Identification of two distinct phenotypes among hospitalized covid-19 patients using latent class analysis

ABSTRACT

Introduction: COVID-19 pneumonia is a heterogeneous disorder with a complex pathogenesis. Underlying subgroups may exist among patients who are admitted to the hospital with COVID-19 infection. Methods: We reviewed the charts of adult patients who were hospitalized primarily for COVID-19 at Greenwich Hospital. We performed latent class analysis using variables based on patient demographics (age, sex, race, and body mass index), comorbidities (hypertension, diabetes, coronary artery disease, chronic heart failure, chronic kidney disease, neurological disease, and pre-existing respiratory disease), laboratory results, and treatment information (medications received during hospitalization, hospital length of stay, maximized oxygen requirement, and requirement for intubation). Results: Two phenotypes were identified C1 and C2. C1 (n=193) included older individuals with a higher mortality rate (25.4% vs 8.97%, p<0.001) and more comorbidities such as hypertension (88.6% vs 22.8%, p<0.001), coronary artery disease (32.1% vs 0.0%, p<0.001), chronic heart failure (20.7% vs 0%, p<0.001), diabetes mellitus (38.3% vs 17.6%, p<0.001), chronic kidney disease (25.4% vs 2.8%, p<0.001), pre-existing respiratory disease (24.9% vs 11.0%, p=0.004), and preexisting neurological disease (32.1% vs 3.5%, p<0.001). C2 (n=290) consisted of individuals who were younger (53.7 years vs 79.5 years, p<0.001), more likely to be obese (40.3% vs. 28.0%, p=0.007), mostly male (70.3% vs 52.3%, p<0.001), and mostly non-white (69.7% vs. 28.5%, p<0.001), with higher levels of inflammatory markers such as C-reactive protein (18.3±43.4 vs. 10.7±13.7 mg/L, p=0.006) and alanine aminotransferase (209±512 vs. 96.2±204 U/L, p=0.001). Conclusions: Using latent class analysis, we identified two clinical phenotypes of patients who were admitted to the hospital for COVID-19. Our findings may reflect different pathophysiologic processes that lead to moderate to severe COVID-19 and may be useful in the identification of treatment targets and the selection of patients with severe COVID-19 disease for future clinical trials.