Anti‐thrombotic therapy for atrial fibrillation in patients with chronic kidney disease: Current views
Bibliographic record
Abstract
Chronic kidney disease (CKD) occurs in approximately one-third of patients with non-valvular atrial fibrillation (AF). The presence of CKD, particularly advanced CKD, confers increased risk of both thromboembolism and major bleeding in this group of patients who are already at risk for ischemic stroke and systemic embolism and at risk of bleeding due to anticoagulation. Studies assessing the effect of warfarin on risk of ischemic stroke, systemic embolism, and major bleeding have produced disparate results, particularly in patients with advanced CKD including those treated with hemodialysis. The direct oral anticoagulants (DOAC's) have been studied in patients with stage III (moderate) CKD and appear to be as effective or more effective (dabigatran 150 mg twice daily) than warfarin in preventing ischemic stroke or embolism in this group. Two of the DOAC's, apixaban and edoxaban, confer lower risk of major bleeding than warfarin with appropriate dose adjustments. Substantial gaps exist in our knowledge of anti-thrombotic therapy in patients with AF and CKD, primarily due to exclusion of patients with advanced CKD from randomized controlled trials comparing DOAC's with warfarin.
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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) | 0.002 | 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 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".