Abstract P453: Apolipoprotein B, Low-Density Lipoprotein Particle Number, Non-High-Denisity Lipoprotein Cholesterol, Low-Density Lipoprotein Cholesterol, and Total Cholesterol for Atherosclerotic Cardiovascular Disease Risk Prediction in Young Adults
Bibliographic record
Abstract
Introduction: Measures of atherogenic particle number (apoB and LDL particle number [LDL-P]) are stronger predictors of atherosclerotic cardiovascular disease (ASCVD) risk than measures of cholesterol concentration (LDL-C, non-HDL-C, total cholesterol [TC]) in middle-aged adults. It is unclear if this is true for younger adults. Methods: Among CARDIA participants (ppts), NMR was used to measure apoB and LDL-P. Non-HDL-C and TC were measured using standard assays; LDL-C was calculated using the Friedewald equation. We stratified the ppts into two age windows: age 20-30y (n=1645) and age 30-40y (n=2922). We used adjusted Cox proportional hazards models to assess the associations of 1SD higher apoB, LDL-P, non-HDL-C, LDL-C, or TC with incident ASCVD events. We substituted each measure of atherogenic lipid burden for TC in a modified Pooled Cohort Equation (PCE) model (with and without HDL-C); and model performance (discrimination and reclassification) was evaluated. Results: There were 81 and 163 ASCVD events over (median [IQR]) 31.8y (31.1-32.0y) for the age 20-30 age window and over 26.8y (19.1-27.1y) for the 30-40y age window, respectively. In ppts age 20-30y, a 1SD higher apoB, LDL-P, non-HDL-C, and LDL-C were significantly associated with incident ASCVD in demographic adjusted models. The strengths of associations with ASCVD were not significantly different across these measures. For the 30-40y age window, all measures of atherogenic lipoproteins were significantly associated with ASCVD; the strengths of association were not significantly different across atherogenic lipid measures in all models. There were no significant differences in the C-statistic and no improvement in reclassification when each measure was used to replace TC in the PCE model. Conclusions: ApoB, LDL-P, LDL-C or non-HDL-C may be slightly better markers of long-term ASCVD risk than TC in adults < 30y. However, in adults between 30-40y all measures of atherogenic lipid burden appeared to be equivalent predictors of long-term risk.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".