Deep brain stimulation in the treatment of dyskinesia and dystonia
Bibliographic record
Abstract
Deep brain stimulation (DBS) has become a mainstay of treatment for patients with movement disorders. This modality is directed at modulating pathological activity within basal ganglia output structures by stimulating some of their nuclei, such as the subthalamic nucleus (STN) and the globus pallidus internus (GPi), without making permanent lesions. With the accumulation of experience, indications for the use of DBS have become clearer and the effectiveness and limitations of this form of therapy in different clinical conditions have been better appreciated. In this review the authors discuss the efficacy of DBS in the treatment of dystonia and levodopa-induced dyskinesias. The use of DBS of the STN and GPi is very effective for the treatment of movement disorders induced by levodopa. The relative benefits of using the GPi as opposed to the STN as a target are still being investigated. Bilateral GPi stimulation is gaining importance in the therapeutic armamentarium for the treatment of dystonia. The DYT1 forms of generalized dystonia and cervical dystonias respond to DBS better than secondary dystonia does. Discrimination between the diverse forms of dystonia and a better understanding of the pathophysiological features of this condition will serve as a platform for improved outcomes.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| 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) | 0.004 | 0.003 |
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".