Changes in Composition of the Gut Bacterial Microbiome after Fecal Microbiota Transplantation for Recurrent Clostridium difficile Infection in a Pediatric Heart Transplant Patient
Bibliographic record
Abstract
The microbiome is increasingly recognized as an important influence on human health and many of the comorbidities that affect patients after solid organ transplantation (SOT) have been shown to involve changes in gut bacterial populations. Thus, microbiome changes in an individual patient may have important health implications after SOT but this area remains understudied. We describe changes in the composition of the fecal microbiome from a pediatric heart transplant recipient before and >2.5 years after he underwent repeated fecal microbiota transplantation (FMT) for recurrent Clostridium difficile infection (CDI). With both documented episodes of CDI there was marked loss of bacterial diversity with overgrowth of Proteobacteria (>98.9% of phyla identified) associated with symptomatic colitis that was corrected after FMT. We hypothesize that a second CDI occurring after FMT was related to incomplete restoration of normal bowel flora post-FMT with relative deficiencies of the phyla Firmicutes and Bacteroidetes and the Families Lachnospiraceae and Ruminococcaceae. Following the second FMT there was a gradual shift in gut bacterial composition coincident with the recipient developing lymphonodular hyperplasia of the colon and painless hematochezia that resolved with discontinuation of mycophenolate mofetil (MMF). This case documents dynamic changes in the bacterial microbiome after FMT and suggests that MMF may influence the gut microbiome with consequences for the patient.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".