Construction and evaluation of prediction model for renal function recovery in acute kidney injury patients undergoing continuous renal replacement therapy based on machine learning algorithms.

ABSTRACT: Background: The primary objective of this study is to employ machine learning (ML) algorithms to develop predictive models for renal function recovery in critically ill patients undergoing continuous renal replacement therapy (CRRT) due to acute kidney injury (AKI).Methods: Data were retrospectively collected from patients with AKI who underwent CRRT during their first Intensive Care Unit (ICU) admission from the Medical Information Mart for Intensive Care-IV database and at Huzhou Central Hospital. The evaluation of model performance was conducted utilizing metrics including the area under the receiver operating characteristic curve (AUROC), calibration curves and decision curve analysis (DCA).Results: A total of 1078 AKI patients undergoing CRRT were included, with a

SUBMITTER: Zhong L 

PROVIDER: S-EPMC12466188 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature