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.
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