MIASurviveMTP: Machine learning for immediate assessment and survival prediction after massive transfusion protocol.

ABSTRACT: Early triage of trauma patients requiring massive transfusion (MT) may help to marshal appropriate resources and improve treatment and outcome. Artificial intelligence (AI) and machine learning (ML) offer theoretical advantages compared to conventional prediction algorithms but have not been thoroughly evaluated in this population. We hypothesized that AI/ML techniques incorporating all available data in a patient's medical record could achieve similar, if not higher, performance in the prediction of mortality in MT patients as compared to existing models. Patients from the American College of Surgeons Trauma Quality Improvement Project database (TQIP) were retrospectively reviewed. Those receiving ≥ 5 units of red blood cells and/or whole blood within the first four hours of arrival were

SUBMITTER: Cobler-Lichter MD 

PROVIDER: S-EPMC12551842 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature