Simple predictive models identify patients with COVID-19 pneumonia and poor prognosis.
<h4>Background and aims</h4>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.<h4>Methods</h4>Retrospective study of 430 patients admitted...
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doaj-ff1b70cade2549ca8f71e6d9471a99f52021-03-04T12:45:43ZengPublic Library of Science (PLoS)PLoS ONE1932-62032020-01-011512e024462710.1371/journal.pone.0244627Simple predictive models identify patients with COVID-19 pneumonia and poor prognosis.Mar Riveiro-BarcielaMoisés Labrador-HorrilloLaura Camps-RelatsDidac González-SansMeritxell Ventura-CotsMaría Terrones-PeinadorAndrea Nuñez-CondeMónica Martínez-GalloManuel HernándezAndrés AntónAntonio GonzálezRicardo Pujol-BorrellFernando Martínez-Valle<h4>Background and aims</h4>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.<h4>Methods</h4>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.<h4>Results</h4>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%.<h4>Conclusions</h4>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.https://doi.org/10.1371/journal.pone.0244627 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
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 Fernando Martínez-Valle |
spellingShingle |
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 Fernando Martínez-Valle Simple predictive models identify patients with COVID-19 pneumonia and poor prognosis. PLoS ONE |
author_facet |
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 Fernando Martínez-Valle |
author_sort |
Mar Riveiro-Barciela |
title |
Simple predictive models identify patients with COVID-19 pneumonia and poor prognosis. |
title_short |
Simple predictive models identify patients with COVID-19 pneumonia and poor prognosis. |
title_full |
Simple predictive models identify patients with COVID-19 pneumonia and poor prognosis. |
title_fullStr |
Simple predictive models identify patients with COVID-19 pneumonia and poor prognosis. |
title_full_unstemmed |
Simple predictive models identify patients with COVID-19 pneumonia and poor prognosis. |
title_sort |
simple predictive models identify patients with covid-19 pneumonia and poor prognosis. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2020-01-01 |
description |
<h4>Background and aims</h4>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.<h4>Methods</h4>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.<h4>Results</h4>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%.<h4>Conclusions</h4>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. |
url |
https://doi.org/10.1371/journal.pone.0244627 |
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