Parag Kumar Jaiswal Arthroplasty Fellow

1. Early surgery for proximal femoral fractures is associated with lower complication and mortality rates Parag Kumar Jaiswal Arthroplasty Fellow

2. Acknowledgements Hoa Khong ABJHI Chris Smith ABJHI Pam Railton Research assistant and nurse extraordinaire Jim Powell Associate Clinical Professor

3. 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

4. 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

5. 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

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

7. 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

8. Databases • Discharge abstract database • (DAD) • National Ambulatory Care Reporting System • NACRS • Using unique patient identifiers the two databases were merged

9. 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

10. 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

11. 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

12. Charlson Co-morbidity index

13. Mortality Rate

14. Cox regression – timing of surgery Surgery within 48 hours Surgery after 48 hours

15. Cox Regression – Co-morbidity

16. 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

17. Medical Complications

18. Thromboembolic event

19. 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]

20. Length of stay

21. Multiple linear regression – LOG[LOS]

22. Summary • Delay in surgery by greater than 48 hours results in • Higher mortality rate • Higher medical complication rate • Longer post-operative length of stay

23. 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

24. Thank You. Questions?