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Relationship Between Vitamin D and Cardio-Metabolic Biomarkers Among Saudi Postmenopausal Women

2014· article· en· W2089057434 on OpenAlexvenueno aff
Eman M. Alissa, Wafa A. Alnahdi, Nabeel Alama, Gordon A. Ferns

Bibliographic record

VenueJournal of Nutritional Therapeutics · 2014
Typearticle
Languageen
FieldMedicine
TopicVitamin D Research Studies
Canadian institutionsnot available
FundersKing Abdulaziz City for Science and Technology
KeywordsPostmenopausal womenInternal medicineMedicineVitamin D and neurologyVitaminPhysiologyEndocrinology

Abstract

fetched live from OpenAlex

Vitamin D deficiency is prevalent worldwide, and in Saudi Arabia in particular. There is growing evidence that hypovitaminosis D is involved in the pathogenesis of cardiovascular diseases. We determined concentrations of serum 25 hydroxy 25(OH) vitamin D in relation to several metabolic biomarkers including total cholesterol (TC), low density lipoprotein-cholesterol (LDL-C), high density lipoprotein-cholesterol, triglycerides (TG), atherogenic index (AI), glucose, C-reactive protein (CRP), adiposity, and blood pressure in a cross-sectional analysis in 300 Saudi postmenopausal women. Participants completed a detailed questionnaire and fasting blood samples were collected. Vitamin D deficiency was common, affecting 89% of individuals. Higher serum 25(OH) vitamin D levels were consistently found among subjects with no prevalent cardiovascular risk factors (p>0.05) except for those subjects with serum CRP level ≥3mg/dl, HDL-C <1.04mmol/L, AI≥5, exercising ≥3times/week, and those with 4 or more pregnancies. Hypovitaminosis D was inversely correlated with DBP (r=-0.118, p=0.042), TC (r=-0.165, p=0.004), TG (r=-0.119, p=0.040), LDL-C (r=-0.138, p=0.017), AI (r=-0.125, p=0.031), and veiling type (r=-0.127, p=0.028). No significant impact of hypovitaminosis D on CRP, levels of which were similar among vitamin D sufficient and deficient subjects. However, hypovitaminosis D was significantly related to dyslipidemia and diastolic blood pressure in a group of Saudi postmenopausal women.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.493

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.044
GPT teacher head0.321
Teacher spread0.278 · 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 designObservational
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

Citations1
Published2014
Admission routes1
Has abstractyes

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