Anastomotic Stricture in End-to-End Anastomosis—Risk Factors in a Series of 261 Patients with Esophageal Atresia
Bibliographic record
Abstract
Abstract Aim To assess the risk factors for anastomotic stricture (AS) in end-to-end anastomosis (EEA) in patients with esophageal atresia (EA). Methods With ethical consent, hospital records of 341 EA patients from 1980 to 2020 were reviewed. Patients with less than 3 months survival (n = 30) with Gross type E EA (n = 24) and with primary reconstruction (n = 21) were excluded. Outcome measures were revisional surgery for anastomotic stricture (RSAS) and number of dilatations required for anastomotic patency without RSAS. The factors that were tested for risk of RSAS or dilatations were distal tracheoesophageal fistula (TEF) at the carina in C-type EA (congenital TEF [CTEF]), type A/B EA, antireflux surgery (ARS), anastomotic leakage, recurrent TEF, and Spitz group and congenital heart disease. Main Results A total of 266 patients, Gross type A (n = 17), B (n = 3), C (n = 237), or D (n = 9) underwent EEA (early n = 240, delayed n = 26). Early anastomotic breakdown required secondary reconstruction in five patients. Of the remaining 261 patients, 17 (6.1%) had RSAS, whereas 244 patients with intact end to end required a median of five (interquartile range: 2–8) dilatations for anastomotic patency. Main risk factors for RSAS or (> 8) dilatations were CTEF, type A/B, ARS, and anastomotic leakage that increased the risk of RSAS or dilatations from 4.6- to 11-fold. Conclusion The risk of severe AS is associated with long-gap EA, significant gastroesophageal reflux, and anastomotic leakage.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".