• Adrian Ceccato, Carles Forne, Lieuwe D Bos, Marta Camprubí-Rimblas, Aina Areny-Balagueró, Elena Campaña-Duel, Sara Quero, Emili Diaz, Oriol Roca, David De Gonzalo-Calvo, Laia Fernández-Barat, Anna Motos, Ricard Ferrer, Jordi Riera, Jose A Lorente, Oscar Peñuelas, Rosario Menendez, Rosario Amaya-Villar, José M Añón, Ana Balan-Mariño, Carme Barberà, José Barberán, Aaron Blandino-Ortiz, Maria Victoria Boado, Elena Bustamante-Munguira, Jesús Caballero, Cristina Carbajales, Nieves Carbonell, Mercedes Catalán-González, Nieves Franco, Cristóbal Galbán, Víctor D Gumucio-Sanguino, Maria Del Carmen de la Torre, Ángel Estella, Elena Gallego, José Luis García-Garmendia, José Garnacho-Montero, José M Gómez, Arturo Huerta, Ruth Noemí Jorge-García, Ana Loza-Vázquez, Judith Marin-Corral, Amalia Martínez de la Gándara, María Cruz Martin-Delgado, Ignacio Martínez-Varela, MessaJuan LopezJLComplejo Asistencial Universitario de Palencia, Palencia, Spain., Guillermo Muñiz-Albaiceta, María Teresa Nieto, Mariana Andrea Novo, Yhivian Peñasco, Juan Carlos Pozo-Laderas, Felipe Pérez-García, Pilar Ricart, Ferran Roche-Campo, Alejandro Rodríguez, Victor Sagredo, Angel Sánchez-Miralles, Susana Sancho-Chinesta, Lorenzo Socias, Jordi Solé-Violan, Fernando Suarez-Sipmann, Luis Tamayo-Lomas, José Trenado, Alejandro Úbeda, Luis Jorge Valdivia, Pablo Vidal, Jesus Bermejo, Jesica Gonzalez, Ferran Barbe, Carolyn S Calfee, Antonio Artigas, Antoni Torres, and CIBERESUCICOVID Project.
• Critical Care Center, Hospital Universitari Parc Taulí, Institut d'Investigació i Innovació Parc Taulí (I3PT-CERCA), Department of Medicine, Universitat Autonoma de Barcelona, Plaça Torre de L'Aigua, S/N, 08208, Sabadell, Spain. aaceccato@tauli.cat.
• Crit Care. 2024 Mar 21; 28 (1): 9191.

BackgroundAcute respiratory distress syndrome (ARDS) can be classified into sub-phenotypes according to different inflammatory/clinical status. Prognostic enrichment was achieved by grouping patients into hypoinflammatory or hyperinflammatory sub-phenotypes, even though the time of analysis may change the classification according to treatment response or disease evolution. We aimed to evaluate when patients can be clustered in more than 1 group, and how they may change the clustering of patients using data of baseline or day 3, and the prognosis of patients according to their evolution by changing or not the cluster.MethodsMulticenter, observational prospective, and retrospective study of patients admitted due to ARDS related to COVID-19 infection in Spain. Patients were grouped according to a clustering mixed-type data algorithm (k-prototypes) using continuous and categorical readily available variables at baseline and day 3.ResultsOf 6205 patients, 3743 (60%) were included in the study. According to silhouette analysis, patients were grouped in two clusters. At baseline, 1402 (37%) patients were included in cluster 1 and 2341(63%) in cluster 2. On day 3, 1557(42%) patients were included in cluster 1 and 2086 (57%) in cluster 2. The patients included in cluster 2 were older and more frequently hypertensive and had a higher prevalence of shock, organ dysfunction, inflammatory biomarkers, and worst respiratory indexes at both time points. The 90-day mortality was higher in cluster 2 at both clustering processes (43.8% [n = 1025] versus 27.3% [n = 383] at baseline, and 49% [n = 1023] versus 20.6% [n = 321] on day 3). Four hundred and fifty-eight (33%) patients clustered in the first group were clustered in the second group on day 3. In contrast, 638 (27%) patients clustered in the second group were clustered in the first group on day 3.ConclusionsDuring the first days, patients can be clustered into two groups and the process of clustering patients may change as they continue to evolve. This means that despite a vast majority of patients remaining in the same cluster, a minority reaching 33% of patients analyzed may be re-categorized into different clusters based on their progress. Such changes can significantly impact their prognosis.© 2024. The Author(s).

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