An Association of Vitamin D Insufficiency with Elevated Serum Uric Acid Levels Among Postmenopausal Women
Bibliographic record
Abstract
Introduction: Deficiency of vitamin D and raised levels of serum uric acid are considered independent risk factors for causing cardiovascular diseases. Aims & Objectives: This study was carried out to study Serum Uric acid and Vitamin D levels in postmeopausal women to find association of hypovitaminosis D with hyperuricemia. Place and duration of study: It was a cross-sectional analytical study. Postmenopausal women more than 55 years of age with BMI between 25-30 kg/m2 were included in the study. The study was conducted at the Department of Biochemistry and Chemical Pathology, Shaikh Zayed Federal Postgraduate Medical Institute, Lahore over a period of six months. Material & Methods: Eighty subjects were included in this study. They were divided into two groups i-e, normouricemic group and hyperuricemic group based onserum uric acid level.Vitamin D levels of both groups were then measured. Results: The hyperuricemic group had markedly lower vitamin Dlevels as compared to normouricemic group. Moreover, vitamin D had a negative correlation with uric acid in the hyperuricemic group i-e, higher the uric acid level, lower was vitamin D. Multiple regression analysis was also performed for studying the relation of vitamin D with uric acid levels in the two groups overall. It was observed that one mg/dl increase in uric acid caused an average decrease of 2.43 ng/ml in vitamin D. Conclusion: It may be concluded from this study that association of hypovitaminosis D with hyperuricemia in postmenopausal women can be used for planning an early intervention to prevent cardiovascular diseases in them.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".