Predictive model for surgical site infection risk after surgery for high-energy lower-extremity fractures: Development of the Risk of Infection in Orthopedic Trauma Surgery Score

BACKGROUND: Current infection risk scores are not designed to predict the likelihood of surgical site infection after orthopedic fracture surgery. We hypothesized that the National Nosocomial Infections Surveillance (NNIS) System and the Study on the Efficacy of Nosocomial Infection Control (SENIC) scores are not predictive of infection after orthopedic fracture surgery and that risk factors for infection can be identified and a new score created (Emerg Infect Dis. 2003; 9: 196-203). METHODS: We conducted a secondary analysis of data from a trial involving internal fixation of 235 tibial plateau, pilon, and calcaneus fractures treated between 2007 and 2010 at a Level I trauma center. The predictive value of the NNIS System and SENIC scores was evaluated based on areas under the receiver operating characteristic (ROC) curve. Bivariate and multiple logistic regression analyses were used to build an improved prediction model, creating the Risk of Infection in Orthopedic Trauma Surgery (RIOTS) score. The predictive value of the RIOTS score was evaluated via the ROC curve. RESULTS: NNIS System and SENIC scores were not predictive of surgical site infection after orthopedic fracture surgery. In our final regression model, the relative odds of infection among patients with AO [Arbeitsgemeinschaft fur Osteosynthesefragen] type C3 or Sanders type 4 fractures compared with fractures of lower classification was 5.40. American Society of Anesthesiologists class 3 or higher and body mass index less than 30 were also predictive of infection, with odds ratios of 2.87 and 3.49, respectively. The area under the ROC curve for the RIOTS score was 0.75, significantly higher than the areas for the NNIS System and SENIC scores. CONCLUSION: The NNIS System and SENIC scores were not useful in predicting the risk of infection after fixation of fractures. We propose a new score that incorporates fracture classification, American Society of Anesthesiologists classification, and body mass index as predictors of infection. (Copyright (C) 2013 by Lippincott Williams & Wilkins)