Anticoagulant and antiplatelet therapy in patients with chronic kidney disease
Bibliographic record
Abstract
PURPOSE OF REVIEW: Atrial fibrillation and cardiovascular death are increased in end-stage renal disease (ESRD) patients compared to the general population. The effect of anticoagulant and antiplatelet medications for these indications in ESRD is unclear. However, both classes of medications have been used for the preservation of vascular access. This review explores the risks and benefits of anticoagulant and antiplatelet medications in ESRD. RECENT FINDINGS: ESRD patients with atrial fibrillation have a two and three-fold greater risk of death and stroke, respectively, than ESRD patients without atrial fibrillation. Warfarin does not appear to decrease this risk, and increases the risk of bleeding and vascular calcification. Warfarin also does not appear to be effective for vascular access preservation. In a few large observational studies, antiplatelet agents did not decrease the risk of cardiovascular death, but confounding by indication is likely. Antiplatelet agents do appear to prolong unassisted arteriovenous graft patency, but the effect is modest. SUMMARY: The role of anticoagulant and antiplatelet agents for atrial fibrillation and cardiovascular disease in ESRD remains unclear. Well designed randomized controlled trials to determine the role of anticoagulation in ESRD patients with atrial fibrillation, and anticoagulant and antiplatelet medications in the preservation of central venous catheter function are required.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| 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) | 0.004 | 0.001 |
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".