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

Abstract

first_pagesettingsOrder Article Reprints Open AccessFeature PaperArticle A Predictive Model and Risk Factors for Case Fatality of COVID-19 by Melchor Álvarez-Mon 1,2,3,*,Miguel A. Ortega 2,3,4ORCID,Óscar Gasulla 5,Jordi Fortuny-Profitós 6ORCID,Ferran A. Mazaira-Font 7,Pablo Saurina 8,Jorge Monserrat 2,3ORCID,María N. Plana 1,2,3,Daniel Troncoso 2,José Sanz Moreno 1,2,Benjamin Muñoz 1,Alberto Arranz 1,Jose F. Varona 9,10ORCID,Alejandro Lopez-Escobar 10,11ORCID andAngel Asúnsolo-del Barco 3,12,13,¿ORCID 1 Service of Internal Medicine and Immune System Diseases-Rheumatology, University Hospital Príncipe de Asturias, (CIBEREHD), 28806 Alcalá de Henares, Spain 2 Department of Medicine and Medical Specialities, Faculty of Medicine and Health Sciences, University of Alcalá, 28801 Alcalá de Henares, Spain 3 Ramón y Cajal Institute of Sanitary Research (IRYCIS), 28034 Madrid, Spain 4 Cancer Registry and Pathology Department, Hospital Universitario Principe de Asturias, 28806 Alcalá de Henares, Spain 5 Hospital Universitari de Bellvitge¿Universitat de Barcelona, 08907 L´Hospitalet de Llobregat, Spain 6 Campus Nord, Universitat Politècnica de Catalunya, 08034 Barcelona, Spain 7 Departament d¿Econometria, Estadística I Economia Aplicada¿Universitat de Barcelona, 08007 Barcelona, Spain 8 Universidad Complutense de Madrid, 28040 Madrid, Spain 9 Service of Internal Medicine, Hospital Universitario HM Montepríncipe, HM Hospitales, 28660 Boadilla del Monte, Spain 10 Faculty of Medicine, Universidad San Pablo-CEU, CEU Universities, Fundación de Investigación HM Hospitales, 28003 Madrid, Spain

add Show full affiliation list * Author to whom correspondence should be addressed. ¿ For the Covid-19 HM and HUPA Group. J. Pers. Med. 2021, 11(1), 36; https://doi.org/10.3390/jpm11010036 Submission received: 9 December 2020 / Revised: 5 January 2021 / Accepted: 6 January 2021 / Published: 8 January 2021 (This article belongs to the Special Issue COVID-19 Related Complications) Downloadkeyboard_arrow_down Browse Figure Versions Notes

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. Keywords: COVID-19; C-reactive protein; oxygen saturation; ICU; death; predictive model