Simple Endoscopic Score of Crohn Disease and Magnetic Resonance Enterography in Children
Bibliographic record
Abstract
OBJECTIVES: We aimed to explore the ability of magnetic resonance enterography (MRE) to impute the simple endoscopic score of Crohn disease (SES-CD) in children with CD, in whom failure of ileal intubation is common and may impair SES-CD calculation in clinical studies. METHODS: This is a substudy of the prospective ImageKids study in which children with CD underwent ileocolonoscopy (scored by SES-CD) and MRE (scored on a 100 mm visual analogue scale [VAS] and by MaRIA). Mucosal healing (MH) was defined as SES-CD <3, MRE-VAS <20 mm, and/or MaRIA <7. RESULTS: A total of 237 children (22 centers, age 11.5 ± 3.3 years), were enrolled. Ileal intubation has failed in 40 of 237 (17%). The agreement between SES-CD and MRE was 75% (k = 0.508, P < 0.001) in the ileum, and 68% to 85% in the colonic segments (k = 0.21-0.50, P < 0.001). The sensitivity and specificity of ileal MRE-VAS for MH were 91.7% (95% confidence interval 0.84-0.96) and 53.1% (95% confidence interval 0.43-0.63), respectively. The ileal MaRIA score (calculated in 33/40) was higher in the children without ileal intubation than in the others (20.5 ± 7.1 vs 15.1 ± 10.8, respectively, P = 0.0018). In 7% (16/237) of children, isolated active ileal disease would have been missed when considering SES-CD only. A multivariable model predicted the ileal SES-CD subscore from the MaRIA: SES-CDileum = 1.145 + 0.169 × MaRIAileum rounded to the nearest whole number (R = 0.17). Applying this model to the children without ileal intubation revealed that 29 of 33 (88%) had ileal disease; 8 of 29 patients (28%) with normal colonic SES-CD had imputed ileal SES-CD ≥3. CONCLUSIONS: MRE is useful for imputing the ileal disease in pediatric clinical studies, overcoming the problem of ileal nonintubation.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".