Abstract
BackgroundImpaired gait plays an important role for quality of life in patients with Huntington’s disease (HD). Measuring objective gait parameters in HD might provide an unbiased assessment of motor deficits in order to determine potential beneficial effects of future treatments.ObjectiveTo objectively identify characteristic features of gait in HD patients using sensor-based gait analysis. Particularly, gait parameters were correlated to the Unified Huntington’s Disease Rating Scale, total motor score (TMS), and total functional capacity (TFC).MethodsPatients with manifest HD at two German sites (n = 43) were included and clinically assessed during their annual ENROLL-HD visit. In addition, patients with HD and a cohort of age- and gender-matched controls performed a defined gait test (4 × 10 m walk). Gait patterns were recorded by inertial sensors attached to both shoes. Machine learning algorithms were applied to calculate spatio-temporal gait parameters and gait variability expressed as coefficient of variance (CV).ResultsStride length (− 15%) and gait velocity (− 19%) were reduced, while stride (+ 7%) and stance time (+ 2%) were increased in patients with HD. However, parameters reflecting gait variability were substantially altered in HD patients (+ 17% stride length CV up to + 41% stride time CV with largest effect size) and showed strong correlations to TMS and TFC (0.416 ≤ rSp ≤ 0.690). Objective gait variability parameters correlated with disease stage based upon TFC.ConclusionsSensor-based gait variability parameters were identified as clinically most relevant digital biomarker for gait impairment in HD. Altered gait variability represents characteristic irregularity of gait in HD and reflects disease severity.
Highlights
Huntington’s disease (HD) is an autosomal-dominant, neurodegenerative disease characterized by the triad of motor deficits, cognitive decline, and neurobehavioral symptoms [1]
Group differences for parameters representing irregularity of gait were more pronounced in HD in comparison to controls: stride time coefficient of variance (CV) (HD: 4.46 ± 1.55%, controls: 2.80 ± 0.81%, Δ = + 37%, p < 0.000), swing time CV (HD: 5.59 ± 2.51%, controls: 3.28 ± 1.43%, Δ = + 41%, p < 0.000), stance time CV (HD: 3.06 ± 1.26%, controls: 1.91 ± 0.91%, Δ = + 38%, p < 0.000), stride length CV (HD: 7.96 ± 2.13%, controls: 6.59 ± 3.08%, Δ = + 17%, p = 0.001), and gait velocity CV (HD: 8.79 ± 2.43%, controls: 7.39 ± 2.84%, Δ = + 16%, p = 0.001) (Fig. 2)
Our data demonstrate that sensor-based gait variability parameters were identified as the clinically most relevant digital biomarker for gait impairment in HD
Summary
Huntington’s disease (HD) is an autosomal-dominant, neurodegenerative disease characterized by the triad of motor deficits, cognitive decline, and neurobehavioral symptoms [1]. Objective gait parameters may provide metric, granular information complementing the Unified Huntington’s disease Rating Scale total motor score (TMS), and total functional capacity (TFC) as established instruments in daily clinical routine evaluating motor impairment and functionality in HD [5]. Measuring objective gait parameters in HD might provide an unbiased assessment of motor deficits in order to determine potential beneficial effects of future treatments. Gait parameters were correlated to the Unified Huntington’s Disease Rating Scale, total motor score (TMS), and total functional capacity (TFC). Parameters reflecting gait variability were substantially altered in HD patients (+ 17% stride length CV up to + 41% stride time CV with largest effect size) and showed strong correlations to TMS and TFC (0.416 ≤ rSp ≤ 0.690). Altered gait variability represents characteristic irregularity of gait in HD and reflects disease severity
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