Liver Enzyme Elevations Within 3 Months of Diagnosis of Inflammatory Bowel Disease and Likelihood of Liver Disease
Bibliographic record
Abstract
BACKGROUND: Inflammatory bowel disease-associated liver diseases (IBD-LDs) include autoimmune hepatitis (AIH), primary sclerosing cholangitis (PSC), and an overlap syndrome. Prospective unbiased multicenter data regarding the frequency of IBD-LD in patients with pediatric inflammatory bowel disease (IBD) are lacking. We examined early alanine aminotransferase (ALT) and γ-glutamyl transpeptidase (GGT) elevations in children diagnosed as having IBD and assessed the likelihood of IBD-LD. METHODS: Data collected from the prospective observational Pediatric Inflammatory Bowel Disease Collaborative Research Group Registry enrolling children of age <16 years within 30 days of diagnosis. AIH, PSC, and overlap syndrome were diagnosed using local institutional criteria. RESULTS: A total of 1569 subjects had liver enzymes available. Of the total, 757 had both ALT and GGT, 800 had ALT only (no GGT), and 12 had GGT only (no ALT). Overall, 29 of 1569 patients (1.8%) had IBD-LD. IBD-LD was diagnosed in 1 of 661 (0.15%) of patients with both ALT and GGT ≤ 50 IU/L compared with 21 of 42 (50%) of patients with both ALT and GGT > 50 (odds ratio 660, P < 0.0001). Of the 29 patients with IBD-LD, 21 had PSC, 2 had AIH, and 6 had overlap syndrome. IBD-LD was more common in patients with ulcerative colitis and IBD-unclassified (indeterminate colitis) than in those with Crohn disease (4% vs 0.8%, respectively, P < 0.001). CONCLUSIONS: Elevation of both ALT and GGT within 90 days after the diagnosis of IBD is associated with a markedly increased likelihood of IBD-LD. Both ALT and GGT levels should be measured in all of the pediatric patients newly diagnosed as having 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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".