Angiotensin-converting enzyme inhibitors and atherosclerotic plaque: a key role in the cardiovascular protection of patients with coronary artery disease
Bibliographic record
Abstract
In EUROPA, the angiotensin-converting enzyme inhibitor (ACEI) perindopril on top of other preventative therapies reduced the risk of major coronary events (cardiovascular death, myocardial infarction, resuscitated cardiac arrest) by 20% when compared with placebo (P = 0.0003) in patients with stable coronary artery disease (CAD). These cardiovascular benefits may be attributable not only to the blood pressure-lowering effect of the drug, but also potentially to a direct cardioprotective vascular effect as determined in two substudies of EUROPA. Analysis of intravascular ultrasound data from the PERSPECTIVE substudy indicated that perindopril treatment may be associated with favourable patterns of coronary remodelling that are associated with plaque stabilization and may induce regression of non-calcified lesions. In the PERTINENT substudy, there were reductions in markers of coronary vascular endothelial cell dysfunction and the rate of endothelial cell apoptosis in perindopril recipients. Experimental data suggest an advantage of perindopril over other ACEIs at the level of tissue ACE inhibition and relative selectivity for bradykinin, which may explain the mechanism of the beneficial effect of perindopril on the endothelium. These differences may underpin the differential results in large clinical trials of ACEIs in patients with stable CAD.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".