Factors associated with delayed bleeding following ampullectomy: A retrospective cohort study
Bibliographic record
Abstract
Abstract Introduction and objectives Endoscopic ampullectomy is the preferred treatment for selected periampullary lesions, yet up to 10.6% of patients may experience delayed bleeding post‐procedure. This study aims to identify predictors for bleeding, which remain poorly understood. Methods This was a single‐center retrospective cohort study of adult patients who underwent endoscopic ampullectomy (EA) between January 2011 and September 2023. The primary outcome was the risk factors for delayed bleeding, defined as post‐procedural bleeding that necessitated either an emergency department visit, hospital admission, blood transfusion, or re‐intervention. Secondary outcomes included adverse events, such as perforation and pancreatitis. Results A total of 113 patients underwent EA, and 25 (22.1%) experienced delayed bleeding. Of these, 20 (80%) required repeat endoscopy, six (24%) needed blood transfusions, and three (12%) were managed conservatively. Multivariable logistic regression analysis identified international normalized ratio ≥1.2 (odds ratio [OR] 3.32, 95% confidence interval [95% CI] 1.03–10.74, p = 0.05), presence of high‐grade dysplasia or intramucosal cancer (OR 3.76, 95% CI 1.20–11.81, p = 0.03), female sex (OR 3.14, 95% CI 1.11–8.93, p = 0.03), size of lesion (OR 1.04, 95% CI 1.01–1.08, p = 0.03) and procedure duration (OR 0.98, 95% CI 0.97–0.99, p = 0.04) as independent predictors of delayed bleeding. Conclusion Several factors, including features of high‐grade dysplasia‐intramucosal cancer, international normalized ratio ≥1.2, female sex, lesion size, and procedure duration are associated with delayed post‐ampullectomy bleeding. These factors should be taken into consideration when strategizing the reduction of post‐ampullectomy bleeding.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".