Treatment of anastomotic leak after esophagectomy: insights of an international case vignette survey and expert discussions
Bibliographic record
Abstract
Anastomotic leak (AL) is a severe complication after esophagectomy. Clinical presentation of AL is diverse and there is large practice variation regarding treatment of AL. This study aimed to explore different AL treatment strategies and their underlying rationale. This mixed-methods study consisted of an international survey among upper gastro-intestinal (GI) surgeons and focus groups with expert upper GI surgeons. The survey included 10 case vignettes and data sources were integrated after separate analysis. The survey was completed by 188 respondents (completion rate 69%) and 6 focus groups were conducted with 20 international experts. Prevention of mortality was the most important goal of primary treatment. Goals of secondary treatment were to promote tissue healing, return to oral feeding and safe hospital discharge. There was substantial variation in the preferred treatment principles (e.g. drainage or defect closure) and modalities (e.g. stent or endoVAC) within different presentations of AL. Patients with local symptoms were treated by supportive means only or by non-surgical drainage and/or defect closure. Drainage was routinely performed in patients with intrathoracic collections and often combined with defect closure. Patients with conduit necrosis were predominantly treated by resection and reconstruction of the anastomosis or by esophageal diversion. This mixed-methods study shows that overall treatment strategies for AL are determined by vitality of the conduit and presence of intrathoracic collections. There is large variation in preferred treatment principles and modalities. Future research may investigate optimal treatment for specific AL presentations and aim to develop consensus-based treatment guidelines for AL after esophagectomy.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".