Effects of food and formulation on the relative bioavailability of bismuth biskalcitrate, metronidazole, and tetracycline given for <i>Helicobacter pylori</i> eradication
Bibliographic record
Abstract
AIMS: To evaluate the effects of food and formulation on the pharmacokinetics of bismuth biskalcitrate, metronidazole and tetracycline when combined in a new 3-in-1 single capsule (BMT) for eradication of Helicobacter pylori. METHODS: In a randomized, 3 x 3 cross-over design, 23 healthy males received one dose of BMT in the fed and fasting states and equivalent doses of the three drugs given together but as separate capsules while fasting. Bioequivalence was evaluated according to 90% confidence intervals (CIs) of ratios of geometric least square means for C(max), AUC(t), and AUC(infinity). RESULTS: With respect to food, none of the three drugs met bioequivalence guidelines. Bismuth had lower limit CIs ranging from 12% for C(max) to 25% for AUC(infinity). The corresponding values for tetracycline were 59% and 51%. Metronidazole had a lower limit CI of 74% for C(max). With respect to formulation, bismuth had lower limits of CIs ranging from 39% for C(max) to 50% for AUC(t) and higher limits of 146% for AUC(t), metronidazole met bioequivalence guidelines, and tetracycline had lower limits of CIs between 72% for AUC(t) and 74% for AUC(infinity). CONCLUSIONS: Food significantly decreased the relative bioavailability of each drug but formulation was without effect. This decrease may be beneficial when a local gastric action is needed, as confirmed by a near 90% eradication rate when this combined capsule is administered with food to treat gastro-duodenal local infection by H. pylori.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".