Bibliographic record
Abstract
Recent advances in our understanding of the contribution of thrombin generation to arterial thrombosis and the role of platelets in venous thrombosis have prompted new treatment paradigms. Nonetheless, bleeding remains the major side effect of such treatments spurring the quest for new antithrombotic regimens with better benefit-risk profiles and for safer anticoagulants for existing and new indications. The aims of this article are to review the results of recent trials aimed at enhancing the benefit-risk profile of antithrombotic therapy and explain how these findings are changing our approach to the management of arterial and venous thrombosis. Focusing on these 2 aspects of thrombosis management, this article discusses 4 advances: (1) the observation that in some indications, lowering the dose of some direct oral anticoagulants reduces the risk of bleeding without compromising efficacy, (2) the recognition that aspirin is not only effective for secondary prevention of atherothrombosis but also for prevention of venous thromboembolism, (3) the finding that dual pathway inhibition with the combination of low-dose rivaroxaban to attenuate thrombin generation plus aspirin to reduce thromboxane A2-mediated platelet activation is superior to aspirin or rivaroxaban alone for prevention of atherothrombosis in patients with coronary or peripheral artery disease, and (4) the development of inhibitors of factor XI or XII as potentially safer anticoagulants.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.018 |
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".