Manipulation of Intestinal Microbial Flora for Therapeutic Benefit in Inflammatory Bowel Diseases: Review of Clinical Trials of Probiotics, Prebiotics and Synbiotics
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Pathogenesis of Inflammatory Bowel Diseases(Ulcerative Colitis, Crohn's disease and Pouchitis) includes an abnormal immunological response to disturbed intestinal microflora. Therapeutic strategies are designed to intervene in these abnormal host microbial communications. A novel approach in the last decade has been to use other bacteria or selective foods to induce beneficial bacteria to normalize inflammation. In this review we discuss rationale for such use and describe 46 clinical trials gleaned from the literature. Reports are divided into type, indications, and agents used. The search revealed 15 nonrandomized and 31 randomized trials. Of the latter 23 were double-blind and 8 were open-label randomized controlled. In 32 of the total, different probiotics were used, while 10 and 4 used different prebiotics or synbiotics respectively. In 14 nonrandomized trials, outcome was successful. In the randomized controlled trials 12 of 16 ulcerative colitis but only 2 of Crohn's disease trials of biotic therapy were successful. No superiority of any probiotic was clearly evident, but a multi-agent mixture, VSL3# may be better suited in ulcerative colitis and pouchitis while the probiotic Lactobacillus rhamnosus GG appears less useful in inflammatory bowel disease, especially Crohn's disease. Further studies with uniform stringent criteria are needed to provide proof of this therapy in inflammatory bowel disease.
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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 | 0.048 | 0.075 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.005 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 it