Access Type

Open Access Dissertation

Date of Award

January 2022

Degree Type

Dissertation

Degree Name

Ph.D.

Department

Psychiatry and Behavioral Neurosciences

First Advisor

Nora E. Fritz

Abstract

Multiple sclerosis (MS) is a progressive, neurologic disease of the central nervous system that causes debilitating motor, sensory and cognitive impairments. As a result, persons with MS are at an increased risk for falls and falls represent a serious public health concern for the MS population. The current clinical measures used to assess fall risk in MS patients lack sensitivity and predictive validity for falls and are limited in their ability to capture to multiple functional domains (i.e., motor, sensory, cognitive and pathological domains) that are impaired by MS. Backward walking sensitively detects falls in the elderly and other neurologic diseases. However, backward walking and falls has never been explored in the MS population and the underlying reasons as to why backward walking sensitively detects falls remains unknown. Identification of a quick, simply and clinically feasible fall risk measures related to multiple functions impacted by MS and related to fall risk, which can detect falls before they occur is critical for fall prevention and timely and targeted intervention. Therefore, this dissertation examines backward walking as a novel marker of fall risk and its cognitive and pathological underpinnings to support its clinical utility. Our results indicate that backward walking is a sensitive marker of fall risk in the MS population, regardless of co-morbid cognitive deficits, and that examining underlying brain regions likely to contribute to backward walking performance including the corticospinal tract, corpus callosum and cerebellum, with neuroimaging tools sensitive to myelin (i.e., Myelin Water Imaging) demonstrate potential to identify underlying mechanisms of backward walking performance in the MS population. This work is the critical first step in establishing backward walking as a sensitive marker of fall risk for the MS population and leads the way to more personalized fall prevention therapies and interventions to improve clinical outcomes and decrease fall rates in the MS population.

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Neurosciences Commons

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