Dual Antiplatelet Therapy after PCI: When Could We Go Shorter?
Bibliographic record
Abstract
The optimal duration of dual antiplatelet therapy (DAPT) after percutaneous coronary intervention (PCI) remains an important clinical question in interventional cardiology. Several clinical and angiographic variables are associated with an increased risk for thrombotic events, and prolonged DAPT duration may improve long term clinical outcome. However, some patients also present high bleeding risk (HBR) characteristics and may require a shorter DAPT duration. The guidelines recommendations consider the data from randomized clinical trials, however numerous exclusion criteria may create gaps in the evidence leading to uncertainties, the need for expert opinion and patient level decision making. Furthermore, the stent platforms have evolved in such way that opportunities now exist to shorten duration of DAPT. This chapter will review the variables associated with ischemic and bleeding risks as well as different stent platforms to help clinicians optimize DAPT duration in patients undergoing PCI.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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; both teacher heads agree on what is shown here.
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".