The endoscopic transseptal approach for choanal atresia repair
Bibliographic record
Abstract
BACKGROUND: There are many standard repair options for choanal atresia including puncture, dilatation and drilling of the atretic plate. Most of these techniques involve postoperative stenting, which may promote granulation and scarring, with possible progression to restenosis. This article describes a novel approach for choanal atresia repair without postoperative stenting. METHODS: This article describes our experience with this choanal atresia repair technique utilized in 16 pediatric patients and 1 adult patient across multiple tertiary pediatric and rhinology centers during 2008 through 2015. Seven cases were bilateral and 10 were unilateral. Surgery was performed using an endoscopic transseptal approach with preservation of the mucosa and creation of flaps. No stents or packing was used. The main outcome measures were: response to treatment based on endoscopic examination, need for further revision and incidence of complications. RESULTS: All patients underwent routine postoperative endoscopic inspection of their nasal cavity, postnasal space, and assessment of neochoanal patency. The neochoanae of all patients remained patent to a minimum follow-up duration of 9 months with most patients follow up for 2 years or more. Two neonatal patients required transfusion postoperation from intraoperative bleeding. Two pediatric patients developed postoperative respiratory complications. One patient required revision surgery for nasal vestibule scarring from incision made on the nasal alar to facilitate the initial endoscopic approach. CONCLUSION: This novel endoscopic transseptal repair technique is effective in the management of choanal atresia. Careful fashioning of mucosal flaps and the omission of stenting has resulted in lasting patency of the neochoanae.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".