Blood Pressure and Atrial Fibrillation: A Combined AF‐CHF and AFFIRM Analysis
Bibliographic record
Abstract
BACKGROUND: Hypertension is an established risk factor for new-onset atrial fibrillation (AF). However, the relationship between blood pressure and recurrent AF is less well understood. METHODS AND RESULTS: A pooled analysis of patient-level data from AFFIRM and AF-CHF trials was conducted on all 2,715 patients with paroxysmal or persistent AF, 68 ± 8 years, 66% male, randomized to rhythm control and followed for 40.6 ± 16.5 months. We assessed the impact of a baseline systolic blood pressure (SBP; <120 mmHg [N = 1,008], 120-140 mmHg [N = 930], >140 mmHg [N = 777]) on recurrent AF and proportion of time spent in AF. In patients with LVEF >40% (N = 1,719), SBP was not associated with recurrent AF in multivariate regression analyses (P = 0.752). In contrast, in patients with LVEF ≤40% (N = 996), the AF recurrence rate was higher in those with an SBP >140 mmHg compared to 120-140 mmHg (hazard ratio 1.47; 95% CI [1.12-1.93], P = 0.005). The rate of recurrent AF was similar in patients with SBP <120 mmHg compared to 120-140 mmHg (hazard ratio 1.15; 95% CI [0.92-1.43], P = 0.225). Consistently, the proportion of time spent in AF was not influenced by SBP in patients with LVEF >40% (P = 0.645). However, in patients with LVEF ≤40%, the adjusted mean proportion of time spent in AF was 17.2% if SBP was <120 mmHg, 15.4% for SBP 120-140 mmHg, and 24.0% for SBP >140 mmHg (P = 0.025). CONCLUSION: Systolic blood pressure is an important determinant of recurrent AF and overall AF burden in patients with left ventricular dysfunction (LVEF≤40%) but not in those with preserved ventricular function.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".