Abnormal Liver Biochemistry Is Common in Pediatric Inflammatory Bowel Disease
Bibliographic record
Abstract
BACKGROUND: Liver enzymes (LEs) abnormalities associated with pediatric inflammatory bowel diseases (IBD) are understudied. We undertook to describe the development and associations of abnormal LEs in pediatric IBD. METHODS: We ascertained a cohort of 300 children with IBD and collected retrospective data. A Kaplan-Meier analysis determined the time to development of different thresholds of abnormal LEs. Associations between clinical variables and the development of abnormal LEs were determined. RESULTS: The probability of developing the first episode of abnormal LEs above the upper limit of normal (ULN) within 150 months was 58.1% (16.3% by 1 mo post-IBD diagnosis). There was a 6% prevalence of primary sclerosing cholangitis (PSC) or autoimmune sclerosing cholangitis (ASC) in this cohort. Of those diagnosed with PSC/ASC, 93% had persistent LE elevations at a threshold of >2× ULN, while those without PSC/ASC had a 4% probability of this abnormality. Elevated gamma glutamyltranspeptidase levels of 252 U/L had a 99% sensitivity and 71% specificity for PSC/ASC in IBD. After exclusion of patients with PSC/ASC, corticosteroids, antibiotics, and exclusive enteral nutrition demonstrated strongly positive associations with the first development of abnormal LEs >ULN (hazard ratio 2.1 [95% confidence interval, 1.3-3.3], hazard ratio 5.6 [95% confidence interval, 3.6-8.9], hazard ratio 4.2 [95% confidence interval, 1.6-11.3], respectively). CONCLUSIONS: Abnormal LEs are common in pediatric IBD and occur early. PSC/ASC is associated with persistently high LEs and gamma glutamyltranspeptidase levels >252 U/L. Children with IBD are at risk of elevated LEs if they require medications other than 5-ASA to induce IBD remission.
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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 | 0.000 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".