0652 Abnormal Sleep Slow Wave Morphology in Idiopathic Hypersomnia
Bibliographic record
Abstract
Abstract Introduction Abnormal cortical synchronization during sleep could affect the restorative function of sleep and consequently, increase daytime sleepiness. Slow wave (SW) density and characteristics provide a unique window of how cortical neurons synchronize during non-rapid eye movement (NREM) sleep. Here, we aimed at verifying whether NREM sleep SW density and characteristics differed between patients with idiopathic hypersomnia (IH) and healthy controls. Methods 56 participants (38.18 ± 11.21 years old; 53% women) with diagnosed IH (full night of in-laboratory polysomnography followed by a multiple sleep latency test; MSLT) were compared to 128 healthy controls (38.16 ± 14.02 years old; 59% women) studied at our center and matched for age and sex. Exclusion criteria were apnea-hypopnea index ≥15, psychiatric conditions, neurological disorders, other sleep disorders, shift work, and use of psychoactive medications before the PSG. SW were automatically detected on C3 and C4 electrodes in N2 and N3 sleep stages. Group X Sleep cycle ANOVAs were used for SW density and characteristics (e.g., duration, amplitude, and slope, averaged for C3 and C4). Age was added as a control variable in all analyses. Statistical significance was set at p < 0.05. Results Several group effects were found where, compared to healthy controls, IH patients had significantly smaller slow wave negative amplitudes, peak-to-peak amplitudes, and smoother slopes (p < 0.05). The only significant interaction was for slow wave negative amplitudes, where the sleep cycle effect observed in healthy controls was not found in IH patients (p < 0.05). Conclusion Compared to healthy controls, IH patients have slow wave characteristics that suggest a lower cortical synchrony during NREM sleep and could explain the non-restorative effect of sleep often reported by these patients. Support (if any) This project was made possible by an award from the American Academy of Sleep Medicine Foundation, a foundation of the American Academy of Sleep Medicine. Nadia Gosselin hold the Canada Research Chair in sleep disorders and brain health.
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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) | 0.004 | 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".