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.

doi:10.1186/s13054-021-03487-8

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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.

Critical care (London, England) - 15 Feb 2021

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

Abstract excerpt

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 study of critically ill patients with confirmed COVID-19 disease and acute respiratory failure admitted from 63 ICUs...

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PMID: 33588914
DOI: 10.1186/s13054-021-03487-8
PMCID: PMC7883885

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 6 Sept 2026. Manifest publication-graph-cohort-2026-09-06.1.

Source receipt: pubmed, retrieved 6 Sept 2026.

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