Antiplatelet Therapies: Aspirin at the Heart of New Directions
Bibliographic record
Abstract
When introduced over 100 years ago, aspirin was prescribed as an analgesic drug to arthritic patients for pain relief. The prevalence of users grew quite rapidly and to this day, aspirin remains widely used in clinical practice. The popularity of aspirin resulted not only from its analgesic properties but also from a second benefit recognized later as an anti-platelet effect. It was this important activity of aspirin that made it one of the most recommended drugs for the treatment and prevention of cardiovascular diseases. The anti-platelet effect of aspirin emerged from the first few case reports published in the early 1900s and was described as a mild bleeding. The molecular mechanisms involved were described in 1971 and constituted the irreversible inhibition of cyclooxygenase-1 enzyme and prevention of platelet aggregation. Today, the contribution of aspirin to our understanding of cardiovascular health persists and remains considerable. Observations from large cohorts of aspirin users generate massive amount of valuable information used in the identification of factors influencing the potential risk for cardiovascular diseases, including sex, age and genetic predisposition. Aspirin and the path of discovery leading to its anti-platelet activity has taken a hundred years was based on manifestations of effects observed in its users, and it remains a successful strategy for the identification of new avenues to treat cardiovascular diseases associated with hyper-platelet activity. The contribution of aspirin to the understanding of cardiovascular diseases and to the design of effective treatment and prevention strategies, remains of high importance in our society.
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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) | 0.002 | 0.004 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".