DOACs vs warfarin in AF with comorbid CKD or valvular disease: a systematic review and meta-analysis
Bibliographic record
Abstract
Direct oral anticoagulant agents (DOACs) are indicated to prevent vascular events in patients with atrial fibrillation (AF) without concomitant valvular disease or severe chronic kidney disease (CKD), groups in which warfarin is the preferred choice. We aimed to evaluate the safety of DOACs in the aforementioned populations compared to warfarin. We conducted a systematic review in MEDLINE, Embase, and EBM Reviews to identify randomized-controlled trials (RCTs) and non-RCTs assessing warfarin or DOAC (rivaroxaban, dabigatran, apixaban, or edoxaban) in patients with AF with concomitant valvular disease or CKD (according to KDOQI guidelines), and that assessed bleeding, stroke, or systemic/arterial thromboembolism. Meta-analysis was performed for eligible studies using the Mantel-Haenszel method random-effects model. Of 3,172 screened studies, we included 110 studies (310,478 patients with concomitant AF and CKD; 99,299 patients with concomitant AF and valve disease). Meta-analysis showed that compared to warfarin, in patients with concomitant AF and CKD, DOACs were associated with reduced bleeding (OR 0.66, 95% Cl [0.49, 0.88], p=0.005) and strokes (OR 0.60, 95% CI [0.43, 0.85]; p=0.004), particularly in stages 4 and 5 CKD and in dialysis patients. In patients with concomitant AF and valvular disease, DOACs were associated with reduced bleeding (OR 0.75, 95% CI [0.57, 0.97], p=0.03) and stroke incidence (OR 0.66, 95% CI [0.47, 0.93], p=0.02). Differences were noted for RCTs and non-RCTs. Our findings suggest that DOACs may be equivalent or superior to warfarin both in the prevention of thromboembolic event and reduction of bleeding in the aforementioned patients.
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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 | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.042 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".