A national study of choanal atresia in tertiary care centers in Canada – part II: Clinical management
Bibliographic record
Abstract
Background To evaluate the clinical management of choanal atresia (CA) in tertiary centers across Canada. Methods Multi-centre case series involving six tertiary care pediatric hospitals across Canada. Retrospective chart review of patients born between 1980 and 2010 diagnosed with choanal atresia to a participating center. Results The health charts of 215 patients (59.6% female) with choanal atresia (CA) were reviewed. Mean age of initial surgical repair was 0.8 months for bilateral CA, and 48.6 months for unilateral CA. Approaches of surgical repair consisted of endoscopic transnasal (31.7%), non-endoscopic transnasal (42.6%), and transpalatal (25.2%). Stents were used on 70.7% of patients. Forty-nine percent of patients were brought back to the OR for a planned second look; stent removal being the most common reason (86.4%). Surgical success rate of initial surgeries was 54.1%. Surgical technique was not associated with rate of restenosis [χ2 (2) = 1.6, p = .46]. Conclusions The present study is the first national multi-institutional study exploring the surgical outcomes of CA over a 30-year period. The surgical repair of CA presents a challenge to otolaryngologists, as the rate of surgical failure is high. The optimal surgical approach, age at surgical repair, use of stents, surgical adjuncts, and need for planned second look warrant further investigation. Graphical Abstract
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".