Safety and Efficacy of DOACs in Patients with Advanced and End-Stage Renal Disease
Bibliographic record
Abstract
The prevalence of chronic kidney disease (CKD) is increasing due to the aging of the population and multiplication of risk factors, such as hypertension, arteriosclerosis and obesity. Impaired renal function increases both the risk of bleeding and thrombosis. There are two groups of orally administered drugs to prevent thromboembolic events in patients with CKD who require anticoagulation: vitamin K antagonists (VKAs) and direct oral anticoagulants (DOACs). Although VKAs remain the first-line treatment in patients with advanced CKD, treatment with VKAs is challenging due to difficulties in maintaining the appropriate anticoagulation level, tendency to accelerate vascular calcification and faster progression of CKD in patients treated with VKAs. On the other hand, the pleiotropic effect of DOACs, including vascular protection and anti-inflammatory properties along with comparable efficacy and safety of treatment with DOACs, compared to VKAs observed in preliminary reports encourages the use of DOACs in patients with CKD. This review summarizes the available data on the efficacy and safety of DOACs in patients with CKD and provides recommendations regarding the choice of the optimal drug and dosage depending on the CKD stage.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".