Ǫuantitative Gait Categorization in Parkinson’s Disease with and without Freezing of Gait
Ǫuantitative Gait Categorization in Parkinson’s Disease with and without Freezing of Gait
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Original abstract
Background Freezing of gait (FOG) is a disabling and often underrecognized feature of Parkinson’s disease (PD). Objective gait analysis may improve characterization of this motor symptom. Objective To compare quantitative 3D gait parameters in PD with FOG (PD F ) and PD without FOG (PD NF ) in a routine clinical cohort. Methods: We retrospectively analyzed a sequential sample of 180 patients with PD referred for motion analysis between 2020 and 2024. All patients underwent 3D motion capture in the off-medication state. Eighteen gait outcomes spanning pace, rhythm, postural control, variability, and asymmetry domains were derived from steady-state walking tasks. FOG status was determined using physician documentation and Movement Disorder Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) items. Group differences between PD F (n=99) and PD NF (n=81) were evaluated using independent samples t-tests, with outcomes adjusted for disease duration and corrected for multiple comparisons. A secondary analysis among PD F compared those in Hoehn and Yahr (HCY) stage ≥III to those in HCY ≤II. Results: PD F had longer disease duration, higher OFF MDS-UPDRS III scores, and higher Hoehn and Yahr stage than PD NF but were similar in age and sex. After adjusting for disease duration and multiplicity, PD F demonstrated reduced step length, stride length, and forward velocity, and greater cadence variability, while most postural control, and asymmetry measures were comparable between groups. Among PD F , advanced HCY stage was associated with impaired pace and rhythm, similar to previous reports among PD in general. Conclusion: In this large, sequential, clinically referred cohort, FOG was associated with more advanced PD and specific impairments in pace and gait variability. These findings support comprehensive 3D gait analysis as an objective tool to better delineate FOG-related gait abnormalities and identify features that may predict FOG, informing targeted interventions.