Management of bleeding with oral anticoagulants in patients with atrial fibrillation
Bibliographic record
Abstract
Fear of bleeding is a common barrier to the use of anticoagulants. Warfarin has been the only oral anticoagulant for more than 60 years and warfarin-related bleeding is reported to be the most common drug-related cause of emergency hospitalization in elderly Americans. Non-vitamin K oral antagonists were introduced five years ago and compared with warfarin are associated with lower risk of intracranial bleeding, and similar or lower case fatality after major bleeding. Despite their superior safety profile, serious bleeding can occur. Most bleeding can be managed with holding the drug, local measures to control the bleeding and transfusion support as required because the NOACs have a relatively short half life and their anticoagulant effect rapidly dissipates. In patients with ongoing bleeding despite supportive measures and in those with life-threatening bleeding, consideration may be given to the use of general hemostatic agents. Experimental and animal evidence suggests that 3 and 4 factor prothrombin complex concentrates can improve hemostasis in the presence of a NOAC and this is reinforced by anecdotal evidence in humans. Specific antidotes are currently in phase 3 trials and could become available in the near future.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".