Anticoagulation and population risk of stroke and death in incident atrial fibrillation: a population-based cohort study
Bibliographic record
Abstract
BACKGROUND: Atrial fibrillation increases the risk of stroke and death. Anticoagulation therapy is an effective treatment for stroke prevention, but remains underused in the community. We sought to determine the effectiveness and safety of anticoagulation therapy in an inception cohort with new-onset atrial fibrillation in the province of Alberta, Canada. METHODS: We conducted a population-based cohort study of atrial fibrillation using an administrative database from Alberta's publicly funded and universally available health care system. All new-onset atrial fibrillation patients from Jan. 1, 2009, to Dec. 31, 2010, were included in the cohort and followed through Dec. 31, 2013. We assessed anticoagulation status as a predictor of stroke and death using time-to-event analysis and adjusted for sex and CHADS2 (congestive heart failure, hypertension, age ≥ 75 yr, diabetes mellitus and prior stroke or transient ischemic attack) score using Cox proportional hazards modelling. RESULTS: We identified 10 745 patients, 7358 (68.5%) of whom received anticoagulation therapy, principally with warfarin (n = 6997, 95.1%). Anticoagulation therapy was associated with significantly decreased risk of ischemic stroke (hazard ratio [HR] 0.69, 95% confidence interval [CI] 0.58-0.82), all stroke (HR 0.77, 95% CI 0.65-0.91), all stroke and death (HR 0.70, 95% CI 0.62-0.72) and all-cause mortality (HR 0.67, 95% CI 0.62-0.72), despite an association with increased risk of hemorrhagic stroke (HR 1.92, 95% CI 1.17-3.16). There was a neutral association with subdural (HR 1.01, 95% CI 0.53-1.93) and gastrointestinal (HR 0.96, 95% CI 0.70-1.31) hemorrhage. INTERPRETATION: Anticoagulation therapy is effective and safe for stroke prevention and decreases mortality in patients with incident atrial fibrillation. These population data support an aggressive approach to screening for atrial fibrillation and treatment with anticoagulant medicines to prevent stroke and death.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".