Unraveling upper extremity performance in DMD: a biophysical model | DuchenneXchange

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Abstracts & Posters

Unraveling upper extremity performance in DMD: a biophysical model

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source: Neuromuscular Disorders

year: 2017

authors: M. Janssen, J. Harlaar, H. Koopman, I. de Groot


Upper extremity (UE) activity scales are currently used as the golden standard for defining UE function in non-ambulant Duchenne muscular dystrophy (DMD) patients. These scales, however, are not able to explain the biophysical working mechanism behind changes in UE function. Therefore, we aimed to identify critical physiological outcome variables underlying reduced UE task performance in DMD. These critical variables were used to construct an explanatory biophysical model of the UE working mechanism in DMD. The most critical physiologic outcome variables related to UE task performance (Brooke scale and Performance of Upper Limb (PUL) scale) were maximal active joint angle, followed by maximal muscle torque, maximal muscle activity, echogenicity (fatty infiltration) and maximal passive range of motion. These variables explained more than 90% of the variability in UE task performance. Based on these critical variables a biophysical model was constructed. In this model we considered UE task performance to be mainly dependent on the ability to move your arms actively, which is influenced by both passive range of motion and the available joint torque. The available joint torque is dependent on muscle capacity, and should be sufficient to lift the weight of the arm against gravity and to overcome passive joint torque (stiffness). Muscle capacity is influenced by both the ability to activate the muscle and the muscle force that is generated at the joint level. This model allows us to understand the underlying cause of UE limitations. Based on this knowledge one can select appropriate interventions to improve UE function, such as arm supports to improve the reachable workspace, contracture prevention, or medication to improve muscle strength. In addition, the model could form the basis for the development of new composite outcome measures for clinical trials.

organisation: Radboudumc, Netherlands; Free University medical centre, Netherlands; University of Twente, Netherlands

DOI: 10.1016/j.nmd.2017.06.500

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