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Sensing data and methodology from the Adaptive DBS Algorithm for Personalized Therapy in Parkinson’s Disease (ADAPT-PD) clinical trial
- Stanslaski, Scott;
- Summers, Rebekah LS;
- Tonder, Lisa;
- Tan, Ye;
- Case, Michelle;
- Raike, Robert S;
- Morelli, Nathan;
- Herrington, Todd M;
- Beudel, Martijn;
- Ostrem, Jill L;
- Little, Simon;
- Almeida, Leonardo;
- Ramirez-Zamora, Adolfo;
- Fasano, Alfonso;
- Hassell, Travis;
- Mitchell, Kyle T;
- Moro, Elena;
- Gostkowski, Michal;
- Sarangmat, Nagaraja;
- Bronte-Stewart, Helen
Published Web Location
https://doi.org/10.1038/s41531-024-00772-5Abstract
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.
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