Development and Validation of a Machine Learning Predictive Model for Cardiac Surgery-Associated Acute Kidney Injury.

ABSTRACT:

Objective

We aimed to develop and validate a predictive machine learning (ML) model for cardiac surgery associated with acute kidney injury (CSA-AKI) based on a multicenter randomized control trial (RCT) and a Medical Information Mart for Intensive Care-IV (MIMIC-IV) dataset.

Methods

This was a subanalysis from a completed RCT approved by the Ethics Committee of Fuwai Hospital in Beijing, China (NCT03782350). Data from Fuwai Hospital were randomly assigned, with 80% for the training dataset and 20% for the testing dataset. The data from three other centers were used for the external validation dataset. Furthermore, the MIMIC-IV dataset was also utilized to validate the performance of the predictive model. The area under the receiver operating characteristic curve (ROC-AUC),

SUBMITTER: Li Q 

PROVIDER: S-EPMC9917969 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature