biostudies-literatureGao Hthe National Key Research and Development Program of ChinaBeijing Nova Programthe Key Research & Development Program of GuangxiNational Natural Science Foundation of ChinaYoung Elite Scientists Sponsorship Program by CASTthe Joint Project on Regional High-Incidence Diseases Research of Guangxi Natural Science Foundation41581https://www.ebi.ac.uk/biostudies/studies/S-EPMC12644694biostudies-literatureUnknown15(1)This study aims to develop and validate a machine learning-based mortality risk prediction model for V-A ECMO patients to improve the precision of clinical decision-making. This multicenter retrospective cohort study included 280 patients receiving V-A ECMO from the Second Affiliated Hospital of Guangxi Medical University, Yulin First People's Hospital, and the MIMIC-IV database. The data from the Second Affiliated Hospital of Guangxi Medical University and the MIMIC-IV database were merged and randomly divided in a 7:3 ratio into a training set and an internal validation set, respectively. The dataset from Yulin First People's Hospital was reserved as an external validation cohort. The primary study outcome was defined as in-hospital mortality.Feature selection was conducted using Lasso rScientific reportsDevelopment and validation of a machine learning model for predicting mortality risk in veno-arterial extracorporeal membrane oxygenation patients.PMC12644694GuiKeAB220800882022QNRC00182360372202204840532021YFC27017002023GXNSFDA026023Ling YLi SHuang XMou CLu JChen YGao HZhou KfalseDevelopment and validation of a machine learning model for predicting mortality risk in veno-arterial extracorporeal membrane oxygenation patients.This study aims to develop and validate a machine learning-based mortality risk prediction model for V-A ECMO patients to improve the precision of clinical decision-making. This multicenter retrospective cohort study included 280 patients receiving V-A ECMO from the Second Affiliated Hospital of Guangxi Medical University, Yulin First People's Hospital, and the MIMIC-IV database. The data from the Second Affiliated Hospital of Guangxi Medical University and the MIMIC-IV database were merged and randomly divided in a 7:3 ratio into a training set and an internal validation set, respectively. The dataset from Yulin First People's Hospital was reserved as an external validation cohort. The primary study outcome was defined as in-hospital mortality.Feature selection was conducted using Lasso r2025-01-01T00:00:00Z2025 Nov2026-06-05T18:54:55.85Z2026-05-20T03:14:45.275ZS-EPMC126446944128608910.1038/s41598-025-25423-4