Daytime Sleepiness in Obesity: Mechanisms Beyond Obstructive Sleep Apnea—A Review
Bibliographic record
Abstract
Increasing numbers of overweight children and adults are presenting to sleep medicine clinics for evaluation and treatment of sleepiness. Sleepiness negatively affects quality of life, mental health, productivity, and safety. Thus, it is essential to comprehensively address all potential causes of sleepiness. While many obese individuals presenting with hypersomnolence will be diagnosed with obstructive sleep apnea and their sleepiness will improve with effective therapy for sleep apnea, a significant proportion of patients will continue to have hypersomnolence. Clinical studies demonstrate that obesity without sleep apnea is also associated with a higher prevalence of hypersomnolence and that bariatric surgery can markedly improve hypersomnolence before resolution of obstructive sleep apnea. High fat diet in both humans and animals is associated with hypersomnolence. This review critically examines the relationships between sleepiness, feeding, obesity, and sleep apnea and then discusses the hormonal, metabolic, and inflammatory mechanisms potentially contributing to hypersomnolence in obesity, independent of sleep apnea and other established causes of excessive daytime sleepiness.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".