Characteristics and Outcomes of ERCP at a Canadian Tertiary Centre: Initial Results from a Prospective High-Fidelity Biliary Endoscopy Registry
Bibliographic record
Abstract
BACKGROUND: Endoscopic retrograde cholangiopancreatography (ERCP) is an essential procedure in the management of pancreatic and biliary disease. While its role is firmly established, further well-designed prospective ERCP research is required, as a large portion of previous work has employed retrospective or administrative methodologies, both prone to potential biases. The aim of the Calgary Registry for Advanced and Therapeutic Endoscopy (CReATE) is to be a high-fidelity prospective multicentre registry. METHODS: The study population consisted of consecutive adult ERCP patients from September 2018 to September 2019. Informed consent was acquired for each patient. All relevant preprocedural, procedural, peri-procedural and postprocedural data were captured in real time by a full-time third-party research assistant directly observing procedures. Outcomes were ascertained by comprehensive medical record review and patient phone interview 30 days after the index procedure. RESULTS: Five endoscopists performed 895 ERCP procedures, 90.1% of which were deemed successful. Suspected choledocholithiasis was the most common indication for ERCP, followed by suspected or confirmed stricture(s), at 61.0% and 29.5%, respectively. 61.0% of procedures were performed on ERCP-naive patients. Post-ERCP pancreatitis occurred following 4.9% of procedures, with clinically significant bleeding or perforation occurring following 1.8% and 0.1% of procedures, respectively. DISCUSSION: Through 12 months, CReATE captured 895 procedures prospectively, with each entry containing over 300 data fields. Active expansion to additional tertiary centres is underway, and this will enhance the existing data pool. CReATE has the potential to improve multiple facets of ERCP, including training, optimal procedural techniques, mitigation of adverse events and personalized patient care.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".