Serum Cholesterols Have a More Important Role Than Triglycerides in Determining Intima-Media Thickness of the Common Carotid Artery in Subjects Younger Than 55 Years of Age
Bibliographic record
Abstract
OBJECTIVE: The role of serum cholesterol and triglycerides in carotid artery atherosclerosis is controversial. We measured carotid artery intima-media thickness (IMT), a marker of atherosclerosis in subjects younger than 55 years of age with a 6-fold range of serum cholesterol levels (3.93-25.03 mmol/L) and a 200-fold range of triglyceride levels (0.36-75.97 mmol/L). METHODS: Eighty-six patients with increased serum lipid values and 30 subjects with normal lipid values were included. Serum lipids were measured after an overnight fast. High-resolution sonographic investigations of the carotid arteries of all patients were videotaped. Intima-media thickness was measured offline at 1-mm increments in the distal 10-mm segments of both common carotid arteries by a reader blinded to patient characteristics. First, IMT was compared among groups defined by their cholesterol and triglyceride levels with the use of traditional cutoff values. Next, all subjects were pooled, and general regression analysis was performed to identify significant predictors of IMT with age, body mass index, lipid values, sex, diabetes, hypertension, and smoking status as independent variables. RESULTS: Intima-media thickness was larger in patient groups with high cholesterol levels (ie, the hypercholesterolemic and combined hyperlipidemic groups) than in the control, borderline, and isolated hypertriglyceridemic groups (P < .01). In the general multiple regression model, IMT correlated positively with total cholesterol level (beta = 0.343; P = .002) and age (beta = 0.3; P = .006) but not with triglyceride level. CONCLUSIONS: Both the group comparisons and the general regression analysis of the pooled data suggest that hypercholesterolemia has an important role in early onset IMT changes in the common carotid artery, whereas hypertriglyceridemia does not have an appreciable role.
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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 | 0.000 | 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) | 0.002 | 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".