Abstract
Heterogeneity has been observed in outcomes of hospitalized patients with coronavirus disease 2019 (COVID-19). Identification of clinical phenotypes may facilitate tailored therapy and improve outcomes. The purpose of this study is to identify specific clinical phenotypes across COVID-19 patients and compare admission characteristics and outcomes. This is a retrospective analysis of COVID-19 patients from March 7, 2020 to August 25, 2020 at 14 U.S. hospitals. Ensemble clustering was performed on 33 variables collected within 72 hours of admission. Principal component analysis was performed to visualize variable contributions to clustering. Multinomial regression models were fit to compare patient comorbidities across phenotypes. Multivariable models were fit to estimate associations between phenotype and in-hospital complications and clinical outcomes. The database included 1,022 hospitalized patients with COVID-19. Three clinical phenotypes were identified (I, II, III), with 236 [23.1%] patients in phenotype I, 613 [60%] patients in phenotype II, and 173 [16.9%] patients in phenotype III. Patients with respiratory comorbidities were most commonly phenotype III (p = 0.002), while patients with hematologic, renal, and cardiac (all p<0.001) comorbidities were most commonly phenotype I. Adjusted odds of respiratory, renal, hepatic, metabolic (all p<0.001), and hematological (p = 0.02) complications were highest for phenotype I. Phenotypes I and II were associated with 7.30-fold (HR:7.30, 95% CI:(3.11-17.17), p<0.001) and 2.57-fold (HR:2.57, 95% CI:(1.10-6.00), p = 0.03) increases in hazard of death relative to phenotype III. We identified three clinical COVID-19 phenotypes, reflecting patient populations with different comorbidities, complications, and clinical outcomes. Future research is needed to determine the utility of these phenotypes in clinical practice and trial design.
Highlights
The coronavirus disease 2019 (COVID-19), a disease caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has infected over 18 million and led to over 700,000 deaths since first appearing in late 2019 [1]
We identified three clinical COVID-19 phenotypes, reflecting patient populations with different comorbidities, complications, and clinical outcomes
A classic ARDS phenotype exists with poorly compliant lungs and poor gas exchange; a phenotype with normal lung compliance exists in COVID-19 and is hypothesized to be driven by shunting secondary to pulmonary microthrombi [6, 7]
Summary
The coronavirus disease 2019 (COVID-19), a disease caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has infected over 18 million and led to over 700,000 deaths since first appearing in late 2019 [1]. Researchers are rapidly attempting to understand the natural history of and immune response to COVID-19 [2]. COVID-19 results in a constellation of symptoms, laboratory derangement, immune dysregulation, and clinical complications [5]. Emergency department presentation varies widely, suggesting distinct clinical phenotypes exist and, importantly, it is likely these distinct phenotypes respond differently to treatment. Two early phenotypes of respiratory failure likely exist in COVID-19. A classic ARDS phenotype exists with poorly compliant lungs and poor gas exchange; a phenotype with normal lung compliance exists in COVID-19 and is hypothesized to be driven by shunting secondary to pulmonary microthrombi [6, 7]. Multidimensional view is required to adequately understand the disease and account for the variation in clinical outcomes. Patients could benefit from phenotype-specific medical care, which may differ from established standards of care
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