P311 Reliability of computed tomography enterography for evaluation of stricturing Crohn’s disease: Development of a Crohn’s disease stricture index
Bibliographic record
Abstract
Abstract Background Computed tomography enterography (CTE) is frequently used to assess stricturing Crohn’s disease (CD). However, the reliability of CTE items used for assessment has not been established and there is no validated radiologic stricture severity index. Methods We conducted a retrospective study of 43 patients with symptomatic, terminal ileal stricturing CD. Four radiologists assessed a comprehensive list of pre-defined radiologic items potentially associated with stricture severity in 48 CTE scans in two separate rounds in random order. Reliability was quantified using the intraclass correlation coefficient (ICC). Items with at least moderate (ICC≥0.41) inter-rater reliability that were correlated with a visual analogue scale of overall stricture severity were candidate items for the development of a CTE stricture index. Results Inter-rater reliability was almost perfect for assessment of luminal diameter of pre-stenotic dilation (ICC 0.817 [95% confidence interval 0.703, 0.878]), substantial for stricture length (ICC 0.628 [0.419, 0.797]), and moderate for stricture wall thickness (0.482 [0.330, 0.601]). Intra-rater reliability was almost perfect (ICC ≥ 0.850) for all three items. A stricture severity index was derived and was well calibrated (optimism-adjusted calibration slope = 1.009), with scores calculated as the sum of stricture length (cm) + luminal diameter of pre-stenotic dilation (mm) + 5 x stricture wall thickness (mm). Conclusion Stricture length, prestenotic dilation, and stricture wall thickness can be reliably assessed, and are component items for a novel CTE stricture index (CTE-SI) of stricture severity for CD-related terminal ileal strictures. Additional external index validation for clinical and research contexts is required.
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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 | 0.012 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".