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提高 EQ-5D-5L 在捕捉新冠后患者最常见症状方面的灵敏度:一项关注疲劳、记忆/注意力问题和呼吸困难维度的探索性横断面研究。

Enhancing EQ-5D-5L Sensitivity in Capturing the Most Common Symptoms in Post-COVID-19 Patients: An Exploratory Cross-Sectional Study with a Focus on Fatigue, Memory/Concentration Problems and Dyspnea Dimensions.

机构信息

Department of Medical Sciences, Section of Infectious Diseases, Uppsala University, 751 85 Uppsala, Sweden.

Department of Statistics, Uppsala University, 751 20 Uppsala, Sweden.

出版信息

Int J Environ Res Public Health. 2024 May 3;21(5):591. doi: 10.3390/ijerph21050591.

Abstract

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.

摘要

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。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3314/11121728/8ee5432a91fa/ijerph-21-00591-g001.jpg

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