0551 Predicting Daytime Alertness Impairment in Obstructive Sleep Apnea
Bibliographic record
Abstract
Abstract Introduction Obstructive sleep apnea (OSA) reduces daytime alertness leading to social and occupational impairment. The Maintenance of Wakefulness Test (MWT), a gold-standard test for daytime alertness, is time-consuming and not routinely available in clinical practice. We examined EEG-based and clinical parameters derived from diagnostic polysomnography (PSG) as predictors of alertness impairment in adults with OSA. Methods Eighty-two participants with untreated OSA on diagnostic PSG (apnea hypopnea index, AHI ≥5/hour), enrolled in a two-center clinical trial were included. The day following PSG, each participant completed four 40-minute MWT and four 10-minute Psychomotor Vigilance Tests (PVT). The outcomes were MWT mean sleep latency (MSL) and PVT lapses (reaction time ≥500 milliseconds, square root transformed). Three multiple linear regression models were used: 1. “standard predictors” (total sleep time, TST, percent REM and slow wave sleep, AHI, time < 90% oxygen saturation, and arousal index), 2. “novel predictors” derived by spectral analysis and averaged across right and left central EEG (normalized EEG power, odds ratio product; ORP parameters, and spindle characteristics), and 3. combined standard and novel predictors. Age, sex, and body mass index (BMI) were included in each model, and backward elimination (step AIC) was used for models 2 and 3. Results Participants were middle-aged (mean ± standard deviation, SD 53.5±8.7 years), with moderate OSA (AHI 33.8±18.2) and daytime sleepiness (Epworth Sleepiness Scale 11.7±3.9), and 86% were men. The adjusted r2 for MSL were: model 1=0.09, model 2=0.16, and model 3=0.27, and PVT lapses were: model 1=0.09, model 2=0.31, and model 3=0.34. For MSL, the significant predictors in model 3 included TST (t-statistic -3.59, p=0.0007), REM% (2.51, p=0.01), ORP-9 (2.95, p=0.004), ORP NREM (-3.15, p=0.002), spindle frequency (-2.95, p=0.004), and normalized EEG power (-2.59, p=0.01). For PVT lapses, model 3 predictors included 2.25-2.5 ORP% (-2.91, p=0.005), normalized EEG power (3.22, p=0.002), spindle power (-4.30, p< 0.0001), spindle frequency (2.83, p=0.006), and sex (men vs. women, -2.56, p=0.01). Conclusion We have identified several novel PSG EEG-based predictors of impaired daytime alertness in OSA that will improve occupational evaluation and prognostication in OSA after future validation. Support (if any) National Institutes of Health, UM1-HL112856, UL1TR001422, and UL1TR002003.
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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 | 0.001 | 0.003 |
| 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) | 0.002 | 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".