A Predictive Model and Risk Factors for Case Fatality of COVID-19

This study aimed to create an individualized analysis model of the risk of intensive care unit (ICU) admission or death for coronavirus disease 2019 (COVID-19) patients as a tool for the rapid clinical management of hospitalized patients in order to achieve a resilience of medical resources. This is...

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Autores: Álvarez Mon, Melchor, Ortega, Miguel A., Gasulla, Óscar, Fortuny Profitós, Jordi, Mazaira-Font, Ferran, Saurina, Pablo, Monserrat, Jorge, Plana, María N., Troncoso, Daniel, Moreno, José Sanz, Muñoz, Benjamin, Arranz, Alberto, Varona, José F., López Escobar, Alejandro, Asunsolo, Angel
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2021
País:España
Institución:Universidad de Barcelona
Repositorio:Dipòsit Digital de la UB
OAI Identifier:oai:diposit.ub.edu:2445/174450
Acceso en línea:https://hdl.handle.net/2445/174450
Access Level:acceso abierto
Palabra clave:COVID-19
Mortalitat
Mortality
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spelling A Predictive Model and Risk Factors for Case Fatality of COVID-19Álvarez Mon, MelchorOrtega, Miguel A.Gasulla, ÓscarFortuny Profitós, JordiMazaira-Font, FerranSaurina, PabloMonserrat, JorgePlana, María N.Troncoso, DanielMoreno, José SanzMuñoz, BenjaminArranz, AlbertoVarona, José F.López Escobar, AlejandroAsunsolo, AngelCOVID-19MortalitatCOVID-19MortalityThis study aimed to create an individualized analysis model of the risk of intensive care unit (ICU) admission or death for coronavirus disease 2019 (COVID-19) patients as a tool for the rapid clinical management of hospitalized patients in order to achieve a resilience of medical resources. This is an observational, analytical, retrospective cohort study with longitudinal follow-up. Data were collected from the medical records of 3489 patients diagnosed with COVID-19 using RT-qPCR in the period of highest community transmission recorded in Europe to date: February-June 2020. The study was carried out in in two health areas of hospital care in the Madrid region: the central area of the Madrid capital (Hospitales de Madrid del Grupo HM Hospitales (CH-HM), n = 1931) and the metropolitan area of Madrid (Hospital Universitario Príncipe de Asturias (MH-HUPA) n = 1558). By using a regression model, we observed how the different patient variables had unequal importance. Among all the analyzed variables, basal oxygen saturation was found to have the highest relative importance with a value of 20.3%, followed by age (17.7%), lymphocyte/leukocyte ratio (14.4%), CRP value (12.5%), comorbidities (12.5%), and leukocyte count (8.9%). Three levels of risk of ICU/death were established: low-risk level (<5%), medium-risk level (5-20%), and high-risk level (>20%). At the high-risk level, 13% needed ICU admission, 29% died, and 37% had an ICU-death outcome. This predictive model allowed us to individualize the risk for worse outcome for hospitalized patients affected by COVID-19.MDPI2021info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://hdl.handle.net/2445/174450Articles publicats en revistes (Institut d'lnvestigació Biomèdica de Bellvitge (IDIBELL))reponame:Dipòsit Digital de la UBinstname:Universidad de BarcelonaInglésReproducció del document publicat a: https://doi.org/10.3390/jpm11010036Journal of Personalized Medicine, 2021, vol. 11, num. 1https://doi.org/10.3390/jpm11010036cc by (c) Álvarez Mon et al., 2021http://creativecommons.org/licenses/by/3.0/es/info:eu-repo/semantics/openAccessoai:diposit.ub.edu:2445/1744502026-05-27T06:46:51Z
dc.title.none.fl_str_mv A Predictive Model and Risk Factors for Case Fatality of COVID-19
title A Predictive Model and Risk Factors for Case Fatality of COVID-19
spellingShingle A Predictive Model and Risk Factors for Case Fatality of COVID-19
Álvarez Mon, Melchor
COVID-19
Mortalitat
COVID-19
Mortality
title_short A Predictive Model and Risk Factors for Case Fatality of COVID-19
title_full A Predictive Model and Risk Factors for Case Fatality of COVID-19
title_fullStr A Predictive Model and Risk Factors for Case Fatality of COVID-19
title_full_unstemmed A Predictive Model and Risk Factors for Case Fatality of COVID-19
title_sort A Predictive Model and Risk Factors for Case Fatality of COVID-19
dc.creator.none.fl_str_mv Álvarez Mon, Melchor
Ortega, Miguel A.
Gasulla, Óscar
Fortuny Profitós, Jordi
Mazaira-Font, Ferran
Saurina, Pablo
Monserrat, Jorge
Plana, María N.
Troncoso, Daniel
Moreno, José Sanz
Muñoz, Benjamin
Arranz, Alberto
Varona, José F.
López Escobar, Alejandro
Asunsolo, Angel
author Álvarez Mon, Melchor
author_facet Álvarez Mon, Melchor
Ortega, Miguel A.
Gasulla, Óscar
Fortuny Profitós, Jordi
Mazaira-Font, Ferran
Saurina, Pablo
Monserrat, Jorge
Plana, María N.
Troncoso, Daniel
Moreno, José Sanz
Muñoz, Benjamin
Arranz, Alberto
Varona, José F.
López Escobar, Alejandro
Asunsolo, Angel
author_role author
author2 Ortega, Miguel A.
Gasulla, Óscar
Fortuny Profitós, Jordi
Mazaira-Font, Ferran
Saurina, Pablo
Monserrat, Jorge
Plana, María N.
Troncoso, Daniel
Moreno, José Sanz
Muñoz, Benjamin
Arranz, Alberto
Varona, José F.
López Escobar, Alejandro
Asunsolo, Angel
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv COVID-19
Mortalitat
COVID-19
Mortality
topic COVID-19
Mortalitat
COVID-19
Mortality
description This study aimed to create an individualized analysis model of the risk of intensive care unit (ICU) admission or death for coronavirus disease 2019 (COVID-19) patients as a tool for the rapid clinical management of hospitalized patients in order to achieve a resilience of medical resources. This is an observational, analytical, retrospective cohort study with longitudinal follow-up. Data were collected from the medical records of 3489 patients diagnosed with COVID-19 using RT-qPCR in the period of highest community transmission recorded in Europe to date: February-June 2020. The study was carried out in in two health areas of hospital care in the Madrid region: the central area of the Madrid capital (Hospitales de Madrid del Grupo HM Hospitales (CH-HM), n = 1931) and the metropolitan area of Madrid (Hospital Universitario Príncipe de Asturias (MH-HUPA) n = 1558). By using a regression model, we observed how the different patient variables had unequal importance. Among all the analyzed variables, basal oxygen saturation was found to have the highest relative importance with a value of 20.3%, followed by age (17.7%), lymphocyte/leukocyte ratio (14.4%), CRP value (12.5%), comorbidities (12.5%), and leukocyte count (8.9%). Three levels of risk of ICU/death were established: low-risk level (<5%), medium-risk level (5-20%), and high-risk level (>20%). At the high-risk level, 13% needed ICU admission, 29% died, and 37% had an ICU-death outcome. This predictive model allowed us to individualize the risk for worse outcome for hospitalized patients affected by COVID-19.
publishDate 2021
dc.date.none.fl_str_mv 2021
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2445/174450
url https://hdl.handle.net/2445/174450
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Reproducció del document publicat a: https://doi.org/10.3390/jpm11010036
Journal of Personalized Medicine, 2021, vol. 11, num. 1
https://doi.org/10.3390/jpm11010036
dc.rights.none.fl_str_mv cc by (c) Álvarez Mon et al., 2021
http://creativecommons.org/licenses/by/3.0/es/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv cc by (c) Álvarez Mon et al., 2021
http://creativecommons.org/licenses/by/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv Articles publicats en revistes (Institut d'lnvestigació Biomèdica de Bellvitge (IDIBELL))
reponame:Dipòsit Digital de la UB
instname:Universidad de Barcelona
instname_str Universidad de Barcelona
reponame_str Dipòsit Digital de la UB
collection Dipòsit Digital de la UB
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.301603

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