High- vs. low-intensity statin therapy and changes in coronary artery calcification density after one year
Bibliographic record
Abstract
Abstract Introduction High-dose statin therapy (HIST) halts coronary plaque progression and reduces the risk of cardiovascular events by increasing atheroma calcification. The Agatston score is well established in the clinical routine for assessment of coronary artery calcification using non-contrast computed tomography. However, randomized controlled trials failed to detect an influence of HIST vs. low-to-intermediate statin therapy (LIST) on the Agatston and CAC volume score after one year. Coronary plaques with lower density including spotty calcifications may represent dynamic and early stages of atherosclerosis. We evaluated whether CAC density differentiates in HIST- vs. LIST-treated patients after one year. Methods The meta-analysis contains data from two prospective, randomized, double-blind studies (BELLES, EBEAT) that were designed to detect CAC changes after one year comparing HIST vs. LIST. In both studies, patient's coronary calcification burden was measured at baseline and one-year follow-up using electron beam computed tomography (EBCT). Patients data were pooled and stratified by intensity of statin therapy. Furthermore, the cohort was divided into several subgroup analyses, accounting for LDL-Cholesterol reduction, initial Agatston score and a consistent number of lesions. Results Data from 852 patients, 66% female were included. The amount of CAC overall increased after 1 year [Agatston score: 169.3 (80.0, 377.1) vs. 214.9 (95.4, 450.0); p<0.0001NP; volume score: 292.1±445.4 vs. 355.5±482.4; p<0.0001; number of lesions: 6 (3,10) vs. 7 (4,12); p<0.0001NP, at baseline and follow-up, respectively]. Likewise, the average CAC density was higher at follow-up [CAC density: 228.8±35.4 vs. 232.6±37.0; p<0.0001]. HIST vs. LIST more effectively reduced LDL-cholesterol (annualized change: −58.6±50.9 vs. −44.4±43.7 mg/dL, p=0.005). Comparing patients on HIST vs. LIST, CAC density at follow-up (231.9±36.1 HU vs. 233.3±37.7, p=0.59) and its change from baseline (4.0±19.1 HU vs. 3.6±19.6 HU, p=0.73) did not differ. Subgroup analyses, stratifying by LDL-reduction ( Conclusion HIST vs. LIST leads to a higher reduction in cholesterol levels, which does not translate into relevant differences in the change of CAC density at one-year follow-up. Funding Acknowledgement Type of funding sources: None.
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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.010 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".