245. A SYSTEMATIC REVIEW AND META ANALYSIS OF THE NECESSITY FOR ROUTINE JEJUNOSTOMY POST ESOPHAGECTOMY
Bibliographic record
Abstract
Abstract Background The routine use of a feeding jejunostomy tube (FJT) after esophagectomy is increasingly debated, as evidence suggests it may be outdated due to concerns over postoperative and tube-related complications, including bowel dysfunction, infections, and long-term morbidity. This debate is even more pronounced in the era of minimally invasive esophagectomy (MIE), including robotic-assisted MIE, where enhanced recovery protocols favor early oral feeding and alternative nutritional strategies. This systematic review and meta-analysis consolidates existing research to assess the risks and benefits of FJT, guiding clinical decisions on patient selection and postoperative nutrition management. Methods A systematic search was conducted in EMBASE, PubMed, and the Cochrane Library from inception until August 24 2024, identifying 24 studies, including 12 newly published studies. A random-effects meta-analysis was performed to compare paired outcomes between patients with and without FJT. Risk ratios (RR) with 95% confidence intervals (CI) were calculated using the Mantel–Haenszel method, with heterogeneity assessed via I2 statistics. Publication bias was evaluated using funnel plots. Risk of bias was assessed using the Cochrane Risk of Bias Tool for randomized controlled trials (RCTs) and the Newcastle-Ottawa Scale (NOS) for observational studies. Results No significant difference was observed between FJT and non-FJT groups in 30-day mortality, readmission rates, sepsis, thromboembolic events, chyle leak, and recurrent laryngeal nerve palsy. However, several outcomes indicated potential drawbacks of FJT placement: Further subgroup analyses are planned to explore additional factors influencing these outcomes. Conclusion
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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 | 0.023 | 0.061 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.048 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".