Adenotonsillectomy for Sleep-Disordered Breathing in Children With Syndromic Craniosynostosis
Bibliographic record
Abstract
Syndromic craniosynostosis (SCS) is known to be associated with sleep-disordered breathing (SDB) in childhood. Problems can occur at various levels, but midface hypoplasia is a major factor in affected infants.Adenotonsillectomy (AT) has been proven to be efficacious as a first-line treatment of SDB in healthy children. However, its role in the treatment of this issue in those with SCS has not been evaluated. Owing to the multiple possible levels of obstruction in such individuals, AT may have no benefit. This study therefore aimed to evaluate the effectiveness of AT in this group of patients.Twenty-six children with SCS with moderate to severe obstructive sleep apnea (OSA) were treated with AT. The mean age at surgery was 4.5 years (range, 1.6-13.9 y). Seven had severe OSA, 11 had moderate OSA, and 7 had mild OSA preoperatively. Of 25 children, 15 (60%) demonstrated an improvement in sleep severity scores postoperatively.Overall, there was a significant improvement in the mean number of saturation dips greater than 4%/h and in the mean nadir of dips in saturation after the operation. There was no significant difference in mean oxygen saturation, number of pulse rate rises per hour, or percentage time spent less than 90% SaO2.Clinically, there is thought to be some benefit in performing AT in these groups of patients. In children with SCS, in whom the cause of obstruction might be at multiple levels, AT should still to be considered as first-line treatment in the management of OSA/SDB.We acknowledge that some children may still go on to require further airway intervention. Further multicenter trials would be useful to examine more closely the significance of the effects of AT in children with craniofacial disorders experiencing SDB.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".