Multicenter retrospective cohort of EUS-guided anterograde pancreatic duct access
Bibliographic record
Abstract
Abstract Background and study aims Pancreatic duct (PD) cannulation may be difficult during conventional endoscopic retrograde cholangiopancreatography (ERCP) due to underlying pathology, anatomical variants or surgically altered anatomy. Pancreatic access in these cases previously necessitated percutaneous or surgical approaches. Endoscopic ultrasound (EUS) allows for an alternative and can be combined with ERCP for rendezvous during the same procedure, or for other salvage options. Patients and methods Patients with attempted EUS access of the PD from tertiary referral centers between 2009 and 2022 were included in the cohort. Demographic data, technical data, procedural outcomes and adverse events were collected. The primary outcome was rendezvous success. Secondary outcomes included rates of successful PD decompression and change in procedural success over time. Results The PD was accessed in 105 of 111 procedures (95 %), with successful subsequent ERCP in 45 of 95 attempts (47 %). Salvage direct PD stenting was performed in 5 of 14 attempts (36 %). Sixteen patients were scheduled for direct PD stenting (without rendezvous) with 100 % success rate. Thus 66 patients (59 %) had successful decompression. Success rates improved from 41 % in the first third of cases to 76 % in the final third. There were 13 complications (12 %), including post-procedure pancreatitis in seven patients (6 %). Conclusions EUS-guided anterograde pancreas access is a feasible salvage method if retrograde access fails. The duct can be cannulated, and drainage can be achieved in the majority of cases. Success rates improve over time. Future research may involve investigation into technical, patient and procedural factors contributing to rendezvous success.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".