Antibiotic Cocktail for Pediatric Acute Severe Colitis and the Microbiome: The PRASCO Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Alterations in the microbiome have been postulated to drive inflammation in IBD. In this pilot randomized controlled trial, we evaluated the effectiveness of quadruple antibiotic cocktail in addition to intravenous-corticosteroids (IVCSs) in acute severe colitis (ASC). METHODS: Hospitalized children with ASC (pediatric ulcerative colitis activity index [PUCAI] ≥65) were randomized into 2 arms: the first received antibiotics in addition to IVCS (amoxicillin, vancomycin, metronidazole, doxycycline/ciprofloxacin [IVCS+AB]), whereas the other received only IVCS for 14 days. The primary outcome was disease activity (PUCAI) at day 5. Microbiome was analyzed using 16S rRNA gene and metagenome. RESULTS: Twenty-eight children were included: 16 in the AB + IVCS arm and 12 in the IVCS arm (mean age 13.9 ± 4.1 years and 23 [82%] with extensive colitis). The mean day-5 PUCAI was 25 ± 16.7 vs 40.4 ± 20.4, respectively (P = 0.037). Only 3 and 2 children, respectively, required colectomy during 1-year follow-up (P = 0.89). Microbiome data at time of admission were analyzed for 25 children, of whom 17 (68%) had a predominant bacterial species (>33% abundance); response was not associated with the specific species, whereas decreased microbiome diversity at admission was associated with day-5 response in the IVCS arm. CONCLUSION: Patients with ASC have alterations in the microbiome characterized by loss of diversity and presence of predominant bacterial species. Quadruple therapy in addition to IVCS improved disease activity on day 5, but larger studies are needed to determine whether this is associated with improved long-term outcomes (clinicaltrials.gov NCT02033408).
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".