Lucas Anissian,MD,PhD,FACS James T. Nichols,MD First Coast Orthopaedics, Orange Park, FL

1. Retrospective Evaluation of Patients with Pelvic Fractures: Analysis of Mortality, ISS, and Hemodynamic Parameters Lucas Anissian,MD,PhD,FACS James T. Nichols,MD First Coast Orthopaedics, Orange Park, FL

2. Impetus For Investigation and Objectives • LSUHSC-S population has 100% mortality with ISS > 54 and 86% mortality with ISS > 43 • Statistical validation and investigation of observed trend • Evaluate probability of death given ISS • Determine other independent predictors of mortality in our population

3. Introduction • Approximately 50% of patients who die following pelvic fracture have associated hemorrhage • Study goal: Examine the LSUHSC-S experience with the pelvic fracture cohort • Effect of ISS, blood transfusion and hemodynamic parameters on mortality

4. Introduction: ISS • Anatomical scoring system • Values from 1-75 • Based on the AIS • Sum of squares for 3 most significant injured regions • Different injury patterns can result in same score • Scores not weighted based on region injured • Extent of injuries not known until full investigation completed: limits triage capabilities

5. ISS is correlated with mortality (1) Death frequently secondary to non pelvic injury Early significant transfusion volumes often required (3) Introduction (Cont)

6. Introduction (Cont) • The majority of transfusion in the trauma patient is given in the first 24 hours (6) • Efficacy of massive transfusions has been questioned (4,5) • Continued transfusion supported in the setting of massive requirement and associated injuries (6)

7. Methods • IRB approval obtained • LSUHSC-S trauma registry 2005-2010 • Polytrauma Patients admitted with pelvic fractures

8. Patients divided into two groups based on mortality Each group analyzed with respect to Age and race Hemodynamic parameters Transfusion requirements in first 24h ISS GCS Methods (cont)

9. Results: Descriptive

10. Univariate Analyses * *Factors Significantly Associated with Mortality

11. Distribution of ISS

12. ISS

13. Multiple Logistic Regression Analysis • Used to determine independent and significant risk factors for mortality • A patient would be predicted to die if probability of death given values for the independent risk factors was greater than observed mortality rate • ISS threshold for predicting death was determined by equating observed mortality with estimated probability of death given ISS

14. Multivariate Analysis • Adjusting for the effects of other significant factors, odds for death: • Increases by 12% for each unit decrease in GCS • Increases by 15% for each unit increase in ISS • Increases by 5% for each year increase in age

15. Odds for death increases by 15% for each unit increase in ISS

16. Probability of Death • Patient will be predicted to die if probability of death using multiple logistic regression model is greater than 0.057 (observed mortality) • Estimated probability of death is 5.6% at ISS of 26

17. Observed and Predicted Mortality Using Independent Variables * -Among all patients, total error rate = (9+111)/957 = 12.5% -Among the 55 patients who died, error rate = 9/55 = 16.4%(wrongly predicted to live) -Among the 902 who lived, error rate = 111/902 = 12.3%(wrongly predicted to die) *ISS, GCS, Age

18. Observed and Predicted Mortality Using ISS And Total Units Transfused -Among all 959 patients, total prediction error rate = 11.3% -Among the 55 patients who died, 8 were predicterd to live; error rate 14.6% -Among the 904 patients who lived, 100 were predicted to die; error rate 11.1%

20. Conclusion • Two sets of independent risk factors for death identified: • GCS, ISS, age at admission • ISS and total units blood transfused in first 24 hours • Using the second group (ISS and TBU) to predict death results in lowest prediction errors (11.1%)

21. Limitations • Population included acetabular fractures and isolated sacral fractures • Significant potential for recording bias given retrospective analysis • Any error in AIS scoring increases ISS error significantly • Full description of patient injuries not known until full investigation completed; limits triage capabilities

22. References • Balogh J, Varga E, Tomka J, Suveges G, Toth L, Simonka J. The New Injury Severity Score is a Better Predictor of Extended Hospitalization and Intensive Care Unit Admission Than the Injury Severity Score in Patients With Multiple Orthopaedic Injuries. Journal of Orthopaedic Trauma. 17: 508-512, August 2003. • Demetriades D, Karaiskakis M, Toutouzas K, Alo K, Velmahos G, Chan L. Pelvic Fractures: Epidemiology and Predictors of Associated Abdominal Injuries and Outcomes. Journal of the American College of Surgeons. 195: 1-10, July 2002. • Tachibana T, Yokoi H, Kirita M, Marukawa S, Yoshiya S. Instability of the Pelvic Ring and Injury Severity can be Predictors of Death in Patients with Pelvic Ring Fractures: A Retrospective Study. Journal of Orthopaedic Traumatology. 10(2): 79-82, April 2009. • Velmahos G, Chan L, Chan M, Tatevossian R, Cornwell E, Asensio J, Berne T, Demetriades D. Is There a Limit to Massive Blood Transfusion After Severe Trauma? Archives of Surgery. 133: 947-952, September 1998. • Vaslef S, Dnudsen N, Neligan P, Sebastian M. Massive Transfusion Exceeding 50 Units of Blood Products in Trauma Patients. Journal of Trauma-Injury Infection & Critical Care. 53(2): 291-296, August 2002. • Como J, Dutton R, Scalea T, Edelman B, Hess J. Blood Transfusion Rates in the Care of Acute Trauma. Transfusion. 44:809-813, June 2004.

23. Thank You