SpHincterotomy for Acute Recurrent Pancreatitis Randomized Trial
Bibliographic record
Abstract
OBJECTIVES: In patients with acute recurrent pancreatitis (ARP), pancreas divisum, and no other etiologic factors, endoscopic retrograde cholangiopancreatography (ERCP) with minor papilla endoscopic sphincterotomy (miES) is often performed to enlarge the minor papillary orifice, based on limited data. The aims of this study are to describe the rationale and methodology of a sham-controlled clinical trial designed to test the hypothesis that miES reduces the risk of acute pancreatitis. METHODS: The SpHincterotomy for Acute Recurrent Pancreatitis (SHARP) trial is a multicenter, international, sham-controlled, randomized trial comparing endoscopic ultrasound + ERCP with miES versus endoscopic ultrasound + sham for the management of ARP. A total of 234 consented patients having 2 or more discrete episodes of acute pancreatitis, pancreas divisum confirmed by magnetic resonance cholangiopancreatography, and no other clear etiology for acute pancreatitis will be randomized. Both cohorts will be followed for a minimum of 6 months and a maximum of 48 months. RESULTS: The trial is powered to detect a 33% risk reduction of acute pancreatitis frequency. CONCLUSIONS: The SHARP trial will determine whether ERCP with miES benefits patients with idiopathic ARP and pancreas divisum. Trial planning has informed the importance of blinded outcome assessors and long-term follow-up.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 0.001 |
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".