Vitamin D supplementation in the treatment of type 2 diabetic microangiopathy
Bibliographic record
Abstract
BACKGROUND: The number of people with diabetes is growing exponentially.Human studies have shown that vitamin D supplementation is beneficial for type 2 diabetic microangiopathy. However, owing to the low quality, small sample size, and methodological heterogeneity of these studies, this conclusion is not convincing. Consequently, in order to determine whether vitamin D supplementation is effective and safe in type 2 diabetic microangiopathy, it is necessary to conduct a meta-analysis of high-quality clinical trials. METHODS: We will search each database from the built-in until March 2020. The English literature mainly searches Cochrane Library, PubMed, EMBASE, and Web of Science, while the Chinese literature comes from CNKI, CBM, VIP, and Wangfang database. Simultaneously we will retrieval clinical registration tests and grey literatures. In this study, only the clinical randomized controlled trials were selected to evaluate the efficacy and safety of vitamin D in the treatment of type 2 diabetic microangiopathy. The two researchers independently conducted literature selection, data extraction and quality assessment. Statistical heterogeneity among studies will be evaluated using the Cochran Q test (x) and the I statistical value. We will utilize the Review Manage software V5.3.0 (The Nordic Cochrane Center, The Cochrane Collaboration, 2014, Copenhagen, Denmark) to statistically analyze all data. ETHICS AND DISSEMINATION: Ethics and dissemination: This study is a systematic review of vitamin D supplementation as a treatment of type 2 diabetic microangiopathy. RESULTS: This study will provide high-quality synthesis of effectiveness and safety of vitamin D supplementation for type 2 diabetic microangiopathy. CONCLUSION: This systematic review aims to provide new options for vitamin D treatment of type 2 diabetic microangiopathy in terms of its efficacy and safety. REGISTRATION NUMBER: LNPLASY202050055.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".