Abstract 18267: Coronary Risk Factors and Prevalence and Severity of Coronary Atherosclerosis in the Young
Bibliographic record
Abstract
Purpose. We examined the relationship between coronary risk factors (RF) and prevalence and severity of coronary atherosclerosis in young individuals undergoing coronary CT angiography (CCTA). Methods. Of 27125 patients undergoing CCTA, 1635 young (50%stenosis), and presences of calcified plaque (CP) and non-calcified plaque (NCP). Results. Among 1635 subjects (70% men, age 38±6 years), 6% had diabetes (DM), 31% had hypertension (HTN), 37% had dyslipidemia (CHOL), 21% had smoking (SM) and 33% had family history (FH) of CAD. Among all young individuals, any CAD, obs CAD, CP and NCP were observed in 19%, 4%, 5%, and 8%, respectively. Compared to women, men demonstrated higher rates of any CAD (21% vs 12% P<0.001), CP (6% vs 3% P=0.01), and NCP (9% vs 5% P=0.008), although no difference was observed for rates of obs CAD (5% vs. 4% P=NS). Any CAD, obs CAD, and NCP were higher for young individuals with DM, HTN, CHOL, SM or FH of CAD; while only DM and CHOL were associated with CP (Table). In multivariable analysis adjusting for sex and RFs, male sex was the strongest predictor for any CAD (Odds Ratio [OR] 1.95, 95% Confidence Interval [CI] 1.43-2.66, P<0.001), CP (OR 1.46, 95%CI 1.08-1.98, P=0.014) and NCP (OR 1.33, 95%CI 1.06-1.67, P=0.014); while FH of CAD was the strongest predictor for obs CAD (OR 2.71, 95% CI 1.65-4.45, P3 RFs manifesting a significant increase in any CAD (P<0.001 for trend); obs CAD (P<0.001 for trend); NCP (P<0.001 for trend) and CP (P=0.008 for trend). Conclusions. CAD is present in 1 in 5 young individuals, with sex and coronary RFs associated with increasing presence and severity of CAD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".