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Role of a Chest X-ray Severity Score in a Multivariable Predictive Model for Mortality in Patients with COVID-19: A Single-Center, Retrospective Study
Predicting the mortality risk of patients with Coronavirus Disease 2019 (COVID-19) can be valuable in allocating limited medical resources in the setting of outbreaks. This study assessed the role of a chest X-ray (CXR) scoring system in a multivariable model in predicting the mortality of COVID-19...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9025720/ https://www.ncbi.nlm.nih.gov/pubmed/35456249 http://dx.doi.org/10.3390/jcm11082157 |
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author | Baikpour, Masoud Carlos, Alex Morasse, Ryan Gissel, Hannah Perez-Gutierrez, Victor Nino, Jessica Amaya-Suarez, Jose Ali, Fatimatu Toledano, Talya Arampulikan, Joseph Gold, Menachem Venugopal, Usha Pillai, Anjana Omonuwa, Kennedy Menon, Vidya |
author_facet | Baikpour, Masoud Carlos, Alex Morasse, Ryan Gissel, Hannah Perez-Gutierrez, Victor Nino, Jessica Amaya-Suarez, Jose Ali, Fatimatu Toledano, Talya Arampulikan, Joseph Gold, Menachem Venugopal, Usha Pillai, Anjana Omonuwa, Kennedy Menon, Vidya |
author_sort | Baikpour, Masoud |
collection | PubMed |
description | Predicting the mortality risk of patients with Coronavirus Disease 2019 (COVID-19) can be valuable in allocating limited medical resources in the setting of outbreaks. This study assessed the role of a chest X-ray (CXR) scoring system in a multivariable model in predicting the mortality of COVID-19 patients by performing a single-center, retrospective, observational study including consecutive patients admitted with a confirmed diagnosis of COVID-19 and an initial CXR. The CXR severity score was calculated by three radiologists with 12 to 15 years of experience in thoracic imaging, based on the extent of lung involvement and density of lung opacities. Logistic regression analysis was used to identify independent predictive factors for mortality to create a predictive model. A validation dataset was used to calculate its predictive value as the AUROC. A total of 628 patients (58.1% male) were included in this study. Age (p < 0.001), sepsis (p < 0.001), S/F ratio (p < 0.001), need for mechanical ventilation (p < 0.001), and the CXR severity score (p = 0.005) were found to be independent predictive factors for mortality. We used these variables to develop a predictive model with an AUROC of 0.926 (0.891, 0.962), which was significantly higher than that of the WHO COVID severity classification, 0.853 (0.798, 0.909) (one-tailed p-value = 0.028), showing that our model can accurately predict mortality of hospitalized COVID-19 patients. |
format | Online Article Text |
id | pubmed-9025720 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-90257202022-04-23 Role of a Chest X-ray Severity Score in a Multivariable Predictive Model for Mortality in Patients with COVID-19: A Single-Center, Retrospective Study Baikpour, Masoud Carlos, Alex Morasse, Ryan Gissel, Hannah Perez-Gutierrez, Victor Nino, Jessica Amaya-Suarez, Jose Ali, Fatimatu Toledano, Talya Arampulikan, Joseph Gold, Menachem Venugopal, Usha Pillai, Anjana Omonuwa, Kennedy Menon, Vidya J Clin Med Article Predicting the mortality risk of patients with Coronavirus Disease 2019 (COVID-19) can be valuable in allocating limited medical resources in the setting of outbreaks. This study assessed the role of a chest X-ray (CXR) scoring system in a multivariable model in predicting the mortality of COVID-19 patients by performing a single-center, retrospective, observational study including consecutive patients admitted with a confirmed diagnosis of COVID-19 and an initial CXR. The CXR severity score was calculated by three radiologists with 12 to 15 years of experience in thoracic imaging, based on the extent of lung involvement and density of lung opacities. Logistic regression analysis was used to identify independent predictive factors for mortality to create a predictive model. A validation dataset was used to calculate its predictive value as the AUROC. A total of 628 patients (58.1% male) were included in this study. Age (p < 0.001), sepsis (p < 0.001), S/F ratio (p < 0.001), need for mechanical ventilation (p < 0.001), and the CXR severity score (p = 0.005) were found to be independent predictive factors for mortality. We used these variables to develop a predictive model with an AUROC of 0.926 (0.891, 0.962), which was significantly higher than that of the WHO COVID severity classification, 0.853 (0.798, 0.909) (one-tailed p-value = 0.028), showing that our model can accurately predict mortality of hospitalized COVID-19 patients. MDPI 2022-04-12 /pmc/articles/PMC9025720/ /pubmed/35456249 http://dx.doi.org/10.3390/jcm11082157 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Baikpour, Masoud Carlos, Alex Morasse, Ryan Gissel, Hannah Perez-Gutierrez, Victor Nino, Jessica Amaya-Suarez, Jose Ali, Fatimatu Toledano, Talya Arampulikan, Joseph Gold, Menachem Venugopal, Usha Pillai, Anjana Omonuwa, Kennedy Menon, Vidya Role of a Chest X-ray Severity Score in a Multivariable Predictive Model for Mortality in Patients with COVID-19: A Single-Center, Retrospective Study |
title | Role of a Chest X-ray Severity Score in a Multivariable Predictive Model for Mortality in Patients with COVID-19: A Single-Center, Retrospective Study |
title_full | Role of a Chest X-ray Severity Score in a Multivariable Predictive Model for Mortality in Patients with COVID-19: A Single-Center, Retrospective Study |
title_fullStr | Role of a Chest X-ray Severity Score in a Multivariable Predictive Model for Mortality in Patients with COVID-19: A Single-Center, Retrospective Study |
title_full_unstemmed | Role of a Chest X-ray Severity Score in a Multivariable Predictive Model for Mortality in Patients with COVID-19: A Single-Center, Retrospective Study |
title_short | Role of a Chest X-ray Severity Score in a Multivariable Predictive Model for Mortality in Patients with COVID-19: A Single-Center, Retrospective Study |
title_sort | role of a chest x-ray severity score in a multivariable predictive model for mortality in patients with covid-19: a single-center, retrospective study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9025720/ https://www.ncbi.nlm.nih.gov/pubmed/35456249 http://dx.doi.org/10.3390/jcm11082157 |
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