Cardiovascular risk and subclinical atherosclerosis in first-degree relatives of patients with premature cardiovascular disease
Bibliographic record
Abstract
Screening first-degree relatives (FDRs) of patients with premature coronary artery disease (CAD) is recommended but not routinely performed. To assess the diagnostic yield and impact on clinical management of a clinical and imaging-based screening program of FDRs delivered in the setting of routine clinical care. We recruited FDRs of patients with premature CAD with no personal history of CAD and prospectively assessed for: 1) cardiovascular risk and presence of significant subclinical atherosclerosis (SA) defined as plaque on carotid ultrasound, stenosis >50% or extensive atherosclerosis on coronary computed tomography angiography, or coronary artery calcium scores >100 Agatston units or >75% percentile for age and sex; 2) utilization of preventive medications and lipid levels prior enrolment and after completion of the assessment. We assessed 132 FDRs (60.6% females), mean (SD) age 47(17) years old. Cardiovascular risk was high in 38.2%, moderate in 12.2%, and low in 49.6% of FDRs. SA was present in 34.1% of FDRs, including 12.5% in low, 51.9% in moderate, and 55.0% in high calculated risk groups. After assessment, LLT was initiated in 32.6% of FDRs and intensified in 16.0% leading to mean (SD) LDL-C decrease of 1.07(1.10) mmol/L in patients with high calculated risk or SA. LLT was recommended to all patients with high calculated risk, but those with SA were more likely to receive the medications from pharmacies (93.3% vs 60.0%, p = 0.006). Screening the FDRs of patients with premature CAD is feasible, may have high diagnostic yield and impact risk factor management.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".