Comparative Study of Salivary and Serum Levels of Vitamin D in Patients with a History of High Blood Pressure and Healthy People
Bibliographic record
Abstract
Introduction: Vitamin D deficiency is a major public health problem. Low vitamin D levels associated with adverse health consequences such as musculoskeletal health, cognitive decline and progression of cancer and death. The lack of vitamin D associated with major risk factors for cardiovascular disease (CVD) includes hypertension is considered. The ability to assess the general health, disease and treatment outcomes through saliva as a non-invasive, inexpensive and simple method of interest is located. The aim of this study was a comparative study of salivary and serum levels of vitamin D3 in patients with a history of developing high blood pressure and a healthy person.Methods: This study was a case - control survey, in which 40 patients with high blood pressure were examined. The control group including 40 healthy subjects. Both groups were matched in terms of age and gender. After collecting samples of serum and saliva, the amount of vitamin D level samples were measured using ELISA method by electrochemiluminescence (ELC), and then analyzed the results using software SPSS 16 and statistical test including Chi Square Test, Independent-Samples, linear regression model, the Mann-Whitney Test and Spearman correlation coefficient.Results: There was no significant difference in the mean serum levels of vitamin D among patients and healthy subjects (p= 0.588). In addition, there was no significant difference in the mean salivary levels of vitamin D between patients and healthy subjects (p= 0.833). There was no significant relationship between salivary and serum level of vitamin D in healthy individuals (p= 0.095). As well as there was no significant correlation between salivary and serum level of vitamin D in patients (p= 0.5).Conclusions: This study showed that vitamin D is a measurable marker in saliva, but its analysis in saliva, may not be a reliable tool for determining the vitamin D levels.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".