Bibliographic record
Abstract
BACKGROUND: Amiodarone is an increasingly popular and uniquely effective antiarrhythmic agent for which population pharmacokinetic parameters in patients receiving long-term oral therapy have not been defined previously. METHODS: We collected 605 observations of serum amiodarone and desethylamiodarone metabolite concentrations from 77 patients (mean follow-up, 2 years). Mixed-effects modeling (NONMEM) was used to determine the typical population pharmacokinetic parameters, their respective variabilities, and a simple oral dosing regimen to rapidly achieve and maintain a target concentration of 1.5 mg/L. Individual serum concentration versus time curves were simulated for the study population based on regimens outlined in the product monograph and were compared with those for the proposed dosing regimen. The relationship between the duration of amiodarone therapy and the rate of decrement in serum concentration after discontinuation was explored. RESULTS: Amiodarone concentrations were best described by a two-compartment model with the typical parameters +/- interindividual coefficients of variation (where applicable) as follows: volumes of distribution/bioavailability (V1/F = 882 L; V2/F = 12,700 L +/- 58%) and clearances/bioavailability (CL1/F = 229 L/day +/- 31%; and CL2/F = 599 L/day +/- 56%). Rapid distribution half-life was 17 hours, and terminal half-life was 55 days. A practical dosing regimen of 1600 mg/d for 2 days, 1,200 mg/d for 5 days, 1,000 mg/d for 7 days, 800 mg/d for 7 days, 600 mg/d for 7 days, and 400 mg/d for 62 days followed by a maintenance dose of 343 mg/d (400 mg/d for 6 of 7 days) is proposed. After steady state is reached, cessation of dosing produces a 25% serum concentration decrement in 3 days and 50% in 36 days. CONCLUSIONS: Population pharmacokinetics confirm that amiodarone has an extraordinarily long half-life. The slow elimination rate makes anticipating the timing of adjustments in amiodarone therapy to avoid toxicity unusually perplexing. However, based on the estimated variability, the proposed dosing regimen would produce steady-state concentrations within the therapeutic window for 90% of 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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".