Risk factors for neurodegeneration in idiopathic rapid eye movement sleep behavior disorder: A multicenter study
Bibliographic record
Abstract
OBJECTIVE: To assess whether risk factors for Parkinson disease and dementia with Lewy bodies increase rate of defined neurodegenerative disease in idiopathic rapid eye movement (REM) sleep behavior disorder (RBD). METHODS: Twelve centers administered a detailed questionnaire assessing risk factors for neurodegenerative synucleinopathy to patients with idiopathic RBD. Variables included demographics, lifestyle factors, pesticide exposures, occupation, comorbid conditions, medication use, family history, and autonomic/motor symptoms. After 4 years of follow-up, patients were assessed for dementia or parkinsonism. Disease risk was assessed with Kaplan-Meier analysis, and epidemiologic variables were compared between convertors and those still idiopathic using logistic regression. RESULTS: Of 305 patients, follow-up information was available for 279, of whom 93 (33.3%) developed defined neurodegenerative disease. Disease risk was 25% at 3 years and 41% after 5 years. Patients who converted were older (difference = 4.5 years, p < 0.001), with similar sex distribution. Neither caffeine, smoking, nor alcohol exposure predicted conversion. Although occupation was similar between groups, those who converted had a lower likelihood of pesticide exposure (occupational insecticide = 2.3% vs 9.0%). Convertors were more likely to report family history of dementia (odds ratio [OR] = 2.09), without significant differences in Parkinson disease or sleep disorders. Medication exposures and medical history were similar between groups. Autonomic and motor symptoms were more common among those who converted. Risk factors for primary dementia and parkinsonism were generally similar, except for a notably higher clonazepam use in dementia convertors (OR = 2.6). INTERPRETATION: Patients with idiopathic RBD are at very high risk of neurodegenerative synucleinopathy. Risk factor profiles between convertors and nonconvertors have both important commonalities and differences.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".