Pathological gambling in Parkinson's disease improves on chronic subthalamic nucleus stimulation
Bibliographic record
Abstract
Pathological gambling (PG) related to dopaminergic treatment in Parkinson's disease (PD) is part of a spectrum of behavioral disorders called the dopamine dysregulation syndrome (DDS). We describe a series of PD patients with preoperative active PG due to dopaminergic treatment from a total of 598 patients who have undergone surgery for subthalamic nucleus stimulation for disabling motor fluctuations. The patients had systematic open assessment of behavioral symptoms and standardized assessments of motor symptoms, mood, and apathy. Seven patients (6 men, 1 woman; age, 54 +/- 9 years; levodopa equivalent dose, 1,390 +/- 350 mg/day) had preoperative PG over a mean of 7 years, intolerant to reduction in medication. Six had nonmotor fluctuations and four had other behavioral symptoms consistent with a diagnosis of the DDS. After surgery, motor symptoms improved, allowing for 74% reduction of dopaminergic treatment, below the dosage of gambling onset. In all patients, PG resolved postoperatively after 18 months on average (range, 0-48), although transient worsening occurred in two. Improvement paralleled the time course and degree of reduction in dopaminergic treatment. Nonmotor fluctuations, off period dysphoria, and other symptoms of the DDS improved. Two patients developed persistent apathy. In conclusion, PG and other symptoms of the DDS-associated dopaminergic treatment improved in our patients following surgery. Dopaminergic dysregulation commonly attributed to pulsatile overstimulation of the limbic dopaminergic system may be subject to desensitization on chronic subthalamic stimulation, which has a relative motor selectivity and allows for decrease in dopaminergic treatment.
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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 | 0.001 |
| 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) | 0.001 | 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 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".