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. 2019 Aug 23;16(1):105.
doi: 10.1186/s12984-019-0573-1.

Three distinct physical behavior types in fatigued patients with multiple sclerosis

Collaborators, Affiliations

Three distinct physical behavior types in fatigued patients with multiple sclerosis

H E M Braakhuis et al. J Neuroeng Rehabil. .

Abstract

Background: Multiple sclerosis often leads to fatigue and changes in physical behavior (PB). Changes in PB are often assumed as a consequence of fatigue, but effects of interventions that aim to reduce fatigue by improving PB are not sufficient. Since the heterogeneous nature of MS related symptoms, levels of PB of fatigued patients at the start of interventions might vary substantially. Better understanding of the variability by identification of PB subtypes in fatigued patients may help to develop more effective personalized rehabilitation programs in the future. This study aimed to identify PB subtypes in fatigued patients with multiple sclerosis based on multidimensional PB outcome measures.

Methods: Baseline accelerometer (Actigraph) data, demographics and clinical characteristics of the TREFAMS-ACE participants (n = 212) were used for secondary analysis. All patients were ambulatory and diagnosed with severe fatigue based on a score of ≥35 on the fatigue subscale of the Checklist Individual Strength (CIS20r). Fifteen PB measures were used derived from 7 day measurements with an accelerometer. Principal component analysis was performed to define key outcome measures for PB and two-step cluster analysis was used to identify PB types.

Results: Analysis revealed five key outcome measures: percentage sedentary behavior, total time in prolonged moderate-to-vigorous physical activity, number of sedentary bouts, and two types of change scores between day parts (morning, afternoon and evening). Based on these outcomes three valid PB clusters were derived.

Conclusions: Patients with severe MS-related fatigue show three distinct and homogeneous PB subtypes. These PB subtypes, based on a unique set of PB outcome measures, may offer an opportunity to design more individually-tailored interventions in rehabilitation.

Trial registration: Clinical trial registration no ISRCTN 82353628 , ISRCTN 69520623 and ISRCTN 58583714 .

Keywords: Cluster analysis; Multiple sclerosis; Physical behavior; Principal component analysis.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Plot of Z-scores of five key outcome measures of PB per cluster
Fig. 2
Fig. 2
Percentage of sedentary behavior of clusters in the morning, afternoon and evening

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