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Record W2111097094 · doi:10.1161/strokeaha.107.484113

Visceral Adipose Tissue, a Potential Risk Factor for Carotid Atherosclerosis

2007· article· en· W2111097094 on OpenAlexaff
Scott A. Lear, Karin H. Humphries, Jiří Fröhlich, C. Laird Birmingham, G.B. John Mancini

Bibliographic record

VenueStroke · 2007
Typearticle
Languageen
FieldMedicine
TopicDiabetes, Cardiovascular Risks, and Lipoproteins
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsMedicineWaistRisk factorBody mass indexInternal medicineAdipose tissueIntra-Abdominal FatObesityAbdominal obesityCardiologyInsulin resistanceVisceral fat

Abstract

fetched live from OpenAlex

BACKGROUND AND PURPOSE: The association between abdominal obesity and atherosclerosis is believed to be due to excess visceral adipose tissue (VAT), which is associated with traditional risk factors. We hypothesized that VAT is an independent risk factor for atherosclerosis. METHODS: Healthy men and women (N=794) matched for ethnicity (aboriginal, Chinese, European, and South Asian) and body mass index range (<25, 25 to 29.9, or > or =30 kg/m(2)) were assessed for VAT (by computed tomography scan), carotid atherosclerosis (by ultrasound), total body fat, cardiovascular risk factors, lifestyle, and demographics. RESULTS: VAT was associated with carotid intima-media thickness (IMT), plaque area, and total area (IMT area and plaque area combined) after adjusting for demographics, family history, smoking, and percent body fat in men and women. In men, VAT was associated with IMT and total area after adjusting for insulin, glucose, homocysteine, blood pressure, and lipids. This association remained significant with IMT after further adjustment for either waist circumference or the waist-to-hip ratio. In women, VAT was no longer associated with IMT or total area after adjusting for risk factors. CONCLUSIONS: VAT is the primary region of adiposity associated with atherosclerosis and likely represents an additional risk factor for carotid atherosclerosis in men. Most but not all of this risk can be reflected clinically by either the waist circumference or waist-hip ratio measures.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.912
Threshold uncertainty score0.823

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.013
GPT teacher head0.261
Teacher spread0.248 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

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

Citations111
Published2007
Admission routes1
Has abstractyes

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