Health-Related Quality of Life for Patients with Post-Acute COVID-19 Syndrome: Identification of Symptom Clusters and Predictors of Long-Term Outcomes.

Abstract

Following COVID-19 infection, as many as a third of patients have long-term symptoms, known as post-acute sequelae (PASC). The mechanisms contributing to PASC remain largely unknown and, due to the heterogeneity of symptoms, treating PASC provides unique challenges. Our study sought to (1) identify clinical symptom profiles based on PROMIS Global Health (GH) items, (2) evaluate demographic and clinical differences across profiles, and (3) identify predictors of change in health-related quality of life (HRQL) over time. This was an observational cohort study of patients with PASC who completed PROMIS-GH between 2/11/21 and 12/3/21 as part of routine care, with data extracted from the electronic health record. There were 1407 adult patients (mean age 49.6 ± 13.7, 73% female, 81% White race) with PASC seen in the recovery clinic between 2/11/21 and 12/3/21, with 1129 (80.2%) completing PROMIS-GH as routine care. HRQL was measured with PROMIS-GH at initial visit and after 12months. Latent profile analysis identified symptom classes based on five PROMIS-GH items (mental health, ability to carry out physical activities, pain, fatigue, and emotional problems). Four latent profiles were identified: (1) "Poor HRQL" (n = 346), (2) "Mixed HRQL: good mental/poor physical" (n = 232), (3) "Mixed HRQL: poor mental/good physical" (n = 324), and (4) "Good HRQL" (n = 227). Demographics and comorbidities varied significantly across profile with patients with more severe COVID-19 infection more likely to be in profiles 1 and 2. Overall, patients improved 2T-score points on PROMIS-GH after 12months, with differences by profile. Predictors of improved HRQL included profile, lower body mass index, and fewer COVID symptoms. Patients with PASC have distinct HRQL symptom profiles which were able to differentiate across COVID-19 severity and symptoms. Improvement over 12months differed by profile. These profiles may be used to better understand the mechanisms behind PASC. Future research should evaluate their ability to guide treatment decisions to improve HRQL.