Angiotensin receptor blockers and risk of myocardial infarction: systematic review
Bibliographic record
Abstract
OBJECTIVE: To evaluate the effect of angiotensin receptor blockers on the risk of myocardial infarction in patients at risk for cardiovascular events. DESIGN: Systematic review of controlled trials of angiotensin receptor blockers. DATA SOURCES: Medline, Embase, Cochrane central register of controlled trials, hand search, and contact with investigators. SELECTION OF STUDIES: Predefined criteria were used to select controlled clinical trials comparing use of angiotensin receptor blockers with angiotensin converting enzyme (ACE) inhibitors or placebo in patients at risk for cardiovascular events. Data were extracted for patients' characteristics, interventions, quality of trials, and rates of myocardial infarction. RESULTS: 19 studies with 31,569 patients were included in the analysis. Two studies investigated the use of angiotensin receptor blockers in hypertensive patients, four studies in patients with diabetes and nephropathy, 10 studies in patients with heart failure, and three in patients with recent myocardial infarction or ischaemic syndrome. 11 studies of 21,062 patients allowed for comparison between angiotensin receptor blockers and placebo; nine studies of 10,625 patients allowed for comparison between angiotensin receptor blockers and ACE inhibitors. Use of angiotensin receptor blockers was not associated with increased risk of myocardial infarction compared with placebo (odds ratio 0.94, 95% confidence interval 0.75 to 1.16) nor with increased risk of myocardial infarction compared with ACE inhibitors (1.01, 0.87 to 1.16). CONCLUSIONS: Treatment with angiotensin receptor blockers was not associated with a significantly increased risk of myocardial infarction. The 95% confidence intervals do, however, not exclude an increase of up to 16% in the risk of myocardial infarction or a reduction in risk of up to 25%. Until further information specifically dealing with this issue is available from large prospective trials, our findings may alleviate recent concerns over the safety of this class of medications.
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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 | 0.007 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.007 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".