Early surgery for proximal femoral fractures is associated with lower complication and

mortality rates

Parag Kumar JaiswalArthroplasty Fellow

Acknowledgements

Hoa Khong ABJHIChris Smith ABJHIPam Railton Research assistant

and nurse extraordinaireJim Powell Associate Clinical

Professor

Introduction

• Hip fractures are a significant cause of morbidity and mortality

• Nearly 300,000 hip fractures occur in the US annually

• Lack of consensus within the orthopaedic community on relationship bewteen timing of surgery and mortality outcomes

• Uzoigwe et al 2013 – 2056 patients– Increased mortality after 36 hours

• Shiga et al 2008 (Can J Anaes) Meta-analysis– 16 studies found delay beyond 48 hours increased

mortality rates

• Moja et al 2012 - 35 studies, 191,873 patients– Surgery conducted within 24 to 48 hours was

associated with lower mortality

• Moran et al JBJS 2005 analysis of 2660– showed that there was no effect in mortality with

surgical delay of up to 4 days

• Orosz et al. 2004 - In 1178 patients– Early surgery within 24 hours was not associated

with improved survival

• Khan et al 2009 - Systematic review of 291,143– observed that when adjusting for confounding

variables, they were less likely to report improved survival

Hypothesis

• Delay in surgery by more than 48 hours will have and adverse effect on:– Mortality rate– Medical complication rates– Length of stay

Patients and Methods

• Retrospective cohort study

• All patients that underwent operative treatment for proximal femoral fractures in 15 centres throughout Alberta between April 2009 and 2013

Comprehensive data on:• Demographics• Date & time of

presentation to emergency department

• Date & time taken to OR

• Date of discharge• Medical co-morbidities

Databases

• Discharge abstract database– (DAD)

• National Ambulatory Care Reporting System– NACRS

• Using unique patient identifiers the two databases were merged

Statistical Analysis

• Multiple logistic regression were used for the outcomes of in-hospitality mortality and medical complications

• Cox-regression to calculate survival curves• Multiple linear regression to determine how

length of stay was affected

Co-factors and co-variates

• Age• Gender• Time to surgery– Within 48 hours– After 48 hours

• Dementia• Charlson co-morbidity index– 0– 1– 2 or more

Results

• 14344 patients had procedures performed with recorded time to OR

• Excluded 60 as they were extreme outliers – Time to OR was greater than 30 days from

presentation to emergency department

• Mean age 77.8 (range 18 to 105)• 67.4% were females• 75.5% patients received surgery within 48

hours

Charlson Co-morbidity index

Mortality Rate

Variable Odds ratio

95% Confidence Interval for Odds ratio

Lower Bound

Upper Bound p value

Age 1.06 1.06 1.08 <0.001

Female 0.6 0.48 0.68

<0.001Male . . .

No Dementia . . .0.37

Dementia 0.91 0.75 1.1 Surgery after 48 hours 1.75 1.47 2.08

<0.001Surgery within 48 hours . . . Charlson = 0 . . .

<0.001

Charlson = 1 1.83 1.42 2.36

Charlson = 2 or more 4.65 3.73 5.8

Cox regression – timing of surgery

Surgery within 48 hours

Surgery after 48 hours

Cox Regression – Co-morbidity

Complications

• Medical complications included:– Thromboembolic event– MI– CVA– Pneumonia– Ileus– GI bleed

• 915/14282 (6.4%) had one complication • 122 (0.9%) had more than one

Medical Complications

Variable Odds ratio

95% Confidence Interval for Odds ratio

Lower Bound

Upper Bound p value

<0.001Age 1.02 1.01 1.03

Female 0.72 0.63 0.83 <0.001Male . . .

Surgery after 48 hours 1.3 1.13 1.49 <0.001

Surgery within 48 hours . . . Charlson = 0 . . .

<0.001

Charlson = 1 1.66 1.36 2

Charlson = 2 or more 5.1 4.32 .

Thromboembolic event

Variable Odds ratio

95% Confidence Interval for Odds ratio

p value

Lower Bound

Upper Bound

Age 1.02 1.01 1.03 <0.001

Female 0.82 0.65 1.03

Male . . . 0.084

Surgery after 48 hours 1.6 1.28 2

Surgery within 48 hours . . . <0.001

Charlson = 0 . .

<0.001

Charlson = 1 1.1 0.8 1.49

Charlson = 2 2.74 2.13 3.52

Length of stay (LOS)

• Multiple linear regression model relies on a normal distribution of the dependent variable

• LOS has a positive skew following most surgical procedures

• Therefore data was transformed to log[LOS]

Length of stay

Multiple linear regression – LOG[LOS]

VariableMagnitude

of effect

95% Confidence Interval

p valueLower Bound

Upper Bound

<0.001Age 0.14 0.12 0.17

Female -0.73 -1.4 -0.007 0.048Male . . .

Surgery after 48 hours 1.5 0.72 2.24 <0.001Surgery within 48 hours . . .Dementia 4.43 3.5 5.4 <0.001No Dementia . . .

Charlson = 0 . . .

<0.001

Charlson = 1 2.12 1.24 3

Charlson = 2 or more 6.4 5.5 7.31

Summary

• Delay in surgery by greater than 48 hours results in– Higher mortality rate

– Higher medical complication rate

– Longer post-operative length of stay

Conclusion

• The message is unequivocal and clear

• Delay in surgery is not good!

• Patients should be medically optimised and prioritised to be undergo surgery in the next available trauma list

Thank You.

Questions?