Deep brain stimulation for the treatment of hyperkinetic movement disorders
Bibliographic record
Abstract
INTRODUCTION: Deep brain stimulation effectiveness is well recognized for different movement disorders including Parkinson's disease, dystonia and essential tremor, however several other diseases in this field may benefit from the technique although experience is sparse and evidences of benefit and risks are not established. AREAS COVERED: In this review, we explored available evidence for effectiveness and safety of DBS in selected hyperkinetic movement disorders, including tardive dyskinesia, Huntington's disease, neuroacanthocytosis, myoclonus-dystonia, Tourette syndrome, orthostatic and Holmes' tremor. Expert commentary: The data referenced and discussed showed potential effectiveness for DBS in these disabling and refractory diseases. On the other hand, these disorders are quite complex and multifaceted, often composed of different movement disorders, as well as other motor and non-motor symptoms. Therefore, the possible contribution of DBS in improving patients' quality of life should be weighted in a strictly individual basis, keeping in mind the progressive nature of most of these disorders, as well as risk/benefit ratio.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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".