Effect of vitamin D supplementation on glycemic control in patients with type 2 diabetes: a systematic review of interventional studies
Bibliographic record
Abstract
BACKGROUND: Diabetes and vitamin D deficiency are global epidemics. Researchers have long been exploring the role of potentially modifiable factors to manage type 2 diabetes. We conducted a systematic review of prospective studies and randomized controlled trials that involved vitamin D supplementation and specifically intended to study glycemic outcomes related to type 2 diabetes. METHODS: Two authors independently searched Medline and PubMed for longitudinal studies that had assessed the effect of vitamin D supplements on glycemic control, insulin resistance and beta-cell dysfunction in patients with diabetes. RESULTS: Seventeen randomized control trials and seven longitudinal studies with a minimum follow-up of one month were included. Results of the various short-term studies (follow up ≤ 3 months) suggested that vitamin D supplementation had a positive impact on glycemic control and metabolic parameters such as insulin resistance and beta cell dysfunction. However, the evidence was weak due to the low methodological quality of the studies. There was no significant effect on HbA1c, beta cell function and insulin resistance in the long-term studies (follow up > 3 months). There existed heterogeneity in the methodology of the studies, inclusion criteria, mode of supplementation of vitamin D and the duration of follow up. CONCLUSIONS: Current evidence based on randomized controlled trials and longitudinal studies do not support the notion that vitamin D supplementation can improve hyperglycemia, beta cell secretion or insulin sensitivity in patients with type 2 diabetes. Large-scale trials with proper study design, optimal vitamin D supplementation and longer follow up need to be conducted.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".