Nonvitamin K antagonist oral anticoagulant use in patients with renal impairment
Bibliographic record
Abstract
The nonvitamin K antagonist oral anticoagulants (NOACs), also referred to as direct oral anticoagulants (DOACs), dabigatran, apixaban, edoxaban, and rivaroxaban, have emerged as effective alternatives to vitamin K antagonists (VKAs) across several indications, including the prevention of stroke and systemic embolism (SSE) in patients with atrial fibrillation (AF) and the treatment of venous thromboembolism (VTE). Their use in patients with renal impairment is of particular importance, given the prevalence of renal dysfunction in the indicated populations and the impact of renal function on the metabolism of the NOACs. This publication reviews the pharmacokinetic/pharmacodynamic properties of the NOACs and clinical trial results for patients with renal impairment within the AF and VTE indications. Pharmacokinetic/pharmacodynamic data show the NOACs are dependent on renal clearance to varying extents. Relative to VKAs, the efficacy and safety of the NOACs is preserved in patients with moderate renal impairment. The dosing recommendations for patients with renal impairment differ depending on the NOAC, whereby some of the NOACs require dose reductions based solely on renal function, while others require consideration of additional criteria. However, despite these specific dosing recommendations, emerging real-world evidence suggests patients are not being dosed appropriately, indicating a possible knowledge gap. Adherence to recommended dosing algorithms has implications on the optimal efficacy and safety of the NOACs. To this end, renal function should be assessed in patients on a NOAC, as worsening of renal function may warrant change in the dose of a NOAC or change in oral anticoagulant.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".