Exclusive Enteral Nutrition Therapy in Paediatric Crohn’s Disease Results in Long-term Avoidance of Corticosteroids: Results of a Propensity-score Matched Cohort Analysis
Bibliographic record
Abstract
BACKGROUND AND AIMS: Exclusive enteral nutrition [EEN] is recommended as a first-line induction therapy for paediatric Crohn's disease [CD] although corticosteroids [CS] are still used commonly. Our aim was to compare short- and long-term disease outcomes of paediatric CD patients initially managed with either EEN or CS. METHODS: Medical records of newly diagnosed paediatric CD patients treated with EEN or CS as induction therapy were retrospectively reviewed. To minimise selection bias inherent in observational cohort studies, propensity analysis was carried out. Data on anthropometrics, medical history, and presenting phenotype were collected at time of diagnosis [baseline]; outcomes of interest, including medication use, hospitalisation, surgical procedures, and disease progression were assessed up to 6 years following diagnosis. RESULTS: Of 127 patients reviewed, a total of 111 propensity-score matched CD patients receiving EEN [n = 76] or CS [n = 35] were analysed. By 4-12 weeks of induction therapy, 86.6% of EEN-treated patients achieved remission (Paediatric Crohn's Disease Activity Index [PCDAI] ≤ 7.5) compared with 58.1% of patients in the CS-treated group [p < 0.01]. Choice of EEN over CS for induction was associated with avoidance of corticosteroids over a 6-year follow-up period. Analysis of long-term linear growth, hospitalisation, need for biologic therapy, or surgical intervention did not reveal any significant differences. CONCLUSIONS: These findings suggest that EEN induction therapy is more effective in achieving early remission and is associated with long-term steroid avoidance without increased use of biologics or need for surgery.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".