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Dietary cholesterol and the risk of cardiovascular disease in patients: a review of the Harvard Egg Study and other data

2009· review· en· W2017300603 on OpenAlexaff
Peter J.H. Jones

Bibliographic record

VenueInternational Journal of Clinical Practice · 2009
Typereview
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMedicineDiseaseCholesterolDietary CholesterolAtherosclerotic cardiovascular diseaseGerontologyInternal medicine

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.028
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.937
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.155
GPT teacher head0.485
Teacher spread0.330 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations36
Published2009
Admission routes1
Has abstractyes

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