Application of a pattern‐based approach to histological diagnosis in very early onset IBD (VEO‐IBD) in a multicentric cohort of children with emphasis on monogenic disease with IBD‐like morphology
Bibliographic record
Abstract
AIMS: Very early-onset inflammatory bowel disease (VEO-IBD) is a clinical umbrella term referring to IBD-like symptoms arising in children before the age of 6 years, encompassing both 'pure' IBD, such as ulcerative colitis (UC) and Crohn's disease (CD) and monogenic diseases (MDs), the latter often involving genes associated with primary immunodeficiencies. Moreover, histological features in gastrointestinal (GI) biopsies in MD can also have IBD-like morphology, making differential diagnosis difficult. Correct diagnosis is fundamental, as MDs show a more severe clinical course and their inadequate/untimely recognition leads to inappropriate therapy. METHODS AND RESULTS: Biopsy samples from the lower and upper GI tract of 93 clinically diagnosed VEO-IBD children were retrospectively selected in a multicentre cohort and histologically re-evaluated by 10 pathologists blinded to clinical information. Each case was classified according to morphological patterns, including UC-like; CD-like; enterocolitis-like; apoptotic; eosinophil-rich; and IBD-unclassified (IBD-U). Nine (69%) MD children showed IBD-like morphology; only the IBD-U pattern correlated with MD diagnosis (P = 0.02) (available in 64 cases: 51 non-MD, true early-onset IBD/other; 13 MD cases). MD patients showed earlier GI symptom onset (18.7 versus 26.9 months) and were sent to endoscopy earlier (22 versus 37 months), these differences were statistically significant (P < 0.05). Upper GI histology was informative in 37 biopsies. CONCLUSIONS: The diagnosis of the underlying cause of VEO-IBD requires a multidisciplinary setting, and pathology, while being one of the fundamental puzzle pieces, is often difficult to interpret. A pattern-based histological approach is therefore suggested, thus aiding the pathologist in VEO-IBD reporting and multidisciplinary discussion.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".