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Record W4413307108 · doi:10.1177/17562848251363703

Asia Pacific association of gastroenterology consensus statements on histopathological evaluation of inflammatory bowel diseases

2025· article· en· W4413307108 on OpenAlexaff
Rupert W. Leong, Thanaboon Chaemsupaphan, Huiyu Lin, Wee Chian Lim, Choon Jin Ooi, John David Chetwood, Ren Mao, Hualian Wu, Govind Makharia, Vineet Ahuja, Rupa Banerjee, Raja Atreya, Julajak Limsrivilai, Satimai Aniwan, Pises Pisespongsa, Ida Hilmi, Raja Affendi Raja Ali, Wai K. Leung, Siew C. Ng, Byong Duk Ye, Taku Kobayashi, Katsuyoshi Matsuoka, C.Y.P. Chau, Anapat Sanpavat, Chia‐Tung Shun, Pavitratha Puspanathan, Richard B. Gearry, Silvio Danese, Christopher Ma, Aviv Pudipeddi, Sudarshan Paramsothy

Bibliographic record

VenueTherapeutic Advances in Gastroenterology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineInflammatory bowel diseaseGastroenterologyInternal medicineInflammatory Bowel DiseasesUlcerative colitisAsia pacificAssociation (psychology)PathologyGeneral surgeryDisease

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.197
metaresearch head score (Gemma)0.264
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.197
Threshold uncertainty score0.990

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1970.264
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0110.009
Science and technology studies0.0040.005
Scholarly communication0.0070.005
Open science0.0080.012
Research integrity0.0110.013
Insufficient payload (model declined to judge)0.0060.004

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.

Opus teacher head0.011
GPT teacher head0.307
Teacher spread0.296 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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