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Identification of Distinct Clinical Subphenotypes in Critically Ill Patients With COVID-19
BACKGROUND: Subphenotypes have been identified in patients with sepsis and ARDS and are associated with different outcomes and responses to therapies. RESEARCH QUESTION: Can unique subphenotypes be identified among critically ill patients with COVID-19? STUDY DESIGN AND METHODS: Using data from a mu...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American College of Chest Physicians. Published by Elsevier Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8099539/ https://www.ncbi.nlm.nih.gov/pubmed/33964301 http://dx.doi.org/10.1016/j.chest.2021.04.062 |
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author | Vasquez, Charles R. Gupta, Shruti Miano, Todd A. Roche, Meaghan Hsu, Jesse Yang, Wei Holena, Daniel N. Reilly, John P. Schrauben, Sarah J. Leaf, David E. Shashaty, Michael G.S. |
author_facet | Vasquez, Charles R. Gupta, Shruti Miano, Todd A. Roche, Meaghan Hsu, Jesse Yang, Wei Holena, Daniel N. Reilly, John P. Schrauben, Sarah J. Leaf, David E. Shashaty, Michael G.S. |
author_sort | Vasquez, Charles R. |
collection | PubMed |
description | BACKGROUND: Subphenotypes have been identified in patients with sepsis and ARDS and are associated with different outcomes and responses to therapies. RESEARCH QUESTION: Can unique subphenotypes be identified among critically ill patients with COVID-19? STUDY DESIGN AND METHODS: Using data from a multicenter cohort study that enrolled critically ill patients with COVID-19 from 67 hospitals across the United States, we randomly divided centers into discovery and replication cohorts. We used latent class analysis independently in each cohort to identify subphenotypes based on clinical and laboratory variables. We then analyzed the associations of subphenotypes with 28-day mortality. RESULTS: Latent class analysis identified four subphenotypes (SP) with consistent characteristics across the discovery (45 centers; n = 2,188) and replication (22 centers; n = 1,112) cohorts. SP1 was characterized by shock, acidemia, and multiorgan dysfunction, including acute kidney injury treated with renal replacement therapy. SP2 was characterized by high C-reactive protein, early need for mechanical ventilation, and the highest rate of ARDS. SP3 showed the highest burden of chronic diseases, whereas SP4 demonstrated limited chronic disease burden and mild physiologic abnormalities. Twenty-eight-day mortality in the discovery cohort ranged from 20.6% (SP4) to 52.9% (SP1). Mortality across subphenotypes remained different after adjustment for demographics, comorbidities, organ dysfunction and illness severity, regional and hospital factors. Compared with SP4, the relative risks were as follows: SP1, 1.67 (95% CI, 1.36-2.03); SP2, 1.39 (95% CI, 1.17-1.65); and SP3, 1.39 (95% CI, 1.15-1.67). Findings were similar in the replication cohort. INTERPRETATION: We identified four subphenotypes of COVID-19 critical illness with distinct patterns of clinical and laboratory characteristics, comorbidity burden, and mortality. |
format | Online Article Text |
id | pubmed-8099539 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | American College of Chest Physicians. Published by Elsevier Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-80995392021-05-06 Identification of Distinct Clinical Subphenotypes in Critically Ill Patients With COVID-19 Vasquez, Charles R. Gupta, Shruti Miano, Todd A. Roche, Meaghan Hsu, Jesse Yang, Wei Holena, Daniel N. Reilly, John P. Schrauben, Sarah J. Leaf, David E. Shashaty, Michael G.S. Chest Critical Care: Original Research BACKGROUND: Subphenotypes have been identified in patients with sepsis and ARDS and are associated with different outcomes and responses to therapies. RESEARCH QUESTION: Can unique subphenotypes be identified among critically ill patients with COVID-19? STUDY DESIGN AND METHODS: Using data from a multicenter cohort study that enrolled critically ill patients with COVID-19 from 67 hospitals across the United States, we randomly divided centers into discovery and replication cohorts. We used latent class analysis independently in each cohort to identify subphenotypes based on clinical and laboratory variables. We then analyzed the associations of subphenotypes with 28-day mortality. RESULTS: Latent class analysis identified four subphenotypes (SP) with consistent characteristics across the discovery (45 centers; n = 2,188) and replication (22 centers; n = 1,112) cohorts. SP1 was characterized by shock, acidemia, and multiorgan dysfunction, including acute kidney injury treated with renal replacement therapy. SP2 was characterized by high C-reactive protein, early need for mechanical ventilation, and the highest rate of ARDS. SP3 showed the highest burden of chronic diseases, whereas SP4 demonstrated limited chronic disease burden and mild physiologic abnormalities. Twenty-eight-day mortality in the discovery cohort ranged from 20.6% (SP4) to 52.9% (SP1). Mortality across subphenotypes remained different after adjustment for demographics, comorbidities, organ dysfunction and illness severity, regional and hospital factors. Compared with SP4, the relative risks were as follows: SP1, 1.67 (95% CI, 1.36-2.03); SP2, 1.39 (95% CI, 1.17-1.65); and SP3, 1.39 (95% CI, 1.15-1.67). Findings were similar in the replication cohort. INTERPRETATION: We identified four subphenotypes of COVID-19 critical illness with distinct patterns of clinical and laboratory characteristics, comorbidity burden, and mortality. American College of Chest Physicians. Published by Elsevier Inc. 2021-09 2021-05-06 /pmc/articles/PMC8099539/ /pubmed/33964301 http://dx.doi.org/10.1016/j.chest.2021.04.062 Text en © 2021 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Critical Care: Original Research Vasquez, Charles R. Gupta, Shruti Miano, Todd A. Roche, Meaghan Hsu, Jesse Yang, Wei Holena, Daniel N. Reilly, John P. Schrauben, Sarah J. Leaf, David E. Shashaty, Michael G.S. Identification of Distinct Clinical Subphenotypes in Critically Ill Patients With COVID-19 |
title | Identification of Distinct Clinical Subphenotypes in Critically Ill Patients With COVID-19 |
title_full | Identification of Distinct Clinical Subphenotypes in Critically Ill Patients With COVID-19 |
title_fullStr | Identification of Distinct Clinical Subphenotypes in Critically Ill Patients With COVID-19 |
title_full_unstemmed | Identification of Distinct Clinical Subphenotypes in Critically Ill Patients With COVID-19 |
title_short | Identification of Distinct Clinical Subphenotypes in Critically Ill Patients With COVID-19 |
title_sort | identification of distinct clinical subphenotypes in critically ill patients with covid-19 |
topic | Critical Care: Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8099539/ https://www.ncbi.nlm.nih.gov/pubmed/33964301 http://dx.doi.org/10.1016/j.chest.2021.04.062 |
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