Asia Pacific association of gastroenterology consensus statements on histopathological evaluation of inflammatory bowel diseases
Bibliographic record
Abstract
Background: Mucosal histological activity is increasingly valued as a treatment endpoint in inflammatory bowel diseases (IBD). In the Asia Pacific region, the utility and acceptability of IBD histology as a treatment endpoint are uncertain due to the heterogeneity of IBD prevalence, resourcing and level of knowledge among practitioners. There is an opportunity to engage clinicians to harmonise histology reporting and collaborate with pathologists in this field. Objectives: We aimed to develop consensus statements through anonymous voting on histological features, processing, reporting and relevance to treatment outcomes in IBD, including ulcerative colitis (UC) and Crohn's disease (CD). Design: The consensus document was developed through a comprehensive literature review, followed by a deliberation process among experts in the field. Methods: Representatives of the Asia Pacific Association of Gastroenterology, in collaboration with pathologists, voted anonymously in accordance with modified Delphi methodology on statements relevant to IBD and histology. Domains of interest were histological features of UC and CD, relevance to clinical management and the potential utility of artificial intelligence (AI) in grading histological disease severity. Level of evidence and recommendation grade were included in accordance with the National Health and Medical Research Council, Australia guidelines of Australia. Results: Consensus was reached on 37 out of 38 statements concerning definitions, pathology processing and reporting, scoring system and relevance to clinical outcomes. Knowledge gaps were identified with uncertainty over the role of AI. Conclusion: These consensus statements provide recommendations, with specific relevance to the Asia Pacific region, on the role of histology in IBD to harmonise its use. The statements will promote understanding and applicability in research and in the routine management of IBD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".