The relationship between serum magnesium levels and mortality in non‐diabetic hemodialysis patients: A 10‐year follow‐up study
Bibliographic record
Abstract
Introduction Recently, although there are many reports showing that serum magnesium concentration is a predictor of mortality in dialysis patients, the observation periods of those reports were of short duration, typically around 12 months. Thus, we investigated this relationship over a longer follow-up period. Methods This retrospective, observational study included a total of 83 non-diabetic hemodialysis patients. The follow-up period was 120 months. Patients were divided into two groups, those with serum magnesium ≥2.5 mg/dL (Mg ≥2.5 mg/dL group) and serum magnesium <2.5 mg/dL (Mg <2.5 mg/dL group), and Kaplan-Meier analysis and Cox proportional hazards analysis were conducted. In addition to the above analysis, single and multiple regression analysis were performed at baseline to reveal the relationship between serum magnesium and clinical parameters. Findings During the follow-up period, 31 out of 83 patients died. Kaplan-Meier analysis showed a significantly higher incidence of death in the Mg <2.5 mg/dL group (log-rank test 4.951, P = 0.026). Multivariate Cox proportional hazards analysis showed a 62% decreased risk of mortality in the Mg ≥2.5 mg/dL group compared to the Mg <2.5 mg/dL group after adjustment for several confounding factors. Simple correlation coefficient analysis showed positive correlations of serum magnesium levels with serum creatinine, phosphorus, high-density lipoprotein, ankle-brachial index and KT/V, and a negative correlation with age. Multiple linear regression analysis showed that the ankle-brachial index was the only parameter that had a positive and significant correlation with the serum magnesium level. Conclusion Our study demonstrated that higher serum magnesium levels were associated with improved survival in non-diabetic hemodialysis patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".