Deep brain stimulation for the treatment of uncommon tremor syndromes
Bibliographic record
Abstract
INTRODUCTION: Deep brain stimulation (DBS) has become a standard therapy for the treatment of select cases of medication refractory essential tremor and Parkinson's disease however the effectiveness and long-term outcomes of DBS in other uncommon and complex tremor syndromes has not been well established. Traditionally, the ventralis intermedius nucleus (VIM) of the thalamus has been considered the main target for medically intractable tremors; however alternative brain regions and improvements in stereotactic techniques and hardware may soon change the horizon for treatment of complex tremors. AREAS COVERED: In this article, we conducted a PubMed search using different combinations between the terms 'Uncommon tremors', 'Dystonic tremor', 'Holmes tremor' 'Midbrain tremor', 'Rubral tremor', 'Cerebellar tremor', 'outflow tremor', 'Multiple Sclerosis tremor', 'Post-traumatic tremor', 'Neuropathic tremor', and 'Deep Brain Stimulation/DBS'. Additionally, we examined and summarized the current state of evolving interventions for treatment of complex tremor syndromes. Expert commentary: Recently reported interventions for rare tremors include stimulation of the posterior subthalamic area, globus pallidus internus, ventralis oralis anterior/posterior thalamic subnuclei, and the use of dual lead stimulation in one or more of these targets. Treatment should be individualized and dictated by tremor phenomenology and associated clinical features.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".