Alharbi Abdulrahman, Almogbel Faisal, Rabbani Unaib, Memish Ziad A
Family Medicine Academy, Qassim Health Cluster, Qassim, Saudi Arabia.
College of Medicine, Alfaisal University, Riyadh, Saudi Arabia.
J Epidemiol Glob Health. 2024 Dec;14(4):1602-1608. doi: 10.1007/s44197-024-00312-7. Epub 2024 Oct 14.
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.
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.
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.
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.
2019冠状病毒病(COVID-19)即便在感染消退后仍会出现各种表现。本研究旨在评估COVID-19后疲劳的患病率及其预测因素。
2021年7月至2022年2月,我们在沙特阿拉伯对经聚合酶链反应检测确诊的COVID-19病例进行了一项全国性横断面研究。我们通过电话访谈收集数据,内容涵盖社会人口统计学、合并症、体重指数、吸烟情况、疾病严重程度和COVID-19疫苗接种状况。我们使用疲劳严重程度量表评估疲劳,同时使用患者健康问卷-2评估抑郁。采用逻辑回归分析COVID-19后疲劳与抑郁之间的关系。
分析纳入了361名参与者,平均年龄为37±10.5岁,其中43%为女性。约10%的参与者有合并症,21%为当前吸烟者。近三分之二(68%)的参与者报告病情较轻。自我感觉疲劳的患病率为22.7%,而通过疲劳严重程度量表测得的疲劳患病率为14.4%。多变量逻辑回归模型显示,COVID-19严重程度和抑郁是COVID-19后疲劳的重要预测因素;调整后的比值比分别为1.87(95%置信区间:1.10至3.18)和14.3(95%置信区间:4.55至45.0)。
我们的研究结果表明,自我感觉疲劳的患病率高于通过疲劳严重程度量表测得的患病率,这凸显了在COVID-19患者中使用有效的疲劳评估工具以确保适当管理的重要性。COVID-19后疲劳与抑郁之间的显著关联凸显了对COVID-19患者进行心理评估以提高其感染后生活质量的必要性。