Effectiveness of Medilac-S as an Adjuvant to Conventional Irritable Bowel Syndrome Treatments: A Systematic Review with Meta-Analysis
Bibliographic record
Abstract
Numerous clinical studies published in the Chinese language support the use of Medilac-S (Bacillus subtilis R0179 and Enterococcus faecium R0026; non-commercial name IBacilluS+) as an adjuvant in various indications, including ulcerative colitis, irritable bowel syndrome, acute gastritis, and Helicobacter pylori therapy. This systematic review with a meta-analysis was conducted to summarize clinical studies evaluating the efficacy of this probiotic formulation as an adjuvant to conventional IBS medications. The systematic literature searches in six international and Chinese databases identified 37 eligible studies, of which 33 reported the efficacy of Medilac-S adjunctive therapy using a standardized categorical scale. These 33 studies were included in the meta-analysis using a random-effect model with a stratification by IBS subtype. Overall, Medilac-S significantly improved the efficacy of conventional IBS treatment (RR = 1.21; 95% CI: 1.17–1.25; and p < 0.0001) with an average probability of treatment effectiveness being 21% higher with the probiotic adjuvant, regardless of the subtype. Adverse events, reported in 78% of the trials, were described as mild-to-moderate and self-resolving, with a similar incidence in the probiotic adjuvant (6.2%; n = 1347) and control (5.9%; n = 1331) groups. The results of this meta-analysis strengthen the conclusions that Medilac-S is a safe and effective adjuvant to a variety of conventional treatments in IBS patients.
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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 | 0.016 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.049 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".