Predictors of failure of endoscopic retrograde cholangiography in clearing bile duct stone on the initial procedure
Bibliographic record
Abstract
BACKGROUND/AIMS: The aim of this study is to predict cases where the clearance of the biliary system from stones at the initial endoscopic retrograde cholangiopancreatography (ERCP) might be of value for better risk-stratifying patients. We attempted to identify factors that are associated with a higher failure rate of clearing the biliary system on the index ERCP. PATIENTS AND METHODS: This is a retrospective study from January 2008 to January 2015. All patients with bile duct stones confirmed on ERCP were included in this study. Patients who had prior attempts of bile duct stone extraction were excluded. RESULTS: A total of 554 ERCPs were performed to extract biliary duct stones from 426 patients. The mean age was 46.3 years and 41.7% were males. The group where the index ERCP did not clear the biliary system tended to be older (50.4 vs. 45.2 years, P = 0.03). On multivariate analysis, the presence of fever (OR 4.64; 95% CI, 1.66-12.79), a larger number of filling defects (OR 1.34; 95% CI, 1.13-1.93), presence of a stricture distal to a stone (OR 4.63; 95% CI, 1.36-15.78), the use of an extraction basket (OR 3.23; 95% CI, 1.56-6.74), and/or mechanical lithotripsy (OR 3.05; 95% CI, 1.10-8.49) were all associated with a lower odds of clearing the biliary system. The use of an extraction balloon was associated with the success of clearing the biliary system (99.7% vs. 77.4%, P < 0.01) and a lower odds of failing (OR 0.01; 95% CI, 0.00-0.08) on multivariate analysis. CONCLUSION: A few of the characteristics that are found on cholangiography at the index ERCP could be used to identify patients that might require more than one ERCP to clear the biliary system from stones.
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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 | 0.009 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".