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Identification and validation of clinical phenotypes with prognostic implications in patients admitted to hospital with COVID-19: a multicentre cohort study

Authors :
Universidad de Sevilla. Departamento de Medicina
Universidad de Sevilla. Departamento de Medicina Preventiva y Salud Pública
Instituto de Salud Carlos III
Gutiérrez Gutiérrez, Belén
Toro López, María Dolores del
Borobia, Alberto M.
Carcas, Antonio
Jarrín, Inmaculada
Yllescas, María
Pachón Díaz, Jerónimo
Rodríguez-Baño, Jesús
Salamanca Rivera, Celia
Valido-Morales, Agustín S.
Retamar Gentil, Pilar
Cisneros, José Miguel
Nieto Martín, María Dolores
Universidad de Sevilla. Departamento de Medicina
Universidad de Sevilla. Departamento de Medicina Preventiva y Salud Pública
Instituto de Salud Carlos III
Gutiérrez Gutiérrez, Belén
Toro López, María Dolores del
Borobia, Alberto M.
Carcas, Antonio
Jarrín, Inmaculada
Yllescas, María
Pachón Díaz, Jerónimo
Rodríguez-Baño, Jesús
Salamanca Rivera, Celia
Valido-Morales, Agustín S.
Retamar Gentil, Pilar
Cisneros, José Miguel
Nieto Martín, María Dolores
Publication Year :
2021

Abstract

Background The clinical presentation of COVID-19 in patients admitted to hospital is heterogeneous. We aimed to determine whether clinical phenotypes of patients with COVID-19 can be derived from clinical data, to assess the reproducibility of these phenotypes and correlation with prognosis, and to derive and validate a simplified probabilistic model for phenotype assignment. Phenotype identification was not primarily intended as a predictive tool for mortality. Methods In this study, we used data from two cohorts: the COVID-19@Spain cohort, a retrospective cohort including 4035 consecutive adult patients admitted to 127 hospitals in Spain with COVID-19 between Feb 2 and March 17, 2020, and the COVID-19@HULP cohort, including 2226 consecutive adult patients admitted to a teaching hospital in Madrid between Feb 25 and April 19, 2020. The COVID-19@Spain cohort was divided into a derivation cohort, comprising 2667 randomly selected patients, and an internal validation cohort, comprising the remaining 1368 patients. The COVID-19@HULP cohort was used as an external validation cohort. A probabilistic model for phenotype assignment was derived in the derivation cohort using multinomial logistic regression and validated in the internal validation cohort. The model was also applied to the external validation cohort. 30-day mortality and other prognostic variables were assessed in the derived phenotypes and in the phenotypes assigned by the probabilistic model. Findings Three distinct phenotypes were derived in the derivation cohort (n=2667)—phenotype A (516 [19%] patients), phenotype B (1955 [73%]) and phenotype C (196 [7%])—and reproduced in the internal validation cohort (n=1368)— phenotype A (233 [17%] patients), phenotype B (1019 [74%]), and phenotype C (116 [8%]). Patients with phenotype A were younger, were less frequently male, had mild viral symptoms, and had normal inflammatory parameters. Patients with phenotype B included more patients with obesity, lymphocytopeni

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1367149177
Document Type :
Electronic Resource