Impact of Grapefruit Juice on the Antiplatelet Activity of Loading and Maintenance Doses of Clopidogrel in Healthy Volunteers
Bibliographic record
Abstract
Background: Grapefruit juice impacts the metabolism of a number of drugs via inhibition of a variety of metabolic enzymes. This study evaluated the impact of grapefruit juice on the antiplatelet activity of a loading dose and 7 days of maintenance therapy with clopidogrel. Methods: Healthy volunteers participated in two separate treatment protocols. The first protocol included a single 300 mg loading dose of clopidogrel and the second protocol included maintenance therapy with clopidogrel 75 mg given for 7 consecutive days. In both protocols, subjects were randomized to take clopidogrel with grapefruit juice or with tap water. At 6 h after the loading dose and at 6 h after the last maintenance dose of clopidogrel, a P2Y 12 reaction unit (PRU) value using the VerifyNow ® P2Y12 assay was determined. A PRU value > 235 was defined as high on-treatment platelet reactivity (defined as clopidogrel hyporesponse). Results: Fourteen subjects completed the loading dose protocol while 17 subjects completed the maintenance dose protocol. Following administration of the loading dose, the mean PRUs with grapefruit juice and tap water were 235.2 (95% confidence interval (CI): 210.4-260.0) and 177.4 (95% CI: 141.6-213.2), respectively (P = 0.001). Following administration of the loading dose, the numbers of subjects with a PRU > 235 with grapefruit juice and tap water were 9 (64%) and 3 (21%), respectively (P = 0.05). In the maintenance dose protocol, the mean PRUs with grapefruit juice and tap water were 212.4 (95% CI: 175.8-249.0) and 186.1 (95% CI: 149.6-222.7), respectively (P = 0.059). In the maintenance dose protocol, the proportions of patients with a PRU > 235 with grapefruit juice and tap water were 9 (53%) and 4 (23%), respectively (P = 0.16). Discussion: Compared to tap water, grapefruit juice significantly increased the mean PRU in patients following a 300 mg loading dose of clopidogrel. The increase in mean PRU after 7 days of a 75 mg/day maintenance dose of clopidogrel was also increased by grapefruit juice, but the magnitude of the increase was not statistically significant. The proportion of subjects with high on-treatment platelet reactivity with clopidogrel after ingestion with grapefruit juice was not significant during either the loading or maintenance dose. The results of our study are insufficient to reach a valid conclusion concerning an interaction between clopidogrel and grapefruit juice. Cardiol Res. 2014;5(1):1-7 doi: http://dx.doi.org/ 10.14740 / cr307w
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".