Insomnia and somnolence in idiopathic RBD: a prospective cohort study
Bibliographic record
Abstract
Abstract Although some sleep disorders are markers of prodromal Parkinson’s disease and dementia with Lewy bodies, it is unclear whether insomnia and somnolence can predict disease. We assessed a large cohort of patients with idiopathic rapid eye movement sleep behavior disorder and age/sex matched controls, comparing the Epworth sleepiness scale, the Insomnia Severity Index, the Pittsburgh Sleep Quality Index, and polysomnographic variables. In those with repeated scales, we assessed change over time. Finally, we assessed whether sleep abnormalities predicted defined neurodegenerative disease. The 151 patients (age = 65.9, 75% male) completed sleep scales and were included. Epworth scores were similar between patients and controls (7.0+/−4.6 vs. 7.2+/−4.7, p = 0.77), and did not progress with time (change = +0.46+/−2.1, p = 0.45). Epworth scores were similar between those who developed neurodegenerative disease and those remaining disease-free (6.7+/−4.4 vs. 7.1+/−4.7, p = 0.70). Pittsburgh Index scores were higher in patients than controls (7.2+/−3.8 vs. 4.9+/−3.4, p = 0.004), mainly driven by the sleep disturbance/medication components (reflecting rapid eye movement sleep behavior disorder symptoms/treatment). Baseline Pittsburgh scores did not predict conversion to neurodegeneration, although sleep duration increased over time in those converting to neurodegenerative disease (+0.88+/−1.32 h, p = 0.014). Insomnia index scores were higher in patients than controls (10.0+/−5.5 vs. 6.35+/−4.66, p < 0.001), but declined over time (−1.43+/−5.09, p = 0.029) particularly in those converting to neurodegenerative disease. Finally, on polysomnogram, those with increased tonic rapid eye movement had higher risk of developing defined neurodegenerative disease (HR = 1.88, p = 0.039). In summary, we found that somnolence and insomnia do not predict neurodegeneration in idiopathic rapid eye movement sleep behavior disorder. As neurodegeneration progresses through prodromal stages, patients may have increasing sleep drive and duration.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".