Repeated Internal Validation and Interpretation of Models Predicting Surgery Documented at a Study Institution Within 90 Days After Acute Knee Trauma: A Secondary Analysis

Background and Objectives: A previous study using this cohort evaluated threshold-dependent performance and clinical decision utility for predicting surgery after acute knee trauma. This secondary analysis assessed the stability of discrimination, probabilistic accuracy, calibration, model ranking, and predictor importance under repeated internal validation. Materials and Methods: We analyzed 905 adults with acute knee trauma, including 163 (18.0%) who had a qualifying surgical procedure documented at the study institution within 90 days of the index emergency department visit. Logistic regression, random forest, and gradient-boosted trees were evaluated using 50 repetitions of stratified five-fold cross-validation with identical folds across models. Each patient’s 50 out-of-fold predictions were averaged. Confidence intervals and paired model differences were estimated using 2000 patient-level stratified bootstrap resamples. Random-forest predictor importance was evaluated by validation-fold permutation.