Effects of the Acyl Coenzyme A:Cholesterol Acyltransferase Inhibitor Avasimibe on Human Atherosclerotic Lesions
Bibliographic record
Abstract
BACKGROUND: Inhibition of the acyl coenzyme A:cholesterol acyltransferase (ACAT) enzyme may prevent excess accumulation of cholesteryl esters in macrophages. The ACAT inhibitor avasimibe was shown to reduce experimental atherosclerosis. This study was designed to investigate the effects of avasimibe on human coronary atherosclerosis. METHODS AND RESULTS: This randomized, double-blind, placebo-controlled trial assessed the effects of avasimibe at dosages of 50, 250, and 750 mg QD on the progression of coronary atherosclerosis as assessed by intravascular ultrasound (IVUS). All patients received background lipid-lowering therapy if necessary to reach a target baseline LDL level <125 mg/dL (3.2 mmol/L). IVUS and coronary angiography were performed at baseline and repeated after up to 24 months of treatment. Approximately equal percentages of patients across groups received concurrent statin therapy (87% to 89%). The mean total plaque volume at baseline was approximately 200 mm3, and the least squares mean change at end of treatment was 0.7 mm3 for placebo and 7.7, 4.1, and 4.8 mm3 for the avasimibe 50, 250, and 750 mg groups, respectively (adjusted P=0.17 [unadjusted P=0.057], 0.37, and 0.37, respectively). Percent atheroma volume increased by 0.4% with placebo and by 0.7%, 0.8%, and 1.0% in the respective avasimibe groups (P=NS). LDL cholesterol increased during the study by 1.7% with placebo but by 7.8%, 9.1%, and 10.9% in the respective avasimibe groups (P<0.05 in all groups). CONCLUSIONS: Avasimibe did not favorably alter coronary atherosclerosis as assessed by IVUS. This ACAT inhibitor also caused a mild increase in LDL cholesterol.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".