How can we reverse bleeding in patients on direct oral anticoagulants?
Bibliographic record
Abstract
The direct oral anticoagulants (DOACs), or non-vitamin K antagonist oral anticoagulants (NOACs), including dabigatran, which inhibits thrombin, as well as rivaroxaban, apixaban, edoxaban, and betrixaban, which inhibit coagulation factor Xa, are as-sociated with similar or lower risk of bleeding compared with warfarin. The need for reversal of their anticoagulant effect may occur in patients with life-threatening bleeding or those requiring urgent surgery. Currently, the only specific reversal agent for dabigatran, idarucizumab, is widely available, while andexanet alfa, which reverses factor Xa inhibitors, was approved in the United States in May 2018. Ciraparantag, which has been designed to reverse all DOACs and other anticoagulants, is being investigated in clinical trials. In the absence of licensed reversal agents for the oral factor Xa inhibitors, prothrombin complex concentrates are suggested in patients with life-threatening bleeding. Vitamin K and fresh frozen plasma should not be used to reverse DOACs. This review presents the current evidence regarding bleeding risk on DOACs and the reversal strategies to provide guidance on the management of patients treated with DOACs, who experience serious bleeding.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".