0536 Association of a Novel EEG Biomarker of Sleep Depth with Sleep Disordered Breathing in Adolescents
Bibliographic record
Abstract
Abstract Introduction The odds ratio product (ORP) provides a standardized, continuous measure of sleep depth that ranges from 0 (deep sleep) to 2.5 (full wakefulness). ORP has been shown to increase during adolescence, representing the decline in sleep depth that occurs during this developmental period. In adults, higher ORP has been associated with sleep disordered breathing (SDB), including obstructive sleep apnea (OSA), while there have been no studies in youth. We aimed to determine the association of ORP with SDB in adolescents. Methods We extracted ORP from the sleep EEG of 261 typically developing adolescents aged 12-23y (median 16y) from the Penn State Child Cohort. Higher ORP during rapid eye movement (REM) and non-REM sleep indicates less deep sleep, while higher ORP-9 (i.e., average ORP in the 9-seconds following non-REM cortical arousals) indicates greater arousability. We used general linear models, adjusted for sex, age and race/ethnicity, to examine mean differences in ORP metrics among clinically meaningful groups of SDB based on the apnea/hypopnea index (AHI) consisting of no SDB (AHI<2 and no snoring, n=100), primary snoring (AHI<2 and snoring, n=75), 2≤AHI<5 (n=64), and AHI≥5 (n=22). Results Adolescents with primary snoring or 2≤AHI<5 did not significantly differ in ORP metrics from those without SDB (all p≥0.12). Adolescents with AHI≥5 had higher ORP-NREM compared to those without SDB, with primary snoring or with 2≤AHI<5 (all p≤0.01), while ORP-REM was significantly higher compared to those without SDB (p=0.02). ORP-9 was significantly greater in adolescents with AHI≥5 compared to those with no SDB (p<0.01) and those with primary snoring (p=0.02), but not when compared to those with 2≤AHI<5 (p=0.07). Conclusion Our data suggest that adolescents with OSA experience lower REM and non-REM sleep depth/intensity (higher ORP) compared to those without SDB. In addition, these adolescents experience a slower progression back to deep sleep following cortical arousals (higher ORP-9), which suggests they remain in a high arousability state and, thus, are more likely to repeat arousals. Commensurate with previous studies in adults, our data show that ORP is a useful sleep EEG biomarker able to capture decreased sleep depth in adolescents with OSA. Support (If Any) National Institutes of Health (R01MH118308, UL1TR000127)
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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 | 0.002 |
| 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 | 0.001 | 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".