npj Parkinson's Disease (Sep 2024)

Sensing data and methodology from the Adaptive DBS Algorithm for Personalized Therapy in Parkinson’s Disease (ADAPT-PD) clinical trial

  • Scott Stanslaski,
  • Rebekah L. S. Summers,
  • Lisa Tonder,
  • Ye Tan,
  • Michelle Case,
  • Robert S. Raike,
  • Nathan Morelli,
  • Todd M. Herrington,
  • Martijn Beudel,
  • Jill L. Ostrem,
  • Simon Little,
  • Leonardo Almeida,
  • Adolfo Ramirez-Zamora,
  • Alfonso Fasano,
  • Travis Hassell,
  • Kyle T. Mitchell,
  • Elena Moro,
  • Michal Gostkowski,
  • Nagaraja Sarangmat,
  • Helen Bronte-Stewart,
  • On behalf of the ADAPT-PD Investigators

DOI
https://doi.org/10.1038/s41531-024-00772-5
Journal volume & issue
Vol. 10, no. 1
pp. 1 – 11

Abstract

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Abstract Adaptive deep brain stimulation (aDBS) is an emerging advancement in DBS technology; however, local field potential (LFP) signal rate detection sufficient for aDBS algorithms and the methods to set-up aDBS have yet to be defined. Here we summarize sensing data and aDBS programming steps associated with the ongoing Adaptive DBS Algorithm for Personalized Therapy in Parkinson’s Disease (ADAPT-PD) pivotal trial (NCT04547712). Sixty-eight patients were enrolled with either subthalamic nucleus or globus pallidus internus DBS leads connected to a Medtronic PerceptTM PC neurostimulator. During the enrollment and screening procedures, a LFP (8–30 Hz, ≥1.2 µVp) control signal was identified by clinicians in 84.8% of patients on medication (65% bilateral signal), and in 92% of patients off medication (78% bilateral signal). The ADAPT-PD trial sensing data indicate a high LFP signal presence in both on and off medication states of these patients, with bilateral signal in the majority, regardless of PD phenotype.