Gambling and Increased Sexual Desire With Dopaminergic Medications in Restless Legs Syndrome
Bibliographic record
Abstract
OBJECTIVES: Do patients with restless legs syndrome (RLS) report gambling or other abnormal behaviors as previously reported in Parkinson disease. METHODS: This survey study was sent to 261 idiopathic RLS patients, and it included the Gambling Symptoms Assessment Scale, Altman Self-Rating Mania Scale, and questions pertaining to sexual activity and novelty-seeking behaviors. RESULTS: Ninety-nine patients responded to the survey, and 77 were actively taking 1 or more dopaminergic medications. Of the 70 respondents who answered the gambling questions, 5 (7%) noted a change in gambling, with 4 (6%; 95% confidence interval, 2%-14%) stating that increased urges and time spent gambling occurred specifically after the use of dopaminergic medications (2 on pramipexole, 1 on ropinirole, and 1 on levodopa and pramipexole). Increased sexual desire was reported by 4 (5%) of the 77 respondents, 3 (4%; 95% confidence interval, 1%-11%) reported that this occurred specifically after the use of dopaminergic medications (1 on pramipexole, 1 on ropinirole, and 1 on levodopa). One patient reported both an increase in gambling and sexual habits. CONCLUSIONS: This exploratory survey study revealed the development of gambling and/or increased sexuality in patients with RLS. These data raise the possibility that, as in Parkinson disease, RLS patients should be cautioned about potential behaviors that may occur with the use of dopaminergic medications. Further prospective studies are needed to assess the relationship between these medications and compulsive behaviors associated with the treatment of RLS.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".