Simple predictive models identify patients with COVID-19 pneumonia and poor prognosis.

ABSTRACT:

Background and aims

Identification of SARS-CoV-2-infected patients at high-risk of poor prognosis is crucial. We aimed to establish predictive models for COVID-19 pneumonia severity in hospitalized patients.

Methods

Retrospective study of 430 patients admitted in Vall d'Hebron Hospital (Barcelona) between 03-12-2020 and 04-28-2020 due to COVID-19 pneumonia. Two models to identify the patients who required high-flow-oxygen-support were generated, one using baseline data and another with also follow-up analytical results. Calibration was performed by a 1000-bootstrap replication model.

Results

249 were male, mean age 57.9 years. Overall, 135 (31.4%) required high-flow-oxygen-support. The baseline predictive model showed a ROC of 0.800 based on: SpO2/FiO2 (adjusted Hazar

SUBMITTER: Riveiro-Barciela M 

PROVIDER: S-EPMC7769554 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature