P416 Results of the first paediatric randomised controlled trial of faecal microbiota transplant for ulcerative colitis
Bibliographic record
Abstract
Abstract Background The role of faecal microbiota transplant (FMT) for the treatment of ulcerative colitis (UC) has been reported across 4 randomised-controlled trials (RCT) in adults. Promising data have emerged from small, open-label paediatric case series and case reports but a proper blinded, placebo-controlled RCT has not been described in children. We report results from the first multicentre RCT of FMT in paediatric UC patients, conducted over 36 months in Ontario and Quebec, Canada. Methods We enrolled 25 children, ages 4–17 years old with active UC across two tertiary IBD clinics. Patients had active inflammation and remained on stable doses of medication at entry. Blinded participants received enemas containing healthy donor stool (active) or normal saline (placebo), 2×/week for 6 weeks. Faecal calprotectin (fCal), C-reactive protein (CRP), and paediatric ulcerative colitis activity index (PUCAI) scores were compared between groups during intervention, and at four follow-up time points over 30 weeks. Donor and recipient stools were measured for 16s rRNA and metagenomics analyses. Results In intention-to-treat (ITT) analysis, FMT (n = 13) at 6 weeks was more likely to improve clinical response (OR 9.3, 95% CI [0.7, 122.6]), CRP (OR 4.7, 95% CI [0.8, 28.4]), and fCal (OR 13.3, 95% CI [1.1, 166.4]) from baseline compared with placebo (n = 12). FMT at 30 weeks was also more likely than placebo to improve clinical response, CRP, and fCal (Table 1). In ITT analysis of the open-label arm (n = 7), FMT at 6 weeks and 30 weeks decreased CRP (−42.9%, −28.6%), fCal (−28.6%, −42.9%), and PUCAI score (−14.3%, −42.9%) from baseline. Conclusion Serial FMT enemas containing healthy donor microbiota led to greater improvements in serum and stool inflammatory markers, and rates of clinical response, in paediatric patients with active UC compared with placebo. These improvements largely persisted beyond 6 months after final FMT treatment. This study offers the strongest preliminary evidence, from a blinded, placebo-controlled multicentre RCT for the role of FMT in the management of paediatric UC.
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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".