Association of statin therapy with progression of coronary artery calcium composition and density on noncontrast computed tomography
Bibliographic record
Abstract
Abstract Background The long-term effect of statins on progression of coronary artery calcium (CAC) density as measured by noncontrast computed tomography (CT) remains unknown. Purpose We sought to examine the association of statin therapy with temporal changes in compositional calcium density using quantitative assessment of serial CAC scoring CT. Methods This was a retrospective, single-center study of asymptomatic individuals with serial CAC scoring CT ≥12 months apart. Scans were analyzed using a fully automated deep learning model, with quantification of per-patient total CAC volume and volumes of calcium compositional subtypes stratified by Hounsfield unit (HU) density: 130-199; 200-299; 300-399; ≥400 HU. Results Of 316 patients (58.4±10.1 years of age; 49.1% men) with CAC present at baseline and rescanned at a mean interval of 3.8±1.7 years, 175 (55.4%) patients were statin-treated and 141 (44.6%) patients were statin-naive. In patients exhibiting only low-density calcium (130-199 HU) at baseline, statin therapy was associated with a temporal decrease in CAC volume (β –0.05 [–0.09 to –0.02]; p<0.05). Among patients with ≥2 calcium compositional subtypes at baseline, statin therapy was associated with a greater temporal increase in the volumes of each density stratum (130-199 HU: β 0.05 [0.00-0.11]; 200-299 HU: β 0.11 [0.07-0.14]; 300-399 HU: β 0.11 [0.07-0.16]; ≥400 HU: β 0.11 [0.06-0.16]; all p<0.05) compared with no statin therapy. Similar results were observed for changes in the relative proportions of each density stratum (all p<0.001). Statin therapy was associated with an increase in mean and peak calcium HU density (β 5.93 [4.33-7.54] and β 19.22 [12.04-26.40], respectively; both p<0.01). The effect of statins on compositional CAC volume progression did not differ between patients with baseline CAC score 1-99 or ≥100. Conclusion In asymptomatic individuals undergoing serial CAC scoring CT, statin therapy was associated with a shift toward denser calcium; considered a more stable phenotype. Assessment of CAC density may capture more unique aspects of plaque progression beyond traditional scoring.Change in compositional CAC proportions
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".