VLDL, Apolipoproteins B, CIII, and E, and Risk of Recurrent Coronary Events in the Cholesterol and Recurrent Events (CARE) Trial
Bibliographic record
Abstract
BACKGROUND: Plasma triglyceride concentration has been an inconsistent independent risk factor for coronary heart disease, perhaps because of the metabolic heterogeneity among VLDL particles, the main carriers of triglycerides in plasma. METHODS AND RESULTS: We conducted a prospective, nested case-control study in the Cholesterol and Recurrent Events (CARE) trial, a randomized placebo-controlled trial of pravastatin in 4159 patients with myocardial infarction and average LDL concentrations at baseline (115 to 174 mg/dL, mean 139 mg/dL). Baseline concentrations of VLDL-apolipoprotein (apo) B (the VLDL particle concentration), VLDL lipids, and apoCIII and apoE in VLDL+LDL and in HDL were compared in patients who had either a myocardial infarction or coronary death (cases, n=418) with those in patients who did not have a cardiovascular event (control subjects, n=370) in 5 years of follow-up. VLDL-cholesterol, VLDL-triglyceride, VLDL-apoB, apoCIII and apoE in VLDL+LDL and apoE in HDL were all interrelated, and each was a univariate predictor of subsequent coronary events. The significant independent predictors were VLDL-apoB (relative risk [RR] 3.2 for highest to lowest quintiles, P:=0.04), apoCIII in VLDL+LDL (RR 2.3, P:=0.04), and apoE in HDL (RR 1.8, P:=0.02). Plasma triglycerides, a univariate predictor of coronary events (RR 1.6, P:=0.03), was not related to coronary events (RR 1.3, P:=0.6) when apoCIII in VLDL+LDL was included in the model, whereas apoCIII remained significant. Adjustment for LDL- and HDL-cholesterol did not affect these results. CONCLUSIONS: The plasma concentrations of VLDL particles and apoCIII in VLDL and LDL are more specific measures of coronary heart disease risk than plasma triglycerides perhaps because their known metabolic properties link them more closely to atherosclerosis.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".