Clustering COVID-19 ARDS patients through the first days of ICU admission. An analysis of the CIBERESUCICOVID Cohort

Ceccato, Adrián; Forne, Carles; Bos, Lieuwe D .; Camprubí-Rimblas, Marta; Areny-Balagueró, Aina; Campaña-Duel, Elena; Quero, Sara; Diaz, Emili; Roca, Oriol; de Gonzalo Calvo, David; Fernández-Barat, Laia; Motos, Anna; Ferrer, Ricard; Riera, Jordi; Lorente, Jose A.; Peñuelas, Oscar; Menendez, Rosario; Amaya-Villar, Rosario; Añón, José M.; Balan-Mariño, Ana; Barberà, Carme; Barberán, José; Blandino-Ortiz, Aaron; Boado, Maria Victoria; Bustamante Munguira, Elena; Caballero, Jesús; Carbajales, Cristina; Carbonell, Nieves; Catalán-González, Mercedes; Franco, Nieves; Galbán, Cristóbal; Gumucio-Sanguino, Víctor D.; de la Torre, Maria del Carmen; Estella, Ángel; Gallego, Elena; García-Garmendia, José Luis; Garnacho-Montero, José; Gómez, José M.; Huerta, Arturo; Jorge-García, Ruth Noemí; Loza-Vázquez, Ana; Marin-Corral, Judith; Martínez de la Gándara, Amalia; Martin-Delgado, María Cruz; Martínez-Varela, Ignacio; López Messa, Juan; Muñiz-Albaiceta, Guillermo; Nieto, María Teresa; Novo, Mariana Andrea; Peñasco, Yhivian; Pozo-Laderas, Juan Carlos; Pérez-García, Felipe; Ricart, Pilar; Roche-Campo, Ferran; Rodríguez, Alejandro; Sagredo, Victor; Sánchez-Miralles, Angel; Sancho-Chinesta, Susana; Socias, Lorenzo; Solé-Violan, Jordi; Suarez-Sipmann, Fernando; Tamayo Lomas, Luis; Trenado, José; Úbeda, Alejandro; Valdivia, Luis Jorge; Vidal, Pablo; Bermejo, Jesus; González, Jessica; Barbé Illa, Ferran; Calfee, Carolyn S.; Artigas, Antonio; Torres, Antoni

Clustering COVID-19 ARDS patients through the first days of ICU admission. An analysis of the CIBERESUCICOVID Cohort

Background: Acute 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 ch...

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Autores:	Ceccato, Adrián, Forne, Carles, Bos, Lieuwe D ., Camprubí-Rimblas, Marta, Areny-Balagueró, Aina, Campaña-Duel, Elena, Quero, Sara, Diaz, Emili, Roca, Oriol, de Gonzalo Calvo, David, Fernández-Barat, Laia, Motos, Anna, Ferrer, Ricard, Riera, Jordi, Lorente, Jose A., Peñuelas, Oscar, Menendez, Rosario, Amaya-Villar, Rosario, Añón, José M., Balan-Mariño, Ana, Barberà, Carme, Barberán, José, Blandino-Ortiz, Aaron, Boado, Maria Victoria, Bustamante Munguira, Elena, Caballero, Jesús, Carbajales, Cristina, Carbonell, Nieves, Catalán-González, Mercedes, Franco, Nieves, Galbán, Cristóbal, Gumucio-Sanguino, Víctor D., de la Torre, Maria del Carmen, Estella, Ángel, Gallego, Elena, García-Garmendia, José Luis, Garnacho-Montero, José, Gómez, José M., Huerta, Arturo, Jorge-García, Ruth Noemí, Loza-Vázquez, Ana, Marin-Corral, Judith, Martínez de la Gándara, Amalia, Martin-Delgado, María Cruz, Martínez-Varela, Ignacio, López Messa, Juan, Muñiz-Albaiceta, Guillermo, Nieto, María Teresa, Novo, Mariana Andrea, Peñasco, Yhivian, Pozo-Laderas, Juan Carlos, Pérez-García, Felipe, Ricart, Pilar, Roche-Campo, Ferran, Rodríguez, Alejandro, Sagredo, Victor, Sánchez-Miralles, Angel, Sancho-Chinesta, Susana, Socias, Lorenzo, Solé-Violan, Jordi, Suarez-Sipmann, Fernando, Tamayo Lomas, Luis, Trenado, José, Úbeda, Alejandro, Valdivia, Luis Jorge, Vidal, Pablo, Bermejo, Jesus, González, Jessica, Barbé Illa, Ferran, Calfee, Carolyn S., Artigas, Antonio, Torres, Antoni
Tipo de recurso:	artículo
Estado:	Versión publicada
Fecha de publicación:	2024
País:	España
Institución:	Universitat de Lleida (UdL)
Repositorio:	Repositori Obert UdL
OAI Identifier:	oai:repositori.udl.cat:10459.1/465906
Acceso en línea:	https://doi.org/10.1186/s13054-024-04876-5 https://hdl.handle.net/10459.1/465906
Access Level:	acceso abierto
Palabra clave:	ARDS Clustering Mortality Precision medicine

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oai_identifier_str	oai:repositori.udl.cat:10459.1/465906
network_acronym_str	ES
network_name_str	España
repository_id_str
dc.title.none.fl_str_mv	Clustering COVID-19 ARDS patients through the first days of ICU admission. An analysis of the CIBERESUCICOVID Cohort
title	Clustering COVID-19 ARDS patients through the first days of ICU admission. An analysis of the CIBERESUCICOVID Cohort
spellingShingle	Clustering COVID-19 ARDS patients through the first days of ICU admission. An analysis of the CIBERESUCICOVID Cohort Ceccato, Adrián ARDS Clustering Mortality Precision medicine
title_short	Clustering COVID-19 ARDS patients through the first days of ICU admission. An analysis of the CIBERESUCICOVID Cohort
title_full	Clustering COVID-19 ARDS patients through the first days of ICU admission. An analysis of the CIBERESUCICOVID Cohort
title_fullStr	Clustering COVID-19 ARDS patients through the first days of ICU admission. An analysis of the CIBERESUCICOVID Cohort
title_full_unstemmed	Clustering COVID-19 ARDS patients through the first days of ICU admission. An analysis of the CIBERESUCICOVID Cohort
title_sort	Clustering COVID-19 ARDS patients through the first days of ICU admission. An analysis of the CIBERESUCICOVID Cohort
dc.creator.none.fl_str_mv	Ceccato, Adrián Forne, Carles Bos, Lieuwe D . Camprubí-Rimblas, Marta Areny-Balagueró, Aina Campaña-Duel, Elena Quero, Sara Diaz, Emili Roca, Oriol de Gonzalo Calvo, David Fernández-Barat, Laia Motos, Anna Ferrer, Ricard Riera, Jordi Lorente, Jose A. Peñuelas, Oscar Menendez, Rosario Amaya-Villar, Rosario Añón, José M. Balan-Mariño, Ana Barberà, Carme Barberán, José Blandino-Ortiz, Aaron Boado, Maria Victoria Bustamante Munguira, Elena Caballero, Jesús Carbajales, Cristina Carbonell, Nieves Catalán-González, Mercedes Franco, Nieves Galbán, Cristóbal Gumucio-Sanguino, Víctor D. de la Torre, Maria del Carmen Estella, Ángel Gallego, Elena García-Garmendia, José Luis Garnacho-Montero, José Gómez, José M. Huerta, Arturo Jorge-García, Ruth Noemí Loza-Vázquez, Ana Marin-Corral, Judith Martínez de la Gándara, Amalia Martin-Delgado, María Cruz Martínez-Varela, Ignacio López Messa, Juan Muñiz-Albaiceta, Guillermo Nieto, María Teresa Novo, Mariana Andrea Peñasco, Yhivian Pozo-Laderas, Juan Carlos Pérez-García, Felipe Ricart, Pilar Roche-Campo, Ferran Rodríguez, Alejandro Sagredo, Victor Sánchez-Miralles, Angel Sancho-Chinesta, Susana Socias, Lorenzo Solé-Violan, Jordi Suarez-Sipmann, Fernando Tamayo Lomas, Luis Trenado, José Úbeda, Alejandro Valdivia, Luis Jorge Vidal, Pablo Bermejo, Jesus González, Jessica Barbé Illa, Ferran Calfee, Carolyn S. Artigas, Antonio Torres, Antoni
author	Ceccato, Adrián
author_facet	Ceccato, Adrián Forne, Carles Bos, Lieuwe D . Camprubí-Rimblas, Marta Areny-Balagueró, Aina Campaña-Duel, Elena Quero, Sara Diaz, Emili Roca, Oriol de Gonzalo Calvo, David Fernández-Barat, Laia Motos, Anna Ferrer, Ricard Riera, Jordi Lorente, Jose A. Peñuelas, Oscar Menendez, Rosario Amaya-Villar, Rosario Añón, José M. Balan-Mariño, Ana Barberà, Carme Barberán, José Blandino-Ortiz, Aaron Boado, Maria Victoria Bustamante Munguira, Elena Caballero, Jesús Carbajales, Cristina Carbonell, Nieves Catalán-González, Mercedes Franco, Nieves Galbán, Cristóbal Gumucio-Sanguino, Víctor D. de la Torre, Maria del Carmen Estella, Ángel Gallego, Elena García-Garmendia, José Luis Garnacho-Montero, José Gómez, José M. Huerta, Arturo Jorge-García, Ruth Noemí Loza-Vázquez, Ana Marin-Corral, Judith Martínez de la Gándara, Amalia Martin-Delgado, María Cruz Martínez-Varela, Ignacio López Messa, Juan Muñiz-Albaiceta, Guillermo Nieto, María Teresa Novo, Mariana Andrea Peñasco, Yhivian Pozo-Laderas, Juan Carlos Pérez-García, Felipe Ricart, Pilar Roche-Campo, Ferran Rodríguez, Alejandro Sagredo, Victor Sánchez-Miralles, Angel Sancho-Chinesta, Susana Socias, Lorenzo Solé-Violan, Jordi Suarez-Sipmann, Fernando Tamayo Lomas, Luis Trenado, José Úbeda, Alejandro Valdivia, Luis Jorge Vidal, Pablo Bermejo, Jesus González, Jessica Barbé Illa, Ferran Calfee, Carolyn S. Artigas, Antonio Torres, Antoni
author_role	author
author2	Forne, Carles Bos, Lieuwe D . Camprubí-Rimblas, Marta Areny-Balagueró, Aina Campaña-Duel, Elena Quero, Sara Diaz, Emili Roca, Oriol de Gonzalo Calvo, David Fernández-Barat, Laia Motos, Anna Ferrer, Ricard Riera, Jordi Lorente, Jose A. Peñuelas, Oscar Menendez, Rosario Amaya-Villar, Rosario Añón, José M. Balan-Mariño, Ana Barberà, Carme Barberán, José Blandino-Ortiz, Aaron Boado, Maria Victoria Bustamante Munguira, Elena Caballero, Jesús Carbajales, Cristina Carbonell, Nieves Catalán-González, Mercedes Franco, Nieves Galbán, Cristóbal Gumucio-Sanguino, Víctor D. de la Torre, Maria del Carmen Estella, Ángel Gallego, Elena García-Garmendia, José Luis Garnacho-Montero, José Gómez, José M. Huerta, Arturo Jorge-García, Ruth Noemí Loza-Vázquez, Ana Marin-Corral, Judith Martínez de la Gándara, Amalia Martin-Delgado, María Cruz Martínez-Varela, Ignacio López Messa, Juan Muñiz-Albaiceta, Guillermo Nieto, María Teresa Novo, Mariana Andrea Peñasco, Yhivian Pozo-Laderas, Juan Carlos Pérez-García, Felipe Ricart, Pilar Roche-Campo, Ferran Rodríguez, Alejandro Sagredo, Victor Sánchez-Miralles, Angel Sancho-Chinesta, Susana Socias, Lorenzo Solé-Violan, Jordi Suarez-Sipmann, Fernando Tamayo Lomas, Luis Trenado, José Úbeda, Alejandro Valdivia, Luis Jorge Vidal, Pablo Bermejo, Jesus González, Jessica Barbé Illa, Ferran Calfee, Carolyn S. Artigas, Antonio Torres, Antoni
author2_role	author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author
dc.contributor.none.fl_str_mv	CIBERESUCICOVID Project
dc.subject.none.fl_str_mv	ARDS Clustering Mortality Precision medicine
topic	ARDS Clustering Mortality Precision medicine
description	Background: Acute 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. Methods: Multicenter, 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. Results: Of 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. Conclusions: During 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.
publishDate	2024
dc.date.none.fl_str_mv	2024
dc.type.none.fl_str_mv	info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion
format	article
status_str	publishedVersion
dc.identifier.none.fl_str_mv	https://doi.org/10.1186/s13054-024-04876-5 https://hdl.handle.net/10459.1/465906
url	https://doi.org/10.1186/s13054-024-04876-5 https://hdl.handle.net/10459.1/465906
dc.language.none.fl_str_mv	Inglés
language_invalid_str_mv	Inglés
dc.relation.none.fl_str_mv	Reproducció del document publicat a: https://doi.org/10.1186/s13054-024-04876-5 Critical Care, 2024, vol. 28, núm. 1
dc.rights.none.fl_str_mv	cc-by (c)Authors, 2024 Attribution 4.0 International info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/4.0/
rights_invalid_str_mv	cc-by (c)Authors, 2024 Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv	openAccess
dc.publisher.none.fl_str_mv	BMC
publisher.none.fl_str_mv	BMC
dc.source.none.fl_str_mv	reponame:Repositori Obert UdL instname:Universitat de Lleida (UdL)
instname_str	Universitat de Lleida (UdL)
reponame_str	Repositori Obert UdL
collection	Repositori Obert UdL
repository.name.fl_str_mv
repository.mail.fl_str_mv
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spelling	Clustering COVID-19 ARDS patients through the first days of ICU admission. An analysis of the CIBERESUCICOVID CohortCeccato, AdriánForne, CarlesBos, Lieuwe D .Camprubí-Rimblas, MartaAreny-Balagueró, AinaCampaña-Duel, ElenaQuero, SaraDiaz, EmiliRoca, Oriolde Gonzalo Calvo, DavidFernández-Barat, LaiaMotos, AnnaFerrer, RicardRiera, JordiLorente, Jose A.Peñuelas, OscarMenendez, RosarioAmaya-Villar, RosarioAñón, José M.Balan-Mariño, AnaBarberà, CarmeBarberán, JoséBlandino-Ortiz, AaronBoado, Maria VictoriaBustamante Munguira, ElenaCaballero, JesúsCarbajales, CristinaCarbonell, NievesCatalán-González, MercedesFranco, NievesGalbán, CristóbalGumucio-Sanguino, Víctor D.de la Torre, Maria del CarmenEstella, ÁngelGallego, ElenaGarcía-Garmendia, José LuisGarnacho-Montero, JoséGómez, José M.Huerta, ArturoJorge-García, Ruth NoemíLoza-Vázquez, AnaMarin-Corral, JudithMartínez de la Gándara, AmaliaMartin-Delgado, María CruzMartínez-Varela, IgnacioLópez Messa, JuanMuñiz-Albaiceta, GuillermoNieto, María TeresaNovo, Mariana AndreaPeñasco, YhivianPozo-Laderas, Juan CarlosPérez-García, FelipeRicart, PilarRoche-Campo, FerranRodríguez, AlejandroSagredo, VictorSánchez-Miralles, AngelSancho-Chinesta, SusanaSocias, LorenzoSolé-Violan, JordiSuarez-Sipmann, FernandoTamayo Lomas, Luis Trenado, JoséÚbeda, AlejandroValdivia, Luis JorgeVidal, PabloBermejo, JesusGonzález, JessicaBarbé Illa, FerranCalfee, Carolyn S.Artigas, AntonioTorres, AntoniARDSClusteringMortalityPrecision medicineBackground: Acute 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. Methods: Multicenter, 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. Results: Of 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. Conclusions: During 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.BMCCIBERESUCICOVID Project2024info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttps://doi.org/10.1186/s13054-024-04876-5https://hdl.handle.net/10459.1/465906reponame:Repositori Obert UdL instname:Universitat de Lleida (UdL)InglésReproducció del document publicat a: https://doi.org/10.1186/s13054-024-04876-5Critical Care, 2024, vol. 28, núm. 1cc-by (c)Authors, 2024Attribution 4.0 Internationalinfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/oai:repositori.udl.cat:10459.1/4659062026-06-24T12:42:17Z
score	15.812429

Clustering COVID-19 ARDS patients through the first days of ICU admission. An analysis of the CIBERESUCICOVID Cohort

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