Phenotype and outcomes of very early onset and early onset inflammatory bowel diseases in a Montreal pediatric cohort
Bibliographic record
Abstract
Objectives The incidence of very-early-onset inflammatory bowel disease (VEO-IBD) and early-onset IBD (EO-IBD) is increasing. Here, we report their phenotype and outcomes in a Montreal pediatric cohort. Methods We analyzed data from patients diagnosed with IBD between January 2014 and December 2018 from the CHU Sainte-Justine. The primary endpoint was to compare the phenotypes of VEO-IBD and EO-IBD. The secondary endpoints involved comparing outcomes and rates of steroid-free clinical remission (SFCR) at 12 (±2) months (m) post-diagnosis and at last follow-up. Results 28 (14 males) and 67 (34 males) patients were diagnosed with VEO-IBD and EO-IBD, respectively. Crohn's disease (CD) was more prevalent in EO-IBD (64.2% vs. 39.3%), whereas unclassified colitis (IBD-U) was diagnosed in 28.6% of VEO-IBD vs. 10.4% of EO-IBD (p < 0.03). Ulcerative colitis (UC) and IBD-U predominantly presented as pancolitis in both groups (VEO-IBD: 76.5% vs. EO-IBD: 70.8%). Combining all disease subtypes, histological upper GI lesions were found in 57.2% of VEO-IBD vs. 83.6% of EO-IBD (p < 0.009). In each subtype, no differential histological signature (activity, eosinophils, apoptotic bodies, granulomas) was observed between both groups. At 12 m post-diagnosis, 60.8% of VEO-IBD and 62.7% of EO-IBD patients were in SFCR. At a median follow-up of 56 m, SFCR was observed in 85.7% of VEO-IBD vs. 85.0% of EO-IBD patients. Conclusion The rate of patients in SFCR at 1-year post-diagnosis and at the end of follow-up did not significantly differ between both groups.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".