Please use this identifier to cite or link to this item:
http://hdl.handle.net/2445/174450
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 Mortalitat COVID-19 Mortality |
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. |
Note: | Reproducció del document publicat a: https://doi.org/10.3390/jpm11010036 |
It is part of: | Journal of Personalized Medicine, 2021, vol. 11, num. 1 |
URI: | http://hdl.handle.net/2445/174450 |
Related resource: | https://doi.org/10.3390/jpm11010036 |
Appears in Collections: | Articles publicats en revistes (Institut d'lnvestigació Biomèdica de Bellvitge (IDIBELL)) |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
jpm-11-00036-v2.pdf | 982.13 kB | Adobe PDF | View/Open |
This item is licensed under a Creative Commons License