Predicting Central Line-Associated Bloodstream Infection Risk Using Static and Dynamic Random Forest Models Accounting for Competing Events

Comparison of the predictive performance of random forest models using different outcome operationalizations (binary, multinomial, survival, competing risks) to predict the 7-day risk of central line-associated bloodstream infection (CLABSI) in the presence of competing events (discharge, death).