Predicting clinical outcomes of SARS-CoV-2 infection during the Omicron wave using machine learning
Cogill S, Nallamshetty S, Fullenkamp N, Heberer K, Lynch J, Lee K, Aslan M, Shih M, Lee J. Predicting clinical outcomes of SARS-CoV-2 infection during the Omicron wave using machine learning. PLOS ONE 2024, 19: e0290221. PMID: 38662748, PMCID: PMC11045098, DOI: 10.1371/journal.pone.0290221.Peer-Reviewed Original ResearchConceptsHigh-risk groupSARS-CoV-2 infectionAnticoagulant useAdverse outcomesPredictor of adverse outcomesHigher risk of adverse outcomesLower body mass indexRisk of adverse outcomesVaccination of high-risk groupsOral anticoagulant useOutcome of SARS-CoV-2 infectionRetrospective longitudinal observational studySARS-CoV-2U.S. Veterans Health AdministrationClinical outcomes of SARS-CoV-2 infectionIdentification of patientsBody mass indexVeterans Health AdministrationPredictors of hospitalizationEscalation of careLongitudinal observational studyClinical outcomesOmicron SARS-CoV-2 variantSARS-CoV-2 variantsUnvaccinated patients