Prevalence and Risk Factors of Positional Obstructive Sleep Apnea in Chinese Children: A Retrospective Study
Bibliographic record
Abstract
Objective: To investigate the prevalence, characteristics, risk factors, and clinical outcomes of positional obstructive sleep apnea (POSA) in Chinese children. Methods: This was a retrospective analysis of children aged 4-17 years with OSA from local referrals for sleep-disordered breathing. Children who underwent diagnostic polysomnography (PSG) with at least 30 minutes of total sleep time in both supine and non-supine sleep were included. Standardized sleep questionnaires, Sleepiness Scales, Child Behavior Checklist and 24-hour ambulatory blood pressure monitoring were completed. OSA was defined as obstructive apnea-hypopnea index (OAHI) ≥1/h. POSA was defined as OAHI in the supine position ≥ two times the OAHI in the non-supine position. Results: 314 children (mean age: 10.88±3.22 years; male: 70%) with OSA were analyzed, of whom 147 (46.8%) had moderate/severe OSA (OAHI≥5). Prevalence of POSA was 58% within our cohort and 51% among those with moderate/severe OSA. Children with POSA were older (10.8±3.3 years vs 9.1±2.6 years; p<0.001), had milder disease [OAHI 4.12 (2.14-8.62) events/h vs 6.16 events/h); p=0.026] and had smaller tonsillar size (55% vs 72%; p=0.011). By logistic regression, POSA was associated with older age (OR 1.20; 95% confidence interval (CI) 1.09-1.32; p<0.001) and lower OAHI (B-0.036; SE 0.011; OR 0.964; 95% CI 0.943-0.986; p=0.001). Conclusion: POSA is a prevalent phenotype seen in children, demonstrating strong associations with older age, more mature pubertal development, smaller tonsillar size and milder disease severity. Future studies should also delineate the natural history and longitudinal stability of this subtype over time.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".