Study of clinical phenotypes and its outcomes in patients of COVID-19 in a tertiary care hospital

Abstract

Introduction: The world has witnessed a surge of COVID-19 cases since the first case was reported in 2018 December, and despite the large number of cases seen across the world, there are still many gaps in the understanding of the course of the disease in different people. Several scoring systems and early warning signs have been developed to prognosticate the disease process. Clustering the patients into specific clinical phenotypes is one such strategy. In this study, we have clustered the COVID-19 patients using different variables into phenotypes and studied the outcome based on this classification. Aim and Objectives: To derive clinical phenotypes based on demographic, clinical, and laboratory data of COVID-19 patients and look at the efficiency of the phenotypes as a model for predicting course of disease. Materials and Methods: A retrospective cohort study on COVID-19 patients admitted to a tertiary care hospital in South India between July 2020 and October 2020 was conducted. Nine hundred and eighty-seven subjects fulfilling the inclusion criteria were enrolled. Results: Three clinical phenotypes were derived using 43 independent variables which included epidemiological, symptomatology, comorbidities, and laboratory values. Of the 987 patients studied, patients could be clustered into three phenotypes named A, B, and C. There were 379 patients in phenotype A, 313 in phenotype B, and 295 were in phenotype C. Males predominated in phenotypes C and B, which was 218 patients (73.9%) and 204 (65.2%), respectively. Mild disease was predominant in phenotype A (89.2%) patients, followed by10.3% of moderate disease and 0.5% of severe COVID disease. In phenotype B, 93.3% of patients had mild disease and the rest 21 (61.7%) had moderate disease. In phenotype C, 177 (60%) patients had severe COVID disease. Mortality was seen in phenotype C (23.1%). Conclusions: It can be inferred that among the phenotypes, the hyperinflammatory group was phenotype C. The independent predictive association of each variable such as age, male gender, and comorbidity is an important factor in determining the outcome but, because of the varied distribution of the multiple variables in each patient, it is not possible to consider each of these values independently and deduce the outcome, hence phenotypes which cluster the patients based on all these variables are associated with predictable outcomes The phenotypes thus can be implicated as a tool to aid in clinical management of COVID-19.

Keywords

• clinical phenotypes
• covid-19
• severe covid illness