Identification of Distinct Clinical Phenotypes of Critically Ill COVID-19 Patients

Detalhes bibliográficos
Autor(a) principal: Cidade, José Pedro
Data de Publicação: 2023
Outros Autores: de Souza Dantas, Vicente Cés, de Figueiredo Thompson, Alessandra, de Miranda, Renata Carnevale Carneiro Chermont, Mamfrim, Rafaela, Caroli, Henrique, Escudini, Gabriela, Oliveira, Natalia, Castro, Taiza, Povoa, Pedro
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/152741
Resumo: Purpose: COVID-19 presents complex pathophysiology, and evidence collected points towards an intricate interaction between viral-dependent and individual immunological mechanisms. Identifying phenotypes through clinical and biological markers may provide a better understanding of the subjacent mechanisms and an early patient-tailored characterization of illness severity. Methods: A multicenter prospective cohort study was performed in 5 hospitals in Portugal and Brazil for one year between 2020–2021. All adult patients with an Intensive Care Unit admission with SARS-CoV-2 pneumonia were eligible. COVID-19 was diagnosed using clinical and radiologic criteria with a SARS-CoV-2 positive RT-PCR test. A two-step hierarchical cluster analysis was made using several class-defining variables. Results: 814 patients were included. The cluster analysis revealed a three-class model, allowing for the definition of three distinct COVID-19 phenotypes: 407 patients in phenotype A, 244 patients in phenotype B, and 163 patients in phenotype C. Patients included in phenotype A were significantly older, with higher baseline inflammatory biomarkers profile, and a significantly higher requirement of organ support and mortality rate. Phenotypes B and C demonstrated some overlapping clinical characteristics but different outcomes. Phenotype C patients presented a lower mortality rate, with consistently lower C-reactive protein, but higher procalcitonin and interleukin-6 serum levels, describing an immunological profile significantly different from phenotype B. Conclusions: Severe COVID-19 patients exhibit three different clinical phenotypes with distinct profiles and outcomes. Their identification could have an impact on patients’ care, justifying different therapy responses and inconsistencies identified across different randomized control trial results.
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spelling Identification of Distinct Clinical Phenotypes of Critically Ill COVID-19 PatientsResults from a Cohort Observational Studycluster analysisCOVID-19critical caremortality ratephenotypesMedicine(all)Purpose: COVID-19 presents complex pathophysiology, and evidence collected points towards an intricate interaction between viral-dependent and individual immunological mechanisms. Identifying phenotypes through clinical and biological markers may provide a better understanding of the subjacent mechanisms and an early patient-tailored characterization of illness severity. Methods: A multicenter prospective cohort study was performed in 5 hospitals in Portugal and Brazil for one year between 2020–2021. All adult patients with an Intensive Care Unit admission with SARS-CoV-2 pneumonia were eligible. COVID-19 was diagnosed using clinical and radiologic criteria with a SARS-CoV-2 positive RT-PCR test. A two-step hierarchical cluster analysis was made using several class-defining variables. Results: 814 patients were included. The cluster analysis revealed a three-class model, allowing for the definition of three distinct COVID-19 phenotypes: 407 patients in phenotype A, 244 patients in phenotype B, and 163 patients in phenotype C. Patients included in phenotype A were significantly older, with higher baseline inflammatory biomarkers profile, and a significantly higher requirement of organ support and mortality rate. Phenotypes B and C demonstrated some overlapping clinical characteristics but different outcomes. Phenotype C patients presented a lower mortality rate, with consistently lower C-reactive protein, but higher procalcitonin and interleukin-6 serum levels, describing an immunological profile significantly different from phenotype B. Conclusions: Severe COVID-19 patients exhibit three different clinical phenotypes with distinct profiles and outcomes. Their identification could have an impact on patients’ care, justifying different therapy responses and inconsistencies identified across different randomized control trial results.NOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM)Comprehensive Health Research Centre (CHRC) - pólo NMSRUNCidade, José Pedrode Souza Dantas, Vicente Césde Figueiredo Thompson, Alessandrade Miranda, Renata Carnevale Carneiro ChermontMamfrim, RafaelaCaroli, HenriqueEscudini, GabrielaOliveira, NataliaCastro, TaizaPovoa, Pedro2023-05-12T22:12:08Z2023-042023-04-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10362/152741eng2077-0383PURE: 60176323https://doi.org/10.3390/jcm12083035info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-05-22T18:11:27Zoai:run.unl.pt:10362/152741Portal AgregadorONGhttps://www.rcaap.pt/oai/openairemluisa.alvim@gmail.comopendoar:71602024-05-22T18:11:27Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Identification of Distinct Clinical Phenotypes of Critically Ill COVID-19 Patients
Results from a Cohort Observational Study
title Identification of Distinct Clinical Phenotypes of Critically Ill COVID-19 Patients
spellingShingle Identification of Distinct Clinical Phenotypes of Critically Ill COVID-19 Patients
Cidade, José Pedro
cluster analysis
COVID-19
critical care
mortality rate
phenotypes
Medicine(all)
title_short Identification of Distinct Clinical Phenotypes of Critically Ill COVID-19 Patients
title_full Identification of Distinct Clinical Phenotypes of Critically Ill COVID-19 Patients
title_fullStr Identification of Distinct Clinical Phenotypes of Critically Ill COVID-19 Patients
title_full_unstemmed Identification of Distinct Clinical Phenotypes of Critically Ill COVID-19 Patients
title_sort Identification of Distinct Clinical Phenotypes of Critically Ill COVID-19 Patients
author Cidade, José Pedro
author_facet Cidade, José Pedro
de Souza Dantas, Vicente Cés
de Figueiredo Thompson, Alessandra
de Miranda, Renata Carnevale Carneiro Chermont
Mamfrim, Rafaela
Caroli, Henrique
Escudini, Gabriela
Oliveira, Natalia
Castro, Taiza
Povoa, Pedro
author_role author
author2 de Souza Dantas, Vicente Cés
de Figueiredo Thompson, Alessandra
de Miranda, Renata Carnevale Carneiro Chermont
Mamfrim, Rafaela
Caroli, Henrique
Escudini, Gabriela
Oliveira, Natalia
Castro, Taiza
Povoa, Pedro
author2_role author
author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv NOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM)
Comprehensive Health Research Centre (CHRC) - pólo NMS
RUN
dc.contributor.author.fl_str_mv Cidade, José Pedro
de Souza Dantas, Vicente Cés
de Figueiredo Thompson, Alessandra
de Miranda, Renata Carnevale Carneiro Chermont
Mamfrim, Rafaela
Caroli, Henrique
Escudini, Gabriela
Oliveira, Natalia
Castro, Taiza
Povoa, Pedro
dc.subject.por.fl_str_mv cluster analysis
COVID-19
critical care
mortality rate
phenotypes
Medicine(all)
topic cluster analysis
COVID-19
critical care
mortality rate
phenotypes
Medicine(all)
description Purpose: COVID-19 presents complex pathophysiology, and evidence collected points towards an intricate interaction between viral-dependent and individual immunological mechanisms. Identifying phenotypes through clinical and biological markers may provide a better understanding of the subjacent mechanisms and an early patient-tailored characterization of illness severity. Methods: A multicenter prospective cohort study was performed in 5 hospitals in Portugal and Brazil for one year between 2020–2021. All adult patients with an Intensive Care Unit admission with SARS-CoV-2 pneumonia were eligible. COVID-19 was diagnosed using clinical and radiologic criteria with a SARS-CoV-2 positive RT-PCR test. A two-step hierarchical cluster analysis was made using several class-defining variables. Results: 814 patients were included. The cluster analysis revealed a three-class model, allowing for the definition of three distinct COVID-19 phenotypes: 407 patients in phenotype A, 244 patients in phenotype B, and 163 patients in phenotype C. Patients included in phenotype A were significantly older, with higher baseline inflammatory biomarkers profile, and a significantly higher requirement of organ support and mortality rate. Phenotypes B and C demonstrated some overlapping clinical characteristics but different outcomes. Phenotype C patients presented a lower mortality rate, with consistently lower C-reactive protein, but higher procalcitonin and interleukin-6 serum levels, describing an immunological profile significantly different from phenotype B. Conclusions: Severe COVID-19 patients exhibit three different clinical phenotypes with distinct profiles and outcomes. Their identification could have an impact on patients’ care, justifying different therapy responses and inconsistencies identified across different randomized control trial results.
publishDate 2023
dc.date.none.fl_str_mv 2023-05-12T22:12:08Z
2023-04
2023-04-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/152741
url http://hdl.handle.net/10362/152741
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2077-0383
PURE: 60176323
https://doi.org/10.3390/jcm12083035
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv mluisa.alvim@gmail.com
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