Effect of RAAS blockers on adverse clinical outcomes in high CVD risk subjects with atrial fibrillation
Bibliographic record
Abstract
Recent studies have demonstrated that atrial fibrillation significantly increases the risk of adverse clinical outcomes in high cardiovascular disease risk subjects. Application of renin-angiotensin-aldosterone system blockers for prevention of recurrence of atrial fibrillation and adverse clinical outcomes in subjects with atrial fibrillation is a theoretically appealing concept. However, results of clinical trials evaluating the effect of renin-angiotensin-aldosterone blockers on adverse clinical outcomes in high cardiovascular disease risk subjects with atrial fibrillation remain inconclusive.A pooled study of 6 randomized controlled trials assessing the efficacy of renin-angiotensin-aldosterone blockers on subjects with atrial fibrillation was performed.A total of 6 randomized controlled trials enrolled a total of 53,510 patients followed for 1 to 5 years. RAAS blockade therapy was associated with 14% reduction in the incidence of heart failure (OR: 0.86, [95%CI: 0.76- 0.97], P=0.018) and 17% reduction in the incidence of CVE (OR: 0.83, [95%CI: 0.70-0.99], P = 0.038). The corresponding decline in absolute risk against heart failure (ARR: 1.4%, [95%CI: 0.2-2.6%], P = 0.018) and CVE (ARR: 3.5%, [95%CI: 0.0-6.9%], P = 0.045) in the AF group was much higher than the non-AF group for heart failure (ARR: 0.4%, [95%CI: 0.0-0.7%], P = 0.057) and CVE (ARR: 1.6%, [95%CI: -0.1% to 3.3%], P = 0.071). No significant effect was noted on all-cause or cardiovascular mortality, stroke, or myocardial infarction.This study suggests that RAAS blockade offers protection against heart failure and cardiovascular events in high cardiovascular disease risk subjects with atrial fibrillation.
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 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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".