Phenotypes and Subphenotypes of Patients With COVID-19

Abstract

BACKGROUND: Since COVID-19 was identified, its clinical and biological heterogeneity has been recognized. Identifying COVID-19 phenotypes might help guide basic, clinical, and translational research efforts.RESEARCH QUESTION: Does the clinical spectrum of patients with COVID-19 contain distinct phenotypes and subphenotypes? STUDY DESIGN AND METHODS: We included adult patients ($ 18 years) positive for laboratory-confirmed SARS-CoV-2 infection from a prospective COVID-19 registry database in the Cleveland Clinic Health System in Ohio and Florida. The patients were split into training and testing sets. Using latent class analysis (LCA), we first identified phenotypic clusters of patients with COVID-19 based on demographics, comorbidities, and presenting symptoms. We then identified subphenotypes of hospitalized patients with additional blood biomarker data measured on hospital admission. The associations of phenotypes/subphenotypes and clinical outcomes were investigated. Multivariable prediction models were established to predict assignment to the LCA-defined phenotypes and subphenotypes and then evaluated on an independent testing set. RESULTS:We analyzed data for 20,572 patients. Seven phenotypes were identified on the basis of different profiles of presenting COVID-19 symptoms and existing comorbidities, including the following groups: young, no symptoms; young, symptoms; middle-aged, no symptoms; middle-aged, symptoms; middle-aged, comorbidities; old, no symptoms; and old, symptoms. The rates of inpatient hospitalization for the phenotypes were significantly different (P < .001). Five subphenotypes were identified for the subgroup of hospitalized patients, including the following subgroups: young, elevated WBC and platelet counts; middle-aged, lymphopenic with elevated C-reactive protein; middle-aged, hyperinflammatory; old, leukopenic with comorbidities; and old, hyperinflammatory with kidney dysfunction. The hospital mortality and the times from hospitalization to ICU transfer or death were significantly different (P < .001). The models for predicting the LCA-defined phenotypes and subphenotypes showed high discrimination (concordance index, 0.92 and 0.91).INTERPRETATION: Hypothesis-free LCA-defined phenotypes and subphenotypes of patients with COVID-19 can be identified. These may help clinical investigators conduct stratified analyses in clinical trials and assist basic science researchers in characterizing the pathobiology of the spectrum of COVID-19 presentations.

Sepsis in severe COVID-19 is rarely septic shock: a retrospective single-centre cohort study

“…Sepsis and ARDS represent umbrella syndromes containing multiple subphenotypes with relatively distinct clinical or biological signatures and differing outcomes 2 , 3 . Using latent class analysis, similar findings have also been applied to large population cohorts with COVID-19 4 , 5 . Currently, only one small study of 18 patients hospitalised with COVID-19 has focused on hyperlactataemia but did not report associations with the degree of hypoxaemia or vasopressor use 6 .…”

Prognostic implications of comorbidity patterns in critically ill COVID-19 patients: A multicenter, observational study

“…To date, studies aiming to derive phenotypes of hospitalized COVID-19 patients have been based on previous comorbidities, 6 , 7 , 8 , 15 COVID-19 signs and symptoms, 8 , 9 , 11 , 12 , 16 , 17 variables from blood tests, 8 , 11 , 13 , 14 , 15 , 16 , 17 and chest radiologic features 8 , 10 in an attempt to identify groups of patients with distinct risks of ICU admission, need for mechanical ventilation, and risk of experiencing clinical complications or death. Among those focused on critically ill patients, 11 , 12 , 13 , 14 , 15 , 16 , 17 most studies identified two or three phenotypes corresponding to different degrees of severity with a role of intense inflammation when defining the most severe phenotype.…”

“…To date, several studies have aimed to identify phenotypes among hospitalized COVID-19 patients based on sociodemographic variables, baseline comorbidities, signs and symptoms during the acute phase, and the results of complementary tests, such as biological parameters in the blood test 6 , 7 , 8 , 9 or chest radiological features. 8 , 10 Most interestingly, several studies have focused on patients admitted to the ICU that are those at a higher risk of experiencing severe complications and sequelae.…”

A Practical Guide to Writing Quantitative and Qualitative Research Questions and Hypotheses in Scholarly Articles

“… RESEARCH QUESTION: Does the clinical spectrum of patients with COVID-19 contain distinct phenotypes and subphenotypes? ” 19 …”