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用于测量多发性硬化症疲劳的新方法:实时数字疲劳评分

Novel method for measurement of fatigue in multiple sclerosis: Real-Time Digital Fatigue Score.

作者信息

Kim Edward, Lovera Jesus, Schaben Laura, Melara J, Bourdette Dennis, Whitham Ruth

机构信息

Department of Neurology, School of Medicine, Oregon Health & Science University, Portland, OR 97239, USA.

出版信息

J Rehabil Res Dev. 2010;47(5):477-84. doi: 10.1682/jrrd.2009.09.0151.

Abstract

The study's objective was to develop a real-time measurement for fatigue and to evaluate whether it is an effective clinical trial outcome measure compared with the Fatigue Severity Scale (FSS) and the Modified Fatigue Impact Scale (MFIS). Forty-nine subjects with MS and an FSS >4 recorded Real-Time Digital Fatigue Scores (RDFSs) on a wrist-worn device four times a day over 3 weeks. Scores were scaled 0-10, with 10 representing the worst possible fatigue. FSS and MFIS were evaluated and compared with RDFSs. Mean RDFSs significantly correlated with FSS (r = 0.55, p < 0.001) and MFIS (r = 0.55, p < 0.001). RDFS captured circadian variations in fatigue, with scores increasing from mean 3.4 at 9 a.m., to 4.0 at 1 p.m., 4.5 at 5 p.m., and 5.0 at 9 p.m. When all scores over all days were included in a mixed-model analysis of circadian variation, the differences in RDFS between times were more significant than in an analysis that included only single scores of data isolated from the first day of monitoring. RDFS is a promising measure. RDFS significantly correlated with FSS and MFIS, captured real-time daily and circadian variations in fatigue, and provided multiple measurements of fatigue that provided statistical advantages over FSS and MFIS.

摘要

该研究的目的是开发一种疲劳的实时测量方法,并评估与疲劳严重程度量表(FSS)和改良疲劳影响量表(MFIS)相比,它是否是一种有效的临床试验结果测量方法。49名MS患者且FSS>4,在3周内每天4次在腕戴设备上记录实时数字疲劳评分(RDFS)。评分范围为0-10,10表示最严重的疲劳。对FSS和MFIS进行评估并与RDFS进行比较。平均RDFS与FSS(r = 0.55,p < 0.001)和MFIS(r = 0.55,p < 0.001)显著相关。RDFS捕捉到了疲劳的昼夜变化,评分从上午9点的平均3.4增加到下午1点的4.0、下午5点的4.5和晚上9点的5.0。当将所有天数的所有评分纳入昼夜变化的混合模型分析时,不同时间点RDFS的差异比仅纳入监测第一天孤立数据的单次评分分析更为显著。RDFS是一种有前景的测量方法。RDFS与FSS和MFIS显著相关,捕捉到了疲劳的每日实时和昼夜变化,并提供了多次疲劳测量,与FSS和MFIS相比具有统计学优势。

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