Association of early-onset psychiatric disorders with REM sleep behavior disorder – A retrospective study
Bibliographic record
Abstract
BACKGROUND: REM sleep behaviour disorder (RBD) is a known predictor of the subsequent development of neurodegenerative diseases, particularly Parkinson's disease and other alpha synucleinopathies. RBD has also been found to be common among children with other psychiatric disorders such as anxiety, depression, and ADHD. OBJECTIVE: This retrospective study aims to analyze the prevalence of early-onset psychiatric disorders among patients referred for RBD to our sleep laboratory. Our hypothesis is that early-onset psychiatric disorders are more common in patients with polysomnographically confirmed RBD. METHODS: A retrospective chart review was performed through the Kingston Health Sciences Centre (KHSC) Sleep Laboratory. Data collection involved gathering information regarding the patient's sleep study, psychiatric diagnoses and/or symptoms, mental health medication history and any neurodegenerative conditions noted in hospital clinical notes. RESULTS: Patients referred for and polysomnographically confirmed RBD were more likely to have presented with symptoms, or received a clinical diagnosis, of an early-onset psychiatric disorder at 32 % compared to the obstructive sleep apnea (OSA) control group at 3 %. CONCLUSIONS: History of early-onset psychiatric disorders is more common among patients referred as RBD compared to a control group of patients with OSA. Future studies are required to confirm the validity and replicability of this finding.
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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 | 0.001 |
| 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 | 0.001 |
| Research integrity | 0.000 | 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".