Bleeding and related mortality with NOACs and VKAs in newly diagnosed atrial fibrillation: results from the GARFIELD-AF registry
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Bibliographic record
Abstract
In atrial fibrillation (AF), lower risks of death and bleeding with non-vitamin-K oral anticoagulants (NOACs) were reported in meta-analyses of controlled trials, but whether these findings hold true in real-world practice remains uncertain. Risks of bleeding and death were assessed in 52 032 patients with newly diagnosed AF enrolled in GARFIELD-AF (Global Anticoagulant Registry in the FIELD-Atrial Fibrillation), a worldwide prospective registry. Baseline treatment was vitamin K antagonists (VKAs) with or without antiplatelet (AP) agents (VKA ± AP) (20 151; 39.3%), NOACs ± AP agents (14 103; 27.5%), AP agents only (10 748; 21.0%), or no antithrombotics (6219; 12.1%). One-year follow-up event rates (95% confidence interval [CI]) of minor, clinically relevant nonmajor (CRNM), and major bleedings were 2.29 (2.16-2.43), 1.10 (1.01-1.20), and 1.31 (1.21-1.41) per 100 patient-years, respectively. Bleeding risk was lower with NOACs than VKAs for any bleeding (hazard ratio (HR) [95% CI]), 0.85 [0.73-0.98]) or major bleeding (0.79 [0.60-1.04]). Compared with no bleeding, the risk of death was higher with minor bleeding (adjusted HR [aHR], 1.53 [1.07-2.19]), CRNM bleeding (aHR, 2.59 [1.80-3.73]), and major bleeding (aHR, 8.24 [6.76-10.04]). The all-cause mortality rate was lower with NOACs than with VKAs (aHR, 0.73 [0.62-0.85]). Forty-five percent (114) of all deaths occurred within 30 days, and 40% of these were from intracranial/intraspinal hemorrhage (ICH). The rates of any bleeding and all-cause death were lower with NOACs than with VKAs. Major bleeding was associated with the highest risk of death. CRNM bleeding and minor bleeding were associated with a higher risk of death compared to no bleeding. Death within 30 days after a major bleed was most frequently related to ICH. This trial was registered at www.clinicaltrials.gov as #NCT01090362.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it