Insights into the role of thrombin in the pathogenesis of recurrent ischaemia after acute coronary syndrome
Bibliographic record
Abstract
Acute coronary syndrome (ACS) is a medical emergency. Patients who survive the initial event remain at risk of recurrent cardiovascular events. In most cases, ACS is triggered by thrombosis after rupture of an atherosclerotic plaque. Key to thrombus formation at this site is the generation of thrombin, which not only converts fibrinogen to fibrin but also serves as a potent platelet agonist and induces platelet aggregation at the site of vascular injury. Although dual antiplatelet therapy is more effective for the prevention of recurrent events than aspirin alone after ACS, there remains an approximately 10 % risk of recurrent ischaemic events at one year. Recent studies have evaluated whether the addition of an anticoagulant to antiplatelet therapy reduces the risk of recurrent ischaemia after an ACS event. Rivaroxaban, an oral factor Xa inhibitor, attenuates thrombin generation. When used in conjunction with dual antiplatelet therapy in patients with stabilised ACS, rivaroxaban 2.5 mg twice daily significantly reduced the risk of the composite endpoint of cardiovascular death, myocardial infarction and stroke compared with placebo. Although it increased the risk of bleeding, rivaroxaban was associated with a reduction in mortality; a finding that supports the use of a dual-pathway approach that combines anticoagulant and antiplatelet therapy. This review explores the pathophysiology of ACS to provide perspective on the results of recent clinical trials with novel oral anticoagulants for ACS and to identify their potential role in this setting.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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; 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".