Abstract 10740: Effects of Renin-Angiotensin-Aldosterone-System Inhibitors on Coronary Atherosclerotic Plaques: Results From the Paradigm Registry
Bibliographic record
Abstract
Introduction: Coronary CT Angiogram (CCTA) has become a powerful tool in the diagnosis and risk stratification of coronary artery disease (CAD), but can also provide unique insight into the effects of pharmacotherapy on the progression of atherosclerosis. Although Renin-Angiotensin-Aldosterone-System (RAAS) inhibitors are indicated in patients with stable CAD, their impact on the progression of coronary atherosclerosis is unclear. Methods: We performed a prospective, multinational study consisting of a registry of patients without history of CAD who underwent serial CCTAs at an interscan interval of >2 years. Patients taking RAAS inhibitors were propensity matched to RAAS inhibitor naïve patients based on clinical and CCTA characteristics at the baseline. Atherosclerotic plaques in CCTAs were quantitatively analyzed for percent atheroma volume (PAV) according to plaque composition (necrotic core, fibro-fatty plaque, fibrous plaque, and calcium) using predefined Hounsfield unit thresholds. Results: Of 1,248 patients from the registry, 299 RAAS inhibitor taking patients were matched to 299 RAAS inhibitor naïve patients. Over a median interval of 3.9 years, there was no significant difference in annual progression of total PAV between RAAS inhibitor naive vs taking patients (0.75 vs 0.79 %/year, p = 0.66), nor was there any difference in the progression of necrotic core (-0.02 vs 0.002 %/year, p = 0.09), fibrofatty plaque (-0.03 vs.0.05 %/year, p = 0.67), fibrous plaque (0.29 vs 0.25 %/year, p =0.91), or calcified plaque (0.51 vs. 0.51 %/year, p = 0.37). Conclusions: Within this cohort of patients, the use of RAAS inhibitors over a period of nearly 4 years did not have a measurable impact on progression of total atherosclerotic plaque or any plaque subtypes assessed by CCTA. These results suggest that the benefit of RAAS inhibition is independent of an effect on coronary plaque progression.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".