Effects of RAAS Blockers on Atrial Fibrillation Prophylaxis
Bibliographic record
Abstract
BACKGROUND: Impact of atrial fibrillation on clinical outcomes is well recognized, and application of renin-angiotensin-aldosterone system (RAAS) blockers for the prevention of atrial fibrillation (AF) is a theoretically appealing concept. However, clinical trials have yielded inconsistent results. METHODS: A pooled study of 26 randomized controlled trials (RCTs) assessing the efficacy of RAAS blockers on AF prophylaxis was performed. RESULTS: A total of 28 reports from 26 randomized controlled trials enrolled 165 387 patients, with an overall 24% reduction in the incidence of AF (odds ratio [OR]: 0.76, 95% confidence interval [CI]: 0.68-0.85], P = .000). Forty-nine percent reduction in the incidence of AF (OR: 0.51, 95% CI: 0.30-0.85, P = .010) in systolic heart failure was observed, whereas no significant effect was observed in patients with diastolic heart failure, postmyocardial infarction, and high cardiovascular disease risk. There was a 19% (OR: 0.81, 95% CI: 0.67-1.00, P = .037) reduction in new-onset and 54% (OR: 0.46, 95% CI: 0.33-0.62, P = .000) reduction in recurrent AF in hypertensive patients with 39% (OR: 0.61, 95% CI: 0.44-0.84, P = .003) risk reduction against calcium blockers and 41% (OR: 0.59, 95% CI: 0.44-0.80, P = .001) risk reduction against β blockers. Angiotensin-receptor blocker appeared marginally superior to angiotensin-converting enzyme inhibitor in primary and secondary prevention. CONCLUSION: This study suggests that RAAS blockade effectively suppresses AF in systolic heart failure, and hypertensives derive greater benefit against new-onset and recurrent AF compared to β blockers, calcium channel blockers, and diuretics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.003 | 0.004 |
| 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".