Expert Consensus on Optimal Acquisition and Development of the International Bowel Ultrasound Segmental Activity Score [IBUS-SAS]: A Reliability and Inter-rater Variability Study on Intestinal Ultrasonography in Crohn’s Disease
Bibliographic record
Abstract
BACKGROUND AND AIMS: Intestinal ultrasound [IUS] is an accurate, patient-centreed monitoring tool that objectively evaluates Crohn's disease [CD] activity. However no current, widely accepted, reproducible activity index exists to facilitate consistent IUS identification of inflammatory activity. The aim of this study is to identify key parameters of CD inflammation on IUS, evaluate their reliability, and develop an IUS index reflecting segmental activity. METHODS: There were three phases: [1] expert consensus Delphi method to derive measures of IUS activity; [2] an initial, multi-expert case acquisition and expert interpretation of 20 blinded cases, to measure inter-rater reliability for individual measures; [3] refinement of case acquisition and interpretation by 12 international experts, with 30 blinded case reads with reliability assessment and development of a segmental activity score. RESULTS: Delphi consensus: 11 experts representing seven countries identified four key parameters including: [1] bowel wall thickness [BWT]; [2] bowel wall stratification; [3] hyperaemia of the wall [colour Doppler imaging]; and [4] inflammatory mesenteric fat. Blind read: each variable exhibited moderate to substantial reliability. Optimal, standardised image and cineloop acquisition were established. Second blind read and score development: intra-class correlation coefficient [ICC] for BWT was almost perfect at 0.96 [0.94-0.98]. All four parameters correlated with the global disease activity assessment and were included in the final International Bowel Ultrasound Segmental Activity Score with almost perfect ICC (0.97 [0.95-0.99, p <0.001]). CONCLUSIONS: Using expert consensus and standardised approaches, identification of key activity measurements on IUS has been achieved and a segmental activity score has been proposed, demonstrating excellent reliability.
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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 | 0.244 | 0.336 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".