biostudies-literatureHayashi SJSPS KAKENHIOtsuka Pharmaceutical Co. Ltd.CSL BehringDaiichi Sankyo Company Limitede70091https://www.ebi.ac.uk/biostudies/studies/S-EPMC12459218biostudies-literatureUnknown39(18)<h4>Background</h4>Despite the high prognostic value of D-dimer in various clinical conditions, limited research has addressed short-term fatality prediction across disease categories. This study aimed to develop and compare models predicting 72-h fatality in patients with D-dimer levels ≥ 2 μg/mL, using laboratory variables. This timeframe was chosen based on its clinical relevance for early triage and intervention across multiple acute conditions.<h4>Methods</h4>We retrospectively analyzed data from 5158 patients (241 deaths within 72 h). The primary outcome was 72-h fatality; predictors included age, sex, and 40 routine hematologic, biochemical, and coagulation tests. Traditional multivariate logistic regression analysis (MLRA) was compared with four machine learning (ML) models: PredicJournal of clinical laboratory analysisRoutine Laboratory Tests Predict 72-h Fatality in Patients With D-Dimer Levels ≥ 2 μg/mL: A Retrospective Cohort Study Comparing Statistical and Machine Learning Models.PMC12459218JP22K09170AS2020A000066448AS2022A000064989A21-0363Watanabe TNakamura KSugawara HHayashi SSaito KOmoto KSanayama HFukuchi THayashi RfalseRoutine Laboratory Tests Predict 72-h Fatality in Patients With D-Dimer Levels ≥ 2 μg/mL: A Retrospective Cohort Study Comparing Statistical and Machine Learning Models.<h4>Background</h4>Despite the high prognostic value of D-dimer in various clinical conditions, limited research has addressed short-term fatality prediction across disease categories. This study aimed to develop and compare models predicting 72-h fatality in patients with D-dimer levels ≥ 2 μg/mL, using laboratory variables. This timeframe was chosen based on its clinical relevance for early triage and intervention across multiple acute conditions.<h4>Methods</h4>We retrospectively analyzed data from 5158 patients (241 deaths within 72 h). The primary outcome was 72-h fatality; predictors included age, sex, and 40 routine hematologic, biochemical, and coagulation tests. Traditional multivariate logistic regression analysis (MLRA) was compared with four machine learning (ML) models: Predic2025-01-01T00:00:00Z2025 Sep2026-06-03T19:35:35.959Z2026-04-30T03:12:18.477ZS-EPMC124592184089973810.1002/jcla.70091