Abstract 9301: Comparative Effectiveness and Safety of Direct Oral Anticoagulants versus Warfarin in Patients With Chronic Kidney Disease Stage III and Atrial Fibrillation
Bibliographic record
Abstract
Introduction: The effectiveness and safety of direct oral anticoagulants (DOACs) in atrial fibrillation (AF) patients with stage III chronic kidney disease (CKD) is still questioned. This study assessed the comparative effectiveness and safety of DOACs vs warfarin in stage III CKD AF patients. Methods: A cohort of patients with inpatient or outpatient coding for AF who were newly prescribed an oral anticoagulant (OAC) was created using Quebec provincial administrative databases from 2011-2017. The primary effectiveness outcome was a composite of ischemic stroke, systemic embolism and death and the primary safety outcome was a composite of intracranial, gastrointestinal and major bleeding from other sites in the first year after OAC initiation. Treatment groups were compared using inverse-probability-of-treatment-weighting Cox proportional-hazards models at under-treatment analysis. Results: 14,200 qualifying patients filled a claim for a new OAC prescription; 7,592 for warfarin 1,110 for rivaroxaban 20 mg, 2,084 for apixaban 5 mg and 1,674 for apixaban 2.5 mg. Rivaroxaban 20 mg was associated with a similar composite effectiveness (hazard ratio [HR] 0.84; 95% confidence intervals [CI] 0.62-1.12) and composite safety risk (HR 1.09; 95% CI 0.74-1.62) compared to warfarin (Figure 1). Apixaban 5 mg was associated with a lower composite effectiveness (HR 0.68; 95% CI 0.53-0.86), but similar composite safety risk (HR 0.89; 95% CI 0.64-1.22), whereas apixaban 2.5 mg was associated with a similar composite effectiveness (HR 0.97; 95% CI 0.78-1.21), but lower composite safety risk (HR 0.56; 95% CI 0.37-0.85). Conclusions: In comparison to warfarin, rivaroxaban and apixaban appear to be effective and safe in stage III CKD patients with AF.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".