Prospective and External Validation of Machine Learning Models for Short- and Long-Term Mortality in Acutely Admitted Patients Using Blood Tests.

ABSTRACT: Background: Predicting mortality in emergency departments (EDs) using machine learning models presents challenges, particularly in balancing simplicity with performance. This study aims to develop models that are both simple and effective for predicting short- and long-term mortality in ED patients. Our approach uses a minimal set of variables derived from one single blood sample obtained at admission. Methods: Data from three cohorts at two large Danish university hospitals were analyzed, including one retrospective and two prospective cohorts where prognostic models were applied to predict individual mortality risk, spanning the years 2013-2022. Routine biochemistry analyzed in blood samples collected at admission was the primary data source for the prediction models. The o

SUBMITTER: Jawad BN 

PROVIDER: S-EPMC11546962 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature