Abstract

OBJECTIVE

Quantification of gait with wearable technology is promising; recent cross‐sectional studies showed that gait characteristics are potential prodromal markers for Parkinson’s disease (PD). The aim of this longitudinal prospective observational study was to establish gait impairments and trajectories in the prodromal phase of PD, identifying which gait characteristics are potentially early diagnostic markers of PD.

METHODS

696 healthy controls (HC, 63±7 years) recruited in the TREND study were included. Assessments were performed longitudinally four times at 2‐year intervals and people who converted to PD identified. Participants were asked to walk at different speed under single and dual‐tasking, with a wearable placed on the lower back; fourteen validated clinically relevant gait characteristics were quantified. Cox regression was used to examine whether gait at first visit could predict time to PD conversion after controlling for age and sex. Random effects linear mixed‐models (RELMs) were used to establish longitudinal trajectories of gait and model the latency between impaired gait and PD diagnosis.

RESULTS

Sixteen participants were diagnosed with PD on average 4.5 years after first visit (converters, PDC). Higher step time variability and asymmetry of all gait characteristics were associated with a shorter time to PD diagnosis. RELMs indicated gait (lower pace) deviates from non‐PDC approximately four years prior to diagnosis.

INTERPRETATION

Together with other prodromal markers, quantitative gait characteristics can play an important role to identify prodromal PD and progression within this phase.

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