Bibliographic record
Abstract
Background and Objectives: Pharmacogenetics has the potential to maximize drug efficacy and minimize adverse effects of cardiovascular disease (CVD) but its translation into clinical practice been slow. However, recent advancements in genotyping and statistical methodologies have now provided robust evidence in the support of personalized medicine. This thesis addresses how the advancements in pharmacogenetics may help to gain novel insights into existing drug targets, inform and guide clinical decision-making and validate potential disease target pathways. Methods: This was achieved by exploring whether the COX-2 genetic variant (rs20417) is associated with a decreased risk of CVD outcomes, assessing whether bile acid sequestrants (BAS) are associated with a reduced the risk of coronary artery disease (CAD) using the principles of Mendelian Randomization and investigating whether genetic variants associated with dysglycaemia are associated with an increased risk of CAD. Results: We demonstrated that COX-2 carrier status was associated with a decreased risk of major cardiovascular outcomes. Furthermore, we also showed that BAS appear to be associated with a reduced risk of CAD and genetic variants associated with HbA1c and diabetes were associated with an increased risk of CAD. Conclusions: The convergence of technological and statistical advancements in pharmacogenetics have led to a more high-quality and cost-effective means of assessing the effect of CVD therapeutic agents.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 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".