Using measures of corticospinal excitability to map symptom severity in multiple sclerosis

Wiseman, Hailey (2020) Using measures of corticospinal excitability to map symptom severity in multiple sclerosis. Masters thesis, Memorial University of Newfoundland.

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Abstract

Background: Transcranial magnetic stimulation (TMS) is a tool used to measure corticospinal excitability. To evaluate the usefulness of TMS as a biomarker in multiple sclerosis (MS), the first step is to examine how well variables derived using TMS align with clinical symptoms of MS. Methods: Participants with MS (n=38) were assigned to motor, cognitive, sensory, or asymptomatic clinical group based on their Expanded Disability Status Scale (EDSS) assessment. Following recording of demographic information, subjective health and scoring of walking and cognition, TMS measures were collected from each brain hemisphere. We first examined whether TMS parameters (resting motor threshold (RMT), active motor threshold (AMT), and cortical silent period (CSP)) would differ among clinical groups. Next, we examined whether TMS parameters predicted severity of symptoms. Results: CSP and AMT in the hemisphere corresponding to the weaker hand predicted measures of symptom severity among people with MS in the motor and cognitive profile groups. Longer CSP was the strongest predictor of slower walking speed (F(1,17)=22.82, p<0.001). Higher AMT was the strongest predictor of cognitive impairment using the Montreal Cognitive Assessment (F(1,17)==25.29, p=0.001) and perceived physical impact of MS using the Multiple Sclerosis Impact Scale-29 (F(1,17)=30.63, p<0.001). Conclusions: CSP and AMT in the hemisphere corresponding to the weaker hand predicted severity of symptoms among people with MS in the motor and cognitive groups. In these cases, TMS variables provided greater predictive value than the traditional EDSS, supporting the use of TMS outcomes as biomarkers in MS.

Item Type: Thesis (Masters)
URI: http://research.library.mun.ca/id/eprint/14384
Item ID: 14384
Additional Information: Includes bibliographical references (pages 82-108).
Keywords: TMS, Biomarker, CSP, AMT
Department(s): Medicine, Faculty of > Biomedical Sciences
Date: May 2020
Date Type: Submission

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