What is the impact of the use of transanastomotic feeding tube on patients with esophageal atresia: a systematic review and meta-analysis
Bibliographic record
Abstract
The transanastomotic feeding tube (TAFT) is widely used around the world in patients with esophageal atresia (EA). However, the safety of the use of TAFT is still unknown and remains to be clarified. The following electronic databases were searched: PubMed, EMBASE and Cochrane. Studies comparing outcomes in patients with the use of TAFT (TAFT+) and patients without the use of TAFT (TAFT-) were scrutinized. The quality of included studies was evaluated with the Newcastle–Ottawa scale score. Statistical heterogeneity was assessed using the I 2 value. A fixed or random-effect model was applied. Four retrospective controlled studies involving 455 patients were included. The pooled estimates showed that the use of TAFT significantly increased the risk of stricture, with a risk ratio (RR) of 1.83 (95% CI 1.30–2.58; P = 0.0005). The meta-analyses of other postoperative complications did not show significant differences between TAFT+ and TAFT- group, with a RR of 1.65 (95% CI 0.93–2.93; P = 0.09) for anastomotic leakage, 0.91 (95% CI 0.34–2.44; P = 0.85) for sepsis, 1.89 (95% CI 0.22–16.20; P = 0.56) for tracheomalacia, 0.50 (95% CI 0.13–1.93; P = 0.31) for gastroesophageal reflux, 1.29 (95% CI 0.28–5.92; P = 0.74) for wound infection, and 0.97 (95% CI 0.03–36.75; p = 0.99) for pneumonia. This study demonstrates that the use of TAFT in patients with EA significantly increases the risk of stricture. However, TAFT is not associated with other complications, including anastomotic leakage, sepsis, tracheomalacia, gastroesophageal reflux, wound infection and pneumonia.
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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 | 0.013 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.029 | 0.047 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".