Management of Persistent, Post-adenotonsillectomy Obstructive Sleep Apnea in Children: An Official American Thoracic Society Clinical Practice Guideline
Bibliographic record
Abstract
Abstract Background Obstructive sleep apnea (OSA) is the most common sleep-related breathing disorder. Although adenotonsillectomy is first-line management for pediatric OSA, up to 40% of children may have persistent OSA. This document provides an evidence-based clinical practice guideline on the management of children with persistent OSA. The target audience is clinicians, including physicians, dentists, and allied health professionals, caring for children with OSA. Methods A multidisciplinary international panel of experts was convened to determine key unanswered questions regarding the management of persistent pediatric OSA. We conducted a systematic review of the relevant literature. The Grading of Recommendations, Assessment, Development, and Evaluation approach was used to rate the quality of evidence and the strength of the clinical recommendations. The panel members considered the strength of each recommendation and evaluated the benefits and risks of applying the intervention. In formulating the recommendations, the panel considered patient and caregiver values, the cost of care, and feasibility. Results Recommendations were developed for six management options for persistent OSA. Conclusions The panel developed recommendations for the management of persistent pediatric OSA based on limited evidence and expert opinion. Important areas for future research were identified for each recommendation.
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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 | 0.010 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.005 | 0.006 |
| 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".