Predicting deep infection in pilon and tibial plateau fractures: a secondary analysis of the VANCO and OXYGEN trials.

Abstract

Objectives: To develop and validate a prediction model for a deep surgical site infection (SSI) after fixation of a tibial plateau or pilon fracture.

Design: Pooled data from 2 randomized trials (VANCO and OXYGEN).

Setting: Fifty-two US trauma centers.

Patients: In total, 1847 adult patients with operatively treated tibial plateau or pilon fractures who met criteria for a high risk of infection.

Intervention: We considered 13 baseline patient characteristics and developed and externally validated prediction models using 3 approaches (logistic regression, stepwise elimination, and machine learning).

Main outcomes and measures: The primary prediction model outcome was a deep SSI requiring operative debridement within 182 days of definitive fixation. Our primary prognostic performance metric for evaluating the models was area under the receiver operating characteristic curve (AUC) with clinical utility set at 0.7.

Results: Deep SSI occurred in 75 VANCO patients (8%) and in 56 OXYGEN patients (6%). The machine learning model for VANCO (AUC = 0.65) and stepwise elimination model for OXYGEN (AUC = 0.62) had the highest internal validation AUCs. However, none of the external validation AUCs exceeded 0.64 (range, 0.58 to 0.64).

Conclusions: The predictive models did not reach the prespecified clinical utility threshold. Our models' inability to distinguish high-risk from low-risk patients is likely due to strict eligibility criteria and, therefore, homogeneous patient populations.