A vital sign-based prediction algorithm for differentiating COVID-19 versus seasonal influenza in hospitalized patients.

ABSTRACT: Patients with influenza and SARS-CoV2/Coronavirus disease 2019 (COVID-19) infections have a different clinical course and outcomes. We developed and validated a supervised machine learning pipeline to distinguish the two viral infections using the available vital signs and demographic dataset from the first hospital/emergency room encounters of 3883 patients who had confirmed diagnoses of influenza A/B, COVID-19 or negative laboratory test results. The models were able to achieve an area under the receiver operating characteristic curve (ROC AUC) of at least 97% using our multiclass classifier. The predictive models were externally validated on 15,697 encounters in 3125 patients available on TrinetX database that contains patient-level data from different healthcare organizations. The infl

SUBMITTER: Yanamala N 

PROVIDER: S-EPMC8178379 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature