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, Michał Gostkowski, Nagaraja Sarangmat, Helen Brontë‐Stewart, On behalf of the ADAPT-PD Investigators
Abstract
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 Percept TM 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.