Chronic adaptive versus conventional deep brain stimulation in Parkinson’s disease: a blinded randomized pilot trial
Bibliographic record
Abstract
ABSTRACT Background Adaptive deep brain stimulation (aDBS) is becoming a feasible therapeutic option in patients who are candidates for DBS, and implantable devices are now commercially available. We present the results of a blinded, randomized, crossover pilot trial aimed at comparing aDBS with conventional DBS (cDBS). Methods Fifteen patients were implanted with the AlphaDBS device (Newronika SpA, Milan, Italy, NCT04681534 ). The device replaced a previous Medtronic Activa PC at battery depletion in 11 patients, while the other four were first-time implant patients. Patients underwent two study phases: 1) a two-day, short-term follow-up in the hospital, in which patients received aDBS and cDBS for one day each (in random order); 2) a one-month, long-term follow-up at home, with patients receiving both DBS modes, each for two weeks. Safety endpoints were the occurrence of stimulation-related adverse events and the total electrical energy delivered to the tissue. The clinical endpoints were the Unified Parkinson’s (part III) and Dyskinesia Disease Rating Scales used for in-clinic evaluation, and a three-day diary used for home assessment to estimate good on time without troublesome dyskinesia. At the end of the study, patients blindly decided their preferred stimulation mode. Findings No related adverse events were reported. The AlphaDBS device reliably recorded deep brain signals and applied a linear algorithm that changed the stimulation current every minute based on the average local field potential amplitude, calculated in a patient-specific beta frequency range. In the short-term follow-up, aDBS improved patients as much as cDBS, with lower UDysRS scores. In the long-term follow up, considering intra-patient differences, aDBS provided greater benefit than cDBS in 80% of patients. The same percentage of patients preferred and continued with aDBS (mean follow-up 316 days). Interpretation Our results suggest that aDBS is safe and effective and can be applied in a large population of parkinsonian patients who are candidates for DBS. The majority of patients improved more with aDBS than cDBS, who subjectively preferred aDBS in the long term. Further research is needed to better understand the profile of the best responders and the scheduling of aDBS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".