0280 Change in Sleep Depth Across the Night as a Measure of Sleep Adequacy
Bibliographic record
Abstract
Abstract Introduction It is well known that sleep becomes lighter towards the end of the night reflecting the reduction in homeostatic sleep pressure. We hypothesized that more adequate nocturnal sleep (i.e. sufficient quantity and quality for the individual) would result in a greater reduction in sleep depth across the night and would be reflected in decreased next-day sleep tendency. Methods In a secondary analysis of data from a study in which sleep depth was altered by sleep restriction combined with either placebo or gaboxadol (a delta-promoting drug) we correlated change across the night in two measures of sleep depth with next-day Multiple Sleep Latency Test (MSLT) latencies. Forty-one healthy subjects underwent 8 consecutive sleep studies; two baseline, four sleep restriction (5 hours) and two recovery nights. MSLT was performed following each baseline night and the last two restriction nights. Sleep depth in the first and last hours of NREM sleep was determined by two methods 1) Log delta spectral power; 2) The odds-ratio-product (ORP), a recently introduced continuous measure of sleep depth. The difference between initial and final values was calculated (ΔDelta, ΔORP). Post-restriction MSLT latency was correlated with baseline MSLT latency, ΔDelta, ΔORP, log delta power and ORP in the last hour, lost total sleep time and lost REM time. Results ΔDelta was -0.27 ±0.13 and ΔORP was 0.17 ±0.13, both changes reflecting lightening of sleep across the night. In both univariate and multivariate analysis only baseline MSLT latency (p < 0.001) and ΔORP (p < 0.01) were significantly and positively correlated with post-restriction MSLT latency. Conclusion The reduction in sleep depth across the night as measured by ORP, but not by delta power, is significantly correlated with reduced objective sleepiness following sleep restriction. ΔORP may be a useful index that reflects sleep adequacy during the night. Support None
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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 | 0.000 | 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) | 0.003 | 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".