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Personalised profiling to identify clinically relevant changes in tremor due to multiple sclerosis

Western, David G; Neild, Simon A; Jones, Rosemary; Davies-Smith, Angela

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Authors

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David Western David.Western@uwe.ac.uk
Wallscourt Fellow in Health Technology

Simon A Neild

Rosemary Jones

Angela Davies-Smith



Abstract

Background: There is growing interest in sensor-based assessment of upper limb tremor in multiple sclerosis and other movement disorders. However, previously such assessments have not been found to offer any improvement over conventional clinical observation in identifying clinically relevant changes in an individual's tremor symptoms, due to poor test-retest repeatability.

Method: We hypothesised that this barrier could be overcome by constructing a tremor change metric that is customised to each individual's tremor characteristics, such that random variability can be distinguished from clinically relevant changes in symptoms. In a cohort of 24 people with tremor due to multiple sclerosis, the newly proposed metrics were compared against conventional clinical and sensor-based metrics. Each metric was evaluated based on Spearman rank correlation with two reference metrics extracted from the Fahn-Tolosa-Marin Tremor Rating Scale: a task-based measure of functional disability (FTMTRS B) and the subject's self-assessment of the impact of tremor on their activities of daily living (FTMTRS C).

Results: Unlike the conventional sensor-based and clinical metrics, the newly proposed ’change in scale’ metrics presented statistically significant correlations with changes in self-assessed impact of tremor (max R2>0.5,p< 0.05 after correction for false discovery rate control). They also outperformed all other metrics in terms of correlations with changes in task-based functional performance (R2=0.25 vs. R2=0.15 for conventional clinical observation, both p< 0.05).

Conclusions: The proposed metrics achieve an elusive goal of sensor-based tremor assessment: improving on conventional visual observation in terms of sensitivity to change. Further refinement and evaluation of the proposed techniques is required, but our core findings imply that the main barrier to translational impact for this application can be overcome. Sensor-based tremor assessments may improve personalised treatment selection and the efficiency of clinical trials for new treatments by enabling greater standardisation and sensitivity to clinically relevant changes in symptoms.

Citation

Western, D. G., Neild, S. A., Jones, R., & Davies-Smith, A. (2019). Personalised profiling to identify clinically relevant changes in tremor due to multiple sclerosis. BMC Medical Informatics and Decision Making, 19, Article 162. https://doi.org/10.1186/s12911-019-0881-1

Journal Article Type Article
Acceptance Date Jul 28, 2019
Online Publication Date Aug 16, 2019
Publication Date Aug 16, 2019
Deposit Date Jul 30, 2019
Publicly Available Date Oct 22, 2019
Journal BMC Medical Informatics and Decision Making
Electronic ISSN 1472-6947
Publisher BioMed Central
Peer Reviewed Peer Reviewed
Volume 19
Article Number 162
DOI https://doi.org/10.1186/s12911-019-0881-1
Public URL https://uwe-repository.worktribe.com/output/1804139

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Copyright Statement
© The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.




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