Deep Brain Stimulation Target Selection in Co-Morbid Essential Tremor and Parkinson’s Disease
Bibliographic record
Abstract
Clinical Vignette: A 64-year-old man with essential tremor (ET) and Parkinson's disease (PD) presented with medically refractory, large amplitude, debilitating rest and action tremor in his extremities. Clinical Dilemma: Ventral intermediate nucleus of the thalamus (VIM) deep brain stimulation (DBS) improves tremor in ET and PD but does not ameliorate bradykinesia and rigidity in PD. The comparative efficacy of subthalamic nucleus (STN) DBS in managing action ET tremor remains unclear. Clinical Solution: Bilateral STN was selected as the DBS target. Moderate improvement in rest tremor and mild improvement in action tremor were noted following initial programming. Gap In Knowledge: There are no head-to-head trials to guide DBS target selection in patients with both ET and PD. Current evidence is limited to a few small head-to-head trials that have demonstrated equivalent efficacy in tremor reduction in PD patients using VIM as DBS target and in ET patients using STN. Expert Commentary: Due to limited evidence, DBS treatment of complex cases, such as combined Parkinson's disease and essential tremor, remains based on expert consensus at each institution. Further multi-approach efforts, using imaging, electrophysiologic, and animal data, will be needed to answer the identified gap in knowledge. Highlights: There is limited evidence to guide deep brain target selection in patients with essential tremor and Parkinson's disease. We review existing literature and propose strategies to manage tremor in these patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".