4.5 Article

Motor blocks during bilateral stepping in Parkinson's disease and effects of dopaminergic medication

Journal

PARKINSONISM & RELATED DISORDERS
Volume 85, Issue -, Pages 1-4

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.parkreldis.2021.02.015

Keywords

Freezing of gait; FOG score; Motor block; Virtual reality

Funding

  1. Canadian Institutes of Health Research (CIHR) Foundation Grant [FDN 154292]
  2. Natural Science and Engineering Research Council of Canada [RGPIN202004176]
  3. Queen Elizabeth II Graduate Scholarship in Science Technology
  4. CIHR Doctoral Award [GSD 146290]
  5. Dystonia Medical Research Foundation Canada
  6. CIHR [PDF 338973]

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The study found that lower limb motor blocks during bilateral stepping in a virtual environment can predict the presence and severity of freezing of gait in patients with Parkinson's disease. This method can help detect FOG symptoms in patients who are unable or unsafe to walk.
Introduction: Freezing of gait (FOG) is a complex symptom in Parkinson's disease (PD) that manifests during walking as limited forward progression despite the intention to walk. It is unclear if lower limb motor blocks (LLMB) that occur independently from FOG are related to overground FOG and the effects of dopaminergic medications. Methods: Nineteen patients with PD were tested on two separate days in the dopaminergic medication on and off states. The patients completed a series of freezing-provoking tasks while videotaped. Raters assessed videos for FOG presence using Movement Disorders Society Unified Parkinson's Disease Rating Scale item 3.11 score greater than or equal to 1 and FOG severity using the standardized FOG score. Whilst seated in a virtual environment, patients and 20 healthy controls stepped in right-left sequence on foot pedals. Frequency and percent time in LLMB were assessed for accurate classification of FOG presence and correlation to the FOG score. Results: Frequency and percent time spent in LLMB predicted the presence of FOG in both medication states. Percent time spent in LLMB correlated with FOG severity in both medication states. LLMB frequency predicted FOG severity in the off state only. Conclusions: LLMB during bilateral stepping in a virtual environment predicted the presence and severity of FOG in PD in both on and off medication states. These findings support the use of this non-walking paradigm to detect and assess FOG in PD patients unable or unsafe to walk.

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