Deploying unsupervised clustering analysis to derive clinical phenotypes and risk factors associated with mortality risk in 2022 critically ill patients with COVID-19 in Spain

BACKGROUND: The identification of factors associated with Intensive Care Unit (ICU) mortality and derived clinical phenotypes in COVID-19 patients could help for a more tailored approach to clinical decision-making that improves prognostic outcomes. METHODS: Prospective, multicenter, observational s...

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Detalles Bibliográficos
Autores principales: Rodríguez, Alejandro, Ruiz-Botella, Manuel, Martín-Loeches, Ignacio, Jimenez Herrera, María, Solé-Violan, Jordi, Gómez, Josep, Bodí, María, Trefler, Sandra, Papiol, Elisabeth, Díaz, Emili, Suberviola, Borja, Vallverdu, Montserrat, Mayor-Vázquez, Eric, Albaya Moreno, Antonio, Canabal Berlanga, Alfonso, Sánchez, Miguel, del Valle Ortíz, María, Ballesteros, Juan Carlos, Martín Iglesias, Lorena, Marín-Corral, Judith, López Ramos, Esther, Hidalgo Valverde, Virginia, Vidaur Tello, Loreto Vidaur, Sancho Chinesta, Susana, Gonzáles de Molina, Francisco Javier, Herrero García, Sandra, Sena Pérez, Carmen Carolina, Pozo Laderas, Juan Carlos, Rodríguez García, Raquel, Estella, Angel, Ferrer, Ricard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7883885/
https://www.ncbi.nlm.nih.gov/pubmed/33588914
http://dx.doi.org/10.1186/s13054-021-03487-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7883885/
https://www.ncbi.nlm.nih.gov/pubmed/33588914
http://dx.doi.org/10.1186/s13054-021-03487-8

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