Impact of citrus soft drinks relative to grapefruit juice on ciclosporin disposition
Bibliographic record
Abstract
AIMS: A recent case report had suggested a citrus soft drink (Sun Drop) may have caused clinically relevant elevations in ciclosporin levels through a grapefruit juice-like mechanism via inactivation of intestinal cytochrome P450 3A4 (CYP3A4). This study was conducted to investigate the effect of grapefruit juice and citrus sodas Sun Drop and Fresca, the latter soda containing 83-fold higher concentration of the proposed CYP3A4 inhibitor bergamottin than Sun Drop, relative to water on oral ciclosporin pharmacokinetics. METHODS: In a randomized four-way crossover study with a washout of at least 1 week, 12 healthy volunteers received a single oral dose of ciclosporin (Neoral) with Sun Drop, Fresca, grapefruit juice and water (control). Each drink (591 ml) was consumed twice on the prior day and three times on the study day. Whole blood concentrations of ciclosporin were measured up to 24 h with a fluorescence polarization immunoassay. RESULTS: Grapefruit juice increased area under the concentration-time curve by 186% (P < 0.0001; 95% confidence interval of mean difference 3302-6240 ng ml h(-1)) and peak concentration by 150% (P < 0.0001) of ciclosporin with a significant decrease in oral clearance of 43% (P < 0.0001) when compared with water. Neither citrus soda altered significantly ciclosporin pharmacokinetic variables; changes in mean values ranged from +/- 3 to 11% of the corresponding water value. CONCLUSION: Although our results do not support a clinically relevant grapefruit juice-like interaction between oral ciclosporin and citrus constituent containing sodas Sun Drop or Fresca, an effect in the setting of chronic ciclosporin therapy cannot be ruled out.
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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 | 0.001 |
| 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) | 0.002 | 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".