Systematic review with meta‐analysis: review of donor features, procedures and outcomes in 168 clinical studies of faecal microbiota transplantation
Bibliographic record
Abstract
BACKGROUND: Faecal microbiota transplantation (FMT) is effective for Clostridium difficile infections (CDI) refractory to standard treatment and is being studied in other diseases. AIM: To evaluate donor characteristics, procedures and clinical outcomes of FMT. METHODS: We systematically reviewed FMT studies published up to 29 August 2018 using MEDLINE (R) and EMBASE and identified clinical studies with FMT donor information. We reported data on donor characteristics, screening criteria, administration, clinical outcomes and adverse events. RESULTS: Among 5267 reports, 239 full-text articles were screened and 168 articles were included. FMT was performed commonly for CDI (n = 108) and inflammatory bowel disease (IBD) (n = 31). We reported characteristics of 1513 donors [58% male; mean age, 34.3 years; mean body mass index, 21.6]. Donors in Asia were younger than the West (mean age 30.7 vs 32.9, P = 0.00075). Less than 50% of studies screened donors for transmittable pathogens. Final cure rate for CDI was 95.6% (95% confidence interval [CI], 93.9%-97.1%) and final remission rates for ulcerative colitis (UC) and Crohn's disease (CD) were 39.6% (95% CI, 25.4%-54.6%) and 47.5% (95% CI, 29.4%-65.8%), respectively. Cure rates in CDI and final remission rates for CD and UC were comparable across all routes of FMT administration. Overall adverse event incidence was <1%, mostly GI-related. Adverse event rates did not differ significantly between routes of FMT administration or indication. CONCLUSIONS: In a systematic review assessing donor characteristics and FMT efficacy, we observed heterogeneity in donor selection, application and outcomes of FMT. These data can facilitate standardisation of FMT protocols for various diseases.
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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 | 0.013 | 0.044 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.028 |
| Bibliometrics | 0.011 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".