Multiple Cholecystoenteric Fistulae With Bouveret Syndrome and Acute Pancreatitis: A Rare Combination
Bibliographic record
Abstract
Multiple cholecystoenteric fistulae, Bouveret syndrome (a form of gallstone ileus), and acute pancreatitis occurring together is very rare. Diagnosis is seldom clinical and is mostly based on computerised tomography (CT) or magnetic resonance imaging (MRI). Endoscopy and minimally invasive surgery have revolutionised the treatment of Bouveret syndrome and cholecystoenteric fistula, respectively, over the last two decades. Laparoscopic repair of cholecystoenteric fistula followed by cholecystectomy is successful on a consistent basis with skilled laparoscopic suturing and advanced laparoscopy. In patients with Bouveret syndrome, when the stone is <4cm and is in the proximal duodenum, it is usually amenable for endoscopic extraction with snares, nets, forceps and lithotripsy. When endoscopy is unavailable or fails, laparoscopic surgery is suitable for these patients. However, stones >4 cm, located in the distal duodenum, multiple fistulae, and associated acute pancreatitis may necessitate open surgery. We present here a case of a 65-year-old Indian female with multiple cholecystoenteric fistulae and Bouveret syndrome with acute pancreatitis with a 6.5 cm gallstone diagnosed on CT scan and MRI and treated successfully by open surgery. We also review the current literature on the management of this complex problem.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".