Cardiac autonomic dysfunction in idiopathic REM sleep behavior disorder
Bibliographic record
Abstract
More than 50% of persons with idiopathic REM sleep behavior disorder (RBD) will develop Parkinson's disease or Lewy body dementia. Symptom screens and metaiodobenzylguanine (MIBG)-scintigraphy suggest autonomic abnormalities in idiopathic RBD, but it is unclear whether autonomic abnormalities can predict neurodegenerative disease. From a cohort of 99 patients with idiopathic RBD, we selected those who developed parkinsonism or dementia. These were matched by age, sex, and follow-up duration to patients with RBD who remained disease free and to matched controls. From the polysomnographic trace performed at baseline evaluation, measures of beat-to-beat RR variability including time domains (mean RR-interval and RR-standard deviation) and frequency domains (low and high frequency components) were retrospectively assessed. Twenty-one patients with idiopathic RBD who developed neurodegenerative disease were included (Parkinson's disease-11, multiple system atrophy-1, and dementia-9). Age at PSG was 66 years, and 86% were male. PSG was performed on average 6.7 years before defined neurodegenerative disease. Comparing all patients with idiopathic RBD to controls, there were significant reductions in RR-standard deviation (24.6 ± 2.2 ms vs. 35.2 ± 3.5 ms, P = 0.006), very low frequency components (238.6 ± 99.6 ms(2) vs. 840.1 ± 188.3 ms(2), P < 0.001), and low frequency components (127.8 ± 26.3 ms(2) vs. 288.7 ± 66.2 ms(2), P = 0.032). However, despite clear differences between patients with idiopathic RBD and controls, there were no differences in any measure between those who did or did not develop disease. RR-variability analysis demonstrates substantial autonomic dysfunction in idiopathic RBD. However, this dysfunction is identical in patients who will or will not develop defined neurodegenerative disease. This suggests that autonomic dysfunction is linked with RBD independent of associated Parkinson's disease or Lewy body dementia.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".