Methods: Patients who underwent ORIF of long bone between January 1, 2012 and December 31, 2013 were included in the study (n = 1163). Patient risk factors, injury risk factors, perioperative risk factors and postoperative risk factors were included in the development of this model. We performed univariate analysis to assess each variable’s association with infection. Risk factors meeting a p-value cut-off <0.30 were considered for inclusion in a multivariate logistic regression model. Potential confounding and multicollinearity were investigated. Once the model was developed, it was applied to a novel dataset of ORIF procedures to determine the expected number of infections. This was compared to the expected number of infections calculated using the NHSN risk adjusted model.
Results: The final multivariate model included age (odds ratio: 1.2, p-value: 0.16, 95% confidence interval: 0.9 – 1.5), ASA (0.6, 0.03, 1.1 – 6.3), length of stay post-operatively (1.0, 0.31, 1.0 – 1.02), and history of MRSA, which was the most important predictor of infection (10.7, <0.001, 1.0 – 27.9). The c-index was 0.795 compared to the c-index of the NHSN model as 0.64, indicating that our model was superior in estimating infection risk. When the developed model was used to predict the number of expected infections on the 2014 data, 17.2 SSI were expected compared to 5.6 calculated by the NHSN model.
Conclusion: The model that was developed uses 4 easily identifiable risk factors that result in a more accurate prediction of infection than the currently used model. Future direction would include applying this model to other facilities to test the fit and accuracy.
C. Mauffrey, None
C. Price, None
H. Young, None