A Narrative Review on Obstructive Sleep Apnea in China: A Sleeping Giant in Disease Pathology
Bibliographic record
Abstract
We review the aspects of obstructive sleep apnea (OSA), which is the most common respiratory disorder of sleep in China. Approximately 176 million people in China have apnea/hypopnea index ≥5/h, ranking first among the ten countries with the highest prevalence rates. Two-thirds of patients do not receive treatment at all or withdraw after only brief treatment in a survey nested in two centers in China. Drowsiness and progressive cognitive impairment related to OSA decrease work performance and add to workplace errors and accidents. Many patients with OSA remain undiagnosed. Untreated OSA increases the risk of developing cardiovascular diseases and metabolic diseases. Undiagnosed and untreated OSA patients place a great burden on healthcare costs and services, and thus enormous economic burdens across most countries across the world, due to the global epidemic of obesity, an important contributor to OSA. Continuous positive airway pressure is the first-line treatment for OSA in China; however, adherence levels are poor. Effective and less labor-intensive methods that improve adherence need to be further investigated. Traditional Chinese medicine and acupuncture are promising treatments but with unproven efficacy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| 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) | 0.007 | 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".