{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Hayashi S"],"funding":["JSPS KAKENHI","Otsuka Pharmaceutical Co. Ltd.","CSL Behring","Daiichi Sankyo Company Limited"],"pagination":["e70091"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12459218"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["39(18)"],"pubmed_abstract":["Background
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.Methods
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: Predic"],"journal":["Journal of clinical laboratory analysis"],"pubmed_title":["Routine 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."],"pmcid":["PMC12459218"],"funding_grant_id":["JP22K09170","AS2020A000066448","AS2022A000064989","A21-0363"],"pubmed_authors":["Watanabe T","Nakamura K","Sugawara H","Hayashi S","Saito K","Omoto K","Sanayama H","Fukuchi T","Hayashi R"],"additional_accession":[]},"is_claimable":false,"name":"Routine 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.","description":"Background
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.Methods
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: Predic","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Sep","modification":"2026-06-03T19:35:35.959Z","creation":"2026-04-30T03:12:18.477Z"},"accession":"S-EPMC12459218","cross_references":{"pubmed":["40899738"],"doi":["10.1002/jcla.70091"]}}