Bibliographic record
Abstract
BACKGROUND: Grapefruit juice can increase the oral bioavailability of a broad range of medications. This interaction has not been assessed in the elderly. METHODS: Twelve healthy elderly people (70 to 83 years of age) were administered 5 mg felodipine extended release with 250 mL grapefruit juice or water in a single-dose study. Subsequently, 6 of these people received 2.5 mg felodipine for 2 days, followed by 5 mg felodipine for 6 days with 250 mL grapefruit juice or water in a steady-state study. Plasma concentrations of felodipine and dehydrofelodipine metabolite, blood pressure, and heart rate were measured over 24 hours after single and final steady-state dose. RESULTS: Mean felodipine area under the curve and maximum concentration were 2.9-fold and 4.0-fold greater, respectively, with grapefruit juice in both studies. Interindividual variability in the extent of the interaction was high. Felodipine apparent elimination half-life was not altered. Dehydrofelodipine area under the curve and maximum concentration were increased and dehydrofelodipine/felodipine area under the curve ratio was reduced. Systolic and diastolic blood pressures were lower with grapefruit juice in the single-dose study, whereas they were not different between treatments in the steady-state study. Curvilinear relationships existed between plasma felodipine concentration and changes in systolic and diastolic blood pressures. Heart rates were higher with grapefruit juice in both studies; however, this effect was greater and more prolonged at steady state. CONCLUSIONS: A normal dietary amount of grapefruit juice produced a pronounced, unpredictable, and sustained pharmacokinetic interaction with felodipine by reducing its presystemic metabolism in the elderly. The different blood pressure results between the studies can be explained by felodipine concentration-blood pressure response relationships. The elderly should be particularly cautioned about concomitant grapefruit juice and felodipine ingestion.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.000 |
| 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".