Dual antiplatelet therapy: A new whiteboard video for patient education
Bibliographic record
Abstract
Coronary artery disease (CAD), including stable angina and acute coronary syndrome (ACS), is a leading cause of death and hospitalization in Canada. 1 About 2.4 million adult Canadians live with CAD, and in 2013, it was estimated that of every 100,000 Canadians, 205 were hospitalized for an acute myocardial infarction. 2 Treatment options for CAD include lifestyle changes, medications, percutaneous coronary intervention (PCI), coronary artery bypass grafting (CABG) and cardiac rehabilitation. 3ual antiplatelet therapy (DAPT)-acetylsalicylic acid (ASA) in combination with a P2Y12 inhibitor such as clopidogrel, ticagrelor or prasugrel-is a cornerstone of medical therapy for patients undergoing revascularization via PCI, both electively and emergently, to reduce the risk of stent thrombosis. 4The use of DAPT reduces angina, recurrent myocardial infarction and death, regardless of revascularization. 4 The 2018 Canadian Cardiovascular Society (CCS)/ Canadian Association of Interventional Cardiology (CAIC) Focused Update of the Guidelines for the Use of Antiplatelet Therapy provides recommendations for the duration of DAPT in patients undergoing PCI for ACS and non-ACS indications, balancing individual bleeding and thrombosis risk, which are dependent on both patient-and procedure-related factors.Recommendations for PCI for ACS indications include standard DAPT duration (12 months) and extended (up to 3 years) and for non-ACS indications include shortened (1-3 months), standard (6-12 months) and extended (up to 3 years) DAPT. 5 It is critical for patients to fill
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.261 | 0.071 |
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".