Protective Role of Vitamin D Therapy in Diabetes Mellitus Type II
Bibliographic record
Abstract
Diabetes Mellitus type II (DM II) is a worldwide disease with a rapidly growing parallel prevalence and adversities affecting multi-body systems. Hence, it is imperative to treat DM II effectively, maintaining glucose homeostasis to avoid complications such as diabetic nephropathy, peripheral neuropathy, and retinopathy. Vitamin D, among many benefits, has positive outcomes on hemoglobin A1c (HbA1c) control. It aids in insulin secretion and sensitivity. We systematically screened four databases for relevant information; PubMed, Medline, PMC, and Google scholar. Inclusion and exclusion criteria were applied, and quality appraisal was then done using certain checklist tools: Newcastle-Ottawa tool, AMSTAR (A Measurement Tool to Assess Systematic Reviews) checklist, SANRA (Scale for the Assessment of Narrative Review Articles) checklist, and Cochrane bias assessment. Data were collected from 14 articles, of which eight are systematic reviews and meta-analysis, one is a narrative review, five are randomized controlled trials and three are general information about DM II and Vitamin D. In addition, this article evaluates the clinical significance of Vitamin D administration in DM II from a glucose homeostasis perspective, and complications such as nephropathy, neuropathy, and retinopathy. Vitamin D had a clinical positive impact on glucose level, particularly on hemoglobin A1c (HbA1c) reduction, alleviation of diabetic neuropathy and nephropathy symptoms, and hyperglycemia induced-oxidative stress on the retinal cells.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".