New anticoagulants for venous thromboembolic disease
Bibliographic record
Abstract
PURPOSE OF REVIEW: In this paper, recent advances in new anticoagulants with the potential to be used for prevention or treatment of venous thrombosis are reviewed. RECENT FINDINGS: Numerous novel anticoagulants targeting specific stages of the coagulant pathway are in various stages of development. Fondaparinux, an indirect activated factor VII inhibitor, has been shown to be effective for initial treatment and prevention of venous thromboembolism, but still requires parenteral administration. Ximelagatran, an oral direct thrombin inhibitor, has also been shown to effective for treatment and prevention of venous thrombosis. Both agents are associated with bleeding, however, and ximelagatran is associated with hepatic toxicity with long-term use. Direct activated factor X inhibitors, orally available forms of heparin, and other direct thrombin inhibitors remain in early stages of development. Further data on the clinical utility of these agents are likely to emerge in the next few years, and uptake of their use will be affected by the cost considerations. SUMMARY: Numerous alternative anticoagulants are in varying stages of development. Clinical data have yet to show that these agents have a clearly superior risk-benefit ratio compared with currently used antithrombotics. Many drugs remain in initial stages of development. The ideal anticoagulant agent is being sought but has yet to be discovered.
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 | 0.000 |
| 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.009 |
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".