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Next move in movement disorders (NEMO): the best clinical tasks for the visibility of essential tremor, dystonia, cortical myoclonus and myoclonus-dystonia. | LitMetric

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Article Abstract

Introduction: The Next Move in Movement Disorders (NEMO) is a cross-sectional study aimed to propose innovative strategies for the classification and management of Hyperkinetic Movement Disorders (HMDs). The clinical visibility of essential tremor, dystonia, cortical myoclonus and myoclonus-dystonia through standardized video procedure is assessed here, with the aim to evaluate the best tasks for eliciting the clinical signs of each specific phenotype.

Methods: Eighty-four patients with HMDs were enrolled: 19 affected by essential tremor, 21 by dystonia, 18 by myoclonus and 26 by myoclonus-dystonia. The video protocol included 21 tasks based on the most common clinical rating scales for HMDs. A total of 1735 videos were rated by three independent movement disorders specialists, assessing the degree of visibility of each phenotype on a five-point rating scale.

Results: Near perfect interrater agreement regarding the visibility of each disorder was reached for essential tremor (ICC 0.87), dystonia (ICC 0.85) and myoclonus-dystonia (ICC 0.81) phenotypes, while substantial agreement was observed for myoclonus (ICC 0.75). The best tasks to increase the visibility for all included phenotypes were 1) pronated outstretched arms and hands with palms facing down, 2) the same task during the serial seven subtraction task, and 3) pronated outstretched arms and extended wrists with palms forward.

Conclusions: Our findings using a standardized video procedure demonstrate that three clinical tasks are satisfactory to elicit all the phenotypes. The accurate choice of specific clinical tasks could help clinicians and researchers to reduce the number of tasks needed in the classification of the different HMD phenotypes and to develop a computer-aided classification tool for HMDs including clinical data, video settings and neurophysiological parameters.

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http://dx.doi.org/10.1016/j.parkreldis.2025.107963DOI Listing

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