Quality of the tools used to assess aerobic capacity in people with multiple sclerosis
Authors:
Valet, M., Lejeune, T., Hakizimana, J. C., and Stoquart, G.
Abstract:
INTRODUCTION: Assessments of physical fitness, including exercise tolerance functions, are valuable in persons with multiple sclerosis (MS). Many tools with widely varying advantages and disadvantages have been used to assess physical fitness in research and clinical practice. To date, there are no recommendations regarding the best tools to use for this purpose in persons with MS. This study aims to systematically review the psychometric properties of the tools used to assess exercise tolerance functions in persons with MS, and to propose recommendations regarding the best test to use.
EVIDENCE ACQUISITION: The literature was searched (PubMed, SPORTdiscus, PEDro, MEDLINE, Embase via Scopus, CINAHL, and PsycInfo) to identify the tools most frequently used to assess exercise tolerance functions. These tools were systematically analyzed.
EVIDENCE SYNTHESIS: Forty-eight articles were selected. Six tools or categories of tools concerning exercise tolerance functions were identified. Whole-body exercise tests combined with gas exchange analysis had the best psychometric properties (e.g., validity, reliability) for assessing aerobic capacity in pwMS with mild to moderate disability (Expanded Disability Status Scale [EDSS] =6.5). Although sometimes used for this purpose, walk tests seemed to assess walking performance rather than exercise tolerance functions. The psychometric properties of other tests had scarcely been studied.
CONCLUSIONS: The tools vary widely in quality. Whole-body exercise testing combined with gas exchange analysis has the best psychometric properties of the reviewed tools. If gas exchange analysis is feasible, whole-body exercise tests combined with gas exchange analysis, with maximal exercise effort for pwMS with EDSS =4 and submaximal exercise effort for pwMS with EDSS >/=4.5, should be recommended to assess exercise tolerance, both in research and in clinical practice. A selection algorithm is proposed.