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Review
. 2006 Apr;162(4):427-36.
doi: 10.1016/s0035-3787(06)75033-0.

[Manual and quantitative muscle testing in neuromuscular disorders. How to assess the consistency of strength measurements in clinical trials?]

[Article in French]
Affiliations
Review

[Manual and quantitative muscle testing in neuromuscular disorders. How to assess the consistency of strength measurements in clinical trials?]

[Article in French]
J Y Hogrel et al. Rev Neurol (Paris). 2006 Apr.

Abstract

Evaluation of functional capacities of patients suffering of neuromuscular disorders, particularly muscle strength, is a critical issue for their diagnosis and follow-up. Within the framework of the natural history of any given disease, such an evaluation may improve the clinician's knowledge of the pathophysiological processes involved, and may help to anticipate and sometimes prevent deleterious consequences as the disease progresses. It is also helpful for identifying correlation between the severity of organic damage and the functional impact of the disease. The measurement of functional capacities must be done with accuracy, sensitivity and reliability, essentially when used as an outcome measure for therapeutic trials. Several evaluation tools for measuring muscle strength are available. They are usually classified into two groups: manual muscle testing (MMT) methods and quantified muscle testing (QMT) methods. In this article, we present the principles of strength measurements, and the different tools and materials that are commonly used in clinical settings. Their limitations and drawbacks are illustrated through several examples. Although QMT is theoretically and potentially more consistent than MMT to precisely follow the muscle capacities of the patients, precise and robust procedures must be elaborated and validated for each tested muscle function. Strength measurements must be performed by trained and experimented clinical evaluators. This issue is critical in the follow up of multicentric therapeutic trials. Inter-rater reliability must be assessed to guarantee the statistical power of the trial.

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