Using cone beam CT to assess the upper airway after surgery in children with sleep disordered breathing symptoms and maxillary-mandibular disproportions: A clinical pilot
Bibliographic record
Abstract
BACKGROUND: The surgical excision of anatomic obstructions such as adenoids, palatine or lingual tonsils are commonly performed in children with sleep disordered breathing (SDB). Imaging studies measuring airway changes post-surgery in the SDB pediatric population are scarce, rarely addresses the nasal cavity, and are based on global measures (e.g. volume) that do not represent the complexity of the upper airway anatomy. The purpose of this pilot is to test the feasibility in using cone beam CT (CBCT) to analyze the nasal and pharyngeal airway space post-surgery using meaningful methods of analyses, and correlating imaging findings with clinical outcomes in children with SDB symptoms and maxillary-mandibular disproportion. METHODS: Twelve non-syndromic children with SDB symptoms and jaw disproportions were evaluated by interdisciplinary airway team before and after upper airway surgery. CBCT and OSA-18 quality of life questionnaire pre and post-operatively were completed. Conventional and new airway variables were measured based on 3D models of the upper airways and correlated with OSA-18. Conventional measures include volume, surface area, and cross-sectional area. New airway measures include constriction and patency; point-based analyses. RESULTS: Eight females and four males were 8.8 ± 2 years with mean BMI of 18.7 ± 3. OSA-18 improved, median (lower quartile-upper quartile) from 64.2 (54.7-79.5) to 37.6 (28.7-43) postoperatively, p < 0.001. The median of all airway measures improved however with very wide range. Subjects with the smallest amounts of constriction relief and/or gain in airway patency presented with least improvement in OSA-18. New airway measures show strong correlation with changes in OSA-18 (ρ = 0.44 to 0.71) whereas conventional measures showed very weak correlation (ρ = -0.04 to 0.37). CONCLUSIONS: Using point-based analyses, new airway measures better explained changes in clinical symptoms compared to conventional measures. Airway patency gained by at least 150% and constriction relief by at least 15% showed marked improvement in OSA-18 by 40-55%, after surgery in the tested cohort.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".