Impulse control disorders in parkinson disease: A multicenter case–control study
Bibliographic record
Abstract
OBJECTIVE: To assess factors associated with impulse control disorders (ICDs) in Parkinson disease (PD) using a multicenter case--control design. METHODS: Patients enrolled in the DOMINION study, a multicenter study assessing the cross-sectional frequency of ICDs in PD, were eligible to participate in the case--control study. PD patients with and without an ICD (n = 282 each) (compulsive gambling, buying, sexual behavior, and eating) were matched individually on age, gender, and dopamine agonist treatment. Subjects were assessed with a comprehensive neurological, psychiatric, and cognitive assessment battery. RESULTS: ICD patients reported more functional impairment (p < 0.001); greater depressive (p < 0.0001), state (p < 0.0001), and trait (p < 0.0001) anxiety; greater obsessive-compulsive symptoms (p < 0.0001); higher novelty-seeking (p < 0.001) and impulsivity (p < 0.001); and differences in reward preference reflecting greater choice impulsivity (p < 0.05). Patients with multiple ICDs had greater dyskinesia scores compared to those with single ICDs. INTERPRETATION: ICDs in PD are associated with multiple psychiatric and cognitive impairments, including affective and anxiety symptoms, as well as elevated obsessionality, novelty seeking, and impulsivity. These results highlight the importance of assessing multiple mental health domains in individuals with PD and ICDs, and suggest possible pathophysiological mechanisms and risk indicators for these disorders.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".