Global Variation in Use of Enteral Nutrition for Pediatric Crohn Disease
Bibliographic record
Abstract
OBJECTIVES: Exclusive enteral nutrition (EEN) is an effective induction treatment for pediatric Crohn disease. Given the center-based variation in use and diversity in practice, we constructed a survey aimed at sharing experience and strategies in administering EEN, stimulating further research, and optimizing therapy. METHODS: This survey was constructed after consultation with experts and designed to address key knowledge gaps. The survey was disseminated through the Pediatric IBD Porto Group of ESPGHAN, Canadian Children IBD Network, selective experts, and was sent twice through the Pediatric Gastrointestinal-Bulletin Board (PEDGI-BB). Data were collected into REDCap and analyzed using descriptive statistics. RESULTS: In total, 146 participants from 26 countries completed the survey. Sixty-five percentage of participants were general, non-inflammatory bowel diseases (IBD)-focused pediatric gastroenterologists, 21% were IBD-focused, and 10% were dietitians. The most common indications (∼90% use) were for ileocecal and ileocolonic disease (Paris L1 and L3). The most common duration was 8 weeks and 66% preferred oral to nasogastric administration. Most (63%) did not allow any additional intake and 69% instructed patients to continue partial enteral nutrition (EN) after completing treatment. Dietitians were identified as essential to EEN success while the primary challenges of EEN programs were adherence and lack of support. Regional and professional practice differences were observed in EEN indication, age, exclusivity, program structure/support, and cost coverage. CONCLUSIONS: We found significant variation in practice and use of EEN with several regional and professional differences. Global variation offers opportunities for research and improving care. This survey establishes a framework and provides resources for collaboration and information sharing.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".