Magnesium and Fracture Risk in the General Population and Patients Receiving Dialysis: A Narrative Review
Bibliographic record
Abstract
Purpose of Review: Magnesium is an essential mineral for bone metabolism, but little is known about how magnesium intake alters fracture risk. We conducted a narrative review to better understand how magnesium intake, through supplementation, diet, or altering the concentration of dialysate magnesium, affects mineral bone disease and the risk of fracture in individuals across the spectrum of kidney disease. Sources of Information: Peer-reviewed clinical trials and observational studies. Methods: We searched for relevant articles in MEDLINE and EMBASE databases. The methodologic quality of clinical trials was assessed using a modified version of the Downs and Black criteria checklist. Key Findings: The role of magnesium intake in fracture prevention is unclear in both the general population and in patients receiving maintenance dialysis. In those with normal kidney function, 2 meta-analyses showed higher bone mineral density in those with higher dietary magnesium, whereas 1 systematic review showed no effect on fracture risk. In patients receiving maintenance hemodialysis or peritoneal dialysis, a higher concentration of dialysate magnesium is associated with a lower concentration of parathyroid hormone, but little is known about other bone-related outcomes. In 2 observational studies of patients receiving hemodialysis, a higher concentration of serum magnesium was associated with a lower risk of hip fracture. Limitations: This narrative review included only articles written in English. Observed effects of magnesium intake in the general population may not be applicable to those with chronic kidney disease particularly in those receiving dialysis.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| 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".