Does serum vitamin D concentration modify the association between arthritis and cardiovascular diseases in both sexes?
Bibliographic record
Abstract
Introduction:The scientific literature shows an association between inflammatory arthritis and cardiovascular diseases (CVD) with inflammation being a shared characteristic between the two types of diseases.Among patients with arthritis, it is possible that the protective factors against inflammation, such as vitamin D, are also protective factors against the development of CVD.This effect may be different according to sex.Objective: To evaluate the impact of serum vitamin D concentration on the association between arthritis and CVD separately among men and women (effect modification of vitamin D and sex).Methods: Data came from a large representative sample of the US population: The National Health and Nutrition Examination Survey (NHANES) 2005-2006, which included 3406 adults aged between 20 and 69 years.Measurements of arthritis (primary independent variable) and CVD (dependent variable) were taken during face-to-face interviews, while the measurement of serum vitamin D was carried out on blood samples.Multivariate logistic regression analyses were performed in which the combined modifying effect of vitamin D (<20 ng/ml/≥20 ng/ml) and sex was tested and adjusted for several potentially confounding variables.Results: Arthritis was statistically associated with CVD in both men and women, with <20 ng/ml or ≥20 ng/ml serum vitamin D. In men, the adjusted ratio of the odds ratios (ROR) comparing the association at <20 ng/ml vitamin D concentration to the association at ≥20 ng/ml concentration was 0.8 (95% CI 0.5 to 1.5); in women, the adjusted ROR was 0.7 (95% CI 0.3 to 1.5). Conclusions:In this large cross-sectional study, arthritis and CVD were statistically associated, but this association was not modified by sex nor vitamin D concentrations.Vitamin D supplementation is not recommended as part of the management of patients of both sexes suffering from inflammatory arthritis to prevent CVD.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".