Dietary cholesterol and the risk of cardiovascular disease in patients: a review of the Harvard Egg Study and other data
Bibliographic record
Abstract
For many years, both the medical community and the general public have incorrectly associated eggs with high serum cholesterol and being deleterious to health, even though cholesterol is an essential component of cells and organisms. It is now acknowledged that the original studies purporting to show a linear relation between cholesterol intake and coronary heart disease (CHD) may have contained fundamental study design flaws, including conflated cholesterol and saturated fat consumption rates and inaccurately assessed actual dietary intake of fats by study subjects. Newer and more accurate trials, such as that conducted by Frank B. Hu of the Harvard School of Public Health (1999), have shown that consumption of up to seven eggs per week is harmonious with a healthful diet, except in male patients with diabetes for whom an association in higher egg intake and CHD was shown. The degree to which serum cholesterol is increased by dietary cholesterol depends upon whether the individual's cholesterol synthesis is stimulated or down-regulated by such increased intake, and the extent to which each of these phenomena occurs varies from person to person. Several recent studies have shed additional light on the specific interplay between dietary cholesterol and cardiovascular health risk. It is evident that the dynamics of cholesterol homeostasis, and of development of CHD, are extremely complex and multifactorial. In summary, the earlier purported adverse relationship between dietary cholesterol and heart disease risk was likely largely over-exaggerated.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".