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

Mar Riveiro-Barciela, Moisés Labrador-Horrillo, Laura Camps-Relats, Didac González-Sans, Meritxell Ventura-Cots, María Terrones-Peinador, Andrea Nuñez-Conde, Mónica Martínez-Gallo, Manuel Hernández, Andrés Antón, Antonio González, Ricardo Pujol-Borrell and Fernando Martínez-Valle

PLOS ONE, 2020, vol. 15, issue 12, 1-14

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 Hazard Ratio-aHR = 8), chest x-ray (aHR = 4), prior immunosuppressive therapy (aHR = 4), obesity (aHR = 2), IL-6 (aHR = 2), platelets (aHR = 0.5). The cut-off of 11 presented a specificity of 94.8%. The second model included changes on the analytical parameters: ferritin (aHR = 7.5 if ≥200ng/mL) and IL-6 (aHR = 18 if ≥64pg/mL) plus chest x-ray (aHR = 2) showing a ROC of 0.877. The cut-off of 12 exhibited a negative predictive value of 92%. Conclusions: SpO2/FiO2 and chest x-ray on admission or changes on inflammatory parameters as IL-6 and ferritin allow us early identification of COVID-19 patients at risk of high-flow-oxygen-support that may benefit from a more intensive disease management.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0244627

DOI: 10.1371/journal.pone.0244627

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