Multicenter validation of a machine learning model to predict intensive care unit readmission within 48 hours after discharge.

ABSTRACT:

Background

Intensive care unit (ICU) readmission is a crucial indicator of patient safety. However, discharge decisions often rely on subjective assessment due to a lack of standardized guidelines. We aimed to develop a machine-learning model to predict ICU readmission within 48 h and compare its performance to traditional scoring systems.

Methods

We developed an ensemble model, iREAD, that generates a probability score at ICU discharge, representing the likelihood of the patient being readmitted to the ICU within 48 h, using data from Seoul National University Hospital (SNUH) and validated it using the MIMIC-III and eICU-CRD datasets. From September 2007 to August 2021, a total of 70,842 patients were included from SNUH. The MIMIC-III datasets comprised 43,237 patients admi

SUBMITTER: Lim L 

PROVIDER: S-EPMC11872568 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature