Comparison of Clopidogrel With Prasugrel and Ticagrelor in Patients With Acute Coronary Syndrome: Clinical Outcomes From the National Cardiovascular Database ACTION Registry
Bibliographic record
Abstract
Background: We aimed to compare the clinical outcomes of clopidogrel, prasugrel, and ticagrelor in clinical practice using the National Cardiovascular Database ACTION Registry ® . Treatment guidelines for patients with acute coronary syndrome (ACS) undergoing percutaneous coronary intervention recommend dual antiplatelet therapy (DAPT) for 12 months. Few clinical trials have compared the safety and efficacy of clopidogrel with that of newer antiplatelet therapies. Methods: A retrospective study of patients hospitalized for ACS at Cleveland Clinic Akron General was conducted. Data elements included detailed medical history and clinical outcomes during hospital stay. The primary outcome was a composite of major clinical events (cardiogenic shock, atrial fibrillation, ventricular fibrillation, ventricular tachycardia, heart failure, bleeding, and mechanical ventilation). The independent variable was the type of DAPT. Statistical analyses were performed using Chi-square and Mann-Whitney U tests. A post-hoc analysis was performed to compare between the antiplatelet drugs head-to-head. Results: Subjects (n = 1,388) admitted between January 2011 and March 2016 with ACS and treated with clopidogrel, prasugrel, or ticagrelor were included in the study. Mean age was 65 ± 14 years and 46% had ST-segment elevation myocardial infarction. Prasugrel administration within 24 h was associated with a lower incidence of the composite outcome (P = 0.049), bleeding (P = 0.028), and heart failure (P = 0.002). Conclusion: There was a significant difference between the type of antiplatelet drug and clinical outcomes in ACS patients who were treated with DAPT. Observations from current study may provide important information for prescribers in clinical decision-making. Cardiol Res. 2017;8(3):105-110 doi: https://doi.org/10.14740/cr560w Â
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".