A Meta‐Analysis on the Effect of Vitamin D Supplementation on Endothelial Function in Adults
Bibliographic record
Abstract
Vitamin D is recognized as a key regulator of endothelial function, and its deficiency has been implicated in the development of endothelial dysfunction, a critical contributor to cardiovascular diseases. Many randomized controlled trials (RCTs) have revealed the benefits of vitamin D on endothelial function, but the results are inconclusive. This meta‐analysis of RCTs aimed to assess the effects of vitamin D on endothelial function. A systematic review of PubMed, Embase, Scopus, Web of Science, and Cochrane Library was conducted and covered all records from database inception through May 2025. Data were pooled using a random‐effects model to calculate standardized mean differences (SMDs) and 95% confidence intervals (CIs). Thirty‐one RCTs comprising 35 intervention arms with 3252 patients were included. Findings indicated no significant changes in terms of endothelial function following vitamin D administration including measures such as flow‐mediated dilation (FMD) (SMD = 0.36; 95% CI: −0.11, 0.83, p = 0.131), augmentation index (AIx) level (SMD = −0.12; 95% CI: −0.33, 0.10, p = 0.293), pulse wave velocity (PWV) (SMD = −0.09; 95% CI: −0.25, 0.07, p = 0.258), and intercellular adhesion molecule‐1 (ICAM‐1) (SMD = −0.78; 95% CI: −1.79, 0.22, p = 0.125). However, subgroup analysis revealed that patients with chronic kidney disease showed a significant improvement in PWV following vitamin D supplementation. The present meta‐analysis demonstrated no significant impact of vitamin D treatment on endothelial function. However, heterogeneity in study populations, baseline vitamin D status, dosage, and intervention duration may have influenced the outcomes. Further well‐designed trials are warranted to illustrate its effects on vascular health in large scale.
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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 | 0.012 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.048 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".