Abstract 83: Effect of Dietary Cholesterol and Egg Consumption On Mortality And Cardiovascular Risk in the REGARDS Study
Bibliographic record
Abstract
Background and purpose: It has long been recommended that patients at risk of cardiovascular events limit their intake of dietary cholesterol to <200 mg/day. One large egg yolk contains more than 200mg of cholesterol, and also contains 250mg of phosphatidylcholine, which is converted by intestinal bacterial to trimethylamine. In the face of increasingly widespread belief that consumption of dietary cholesterol and eggs is harmless, we analyzed the effects of these dietary constituents on mortality and cardiovascular outcomes in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study population. Methods: A longitudinal cohort study of 30,239 community-dwelling black and white individuals aged 45+ years, recruited between January 2003 and October 2007 from the 48 contiguous states. The study oversampled black participants (44%), and residents of the southeastern “stroke belt” (56%). We analyzed total mortality and atherosclerotic events (ischemic stroke, myocardial infarction and revascularization) after 4.9 (SD 1.7) years of followup. Hazard ratios were computed for egg consumption and cholesterol consumption by quartiles, adjusted for race, age, sex, income, education, region, dyslipidemia, exercise, hypertension, diabetes, smoking, atrial fibrillation and caloric intake. Results: As shown in the table, there was a dose-related increase in all-cause mortality and atherosclerotic events with both cholesterol intake and egg consumption. Conclusions: Recommendations to limit the intake of cholesterol remain good advice for patients at risk of cardiovascular events. As one large egg yolk contains more than the daily recommended intake of cholesterol, egg yolk consumption should also be limited.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".