Conventional Versus Rosemont Endoscopic Ultrasound Criteria for Chronic Pancreatitis: Comparing Interobserver Reliability and Intertest Agreement
Bibliographic record
Abstract
BACKGROUND: The Rosemont criteria (RC) were recently proposed by expert consensus to standardize endoscopic ultrasound (EUS) features and thresholds for diagnosing chronic pancreatitis (CP); however, they are cumbersome and are not validated. OBJECTIVE: To determine interobserver agreement between RC and conventional criteria (CC), and to assess intertest agreement in the diagnosis of CP. METHODS: Thirty-six consecutive patients who underwent EUS for abdominal pain or pancreatitis were retrospectively reviewed. Anonymized images were independently chosen as best representations of the pancreatic body and reviewed by three experts who recorded the presence of CC and RC features. Agreement (proportion and kappa statistic) between CC and RC was calculated. Interobserver agreement within the CC and RC was assessed. Secondary comparisons with endoscopic retrograde cholangiopancreatography were made where available. RESULTS: Using CC, 60 readings (83.3%) were negative for CP, while 12 readings (16.7%) were positive. Using RC, 59 readings (81.9%) were negative for CP, while 13 (18.1%) were positive. The weighted kappa for interobserver agreement for CC (four categories: normal⁄low probability, indeterminate, high probability or calcific) was 0.50, with 80.0% overall agreement, versus 0.27 and 68.1% for the four RC categories (normal, indeterminate, suggestive of and consistent with). Agreement on a positive diagnosis with CC was 86.1% (P=0.38 [McNemar's exact test]), with a kappa of 0.47; for RC, agreement was lower at 80.6% (P=0.016 [McNemar's exact test]), with a kappa of 0.38. For patients who underwent endoscopic retrograde cholangiopancreatography (n=12), false-negative and false-positive rates between CC and RC did not appear to be different. CONCLUSIONS: The RC do not appear to achieve the goals of improving accuracy and interobserver agreement for diagnosing CP.
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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 | 0.041 | 0.082 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| 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".