Risk Score for Predicting In-Hospital Mortality in COVID-19 (RIM Score).
dc.contributor.author | López Escobar, Alejandro | |
dc.contributor.author | Madurga Lacalle, Rodrigo | |
dc.contributor.author | Castellano, José María | |
dc.contributor.author | Velázquez, Sara | |
dc.contributor.author | Suárez del Villar, Rafael | |
dc.contributor.author | Menéndez, Justo | |
dc.contributor.author | Peixoto, Alejandro | |
dc.contributor.author | Jimeno, Sara | |
dc.contributor.author | Sol Ventura, Paula | |
dc.contributor.author | Ruiz de Aguiar, Santiago | |
dc.date.accessioned | 2021-04-21T11:47:11Z | |
dc.date.available | 2021-04-21T11:47:11Z | |
dc.date.issued | 2021 | |
dc.description.abstract | Infection by SARS-CoV2 has devastating consequences on health care systems. It is a global health priority to identify patients at risk of fatal outcomes. 1955 patients admitted to HM-Hospitales from 1 March to 10 June 2020 due to COVID-19, were were divided into two groups, 1310 belonged to the training cohort and 645 to validation cohort. Four different models were generated to predict in-hospital mortality. Following variables were included: age, sex, oxygen saturation, level of C-reactive-protein, neutrophil-to-platelet-ratio (NPR), neutrophil-to-lymphocyte-ratio (NLR) and the rate of changes of both hemogram ratios (VNLR and VNPR) during the first week after admission. The accuracy of the models in predicting in-hospital mortality were evaluated using the area under the receiver-operator-characteristic curve (AUC). AUC for models including NLR and NPR performed similarly in both cohorts: NLR 0.873 (95% CI: 0.849–0.898), NPR 0.875 (95% CI: 0.851–0.899) in training cohort and NLR 0.856 (95% CI: 0.818–0.895), NPR 0.863 (95% CI: 0.826–0.901) in validation cohort. AUC was 0.885 (95% CI: 0.885–0.919) for VNLR and 0.891 (95% CI: 0.861–0.922) for VNPR in the validation cohort. According to our results, models are useful in predicting in-hospital mortality risk due to COVID-19. The RIM Score proposed is a simple, widely available tool that can help identify patients at risk of fatal outcomes. | spa |
dc.description.extent | 4007 KB | spa |
dc.identifier.doi | 10.3390/diagnostics11040596 | spa |
dc.identifier.issn | 2075-4418 | spa |
dc.identifier.uri | http://hdl.handle.net/10641/2293 | |
dc.language.iso | eng | spa |
dc.publisher | Diagnostics | spa |
dc.relation.publisherversion | https://www.mdpi.com/2075-4418/11/4/596 | spa |
dc.rights | Atribución-NoComercial-SinDerivadas 3.0 España | * |
dc.rights.accessRights | open access | spa |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ | * |
dc.subject | COVID-19 | spa |
dc.subject | Neutrophil-to-platelet ratio | spa |
dc.subject | Neutrophil-to-lymphocyte ratio | spa |
dc.subject | Hemogram derived ratios | spa |
dc.title | Risk Score for Predicting In-Hospital Mortality in COVID-19 (RIM Score). | spa |
dc.type | journal article | spa |
dc.type.hasVersion | AM | spa |
dspace.entity.type | Publication |
Files
Original bundle
1 - 1 of 1
Loading...
- Name:
- 2.- Risk Score for Predicting In-Hospital.pdf
- Size:
- 3.91 MB
- Format:
- Adobe Portable Document Format
- Description: