Effects of individual micronutrients on blood pressure in patients with type 2 diabetes: a systematic review and meta-analysis of randomized clinical trials
Bibliographic record
Abstract
To investigate the effects of micronutrients on blood pressure (BP) in patients with type 2 diabetes through a systematic review and meta-analysis, randomized clinical trials (RCTs) of the effects of individual micronutrients on BP in patients with type 2 diabetes were searched in the Medline, Embase, Cochrane, and Clinical Trials.gov databases through April 2016. From the 28,164 studies, 11 RCTs (13 interventions, 723 patients, 54% males) with 3 to 52 weeks of follow-up were classified according to the type of micronutrient intervention: sodium (n = 1), vitamin C (n = 2), vitamin D (n = 7), and magnesium (n = 1). The available data enabled us to perform meta-analyses of vitamins C and D. Vitamin C reduced diastolic BP [WMD -2.88 mmHg (95%CI -5.31, -0.46; P = 0.020)] but not systolic BP [WMD -3.93 mmHg (95%CI -14.78, 6.92; P = 0.478)]. Vitamin D caused a reduction of 4.56 mmHg (WMD; 95%CI -7.65, -1.47; P = 0.004) for systolic BP and 2.44 mm Hg (WMD; 95%CI -3.49, -1.39; P < 0.001) for diastolic BP. In conclusion, vitamin D and possibly vitamin C have beneficial effects on BP in patients with type 2 diabetes. These interventions might represent a novel approach to the treatment of hypertension in these patients.
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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 | 0.019 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.028 | 0.040 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".