A275 REVISITING THE DIAGNOSTIC YIELD OF ERCP BRUSH CYTOLOGY FOR INDETERMINATE BILIARY STRICTURES
Bibliographic record
Abstract
Abstract Background Endoscopic Retrograde Cholangiopancreatography (ERCP) brush cytology is the most frequently used tool for sampling indeterminate biliary strictures. Previous studies have demonstrated that the diagnostic yield of brush cytology for malignant biliary strictures is 60%. With improved diagnostic tools, sampling techniques and specimen processing, the yield of ERCP brush cytology may be higher. Aims To assess the diagnostic yield of ERCP brush cytology in patients with indeterminate biliary strictures and to determine factors associated with positive diagnosis. Methods This is a retrospective study of all patients who underwent ERCP with brush cytology at University Health Network (UHN) from October 2016 to September 2019. The cytological samples were taken as follows: the cytology brush is introduced into the stricture ten times under direct fluoroscopy guidance. The brush was cut and placed into a methanol based buffered solution (CytoLyt®). Residual sample was then flushed out of the catheter with the solution and into the sample container. Patient demographic, clinical, procedural and pathological data was collected by chart review. All patients were followed for a minimum of three months after their index ERCP. Post-ERCP sampling via repeat ERCP brushings, endoscopic ultrasound fine needle biopsy, percutaneous biopsy or surgical resection was recorded. Results A total of 97 patients underwent ERCP with brush cytology during the study period (43 females, median age 69 years). Fifty-nine patients (84%) were diagnosed with malignancy via ERCP brush cytology. Using follow up sampling, surgical resection and clinical follow up as the gold standard, the sensitivity, specificity, positive predictive value, negative predictive value and accuracy were 84%, 100%, 100%, and 71% respectively. Patient demographics, degree of cholestasis or stricture location had no significant impact on these outcomes. Conclusions This study shows a high diagnostic yield for ERCP with brush cytology for patients with indeterminate biliary strictures. Large prospective studies using updated tools, techniques and specimen handling processes are needed to confirm our observations. Funding Agencies None
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".