Oral anticoagulants in coronary heart disease (Section IV) Position paper of the ESC Working Group on Thrombosis – Task Force on Anticoagulants in Heart Disease
Bibliographic record
Abstract
Until recently, vitamin K antagonists (VKAs) were the only available oral anticoagulants evaluated for long-term treatment of patients with coronary heart disease (CHD), particularly after an acute coronary syndrome (ACS). Despite efficacy in this setting, VKAs are rarely used because they are cumbersome to administer. Instead, the more readily manageable antiplatelet agents are the mainstay of prevention in ACS patients. This situation has the potential to change with the introduction of non-VKA oral anticoagulants (NOACs), which are easier to administer than VKAs because they can be given in fixed doses without routine coagulation monitoring. The NOACs include dabigatran, which inhibits thrombin, and apixaban, rivaroxaban and edoxaban, which inhibit factor Xa. Apixaban and rivaroxaban were evaluated in phase III trials for prevention of recurrent ischaemia in ACS patients, most of whom were also receiving dual antiplatelet therapy with aspirin and clopidogrel. Although at the doses tested rivaroxaban was effective and apixaban was not, both agents increased major bleeding. The role for the NOACs in ACS management, although promising, is therefore complicated, because it is uncertain how they compare with newer antiplatelet agents, such as prasugrel, ticagrelor or vorapaxar, and because their safety in combination with these other drugs is unknown. Ongoing studies are also now evaluating the use of NOACs in non-valvular atrial fibrillation patients, where their role is established, with coexistent ACS or coronary stenting. Focusing on CHD, we review the results of clinical trials with the NOACs and provide a perspective on their future incorporation into clinical practice.
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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 | 0.011 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.010 | 0.012 |
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".