tetano
Editor, Senior Moderator
Chest
. 2021 May 5;S0012-3692(21)00874-6.
doi: 10.1016/j.chest.2021.04.062. Online ahead of print.
Identification of distinct clinical subphenotypes in critically ill patients with COVID-19
Charles R Vasquez[SUP] 1 [/SUP], Shruti Gupta[SUP] 2 [/SUP], Todd A Miano[SUP] 3 [/SUP], Meaghan Roche[SUP] 4 [/SUP], Jesse Hsu[SUP] 3 [/SUP], Wei Yang[SUP] 3 [/SUP], Daniel N Holena[SUP] 5 [/SUP], John P Reilly[SUP] 6 [/SUP], Sarah J Schrauben[SUP] 4 [/SUP], David E Leaf[SUP] 2 [/SUP], Michael G S Shashaty[SUP] 7 [/SUP], STOP-COVID Investigators
Affiliations
Abstract
Background: Subphenotypes have been identified in patients with sepsis and acute respiratory distress syndrome (ARDS), and are associated with different outcomes and response to therapies.
Research question: Can unique subphenotypes be identified among critically ill patients with coronavirus disease 2019 (COVID-19)?
Study design: & 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 utilized 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 Discovery (45 centers, n=2,188) and Replication (22 centers, n=1,112) cohorts. SP1 was characterized by shock, acidemia, and multi-organ 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 had the highest burden of chronic diseases, while SP4 had limited chronic disease burden and mild physiologic abnormalities. 28-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, SP1 relative risk (RR) 1.67 (95% CI 1.36-2.03); SP2 RR 1.39 (1.17-1.65); SP3 RR 1.39 (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.
Keywords: COVID-19; coronavirus; latent class analysis; subphenotypes.
. 2021 May 5;S0012-3692(21)00874-6.
doi: 10.1016/j.chest.2021.04.062. Online ahead of print.
Identification of distinct clinical subphenotypes in critically ill patients with COVID-19
Charles R Vasquez[SUP] 1 [/SUP], Shruti Gupta[SUP] 2 [/SUP], Todd A Miano[SUP] 3 [/SUP], Meaghan Roche[SUP] 4 [/SUP], Jesse Hsu[SUP] 3 [/SUP], Wei Yang[SUP] 3 [/SUP], Daniel N Holena[SUP] 5 [/SUP], John P Reilly[SUP] 6 [/SUP], Sarah J Schrauben[SUP] 4 [/SUP], David E Leaf[SUP] 2 [/SUP], Michael G S Shashaty[SUP] 7 [/SUP], STOP-COVID Investigators
Affiliations
- PMID: 33964301
- DOI: 10.1016/j.chest.2021.04.062
Abstract
Background: Subphenotypes have been identified in patients with sepsis and acute respiratory distress syndrome (ARDS), and are associated with different outcomes and response to therapies.
Research question: Can unique subphenotypes be identified among critically ill patients with coronavirus disease 2019 (COVID-19)?
Study design: & 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 utilized 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 Discovery (45 centers, n=2,188) and Replication (22 centers, n=1,112) cohorts. SP1 was characterized by shock, acidemia, and multi-organ 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 had the highest burden of chronic diseases, while SP4 had limited chronic disease burden and mild physiologic abnormalities. 28-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, SP1 relative risk (RR) 1.67 (95% CI 1.36-2.03); SP2 RR 1.39 (1.17-1.65); SP3 RR 1.39 (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.
Keywords: COVID-19; coronavirus; latent class analysis; subphenotypes.