ICARUS study: prevalence and clinical features of impulse control disorders in Parkinson’s disease
Bibliographic record
Abstract
BACKGROUND: Impulse control disorders/other compulsive behaviours ('ICD behaviours') occur in Parkinson's disease (PD), but prospective studies are scarce, and prevalence and clinical characteristics of patients are insufficiently defined. OBJECTIVES: To assess the presence of ICD behaviours over a 2-year period, and evaluate patients' clinical characteristics. METHODS: A prospective, non-interventional, multicentre study (ICARUS (Impulse Control disorders And the association of neuRopsychiatric symptoms, cognition and qUality of life in ParkinSon disease); SP0990) in treated Italian PD outpatients. Study visits: baseline, year 1, year 2. Surrogate primary variable: presence of ICD behaviours and five ICD subtypes assessed by modified Minnesota Impulsive Disorder Interview (mMIDI). RESULTS: 1069/1095 (97.6%) patients comprised the Full Analysis Set. Point prevalence of ICD behaviours (mMIDI; primary analysis) was stable across visits: 28.6% (306/1069) at baseline, 29.3% (292/995) at year 1, 26.5% (245/925) at year 2. The most prevalent subtype was compulsive eating, followed by punding, compulsive sexual behaviour, gambling and buying disorder. Patients who were ICD positive at baseline were more likely to be male, younger, younger at PD onset, have longer disease duration, more severe non-motor symptoms (including mood and sexual function), depressive symptoms, sleep impairment and poorer PD-related quality of life. However, they did not differ from the ICD-negative patients in their severity of PD functional disability, motor performance and cognitive function. CONCLUSIONS: Prevalence of ICD behaviours was relatively stable across the 2-year observational period. ICD-positive patients had more severe depression, poorer sleep quality and reduced quality of life.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".