Angiotensin-converting enzyme inhibitors or angiotensin receptor blockers are beneficial in normotensive atherosclerotic patients: a collaborative meta-analysis of randomized trials
Bibliographic record
Abstract
AIMS: It is unclear whether angiotensin-converting enzyme inhibitors (ACE-I) or angiotensin receptor blockers (ARB) are beneficial in individuals with, or at increased risk for, atherosclerotic vascular disease who are normotensive. METHODS AND RESULTS: Two investigators independently searched MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials from 1980 to 2011, bibliographies, and contacted primary study authors for randomized placebo-controlled outcome trials evaluating ACE-I or ARB which enrolled at least 1000 patients with, or at increased risk for, atherosclerotic vascular disease and followed them for at least 12 months. We approached all eligible trials to obtain data stratified by baseline systolic pressures. We pooled data from 13 trials of 80 594 patients; outcomes included 9043 all-cause deaths, 5674 cardiovascular deaths, 3106 myocardial infarctions, and 4452 strokes. Angiotensin-converting enzyme inhibitors or ARB reduced the composite primary outcome of cardiovascular death, non-fatal myocardial infarction, or non-fatal stroke by 11% (95% confidence interval 7-15%), with no variation in efficacy across baseline systolic blood pressure strata. In patients with baseline systolic pressure <130 mmHg, ACE-I or ARB reduced the composite primary outcome by 16% (10-23%) and all-cause mortality by 11% (4-18%)-this benefit was consistent across all subgroups examined including those without systolic heart failure (OR: 0.81, 95% CI: 0.75-0.88) and those without diabetes (OR: 0.79, 95% CI: 0.70-0.89). CONCLUSION: Angiotensin-converting enzyme inhibitors or ARB are beneficial in patients with, or at increased risk for, atherosclerotic disease even if their systolic pressure is <130 mmHg before treatment.
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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 | 0.034 | 0.069 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.028 | 0.056 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".