Effects of Magnesium Supplementation on Blood Pressure
Bibliographic record
Abstract
The antihypertensive effect of magnesium (Mg) supplementation remains controversial. We aimed to quantify the effect of oral Mg supplementation on blood pressure (BP) by synthesizing available evidence from randomized, double-blind, placebo-controlled trials. We searched trials of Mg supplementation on normotensive and hypertensive adults published up to February 1, 2016 from MEDLINE and EMBASE databases; 34 trials involving 2028 participants were eligible for this meta-analysis. Weighted mean differences of changes in BP and serum Mg were calculated by random-effects meta-analysis. Mg supplementation at a median dose of 368 mg/d for a median duration of 3 months significantly reduced systolic BP by 2.00 mm Hg (95% confidence interval, 0.43-3.58) and diastolic BP by 1.78 mm Hg (95% confidence interval, 0.73-2.82); these reductions were accompanied by 0.05 mmol/L (95% confidence interval, 0.03, 0.07) elevation of serum Mg compared with placebo. Using a restricted cubic spline curve, we found that Mg supplementation with a dose of 300 mg/d or duration of 1 month is sufficient to elevate serum Mg and reduce BP; and serum Mg was negatively associated with diastolic BP but not systolic BP (all P<0.05). In the stratified analyses, a greater reduction in BP tended to be found in trials with high quality or low dropout rate (all P values for interaction <0.05). However, residual heterogeneity may still exist after considering these possible factors. Our findings indicate a causal effect of Mg supplementation on lowering BPs in adults. Further well-designed trials are warranted to validate the BP-lowering efficacy of optimal Mg treatment.
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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 | 0.010 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.002 | 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".