Therapeutic modulation of the natural history of coronary atherosclerosis: lessons learned from serial imaging studies
Bibliographic record
Abstract
Despite advances in risk prediction, preventive and therapeutic strategies, atherosclerotic cardiovascular disease remains a major public health challenge worldwide, carrying considerable morbidity, mortality and health economic burden. There continues to be a need to better understand the natural history of this disease to guide the development of more effective treatment, integral to which is the rapidly evolving field of coronary artery imaging. Various imaging modalities have been refined to enable detailed visualization of the pathological substrate of atherosclerosis, providing accurate and reproducible measures of coronary plaque burden and composition, including the presence of high-risk characteristics. The serial application of such techniques, including coronary computed tomography angiography (CTA), intravascular ultrasound (IVUS) and optical coherence tomography (OCT) have uncovered important insights into the progression of coronary plaque over time in patients with stable and unstable coronary artery disease (CAD), and its responsiveness to therapeutic interventions. Here we review the use of different imaging modalities for the surveillance of coronary atherosclerosis and the lessons they have provided about the modulation of CAD by both traditional and experimental therapies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".