Antiplatelet therapy in the era of drug-eluting stents: current and future perspectives
Bibliographic record
Abstract
The use of drug-eluting stents (DESs) dramatically reduced in-stent restenosis. However, the increasing use of these stents has raised concern about their potential thrombogenicity. Indeed, the particularity of DES thrombosis compared with bare metal stent thrombosis is a high rate of late thrombosis. Antiplatelet therapy is efficient in preventing DES thrombosis. However, this therapy could be optimized and may be improved in the future. This article will review the mechanisms and the epidemiology of stent thrombosis. Then, we will summarize the antiplatelet therapeutic strategies used to prevent stent thrombosis and especially DES-associated thrombosis. Finally, we will present some data with regard to potential advantages and pitfalls in DES thrombosis prevention using novel antiplatelet agents currently under development, as well as future stent designs with improved healing properties.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".