Outcomes of endoscopic retrograde cholangiopancreatography performed in the AM versus PM: does procedural timing matter?
Bibliographic record
Abstract
Abstract Background ERCP is a technically demanding procedure that carries a high cumulative adverse event (AE) rate of >10%. Identifying risk factors for adverse events is paramount. Procedure timing, as a surrogate for endoscopist fatigue, has been shown to influence key quality metrics in colonoscopy, but data on this relationship in ERCP is sparse. Methods We conducted a retrospective cohort study of ERCP procedures performed by 5 experienced staff endoscopists, with or without advanced endoscopy fellow (AEF) involvement, from January 1, 2010 to December 1, 2020 at St Michael’s Hospital, Toronto, Ontario, a regional referral center for therapeutic endoscopy. The primary outcome was the difference in rate of selective deep, duct canulation between AM and PM procedures. Results A total of 5672 ERCP procedures were eligible for inclusion. 2793 (49.2%) procedures were performed in the AM and 2879 procedures (50.8%) were performed in the PM. We found no significant difference in the rate of selective ductal cannulation between AM and PM procedures in the unadjusted (82.8% AM vs. 83.1% P-value = .79) or adjusted (OR = 0.98, 95% CI, 0.85-1.12, P-value = .72) analyses. We found no significant difference in the mean procedural duration or rate of perforation between AM and PM procedures. The rate of immediate bleeding was slightly higher in the AM cohort. Conclusion In our single-center retrospective study, ERCP quality, including selective cannulation rates and immediate adverse events were not significantly different in procedures performed in the morning compared to those performed in the afternoon.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".