Comparison of Various Electrophoretic Characteristics of LDL Particles and Their Relationship to the Risk of Ischemic Heart Disease
Bibliographic record
Abstract
BACKGROUND: Several cross-sectional studies and 3 prospective, nested, case-control studies have indicated that individuals with small, dense low density lipoprotein (LDL) particles are at increased risk for ischemic heart disease (IHD). However, whether LDL particle size is an independent risk factor for future IHD events remains controversial. The objective of the present study was to further analyze the cardiovascular risk associated with various electrophoretic characteristics of LDL particles in men. METHODS AND RESULTS: LDL particles were characterized by polyacrylamide gradient gel electrophoresis (PAGGE) in a cohort of 2034 men of the Quebec Cardiovascular Study. All men were initially free of IHD and were followed up for a period of 5 years, during which 108 first IHD events were recorded. Among all LDL characteristics investigated by PAGGE, including LDL peak particle size, the cholesterol concentration in LDL particles with a diameter smaller than 255 A showed the strongest association with the risk of IHD (relative risk=4.6 in men in the third vs first tertile of the distribution, P<0.001). Multivariate logistic and survival models indicated that the relationship between LDL cholesterol levels in particles with a diameter <255 A and IHD risk was independent of all nonlipid risk factors and of LDL cholesterol, high density lipoprotein cholesterol, triglyceride, and lipoprotein(a) levels. CONCLUSIONS: Results from this large, population-based, prospective study suggest that further characterization of LDL particles by PAGGE, in addition to the traditional lipid profile, may improve our ability to predict IHD events in men.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".