staff in the Emergency Department at Manch-ester Royal Infirmary.

Study sponsors: The study was sponsored by CentralManchester & Manchester Childrens NHS Trust, who playedno role in data analysis or the decision to submit themanuscript for publication.

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