INFLIXIMAB AND BONE MINERAL DENSITY IN PEDIATRIC CROHN'S DISEASE
Bibliographic record
Abstract
Diminished bone mineral density (BMD) is a recognized complication of Crohn's disease (CD), and has received increasing attention in the past few years. Infliximab (anti-tumor necrosis factor α) treatment is associated with improved bone mineral density. The pathophysiology of bone disease in patients with CD is unclear but may include a direct effect of inflammatory cytokines. Tumor necrosis factor alpha (TNF-α) plays a key role in the pathogenesis of CD inflammation and has been implicated in the pathogenesis of CD related bone disease. CD related bone disease would be expected to improve following therapy with infliximab. To study the effect of infliximab on BMD in pediatric patients with CD. A retrospective case study of all CD pts. <18 years receiving infliximab at our center. BMD studies (lumbar spine study with z- scores) pre infliximab were compared to that post therapy using paired student t-tests. 20 patients receiving infliximab (5-10 mg/kg per dose) were identified. There were 10 male and 10 female, age range 10-18 years, all on immunosuppressive agents prior to initiation of infliximab. Patients received 2-27 (mean = 12) infusions. Disease location was ileocolonic (10), colonic (8), perianal (2), and duodenal (2). The z-score pre infliximab ranged from + 0.2 to − 5 with a mean of −1.6, 65% had z-score <−1. The z-score post infliximab ranged from −0.2 to −2.7 with a mean of −1.2. This represented an increase in BMD of 0.4 (P < 0.01). In patients with CD treatment with infliximab improves BMD. This suggests that TNF-α may play a role in CD induced bone disease and that treatment with infliximab may result in BMD improvement.
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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 | 0.002 |
| 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 | 0.000 |
| 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".