The effects of vitamin D supplementation on endothelial activation among patients with metabolic syndrome and related disorders: a systematic review and meta-analysis of randomized controlled trials
Bibliographic record
Abstract
The current systematic review and meta-analysis of randomized controlled trials (RCTs) was conducted to summarize the effect of vitamin D supplementation on endothelial activation among patients with metabolic syndrome and related disorders. Cochrane library, Embase, PubMed, and Web of Science database were searched to identify related RCTs published before 30th April 2018. The heterogeneity among the included studies was assessed using Cochran’s Q test and I-square (I2) statistic. Data were pooled by using the random-effect model and standardized mean difference (SMD) was considered as summary effect size. Fourteen clinical trials that contained a total of 1253 participants were included in the current meta-analysis. Vitamin D supplementation significantly decreased von willebrand factor (vWF) (SMD -0.27; 95% CI, − 0.46, − 0.08; P = 0.006; I2:40.5%). However, we found no significant impact of vitamin D supplementation on intercellular adhesion molecule 1(ICAM-1) (SMD -1.96; 95% CI, − 4.02, 0.09; P = 0.06; I2:97.4%), vascular celladhesion molecule 1 (VCAM-1) (SMD -0.50; 95% CI, − 1.19, 0.19; P = 0.15; I2:91.2%), on E-selectin (SMD -0.04; 95% CI, − 0.36, 0.28; P = 0.81; I2:78.8%) and endothelin (SMD -0.49; 95% CI, − 1.18, 0.19; P = 0.15; I2:90.5%). The pooled data from trials of vitamin D supplementation with dosage of ≤4000 IU/day (− 0.37, 95% CI: -0.65, − 0.10, I2: 73.5%) significantly reduced vWF concentrations, while there was no effect of vitamin D supplementation on vWF concentrations among trials with the dosage of intervention > 4000 IU/day (− 0.17, 95% CI: -0.43, 0.10, I2: 0.0%). VWF concentrations significantly reduced in pooled data from trials with duration study ≤8 weeks (− 0.37, 95% CI: -0.67, − 0.07, I2: 60.6%), but there was no effect of vitamin D supplementation on vWF concentrations among trials with > 8 weeks (− 0.20, 95% CI: -0.45, 0.05, I2: 0.0%). While there was no effect of vitamin D supplementation on vWF concentrations among trials with total sample size of ≤60 patients (− 0.03, 95% CI: -0.42, 0.36, I2: 0.0%), vWF concentrations in trials with more than 60 patients decreased significantly (− 0.34, 95% CI: -0.56, − 0.12, I2: 60.9%). Overall, the current meta-analysis demonstrated that vitamin D supplementation to patients with metabolic syndrome and related disorders resulted in an improvement in vWF, but did not affect ICAM-1, VCAM-1, E-selectin and endothelin levels.
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.043 | 0.005 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".