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Title: A Predictive Model and Risk Factors for Case Fatality of COVID-19
Author: 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
Keywords: COVID-19
Issue Date: 8-Jan-2021
Publisher: MDPI
Abstract: 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.
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It is part of: Journal of Personalized Medicine, 2021, vol. 11, num. 1
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Appears in Collections:Articles publicats en revistes (Institut d'lnvestigació Biomèdica de Bellvitge (IDIBELL))

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