Anticoagulation in patients with kidney failure on dialysis: factor XI as a therapeutic target
Bibliographic record
Abstract
Chronic kidney disease is present in almost 10% of the world population and is associated with excess mortality and morbidity. Reduced glomerular filtration rate and the presence and extent of proteinuria, key domains of chronic kidney disease, have both been shown to be strong and independent risk factors for cardiovascular disease. Patients with kidney failure requiring dialysis are at highest risk for cardiovascular events (e.g., stroke or myocardial infarction), and of developing chronic cardiovascular conditions, such as heart failure. Despite the high burden of cardiovascular disease, there is a paucity of evidence supporting therapies to reduce this risk. Although long-term anticoagulant treatment has the potential to prevent thromboembolism in persons with kidney failure on dialysis, this possibility remains understudied. The limited data available on anticoagulation in patients with kidney failure has focused on vitamin K antagonists or direct oral anticoagulants that inhibit thrombin or factor (F) Xa. The risk of bleeding is a major concern with these agents. However, FXI is emerging as a potential safer target for new anticoagulants because FXI plays a greater part in thrombosis than in hemostasis. In this article, we (i) explain the rationale for considering anticoagulation therapy in patients with kidney failure to reduce atherothrombotic events, (ii) highlight the limitations of current anticoagulants in this patient population, (iii) explain the potential benefits of FXI inhibitors, and (iv) summarize ongoing studies investigating FXI inhibition in patients with kidney failure on dialysis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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 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".