Abstract
BACKGROUND AND OBJECTIVES: Coronavirus disease 2019 (COVID-19) is associated with various manifestations even after infection resolution. This study aimed to assess the prevalence of post-COVID-19 fatigue and its predictors. METHODS: We conducted a nationwide cross-sectional study among Polymerase Chain Reaction test confirmed COVID-19 cases in Saudi Arabia from July 2021 to February 2022. We collected data through telephonic interviews covering socio-demographics, comorbidities, body mass index, smoking, illness severity, and COVID-19 vaccination status. We assessed fatigue using Fatigue Severity Scale while depression was assessed using Patient Health Questionnaire-2. Logistic regression was employed to analyze the relationship between post-COVID-19 fatigue and depression. RESULTS: The analysis included 361 participants with a mean age of 37 ± 10.5 years, among whom 43% were female. Approximately 10% had comorbidities, and 21% were current smokers. Nearly two-thirds (68%) of the participants reported mild illness. The prevalence of perceived fatigue was 22.7%, while fatigue measured by the Fatigue Severity Scale was 14.4%. The multivariable logistic regression model revealed that COVID-19 severity and depression were significant predictors of post-COVID-19 fatigue; adjusted odds ratio 1.87 (95% CI: 1.10 to 3.18) and 14.3 (95% CI: 4.55 to 45.0), respectively. CONCLUSION: Our findings suggest a higher prevalence of perceived fatigue compared to that measured by the Fatigue Severity Scale, underscoring the importance of using a valid assessment tool for fatigue among COVID-19 patients to ensure proper management. The significant association between post-COVID-19 fatigue and depression highlights the need for psychological assessment of COVID-19 patients to enhance their post-infection quality of life.