Non‐absorbable antibiotics for managing intestinal gas production and gas‐related symptoms
Bibliographic record
Abstract
BACKGROUND: Simethicone, activated charcoal and antimicrobial drugs have been used to treat gas-related symptoms with conflicting results. AIM: To study the relationship between gaseous symptoms and colonic gas production and to test the efficacy of rifaximin, a new non-absorbable antimicrobial agent, on these symptoms. METHODS: Intestinal gas production was measured by hydrogen (H2) and methane (CH4) breath testing after lactulose in 21 healthy volunteers and 34 functional patients. Only the 34 functional patients took part in a double-blind, double-dummy controlled trial, receiving, at random, rifaximin (400 mg b.d per 7 days), or activated charcoal (400 mg b.d per 7 days). The following parameters were evaluated at the start of the study and 1 and 10 days after therapy: bloating, abdominal pain, number of flatus episodes, abdominal girth, and cumulative breath H2 excretion. RESULTS: Hydrogen excretion was greater in functional patients than in healthy volunteers. Rifaximin, but not activated charcoal, led to a significant reduction in H2 excretion and overall severity of symptoms. In particular, in patients treated with rifaximin, a significant reduction in the mean number of flatus episodes and of mean abdominal girth was evident. CONCLUSIONS: In patients with gas-related symptoms the colonic production of H2 is increased. Rifaximin significantly reduces this production and the excessive number of flatus episodes.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".