Surgical Treatment of Dyskinesia in Parkinson’s Disease
Bibliographic record
Abstract
One of the main indications for stereotactic surgery in Parkinson's disease (PD) is the control of levodopa-induced dyskinesia. This can be achieved by pallidotomy and globus pallidus internus (GPi) deep brain stimulation (DBS) or by subthalamotomy and subthalamic nucleus (STN) DBS, which usually allow for a cut down in the dosage of levodopa. DBS has assumed a pivotal role in stereotactic surgical treatment of PD and, in fact, ablative procedures are currently considered surrogates, particularly when bilateral procedures are required, as DBS does not produce a brain lesion and the stimulator can be programed to induce better therapeutic effects while minimizing adverse effects. Interventions in either the STN and the GPi seem to be similar in controlling most of the other motor aspects of PD, nonetheless, GPi surgery seems to induce a more particular and direct effect on dyskinesia, while the anti-dyskinetic effect of STN interventions is mostly dependent on a reduction of dopaminergic drug dosages. Hence, the si ne qua non-condition for a reduction of dyskinesia when STN interventions are intended is their ability to allow for a reduction of levodopa dosage. Pallidal surgery is indicated when dyskinesia is a dose-limiting factor for maintaining or introducing higher adequate levels of dopaminergic therapy. Also medications used for the treatment of PD may be useful for the improvement of several non-motor aspects of the disease, including sleep, psychiatric, and cognitive domains, therefore, dose reduction of medication withdrawal are not always a fruitful objective.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".