Development and Validation of a Machine Learning Model to Estimate Bacterial Sepsis Among Immunocompromised Recipients of Stem Cell Transplant
Lind M, Mooney S, Carone M, Althouse B, Liu C, Evans L, Patel K, Vo P, Pergam S, Phipps A. Development and Validation of a Machine Learning Model to Estimate Bacterial Sepsis Among Immunocompromised Recipients of Stem Cell Transplant. JAMA Network Open 2021, 4: e214514. PMID: 33871619, PMCID: PMC8056279, DOI: 10.1001/jamanetworkopen.2021.4514.Peer-Reviewed Original ResearchConceptsRecipients of allo-HCTSystemic inflammatory response syndromeArea under the curveAllo-HCTHighest area under the curveNational Early Warning ScoreCell transplantationRecipients of allogeneic hematopoietic cell transplantationRecipients of stem cell transplantationTime of culture collectionAllogeneic hematopoietic cell transplantationSequential Organ Failure AssessmentStem cell transplantationHematopoietic cell transplantationInflammatory response syndromePresentation of sepsisOrgan Failure AssessmentFred Hutchinson Cancer Research CenterShort-term mortalityHigh-risk populationCancer Research CenterBloodstream infectionsImmunocompromised recipientsAtypical presentationPrognostic value