Fecal microbiota transplantation for the treatment of recurrent and severe Clostridium difficile infection in solid organ transplant recipients: A multicenter experience
Bibliographic record
Abstract
Fecal microbiota transplant (FMT) is recommended for Clostridium difficile infection (CDI) treatment; however, use in solid organ transplantation (SOT) patients has theoretical safety concerns. This multicenter, retrospective study evaluated FMT safety, effectiveness, and risk factors for failure in SOT patients. Primary cure and overall cure were defined as resolution of diarrhea or negative C difficile stool test after a single FMT or after subsequent FMT(s) ± anti-CDI antibiotics, respectively. Ninety-four SOT patients underwent FMT, 78% for recurrent CDI and 22% for severe or fulminant CDI. FMT-related adverse events (AE) occurred in 22.3% of cases, mainly comprising self-limiting conditions including nausea, abdominal pain, and FMT-related diarrhea. Severe AEs occurred in 3.2% of cases, with no FMT-related bacteremia. After FMT, 25% of patients with underlying inflammatory bowel disease had worsening disease activity, while 14% of cytomegalovirus-seropositive patients had reactivation. At 3 months, primary cure was 58.7%, while overall cure was 91.3%. Predictors of failing a single FMT included inpatient status, severe and fulminant CDI, presence of pseudomembranous colitis, and use of non-CDI antibiotics at the time of FMT. These data suggest FMT is safe in SOT patients. However, repeated FMT(s) or additional antibiotics may be needed to optimize rates of cure with FMT.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".