International survey of patients undergoing percutaneous coronary intervention and their attitudes toward pharmacogenetic testing
Bibliographic record
Abstract
OBJECTIVE: To evaluate perceptions toward pharmacogenetic testing of patients undergoing percutaneous coronary intervention (PCI) who are prescribed dual antiplatelet therapy (DAPT) and whether geographical differences in these perceptions exist. PARTICIPANTS AND METHODS: TAILOR-PCI is the largest genotype-based cardiovascular clinical trial randomizing participants to conventional DAPT or prospective genotyping-guided DAPT. Enrolled patients completed surveys before and 6 months after randomization. RESULTS: A total of 1327 patients completed baseline surveys of whom 28, 29, and 43% were from Korea, Canada and the USA, respectively. Most patients (77%) valued identifying pharmacogenetic variants; however, fewer Koreans (44%) as compared with Canadians (91%) and USA (89%) patients identified pharmacogenetics as being important (P<0.001). After adjusting for age, sex, and country, those who were confident in their ability to understand genetic information were significantly more likely to value identifying pharmacogenetic variants (odds ratio: 30.0; 95% confidence interval: 20.5-43.8). Only 21% of Koreans, as opposed to 86 and 77% of patients in Canada and USA, respectively, were confident in their ability to understand genetic information (P<0.001). CONCLUSION: Although genetically mediated clopidogrel resistance is more prevalent amongst Asians, Koreans undergoing PCI identified pharmacogenetic variants as less important to their healthcare, likely related to their lack of confidence in their ability to understand genetic information. To enable successful implementation of pharmacogenetic testing on a global scale, the possibility of international population differences in perceptions should be considered.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".