REM Sleep Characteristics in Narcolepsy and REM Sleep Behavior Disorder
Bibliographic record
Abstract
STUDY OBJECTIVES: To assess the presence of polysomnographic characteristics of REM sleep behavior disorder (RBD) in narcolepsy; and to quantify REM sleep parameters in patients with narcolepsy, in patients with "idiopathic" RBD, and in normal controls. DESIGN: Sleep laboratory study PARTICIPANTS: Sixteen patients with narcolepsy and cataplexy matched for age and sex with 16 patients with "idiopathic" RBD and with 16 normal controls were studied. MEASUREMENTS AND RESULTS: Higher percentages of REM sleep without atonia, phasic electromyographic (EMG) activity, and REM density were found in patients with narcolepsy than normal controls. In contrast, RBD patients had a higher percentage of REM sleep without atonia but a lower REM density than patients with narcolepsy and normal controls. Based on a threshold of 80% for percentage of REM sleep with atonia, 50% of narcoleptics and 87.5% of RBD patients had abnormal REM sleep muscle activity. No significant behavioral manifestation in REM sleep was noted in either narcoleptics or controls. We also found a higher frequency of periodic leg movements during wake (PLMW) and during sleep (PLMS) in narcoleptic patients compared to controls. CONCLUSIONS: The present study demonstrates abnormalities in REM sleep motor regulation with an increased frequency of REM sleep without atonia, phasic EMG events and PLMS in narcoleptic patients when compared to controls. These abnormalities were seen more prominently in patients with RBD than in narcoleptics, with the exception of the PLMS index. We proposed that dysfunctions in hypocretin/dopaminergic system may lead to motor dyscontrol in REM sleep that results in dissociated sleep/wake states.
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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) | 0.002 | 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".