Development of an index to define overall disease severity in IBD
Bibliographic record
Abstract
BACKGROUND AND AIM: Disease activity for Crohn's disease (CD) and UC is typically defined based on symptoms at a moment in time, and ignores the long-term burden of disease. The aims of this study were to select the attributes determining overall disease severity, to rank the importance of and to score these individual attributes for both CD and UC. METHODS: Using a modified Delphi panel, 14 members of the International Organization for the Study of Inflammatory Bowel Diseases (IOIBD) selected the most important attributes related to IBD. Eighteen IOIBD members then completed a statistical exercise (conjoint analysis) to create a relative ranking of these attributes. Adjusted utilities were developed by creating proportions for each level within an attribute. RESULTS: For CD, 15.8% of overall disease severity was attributed to the presence of mucosal lesions, 10.9% to history of a fistula, 9.7% to history of abscess and 7.4% to history of intestinal resection. For UC, 18.1% of overall disease severity was attributed to mucosal lesions, followed by 14.0% for impact on daily activities, 11.2% C reactive protein and 10.1% for prior experience with biologics. Overall disease severity indices were created on a 100-point scale by applying each attribute's average importance to the adjusted utilities. CONCLUSIONS: Based on specialist opinion, overall CD severity was associated more with intestinal damage, in contrast to overall UC disease severity, which was more dependent on symptoms and impact on daily life. Once validated, disease severity indices may provide a useful tool for consistent assessment of overall disease severity in patients with IBD.
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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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".