Hypertension prevalence but not control varies across the spectrum of risk in patients with atrial fibrillation: A RE-LY atrial fibrillation registry sub-study
Bibliographic record
Abstract
BACKGROUND: Although hypertension is the most common risk factor for atrial fibrillation (AF), whether blood pressure (BP) control varies across the spectrum of stroke risk in patients with AF or by adequacy of their thromboprophylaxis management is unclear. METHODS: We examined data from the RE-LY AF registry conducted at 164 emergency departments (EDs) in 47 countries between December 2007 and October 2011. RESULTS: Of the 15,400 patients in the registry, we analyzed the 9929 (mean age 67.5 years, 51.9% men) with a prior history of AF and complete BP data. While 6508 (66.5%) AF patients had hypertension, the prevalence varied widely depending on comorbidity profiles: from 45.4% in those without other cardiovascular risk factors to 82.5% in those with AF and diabetes. Although 93.9% of AF patients with hypertension were on at least one antihypertensive agent, fewer than half had BP levels ≤ 140/90 with no difference across risk profiles: 45.9% of those with NVAF and CHADS2 scores of 1 and 45.6% of those with NVAF and CHADS2 scores of 2 or more (46.9% and 45.3% for CHA2DS2-VASc scores of 1 versus 2 or more). BP control rates were not significantly better in those NVAF patients receiving guideline concordant thromboprophylaxis management (47.2%, aOR 1.03, 95%CI 0.89-1.20) than in those not receiving guideline-concordant antithrombotic therapy (45.3%). CONCLUSIONS: Hypertension was common in patients with AF but BP control rates were sub-optimal and varied little across the spectrum of stroke risk or by adequacy of thromboprophylaxis. This highlights the need for an increased focus on total atherosclerotic risk rather than just thromboprophylaxis management in AF patients.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".