Department of Medical Sciences, Section of Infectious Diseases, Uppsala University, 751 85 Uppsala, Sweden.
Department of Statistics, Uppsala University, 751 20 Uppsala, Sweden.
Int J Environ Res Public Health. 2024 May 3;21(5):591. doi: 10.3390/ijerph21050591.
This study aimed to determine whether the EQ-5D-5L tool captures the most common persistent symptoms, such as fatigue, memory/concentration problems and dyspnea, in patients with post-COVID-19 conditions while also investigating if adding these symptoms improves the explained variance of the health-related quality of life (HRQoL). In this exploratory cross-sectional study, two cohorts of Swedish patients (n = 177) with a history of COVID-19 infection answered a questionnaire covering sociodemographic characteristics and clinical factors, and their HRQoL was assessed using EQ-5D-5L with the Visual Analogue Scale (EQ-VAS). Spearman rank correlation and multiple regression analyses were employed to investigate the extent to which the most common persistent symptoms, such as fatigue, memory/concentration problems and dyspnea, were explained by the EQ-5D-5L. The explanatory power of EQ-5D-5L for EQ-VAS was also analyzed, both with and without including symptom(s). We found that the EQ-5D-5L dimensions partly captured fatigue and memory/concentration problems but performed poorly in regard to capturing dyspnea. Specifically, the EQ-5D-5L explained 55% of the variance in memory/concentration problems, 47% in regard to fatigue and only 14% in regard to dyspnea. Adding fatigue to the EQ-5D-5L increased the explained variance of the EQ-VAS by 5.7%, while adding memory/concentration problems and dyspnea had a comparatively smaller impact on the explained variance. Our study highlights the EQ-5D-5L's strength in capturing fatigue and memory/concentration problems in post-COVID-19 patients. However, it also underscores the challenges in assessing dyspnea in this group. Fatigue emerged as a notably influential symptom, significantly enhancing the EQ-5D-5L's predictive ability for these patients' EQ-VAS scores.
本研究旨在确定 EQ-5D-5L 工具是否能捕捉到患有新冠后(post-COVID-19)病症患者最常见的持续性症状,如疲劳、记忆/注意力问题和呼吸困难,同时也研究了是否增加这些症状能提高健康相关生活质量(HRQoL)的解释方差。在这项探索性的横断面研究中,两个瑞典患者队列(n=177)回答了一份问卷,涵盖了社会人口统计学特征和临床因素,并用 EQ-5D-5L 与视觉模拟量表(EQ-VAS)评估他们的 HRQoL。采用 Spearman 秩相关和多元回归分析来研究最常见的持续性症状(如疲劳、记忆/注意力问题和呼吸困难)在多大程度上能被 EQ-5D-5L 解释。还分析了 EQ-5D-5L 对 EQ-VAS 的解释能力,包括是否包含症状。我们发现,EQ-5D-5L 维度部分捕捉到了疲劳和记忆/注意力问题,但在捕捉呼吸困难方面表现不佳。具体来说,EQ-5D-5L 对记忆/注意力问题的方差解释了 55%,对疲劳的方差解释了 47%,对呼吸困难的方差解释了仅 14%。将疲劳添加到 EQ-5D-5L 中,增加了 EQ-VAS 解释方差的 5.7%,而添加记忆/注意力问题和呼吸困难对解释方差的影响较小。我们的研究强调了 EQ-5D-5L 在捕捉新冠后患者的疲劳和记忆/注意力问题方面的优势。然而,它也突出了评估该组呼吸困难的挑战。疲劳是一个显著的影响因素,显著提高了 EQ-5D-5L 对这些患者 EQ-VAS 评分的预测能力。