Predicting prolonged length of stay following revision total knee arthroplasty: A national database analysis using machine learning models.

ML models developed in this study demonstrated good performance in predicting extended LOS in patients undergoing revision TKA. Our findings highlight the importance of utilizing nationally representative patient data for model development. Prolonged operative time, preoperative sepsis, BMI, and elevated preoperative serum creatinine and BUN were noted to be significant predictors of prolonged LOS. Knowledge of these associations may aid with patient-specific preoperative planning, discharge planning, patient counseling, and cost containment with revision TKA.