Systematic review with meta‐analysis: faecal microbiota transplantation for the induction of remission for active ulcerative colitis
Bibliographic record
Abstract
BACKGROUND: Faecal microbiota transplantation (FMT) is emerging as a novel therapy for ulcerative colitis (UC). Interpretation of efficacy of FMT for UC is complicated by differences among studies in blinding, FMT administration procedures, intensity of therapy and donor stool processing methods. AIM: To determine whether FMT is effective and safe for the induction of remission in active UC. METHODS: Medline (Ovid), Embase and the Cochrane Library were searched from inception through February 2017. Original studies reporting remission rates following FMT for active UC were included. All study designs were included in the systematic review and a meta-analysis performed including only randomised controlled trials (RCTs). RESULTS: There were 14 cohort studies and four RCTs that used markedly different protocols. In the meta-analysis of RCTs, clinical remission was achieved in 39 of 140 (28%) patients in the donor FMT groups compared with 13 of 137 (9%) patients in the placebo groups; odds ratio 3.67 (95% CI: 1.82-7.39, P<.01). Clinical response was achieved in 69 of 140 (49%) donor FMT patients compared to 38 of 137 (28%) placebo patients; odds ratio 2.48 (95% CI: 1.18-5.21, P=.02). In cohort studies, 39 of 168 (24%; 95% CI: 11%-40%) achieved clinical remission. CONCLUSIONS: Despite variation in processes, FMT appears to be effective for induction of remission in UC, with no major short-term safety signals. Further studies are needed to better define dose frequency and preparation methods, and to explore its feasibility, efficacy and safety as a maintenance agent.
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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 | 0.016 | 0.045 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.042 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 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".