The association between circulating 25-hydroxyvitamin D and cardiovascular diseases: a meta-analysis of prospective cohort studies
Bibliographic record
Abstract
BACKGROUND: There is a controversy about the association between vitamin D and cardiovascular diseases (CVDs). The effect of serum 25-OH-vitD on the risk of CVDs was evaluated. METHODS: Major electronic databases including Scopus, Science Direct, and PubMed were searched. All prospective cohort studies on the relationship between vitamin D status and CVDs conducted between April 2000 and September 2017 were included, regardless language. The study participants were evaluated regardless of their age, sex, and ethnicity. The Newcastle-Ottawa Scale was used to assess the quality of the studies. Two investigators independently selected the studies and extracted the data. The designated effects were risk ratio (RR) and hazard ratio (HR). The random effects model was used to combine the results. RESULTS: A meta-analysis of 25 studies with 10,099 cases of CVDs was performed. In general, a decrease in the level of vitamin D was associated with a higher relative risk of CVDs (incidence-mortality combined) (RR = 1.44, 95% CI: 1.24-1.69). This accounts for 54% of CVDs mortality rate (RR = 1.54, 95% CI: 1.29-1.84(. However, no significant relationship was observed between the vitamin D status and incidence of CVDs (RR = 1.18, 95% CI: 1-1.39). In general, low serum vitamin D level increased the risk of CVD by 44% (RR = 1.44, 95% CI: 1.24-1.69). It also increased the risk of CVD mortality (RR = 1.54, 95% CI: 1.29-1.84) and incidence rates (RR = 1.18, 95% CI: 1-1.39). CONCLUSIONS: The findings showed that vitamin D deficiency increases the CVDs mortality rate. Due to the limited number of studies on patients of the both genders, further research is suggested to separately evaluate the effect of vitamin D status on CVD in men and women.
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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 | 0.026 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.065 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".