The place of antibiotics in management of irritable bowel syndrome: a systematic review and meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Irritable bowel syndrome (IBS) is a prevalent gastrointestinal disease with an obscure pathophysiology. Current treatments for IBS have modest efficacy at best and the need for a robust therapy for IBS remains unmet. As small intestinal bacterial overgrowth has been proposed to be involved in pathogenesis of IBS, antibacterial agents might be efficacious in treatment of this condition. MATERIAL AND METHODS: PubMed, Embase, Scopus, Google Scholar, Web of Science, and Cochrane Central Register of Controlled Trials were searched for studies comparing the efficacy of antibiotics in the management of IBS and/or IBS type symptoms. Data were collected from 1966 to April 2009. Clinical response was considered as our key outcome of interest. RESULTS: Of five trials that evaluated the effect of antibiotics in IBS, two randomized placebo-controlled trials met the inclusion criteria for the meta-analysis. This meta-analysis included 234 patients with IBS-type symptoms of whom 181 met the Rome criteria for IBS. The pooled relative risk (RR) for "clinical response in IBS" was 2.04 (95% confidence interval [CI] of 1.23-3.40, p = 0.0061). The pooled RR for "clinical response in IBS-type symptoms" was 2.06 (95% CI of 1.3-3.27, p = 0.002). CONCLUSIONS: Although antibiotics have a statistically significant effect on IBS and bloating, given the evidence for the presence of publication bias, methodological variability of the trials and lack of a precise scientific explanation for the role of bacterial overgrowth in the pathophysiology of IBS, use of antibiotics on a regular basis in IBS patients is not recommended.
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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 | 0.025 | 0.059 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.045 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 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".