DOZ047.45: The effect of transanastomotic feeding tubes on anastomotic strictures following esophageal atresia repair
Bibliographic record
Abstract
Abstract Purpose Recent studies have identified the use of transanastomotic tubes (TATs) as an independent risk factor for the development of strictures after repair of esophageal atresia (EA). We retrospectively analyzed a 25-year cohort of EA patients (1993–2018) to investigate the effect of TAT use on stricture formation. Methods Following institutional approval (MP-37–2019-2991), a retrospective study of all Type C and Type D EA patients who underwent primary repair was examined. Infants were included if they had surgery within the first two weeks of life and had a least one year of follow-up. Stricture was defined as the presence of symptoms confirmed by imaging and/or endoscopy. A multiple logistic regression model was used to compare stricture in those with and without TATs. Poisson regression was used to evaluate differences in postoperative outcomes listed in Table 1. Results Strictures occurred in 35 of 85 patients (41%). Of those with strictures, 25 (71%) had transanastomotic tubes. There was no significant difference in stricture rates between those with TATs and without TATs (odd ratio (OR) = 1.94, 95% confidence interval (CI): 0.78–5.06, P = 0.161). However, those who had TATs had a significantly higher number of dilations overall (rate ratio (RR) = 1.47, 95% CI: 1.09–2.03, P = 0.014). In patients with TATs, the time to enteral feeding was significantly shorter (RR = 0.37, 95% CI: 0.28–0.49, P < 0.001), but the time to oral feeding was significantly longer (RR = 1.37, CI: 1.20–1.56, P < 0.001). The TAT group had a 34% lower mean hospital length of stay. On multivariate analysis, there remained no difference in stricture rates between the two groups. Conclusion Transanastomotic tubes do not seem to result in increased strictures rates in our cohort, but significantly decrease time to initiation of enteral feeds and reduce the duration of hospital stay.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".