TY - JOUR
T1 - Simple predictive models identify patients with COVID-19 pneumonia and poor prognosis
AU - Riveiro-Barciela, Mar
AU - Labrador-Horrillo, Moises
AU - Camps-Relats, Laura
AU - Gonzalez-Sans, Didac
AU - Ventura-Cots, Meritxell
AU - Terrones-Peinador, Maria
AU - Nuñez-Conde, Andrea
AU - Martinez-Gallo, Monica
AU - Hernandez, Manuel
AU - Anton, Andres
AU - Gonzalez, Antonio
AU - Pujol-Borrell, Ricardo
AU - Martinez-Valle, Fernando
N1 - Publisher Copyright:
© 2020 Riveiro-Barciela et al.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2020/12/28
Y1 - 2020/12/28
N2 - 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-oxygensupport that may benefit from a more intensive disease management.
AB - 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-oxygensupport that may benefit from a more intensive disease management.
UR - http://www.scopus.com/inward/record.url?scp=85099006111&partnerID=8YFLogxK
U2 - 10.1371/journal.pone.0244627
DO - 10.1371/journal.pone.0244627
M3 - Article
C2 - 33370397
AN - SCOPUS:85099006111
SN - 1932-6203
VL - 15
JO - PloS one
JF - PloS one
IS - 12 December
M1 - e0244627
ER -
