Systematic Review of Observational Studies Assessing Bleeding Risk in Patients with Atrial Fibrillation Not Using Anticoagulants
Bibliographic record
Abstract
BACKGROUND: Patients with atrial fibrillation considering use of anticoagulants must balance stroke reduction against bleeding risk. Knowledge of bleeding risk without the use of anticoagulants may help inform this decision. PURPOSE: To determine the rate of major bleeding reported in observational studies of atrial fibrillation patients not receiving Vitamin K antagonists (VKA). DATA SOURCES: We searched MEDLINE, EMBASE and CINAHL to October 2011 and examined reference lists of eligible studies and related reviews. STUDY SELECTION: All longitudinal cohort studies that included over 100 adult patients with atrial fibrillation not receiving VKA. DATA EXTRACTION: Teams of two reviewers independently and in duplicate adjudicated eligibility, assessed risk of bias and abstracted study characteristics and outcomes. DATA SYNTHESIS: Twenty-one eligible studies included 96,448 patients. Major bleeding rates varied widely, from 0 to 4.69 events per 100 patient-years. The pooled estimate in 13 studies with 78839 patients was 1.59 with a 99% confidence interval of 1.10 to 2.3 and median 1.42 (interquartile range 0.62-2.70). Pooled estimates for fatal bleeding and non-fatal bleeding from 4 studies that reported these outcomes were, respectively, 0.40 (0.34 to 0.46) and 1.18 (0.30 to 4.56) per 100 patient-years. In 9 randomized controlled trials (RCTs) the median rate of major bleeding in patients not receiving either anticoagulant or antiplatelet therapy was 0.6 (interquartile 0.2 to 0.90), and in 12 RCTs the median rate of major bleeding in patients receiving a single antiplatelet agent was 0.75 (interquartile 0.4 to 1.4). CONCLUSION: Results suggest that patients with atrial fibrillation not receiving VKA enrolled in observational studies represent a population on average at higher risk of bleeding.
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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 | 0.029 | 0.161 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.010 |
| Bibliometrics | 0.013 | 0.015 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".