The use of non‐vitamin K oral anticoagulants in dialysis patients—A systematic review
Bibliographic record
Abstract
Non-vitamin K oral anticoagulants (NOACs) are used for prevention of thromboembolic events, but their use in dialysis patients is debatable. This study investigated the available evidence for the use of NOACs in dialysis patients. Online databases were systematically searched for eligible studies including pharmacokinetic (PK) studies, cohort studies, and randomized control trials (RCTs) comparing NOAC with vitamin K antagonist (VKA) or no anticoagulant treatment. Newcastle Ottawa Scale and Cochrane Risk of bias tool were used for quality assessment. Twenty studies were identified (nine PK studies, two RCTs, and nine cohort studies). Most of the studies investigated apixaban or rivaroxaban. In dialysis patients, less accumulation was reported with apixaban and rivaroxaban compared to dabigatran and edoxaban. PK studies indicate that high dose apixaban or rivaroxaban should be avoided. The two RCTs (rivaroxaban/apixaban vs. VKA) were small and underpowered regarding stroke and bleeding outcomes. Most cohort studies found apixaban superior to VKA, whereas comparison of rivaroxaban with VKA yielded conflicting results. Cohort studies comparing apixaban high dose (5 mg) with low dose (2.5 mg) twice daily suggest a lower risk of stroke with high dose but also a higher risk of bleeding with high dose. Apixaban versus no anticoagulation was compared in one cohort study and did not lower the risk of stroke compared with non-treated regardless of apixaban dosage. Widespread use of NOACs in dialysis patients is limited by adequately sized RCTs. Available evidence suggests a potential for use of apixaban and rivaroxaban in reduced dose.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| 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".