Development and validation of a risk stratification model for predicting the mortality of acute kidney injury in critical care patients.

ABSTRACT:

Background

This study aimed to develop and validate a model for mortality risk stratification of intensive care unit (ICU) patients with acute kidney injury (AKI) using the machine learning technique.

Methods

Eligible data were extracted from the Medical Information Mart for Intensive Care (MIMIC-III) database. Calibration, discrimination, and risk classification for mortality prediction were evaluated using conventional scoring systems and the new algorithm. A 10-fold cross-validation was performed. The predictive models were externally validated using the eICU database and also patients treated at the Second People's Hospital of Shenzhen between January 2015 to October 2018.

Results

For the new model, the areas under the receiver operating characteristic curves (AUR

SUBMITTER: Huang H 

PROVIDER: S-EPMC7944298 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature