Unrefreshing naps and sleep architecture during the multiple sleep latency test in idiopathic hypersomnia
Bibliographic record
Abstract
Patients with idiopathic hypersomnia frequently report having unrefreshing naps. However, whether they have abnormal sleep architecture during naps that may explain their unrefreshing aspect is unknown. We compared sleep architecture during short daytime naps in patients with idiopathic hypersomnia reporting unrefreshing and refreshing naps. One-hundred and thirty-four patients tested with one-night polysomnography, followed by an adapted version of the Multiple Sleep Latency Test with four naps, were included. They were asked about the refreshing aspect of their habitual naps during a clinical interview. They were classified as having objective (Multiple Sleep Latency Test ≤ 8 min) or subjective idiopathic hypersomnia (Multiple Sleep Latency Test > 8 min), and as presenting refreshing or unrefreshing naps. We tested Group differences (refreshing versus unrefreshing naps) on nap sleep architecture in the whole sample and for subjective and objective idiopathic hypersomnia subgroups separately using ANCOVAs. No Group effects were observed in the Multiple Sleep Latency Test architecture in the whole sample and in objective and subjective idiopathic hypersomnia subgroups. This study provides preliminary evidence that reporting unrefreshing naps is not associated with clinically significant findings in Multiple Sleep Latency Test sleep architecture in patients with idiopathic hypersomnia. Given that naps taken by patients with idiopathic hypersomnia are typically long, future studies should investigate longer daytime sleep episodes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".