Concurrent use of P-glycoprotein or Cytochrome 3A4 drugs and non-vitamin K antagonist oral anticoagulants in non-valvular atrial fibrillation
Bibliographic record
Abstract
AIM: To determine the concurrent use of P-glycoprotein (P-gp) or Cytochrome (CYP) 3A4 drugs and non-vitamin K antagonist oral anticoagulants (NOACs) among non-valvular AF (NVAF) patients in clinical practice. METHODS AND RESULTS: Administrative databases identified all adults (≥18 years) with incident or prevalent NVAF who initiated a NOAC in an outpatient or inpatient setting, between July 2012 and March 2019 in Alberta, Canada. Concurrent use was defined as a P-gp or CYP3A4 dispensation in the 100 days prior to and overlapping NOAC dispensation. The P-gp and CYP3A4 drugs were categorized into three groups and drug-drug interactions classified according to the 2018 European Heart Rhythm Association practical guide. Time-varying Cox models calculated the crude hazard ratio (HR) of outcomes at 1-year. A total of 642 255 NOAC dispensations occurred for 36 566 NVAF patients. Of these, 71 643 (11.2%) had a concurrent dispensation of an interacting P-gp or CYP3A4 drug. Overall, the drug-drug interaction was defined as contraindicated in 2.5%, avoid/caution in 2.3%, and for another 6.7% should require a dose adjustment. When all drug-drug interactions were considered, inappropriate NOAC prescribing occurred in 63% (n = 45 080) of dispensations. There was a significantly higher risk of death (HR 1.58, 1.47-1.70) for a drug-drug interaction but not for stroke (P = 0.89) or major bleeding risk (P = 0.13). CONCLUSIONS: The concurrent use of P-gp or CYP3A4 drugs and NOACs was uncommon but important since almost two-thirds of patients with drug-drug interactions had inappropriate NOAC dosing and a higher risk of death. More attention to this issue is needed.
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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 | 0.002 | 0.002 |
| 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 | 0.000 | 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".