A Novel UC Exclusion Diet and Antibiotics for Treatment of Mild to Moderate Pediatric Ulcerative Colitis: A Prospective Open-Label Pilot Study
Bibliographic record
Abstract
BACKGROUND: As the microbiome plays an important role in instigating inflammation in ulcerative colitis (UC), strategies targeting the microbiome may offer an alternative therapeutic approach. The goal of the pilot trial was to evaluate the potential efficacy and feasibility of a novel UC exclusion diet (UCED) for clinical remission, as well as the potential of sequential antibiotics for diet-refractory patients to achieve remission without steroids. METHODS: This was a prospective, single-arm, multicenter, open-label pilot study in patients aged 8-19, with pediatric UC activity index (PUCAI) scores >10 on stable maintenance therapy. Patients failing to enter remission (PUCAI < 10) on the diet could receive a 14-day course of amoxycillin, metronidazole and doxycycline (AMD), and were re-assessed on day 21. The primary endpoint was intention-to-treat (ITT) remission at week 6, with UCED as the only intervention. RESULTS: > 0.05). Eight patients received treatment with antibiotics after failing on the diet; 4/8 (50.0%) subsequently entered remission 3 weeks later. CONCLUSION: The UCED appears to be effective and feasible for the induction of remission in children with mild to moderate UC. The sequential use of UCED followed by antibiotic therapy needs to be evaluated as a microbiome-targeted, steroid-sparing strategy.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".