Clustering analysis reveals different profiles associating long-term post-COVID symptoms, COVID-19 symptoms at hospital admission and previous medical co-morbidities in previously hospitalized COVID-19 survivors

Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. The LONG-COVID-EXP-CM is supported by a grant of Comunidad de Madrid y la Unión Europea, a través del Fondo Europeo de Desarrollo Regional (FEDER), Recursos REACT-UE del Programa Operativo de Madrid 2014–2020, finan...

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Detalles Bibliográficos
Autores: Fernández-de-las-Peñas, César, Martín-Guerrero, José D., Florencio, Lidiane L., Navarro-Pardo, Esperanza, Rodríguez-Jiménez, Jorge, Torres-Macho, Juan, Pellicer-Valero, Oscar J.
Tipo de recurso: artículo
Fecha de publicación:2022
País:España
Institución:Universidad Rey Juan Carlos
Repositorio:BURJC-Digital. Repositorio Institucional de la Universidad Rey Juan Carlos
OAI Identifier:oai:burjcdigital.urjc.es:10115/24381
Acceso en línea:https://hdl.handle.net/10115/24381
Access Level:acceso abierto
Palabra clave:COVID-19
K-means clustering
Post-COVID
Long COVID
Groups
Descripción
Sumario:Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. The LONG-COVID-EXP-CM is supported by a grant of Comunidad de Madrid y la Unión Europea, a través del Fondo Europeo de Desarrollo Regional (FEDER), Recursos REACT-UE del Programa Operativo de Madrid 2014–2020, financiado como parte de la respuesta de la Unión a la pandemia de COVID-19The sponsor had no role in the design, collection, management, analysis, or interpretation of the data, draft, review, or approval of the manuscript or its content. The authors were responsible for the decision to submit the manuscript for publication, and the sponsor did not participate in this decision.

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