Unresolved issues in the use of direct acting oral anticoagulants
Bibliographic record
Abstract
INTRODUCTION: Currently approved direct oral anticoagulants (DOACs) target thrombin or coagulation factor Xa. Administered in fixed doses without routine laboratory monitoring, DOACs have simplified the approach to oral anticoagulation, when previously the choice was limited to vitamin K antagonists (VKAs). AREA COVERED: We discuss a) unresolved issues related to optimal use of DOACs and b) new developments including the potential for FXIa inhibitors to be effective and safer anticoagulants. EXPERT OPINION: By simplifying oral anticoagulation, DOACs have facilitated the uptake of anticoagulation. The DOACs are approved for stroke prevention in atrial fibrillation and for the prevention and treatment of venous thromboembolism, and their indications are expanding to include the prevention of atherothrombosis. DOACs have now replaced vitamin K antagonists (VKAs) for most indications, but not all. DOACs are inferior to VKAs for patients with mechanical heart valves, left ventricular assist device, rheumatic atrial fibrillation, and those with antiphospholipid syndrome, and their safety and efficacy are uncertain in some populations (e.g. advanced renal and liver disease). Impediments to use include concerns for bleeding and cost. The newly developed FXIa and FXIIa inhibitors have the potential to be safer than current anticoagulants, but phase 3 trials are needed to confirm their clinical efficacy and safety.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".