Nonlinear kinetics and pharmacologic response to mibefradil
Bibliographic record
Abstract
BACKGROUND: Increasing oral doses of mibefradil (10 to 320 mg) decrease its apparent oral clearance; however, intravenous doses up to 80 mg do not reduce its systemic clearance. This study aimed to understand the mechanisms underlying the zero-order kinetics of mibefradil. METHODS: A group of 10 normotensive volunteers received 50 mg/day oral mibefradil for 8 days and, on days 1 and 8, 5 mg deuterated mibefradil by infusion. Ten additional volunteers observed the same protocol with a daily oral dose of 100 mg mibefradil. Serial blood samples were withdrawn, and mibefradil plasma concentrations were assayed by liquid chromatography-mass spectrometry. Blood pressure and heart rate were measured for 4 hours, and an ECG was performed 2 hours after drug administration. RESULTS: Repeated oral administration of 50 mg mibefradil generated zero-order kinetics secondary to a decrease in mibefradil systemic clearance. Compared with the 50-mg dose, single and repeated oral doses of 100 mg further decreased mibefradil clearance. Mibefradil bioavailability was not affected by increasing mibefradil doses. Mean diastolic blood pressure was decreased by single and repeated doses of 100 mg to the same extent. Repeated doses of 100 mg reduced heart rate and prolonged the PR and QTc, changes that were associated with mibefradil plasma concentrations. CONCLUSIONS: Repeated doses of 50 mg or doses of 100 mg mibefradil generated zero-order kinetics secondary to a decrease in hepatic extraction of the drug. Zero-order kinetics did not affect the response-concentration relationship of mibefradil.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
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".