Effect of Exclusive Enteral Nutrition and Corticosteroid Induction Therapy on the Gut Microbiota of Pediatric Patients with Inflammatory Bowel Disease
Bibliographic record
Abstract
INTRODUCTION: Exclusive enteral nutrition (EEN) and corticosteroids (CS) are effective induction therapies for pediatric Crohn's Disease (CD). CS are also therapy for ulcerative colitis (UC). Host-microbe interactions may be able to explain the effectiveness of these treatments. This is the first prospective study to longitudinally characterize compositional changes in the bacterial community structure of pediatric UC and CD patients receiving EEN or CS induction therapy. METHODS: Patients with diagnoses of CD or UC were recruited from McMaster Children's Hospital (Hamilton, Canada). Fecal samples were collected from participants aged 5-18 years old undergoing 8 weeks of induction therapy with EEN or CS. Fecal samples were submitted for 16S rRNA sequencing. The Shannon diversity index and the relative abundance of specific bacterial taxa were compared using a linear mixed model. RESULTS: The clustering of microbiota was the highest between patients who achieved remission compared to patients still showing active disease (p = 0.029); this effect was independent of the diagnosis or treatment type. All patients showed a significant increase in Shannon diversity over the 8 weeks of treatment. By week 2, a significant difference was seen in Shannon diversity between patients who would go on to achieve remission and those who would not. CONCLUSION: The gut microbiota of pediatric UC and CD patients was most influenced by patients' success or failure to achieve remission and was largely independent of the choice of treatment or disease type. Significant differences in Shannon diversity indices occurred as early as week 2 between patients who went on to achieve remission and those who continued to have active disease.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".