Aspirin Compared to Low Intensity Anticoagulation in Patients with Non-Valvular Atrial Fibrillation. A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Despite its lack of efficacy, aspirin is commonly used for stroke prevention in atrial fibrillation. Since prior studies have suggested a benefit of low-intensity anticoagulation over aspirin in the prevention of vascular events, the aim of this systematic review was to compare the outcomes of patients with non-valvular atrial fibrillation treated with low-intensity anticoagulation with Vitamin K antagonists or aspirin. METHODS: We conducted a systematic review searching Ovid MEDLINE, Embase and the Cochrane Central Register of Controlled Trials, from 1946 to October 14th, 2015. Randomized controlled trials were included if they reported the outcomes of patients with non-valvular atrial fibrillation treated with a low-intensity anticoagulation compared to patients treated with aspirin. The primary outcome was a combination of ischemic stroke or systemic embolism. The random-effects model odds ratio was used as the outcome measure. RESULTS: Our initial search identified 6309relevant articles of which three satisfied our inclusion criteria and were included. Compared to low-intensity anticoagulation, aspirin alone did not reduce the incidence of ischemic stroke or systemic embolism OR 0.94 (95% CI 0.57-1.56), major bleeding OR 1.06 (95% CI 0.42-2.62) or vascular death OR 1.04 (95% CI 0.61-1.75). The use of aspirin was associated with a significant increase in all-cause mortality OR 1.66 (95% CI 1.12-2.48). CONCLUSION: In patients with non-valvular atrial fibrillation, aspirin provides no benefits over low-intensity anticoagulation. Furthermore, the use of aspirin appears to be associated with an increased risk in all-cause mortality. Our study provides more evidence against the use aspirin in patients with non-valvular atrial fibrillation.
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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 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.030 |
| Bibliometrics | 0.005 | 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".