Unknown

Dataset Information

0

Identification of Distinct Clinical Subphenotypes in Critically Ill Patients With COVID-19.


ABSTRACT:

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.

SUBMITTER: Vasquez CR 

PROVIDER: S-EPMC8099539 | biostudies-literature |

REPOSITORIES: biostudies-literature

Similar Datasets

2022-02-28 | GSE197259 | GEO
2021-06-18 | GSE178404 | GEO
| S-EPMC8342520 | biostudies-literature
2023-04-29 | GSE206264 | GEO
2024-10-22 | PXD057019 | Pride
2022-02-28 | GSE197258 | GEO
2022-02-28 | GSE197204 | GEO
2021-07-03 | GSE168400 | GEO
2021-12-10 | PXD029547 | Pride