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The effect of Levodopa and Stimulation on post-surgery Freezing of Gait in STN-DBS Parkinson's Disease patients: a clinical and kinematic analysis

· 2024-04-02

DOI: 10.21203/rs.3.rs-4058858/v1

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Research overview

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Abstract Background Despite the long-term efficacy of high-frequency (HFS) subthalamic nucleus deep brain stimulation (STN-DBS) on appendicular symptoms, its benefit on freezing of gait (FOG) is less clear. Mechanisms and optimal therapeutic approaches to this type of FOG remain unclear. Objective Assess acute post-surgery FOG response to levodopa and stimulation Methods 17 PD STN-DBS patients with a FOG score (item 3.11) ≥ 2 in the MedON/StimON condition were evaluated under 5 experimental conditions, including a low frequency (60Hz) condition maintaining the same total energy delivered. In each condition, gait and FOG episodes (#FOG) were assessed using clinical (including a 3x14 meters Stand-Walk-Sit task) and kinematic metrics using a set of Inertial Measurement Units (IMUs). Results At a cohort level, compared to MedOFF/StimOFF, #FOG was significantly reduced in the MedONStimON 130Hz condition. A high variability in individual responses were seen regarding individual responses to LD or stimulation. While ~ 29% of patients worsened their FOG with LD and were rescued by DBS, ~ 18% presented the reverse pattern. No significant differences were observed in #FOG when low and high frequency were compared, however MDS-UPDRS axial subscores were significantly lower in 60Hz condition. Gait variability emerged as the strongest kinematic dimension associated with FOG. A convolutional neural network model trained to identify FOG episodes on sensor data from an independent cohort of PD presented a good correlation with clinical FOG metrics (r > 0.54). Discussion FOG presenting in the Best-Functional state after surgery is mostly a therapy-resistant FOG partially improved by stimulation and medication. The clinical and kinematic heterogeneity in FOG responses to LD and stimulation (including frequency) should be clinically considered. IMU based tools can provide powerful methods to identify FOG episodes, study gait phenotypes and clarify the circuit mechanisms of FOG, whose treatment remains an unmet clinical need.

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