Growth Retardation in Early-Onset Inflammatory Bowel Disease: Should We Monitor and Treat These Patients Differently?
Bibliographic record
Abstract
Growth impairment and associated pubertal delay are common complications of pediatric inflammatory bowel disease (IBD), particularly Crohn's disease (CD). Chronic undernutrition (related primarily to inadequate intake) and pro-inflammatory cytokines are the two major and interrelated contributory factors. Pathogenic mechanisms include interference with growth hormone/insulin-like growth factor-1 axis, with gonadotropin-releasing hormone secretion patterns, and direct cytokine effects on growing bone. Chronic corticosteroid therapy compounds disease-related causes of growth impairment. The influence on growth of polymorphisms in IBD susceptibility or modifier genes is under study. Accurate recognition of impaired growth requires appreciation of normal growth. Pre-illness standard deviation scores (SDS) for height should be obtained and compared with height SDS at diagnosis, so that the impact of disease on growth can be fully appreciated. The greater the deficit prior to recognition of IBD, the greater is the demand for catch-up growth. Height velocity should be regularly monitored and its adequacy for age and pubertal stage assessed. Restoration and maintenance of pre-illness growth pattern indicate success of therapy. Current treatment regimens limit use of corticosteroids, via optimization of immunomodulatory drugs, use of enteral nutrition in CD, and, if necessary, surgery for ulcerative colitis and for intestinal complications of localized CD. Biologic agents with the potential for mucosal healing hold promise of growth enhancement even among children, whose growth with previously available therapies remained compromised. For all therapies, there is a window of opportunity to achieve normal growth before puberty is too advanced.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".