Prediction of successful weaning from renal replacement therapy in critically ill patients based on machine learning.

ABSTRACT:

Background

Predicting the successful weaning of acute kidney injury (AKI) patients from renal replacement therapy (RRT) has emerged as a research focus, and we successfully built predictive models for RRT withdrawal in patients with severe AKI by machine learning.

Methods

This retrospective single-center study utilized data from our general intensive care unit (ICU) Database, focusing on patients diagnosed with severe AKI who underwent RRT. We evaluated RRT weaning success based on patients being free of RRT in the subsequent week and their overall survival. Multiple logistic regression (MLR) and machine learning algorithms were adopted to construct the prediction models.

Results

A total of 976 patients were included, with 349 patients successfully weaned off RRT. Lon

SUBMITTER: Liang Q 

PROVIDER: S-EPMC10903749 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature