Cargando…

External validation of unsupervised COVID-19 clinical phenotypes and their prognostic impact

BACKGROUND: Hospitalized patients with coronavirus disease 2019 (COVID-19) can be classified into different clinical phenotypes based on their demographic, clinical, radiology, and laboratory features. We aimed to validate in an external cohort of hospitalized COVID-19 patients the prognostic value...

Descripción completa

Detalles Bibliográficos
Autores principales: Giacobbe, Daniele Roberto, Di Maria, Emilio, Tagliafico, Alberto Stefano, Bavastro, Martina, Trombetta, Carlo Simone, Marelli, Cristina, Di Meco, Gabriele, Cattardico, Greta, Mora, Sara, Signori, Alessio, Vena, Antonio, Mikulska, Malgorzata, Dentone, Chiara, Bruzzone, Bianca, Bignotti, Bianca, Orsi, Andrea, Robba, Chiara, Ball, Lorenzo, Brunetti, Iole, Battaglini, Denise, Di Biagio, Antonio, Sormani, Maria Pia, Pelosi, Paolo, Giacomini, Mauro, Icardi, Giancarlo, Bassetti, Matteo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10116925/
https://www.ncbi.nlm.nih.gov/pubmed/37052252
http://dx.doi.org/10.1080/07853890.2023.2195204
_version_ 1785028524184174592
author Giacobbe, Daniele Roberto
Di Maria, Emilio
Tagliafico, Alberto Stefano
Bavastro, Martina
Trombetta, Carlo Simone
Marelli, Cristina
Di Meco, Gabriele
Cattardico, Greta
Mora, Sara
Signori, Alessio
Vena, Antonio
Mikulska, Malgorzata
Dentone, Chiara
Bruzzone, Bianca
Bignotti, Bianca
Orsi, Andrea
Robba, Chiara
Ball, Lorenzo
Brunetti, Iole
Battaglini, Denise
Di Biagio, Antonio
Sormani, Maria Pia
Pelosi, Paolo
Giacomini, Mauro
Icardi, Giancarlo
Bassetti, Matteo
author_facet Giacobbe, Daniele Roberto
Di Maria, Emilio
Tagliafico, Alberto Stefano
Bavastro, Martina
Trombetta, Carlo Simone
Marelli, Cristina
Di Meco, Gabriele
Cattardico, Greta
Mora, Sara
Signori, Alessio
Vena, Antonio
Mikulska, Malgorzata
Dentone, Chiara
Bruzzone, Bianca
Bignotti, Bianca
Orsi, Andrea
Robba, Chiara
Ball, Lorenzo
Brunetti, Iole
Battaglini, Denise
Di Biagio, Antonio
Sormani, Maria Pia
Pelosi, Paolo
Giacomini, Mauro
Icardi, Giancarlo
Bassetti, Matteo
author_sort Giacobbe, Daniele Roberto
collection PubMed
description BACKGROUND: Hospitalized patients with coronavirus disease 2019 (COVID-19) can be classified into different clinical phenotypes based on their demographic, clinical, radiology, and laboratory features. We aimed to validate in an external cohort of hospitalized COVID-19 patients the prognostic value of a previously described phenotyping system (FEN-COVID-19) and to assess the reproducibility of phenotypes development as a secondary analysis. METHODS: Patients were classified in phenotypes A, B or C according to the severity of oxygenation impairment, inflammatory response, hemodynamic and laboratory tests according to the FEN-COVID-19 method. RESULTS: Overall, 992 patients were included in the study, and 181 (18%), 757 (76%) and 54 (6%) of them were assigned to the FEN-COVID-19 phenotypes A, B, and C, respectively. An association with mortality was observed for phenotype C vs. A (hazard ratio [HR] 3.10, 95% confidence interval [CI] 1.81–5.30, p < 0.001) and for phenotype C vs. B (HR 2.20, 95% CI 1.50–3.23, p < 0.001). A non-statistically significant trend towards higher mortality was also observed for phenotype B vs. A (HR 1.41; 95% CI 0.92–2.15, p = 0.115). By means of cluster analysis, three different phenotypes were also identified in our cohort, with an overall similar gradient in terms of prognostic impact to that observed when patients were assigned to FEN-COVID-19 phenotypes. CONCLUSIONS: The prognostic impact of FEN-COVID-19 phenotypes was confirmed in our external cohort, although with less difference in mortality between phenotypes A and B than in the original study.
format Online
Article
Text
id pubmed-10116925
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Taylor & Francis
record_format MEDLINE/PubMed
spelling pubmed-101169252023-04-21 External validation of unsupervised COVID-19 clinical phenotypes and their prognostic impact Giacobbe, Daniele Roberto Di Maria, Emilio Tagliafico, Alberto Stefano Bavastro, Martina Trombetta, Carlo Simone Marelli, Cristina Di Meco, Gabriele Cattardico, Greta Mora, Sara Signori, Alessio Vena, Antonio Mikulska, Malgorzata Dentone, Chiara Bruzzone, Bianca Bignotti, Bianca Orsi, Andrea Robba, Chiara Ball, Lorenzo Brunetti, Iole Battaglini, Denise Di Biagio, Antonio Sormani, Maria Pia Pelosi, Paolo Giacomini, Mauro Icardi, Giancarlo Bassetti, Matteo Ann Med Infectious Diseases BACKGROUND: Hospitalized patients with coronavirus disease 2019 (COVID-19) can be classified into different clinical phenotypes based on their demographic, clinical, radiology, and laboratory features. We aimed to validate in an external cohort of hospitalized COVID-19 patients the prognostic value of a previously described phenotyping system (FEN-COVID-19) and to assess the reproducibility of phenotypes development as a secondary analysis. METHODS: Patients were classified in phenotypes A, B or C according to the severity of oxygenation impairment, inflammatory response, hemodynamic and laboratory tests according to the FEN-COVID-19 method. RESULTS: Overall, 992 patients were included in the study, and 181 (18%), 757 (76%) and 54 (6%) of them were assigned to the FEN-COVID-19 phenotypes A, B, and C, respectively. An association with mortality was observed for phenotype C vs. A (hazard ratio [HR] 3.10, 95% confidence interval [CI] 1.81–5.30, p < 0.001) and for phenotype C vs. B (HR 2.20, 95% CI 1.50–3.23, p < 0.001). A non-statistically significant trend towards higher mortality was also observed for phenotype B vs. A (HR 1.41; 95% CI 0.92–2.15, p = 0.115). By means of cluster analysis, three different phenotypes were also identified in our cohort, with an overall similar gradient in terms of prognostic impact to that observed when patients were assigned to FEN-COVID-19 phenotypes. CONCLUSIONS: The prognostic impact of FEN-COVID-19 phenotypes was confirmed in our external cohort, although with less difference in mortality between phenotypes A and B than in the original study. Taylor & Francis 2023-04-13 /pmc/articles/PMC10116925/ /pubmed/37052252 http://dx.doi.org/10.1080/07853890.2023.2195204 Text en © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.
spellingShingle Infectious Diseases
Giacobbe, Daniele Roberto
Di Maria, Emilio
Tagliafico, Alberto Stefano
Bavastro, Martina
Trombetta, Carlo Simone
Marelli, Cristina
Di Meco, Gabriele
Cattardico, Greta
Mora, Sara
Signori, Alessio
Vena, Antonio
Mikulska, Malgorzata
Dentone, Chiara
Bruzzone, Bianca
Bignotti, Bianca
Orsi, Andrea
Robba, Chiara
Ball, Lorenzo
Brunetti, Iole
Battaglini, Denise
Di Biagio, Antonio
Sormani, Maria Pia
Pelosi, Paolo
Giacomini, Mauro
Icardi, Giancarlo
Bassetti, Matteo
External validation of unsupervised COVID-19 clinical phenotypes and their prognostic impact
title External validation of unsupervised COVID-19 clinical phenotypes and their prognostic impact
title_full External validation of unsupervised COVID-19 clinical phenotypes and their prognostic impact
title_fullStr External validation of unsupervised COVID-19 clinical phenotypes and their prognostic impact
title_full_unstemmed External validation of unsupervised COVID-19 clinical phenotypes and their prognostic impact
title_short External validation of unsupervised COVID-19 clinical phenotypes and their prognostic impact
title_sort external validation of unsupervised covid-19 clinical phenotypes and their prognostic impact
topic Infectious Diseases
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10116925/
https://www.ncbi.nlm.nih.gov/pubmed/37052252
http://dx.doi.org/10.1080/07853890.2023.2195204
work_keys_str_mv AT giacobbedanieleroberto externalvalidationofunsupervisedcovid19clinicalphenotypesandtheirprognosticimpact
AT dimariaemilio externalvalidationofunsupervisedcovid19clinicalphenotypesandtheirprognosticimpact
AT tagliaficoalbertostefano externalvalidationofunsupervisedcovid19clinicalphenotypesandtheirprognosticimpact
AT bavastromartina externalvalidationofunsupervisedcovid19clinicalphenotypesandtheirprognosticimpact
AT trombettacarlosimone externalvalidationofunsupervisedcovid19clinicalphenotypesandtheirprognosticimpact
AT marellicristina externalvalidationofunsupervisedcovid19clinicalphenotypesandtheirprognosticimpact
AT dimecogabriele externalvalidationofunsupervisedcovid19clinicalphenotypesandtheirprognosticimpact
AT cattardicogreta externalvalidationofunsupervisedcovid19clinicalphenotypesandtheirprognosticimpact
AT morasara externalvalidationofunsupervisedcovid19clinicalphenotypesandtheirprognosticimpact
AT signorialessio externalvalidationofunsupervisedcovid19clinicalphenotypesandtheirprognosticimpact
AT venaantonio externalvalidationofunsupervisedcovid19clinicalphenotypesandtheirprognosticimpact
AT mikulskamalgorzata externalvalidationofunsupervisedcovid19clinicalphenotypesandtheirprognosticimpact
AT dentonechiara externalvalidationofunsupervisedcovid19clinicalphenotypesandtheirprognosticimpact
AT bruzzonebianca externalvalidationofunsupervisedcovid19clinicalphenotypesandtheirprognosticimpact
AT bignottibianca externalvalidationofunsupervisedcovid19clinicalphenotypesandtheirprognosticimpact
AT orsiandrea externalvalidationofunsupervisedcovid19clinicalphenotypesandtheirprognosticimpact
AT robbachiara externalvalidationofunsupervisedcovid19clinicalphenotypesandtheirprognosticimpact
AT balllorenzo externalvalidationofunsupervisedcovid19clinicalphenotypesandtheirprognosticimpact
AT brunettiiole externalvalidationofunsupervisedcovid19clinicalphenotypesandtheirprognosticimpact
AT battaglinidenise externalvalidationofunsupervisedcovid19clinicalphenotypesandtheirprognosticimpact
AT dibiagioantonio externalvalidationofunsupervisedcovid19clinicalphenotypesandtheirprognosticimpact
AT sormanimariapia externalvalidationofunsupervisedcovid19clinicalphenotypesandtheirprognosticimpact
AT pelosipaolo externalvalidationofunsupervisedcovid19clinicalphenotypesandtheirprognosticimpact
AT giacominimauro externalvalidationofunsupervisedcovid19clinicalphenotypesandtheirprognosticimpact
AT icardigiancarlo externalvalidationofunsupervisedcovid19clinicalphenotypesandtheirprognosticimpact
AT bassettimatteo externalvalidationofunsupervisedcovid19clinicalphenotypesandtheirprognosticimpact