Canadian Association of Gastroenterology Position Statement: Fecal Microbiota Transplant Therapy
Bibliographic record
Abstract
The increasing public interest in fecal microbiota transplant (FMT) raises serious concerns, when the application of this treatment is still in its infancy and long-term safety is not yet established. Indeed, there is evidence that anecdotal reports of success from initial results of uncontrolled studies are encouraging patients to try this line of treatment in the absence of medical direction or supervision. It is important that medical practitioners, the media and the general public are made aware of the safety issues involved in ‘stool transplant’. While FMT has been widely used in veterinary practice and the exchange of intestinal contents in humans is documented back to the fouth century (1), this intervention requires the exchange of body fluids with all its known and unknown risks. In the early 1980s in Canada, tainted blood and blood products for the treatment of hemophilia led to the serious outbreak of hepatitis C and HIV (2). The stool microbiome is complex, containing, bacterial, viral and fungal components in addition to prions and potentially unknown biologically active substances (3,4). Several excellent studies have indicated the important role of the microbiome in a variety of diseases. In addition to Clostridium difficile infection (CDI) and inflammatory bowel disease (IBD), these include obesity, diabetes and behavioural disorders (5). There is an urgent requirement for further careful prospective and controlled research in a variety of these diseases but especially to protect the safety of patients who, understandably, may be frustrated with the poor efficacy of their current treatments. Here, we consider the evidence for the use of FMT in resistant C difficile infection and its current status as an intervention in IBD, together with a brief summary of the current evidence for the safety of FMT and recommendations for the future.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.022 | 0.017 |
| Insufficient payload (model declined to judge) | 0.053 | 0.020 |
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".