Postoperative serum albumin drop predicts complications in primary total knee arthroplasty: a retrospective cohort study using XGBoost algorithm.

ABSTRACT:

Background

Perioperative complications that occur after TKA are still challenging to manage. While preoperative hypoalbuminemia has been proved to be a risk-factor indicator, the role of ΔAlb is yet to be determined.

Methods

In this retrospective study with a cohort analysis, an XGBoost machine learning model was trained with data collected from 758 TKA patients (2018-2022), to identify predictors that aid in the prediction of joint infections after TKA. The predictors to be entered into the model include 28 variables such as ΔAlb (preoperative values - postoperative values)/preoperative values \* 100%, peak C-reactive protein (CRP) level on postoperative day 2, and erythrocyte sedimentation rate (ESR) dynamics. Validation criteria include AUC-ROC, integrated calibration ind

SUBMITTER: Huang L 

PROVIDER: S-EPMC12801642 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature