New anticoagulants and the management of their bleeding complications
Bibliographic record
Abstract
SUMMARY Limitations of the currently available anticoagulants have fanned the continuing search for new anticoagulants with improved pharmacological and biosafety profile, and equal, if not superior efficacy. Targets of inhibition include the factor VIIa/tissue factor pathway (recombinant nematode anticoagulant peptide c2, tissue factor pathway inhibitor), factor Xa (fondaparinux, idraparinux, razaxaban), factor Va and VIIIa pathway (recombinant activated protein C, soluble thrombomodulin) and thrombin (hirudin, bivalirudin, argatroban, ximelagatran, dabigatran). Irrespective of their mode of action, bleeding complications are invariable with all anticoagulants. Conventional assessment and measures should remain as first‐line responses to bleeding complicating the use of these anticoagulants. Antidotes do not exist for the overwhelming majority of these agents. The role of recombinant activated factor VIIa in controlling bleeding is still investigational. Definitive haemostatic strategies for bleeding complications can only evolve with accumulating experience with these new agents.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".