Azithromycin and metronidazole versus metronidazole-based therapy for the induction of remission in mild to moderate paediatric Crohn’s disease : a randomised controlled trial
Bibliographic record
Abstract
OBJECTIVE: Crohn's disease (CD) pathogenesis associated with dysbiosis and presence of pathobionts in the lumen, intracellular compartments and epithelial biofilms. Azithromycin is active in all three compartments. Our goal was to evaluate if azithromycin-based therapy can improve response and induce remission compared with metronidazole alone in paediatric CD. DESIGN: This blinded randomised controlled trial allocated children 5-18 years with 10 12.5 or remission using intention to treat analysis. RESULTS: 73 patients (mean age 13.8±3.1 years) were enrolled, 35 to group 1 and 38 to group 2. Response and remission rates at week 8 were identical 23/35 (66%) in group 1 and 17/38 (45%) and 15/38 (39%) in group 2 (P=0.07 and P=0.025, respectively). The needed to treat for remission was 3.7. Faecal calprotectin declined significantly in group 1 (P=0.003) but not in group 2 (p=0.33), and was lower at week 8 (P=0.052). Additional therapy was required in 6/35(17%) from group 1 versus 16/38(42%) in group 2 (P=0.027) by week 8. Among 12 failures in group 2, open-label azithromycin led to remission in 10/12 (83%). CONCLUSIONS: The combination of azithromycin and metronidazole failed to improve response but was superior for induction of remission and reduction in calprotectin. TRIAL REGISTRATION NUMBER: NCT01596894.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".