The association between circulating magnesium and clinically relevant outcomes in patients with chronic kidney disease: A systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND & AIMS: Despite modern treatment, risk for cardiovascular disease and mortality in patients with chronic kidney disease (CKD) is unacceptably high. Observational studies have shown associations of magnesium with risk for several clinical outcomes in CKD of variable magnitude. The aim of this review is to provide a systematic overview and meta-analysis of longitudinal studies assessing the association of plasma magnesium concentration with clinically relevant outcomes in adult patients with chronic kidney disease, with a minimal follow-up of 6 months. Primary outcomes of interest were all-cause mortality, cardiovascular mortality, cardiovascular events, sudden death and hospitalisation. METHODS: The electronic databases PubMed, Embase and The Cochrane Library were searched using terms relating to plasma magnesium and CKD patients, and two authors independently selected eligible studies. Study quality was assessed according to the Newcastle-Ottawa Scale. Results of studies with a comparable magnesium exposure and outcome measure, were pooled using a random-effects meta-regression analysis. RESULTS: The search yielded 6156 records of which 33 studies, involving 348,059 patients, met the eligibility criteria. Finally, 22 studies could be included in the meta-analysis. Higher magnesium was associated with a lower risk for all-cause mortality (HR 0.90 [0.87-0.94] per 0.1 mmol/L increase of magnesium) and cardiovascular mortality and events (HR 0.85 [0.77-0.94] per 0.1 mmol/L). CONCLUSIONS: Magnesium concentration is inversely associated with all-cause mortality and cardiovascular mortality and events. Therefore, increasing magnesium may improve risk in patients with chronic kidney disease. This meta-analysis forms a firm base for future prospective trials to test whether increasing plasma magnesium, indeed has beneficial effects on clinical outcomes.
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 | 0.012 | 0.030 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.036 |
| 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 | 0.002 | 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".