Comparative Effectiveness of Nutritional and Biological Therapy in North American Children with Active Crohnʼs Disease
Bibliographic record
Abstract
BACKGROUND: Therapeutic targets in pediatric Crohn's disease include symptoms, quality of life (QOL), and mucosal healing. Although partial enteral nutrition (PEN), exclusive enteral nutritional (EEN), and anti-tumor necrosis factor alpha (anti-TNF) therapy all improve symptoms, the comparative effectiveness of these approaches to improve QOL and achieve mucosal healing has not been assessed prospectively. METHODS: In a prospective study of children initiating PEN, EEN, or anti-TNF therapy for Crohn's disease, we compared clinical outcomes using the Pediatric Crohn's Disease Activity Index (PCDAI), QOL (IMPACT score), and mucosal healing as estimated by fecal calprotectin (FCP). PCDAI, IMPACT, FCP, and diet (prompted 24-h recall) were measured at baseline and after 8 weeks of therapy. RESULTS: We enrolled 90 children with active Crohn's disease (PCDAI, 33.7 ± 13.7; and FCP, 976 ± 754), of whom 52 were treated with anti-TNF, 22 with EEN, and 16 with PEN plus ad lib diet. Clinical response (PCDAI reduction ≥15 or final PCDAI ≤10) was achieved by 64% on PEN, 88% EEN, and 84% anti-TNF (test for trend P = 0.08). FCP ≤250 μg/g was achieved with PEN in 14%, EEN 45%, and anti-TNF 62% (test for trend P = 0.001). Improvement in overall QOL was not statistically significantly different between the 3 groups (P = 0.86). However, QOL improvement was the greatest with EEN in the body image (P = 0.03) domain and with anti-TNF in the emotional domain (P = 0.04). CONCLUSIONS: Although PEN improved clinical symptoms, EEN and anti-TNF were more effective for decreasing mucosal inflammation and improving specific aspects of QOL.
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 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".