Adenotonsillectomy for Obstructive Sleep Apnea in Children with Complex Chronic Conditions
Bibliographic record
Abstract
Objective To estimate the prevalence of persistent obstructive sleep apnea postadenotonsillectomy in children with complex chronic conditions. Study Design A retrospective cohort study. Setting The Hospital for Sick Children Sleep laboratory. Subjects Children ≤18 years of age who had moderate to severe obstructive sleep apnea and had polysomnography pre- and postadenotonsillectomy. Methods Medical and polysomnographic data were reviewed. The prevalence of persistent obstructive sleep apnea postadenotonsillectomy was determined for the following groups: no complex chronic conditions, single-system complex chronic conditions, and multisystem complex chronic conditions. Results We reviewed data of 133 (84 male) children. Their mean (standard deviation) age was 5.5 (3.8) years. The persistent obstructive sleep apnea rate postadenotonsillectomy was highest in children with multisystem complex chronic conditions (57%), intermediate in children with single-system complex chronic conditions (29%), and lowest in children without complex chronic conditions (15%), P = .0004. The odds (confidence interval) of having persistent obstructive sleep apnea postadenotonsillectomy was 7.42 (2.16-25.51) times higher in children with multisystem complex chronic conditions vs no complex chronic conditions and 3.35 (1.16-9.64) times higher in children with multisystem complex chronic conditions vs single-system complex chronic conditions. Conclusions Although adenotonsillectomy is considered first-line therapy in healthy children older than 2 years for the treatment of obstructive sleep apnea, there is a significantly greater risk of persistent obstructive sleep apnea postadenotonsillectomy in children with complex chronic conditions. Therefore, other surgical procedures or nonsurgical management may need to be considered as first-line treatment for this cohort.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".