Machine Learning-Based Prediction of Acute Kidney Injury Following Pediatric Cardiac Surgery: Model Development and Validation Study.

ABSTRACT:

Background

Cardiac surgery-associated acute kidney injury (CSA-AKI) is a major complication following pediatric cardiac surgery, which is associated with increased morbidity and mortality. The early prediction of CSA-AKI before and immediately after surgery could significantly improve the implementation of preventive and therapeutic strategies during the perioperative periods. However, there is limited clinical information on how to identify pediatric patients at high risk of CSA-AKI.

Objective

The study aims to develop and validate machine learning models to predict the development of CSA-AKI in the pediatric population.

Methods

This retrospective cohort study enrolled patients aged 1 month to 18 years who underwent cardiac surgery with cardiopulmonary bypass at 3 me

SUBMITTER: Luo XQ 

PROVIDER: S-EPMC9893730 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature