Toward Optimal Treatment in Women: The Effect of Sex on Metoprolol‐Diphenhydramine Interaction
Bibliographic record
Abstract
The objective of this study was to determine if sex influences the pharmacokinetics and hemodynamics of the CYP2D6 substrate metoprolol and its interaction with diphenhydramine (CYP2D6 inhibitor) in healthy young participants with high (extensive metabolizer [EM]) or low (poor metabolizer [PM]) CYP2D6 activities. A prespecified comparative analysis of data from 2 sequential clinical trials that included 16 EM and 4 PM women and 10 EM and 6 PM men was performed. The participants in the 2 trials were administered a single oral dose of 100 mg metoprolol in the presence of steady-state diphenhydramine or placebo. Serial plasma and urine samples were obtained for 48 hours, and hemodynamic data was obtained for 12 hours after metoprolol. In the placebo arm, EM and PM women had 62% and 59% higher S-metoprolol AUC(0-infinity) and 26% and 71% lower CL/F, respectively, compared to men with the same phenotype (all Ps < .05 women compared to men). These differences dissipated on body weight (WT) correction. Women (especially PMs) experienced greater negative chronotropic effects of metoprolol than men (P < .0001 women compared to men). Diphenhydramine coadministration increased S-metoprolol AUC by 84% in EM women and 45% in EM men (P < .009 women compared to men). In the diphenhydramine arm, sex differences in pharmacokinetics persisted even after WT correction, resulting in greater negative chronotropic effects in women (all Ps < .05 women compared to men). Metoprolol dose should be adjusted for body weight, particularly in women. Coadministration of a CYP2D6 inhibitor such as diphenhydramine, by a patient at similar doses in the 2 sexes, could result in a greater inhibition of clearance of CYP2D6 substrates with a resulting higher risk of pronounced pharmacological and adverse effects in women compared to men.
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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 | 0.010 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 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".