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Composite measures of motor performance and self-efficacy are better determinants of postural instability and gait difficulties than individual clinical measures in Parkinson's disease. | LitMetric
Department of Radiology, University of Michigan, Ann Arbor, MI, USA; Department of Neurology, University of Michigan, Ann Arbor, MI, USA; Functional Neuroimaging, Cognitive, and Mobility Laboratory, Departments of Radiology and Neurology, University of Michigan, Ann Arbor, MI, USA; Morris K. Udall Center of Excellence for Parkinson's Disease Research, University of Michigan, Ann Arbor, MI, USA; Parkinson's Foundation Research Center of Excellence, University of Michigan, Ann Arbor, MI, USA; Neurology Service and GRECC, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA.
Published: February 2023
AI Article Synopsis
Article Abstract
Background: Postural instability and gait difficulties (PIGD) are a significant cause of disability and loss of quality of life (QoL) in Parkinson's Disease. Most research on clinical predictors of PIGD measures have focused on individual clinical often motor performance variables, However, PIGD motor features often result in fear of falling (FoF) lowering a patient's mobility self-efficacy. The purpose of this study was to assess composite measures of motor and self-efficacy determinants PIGD motor features in PD and compare these to analysis of individual clinical metrics.
Methods: 75 PD participants underwent detailed motor and non-motor test batteries. Principal component analysis (PCA) was used to identify clusters of covarying correlates of slow walking, imbalance, falls, freezing of gait, FoG and compare these to traditional univariate analyses.
Results: A single PCA-derived composite measure of motor performance and self-efficacy of mobility was the most robust determinant of all PIGD motor features except for falls. In contrast, analysis of the individual clinical variables showed more limited and diverging findings, including evidence of better cognitive performance but more severe motor parkinsonian ratings in the fall group.
Conclusion: There are robust associations between composite measures of motor performance and self-efficacy of mobility and all PIGD motor features except for falls. Univariate analysis of individual clinical measures showed limited correlates of PIGD motor features. Patient's own perception of motor performance, FoF, and QoL deserve more attention as PIGD therapeutic targets in PD.
