How I treat target-specific oral anticoagulant–associated bleeding
Bibliographic record
Abstract
Target-specific oral anticoagulants (TSOACs) that directly inhibit thrombin (dabigatran) or factor Xa (rivaroxaban, apixaban) are effective and safe alternatives to vitamin K antagonists (VKAs) and low-molecular-weight heparin (LMWH). Although these agents have practical advantages compared with VKAs and LMWH, there are no antidotes that reverse their anticoagulant effect. Clinical evidence for the efficacy of nonspecific therapies that promote formation of fibrin (prothrombin complex concentrate [PCC], activated PCC [aPCC], and recombinant factor VIIa) in the setting of TSOAC-associated bleeding is lacking, and these prohemostatic products are associated with a risk of thrombosis. In the absence of specific antidotes, addition of PCC or aPCC to maximum supportive therapy may be reasonable for patients with severe or life-threatening TSOAC-associated bleeding. Targeted antidotes for these agents are in development.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.011 |
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".