Increased ionized calcium/magnesium ratio in elderly hypertensives
Bibliographic record
Abstract
AimsHyperuricemia is associated with an increased risk of mortality in coronary heart disease (CHD) patients. Magnesium intake is related to reduced mortality due to cardiovascular disease. This study aimed to investigate the association between dietary magnesium intake, magnesium depletion score (MDS) and hyperuricemia-related all-cause mortality or cardiovascular mortality in patients with CHS.MethodsIn this retrospective cohort study, 1,823 CHD patients were selected from the National Health and Nutrition Examination Survey (NHANES). Dietary magnesium intake was determined based on 24-hour dietary recall interviews. MDS was assessed considering four factors: use of diuretics, use of proton pump inhibitors, estimated glomerular filtration rate, and alcohol consumption. Weighted univariate and multivariate Cox regression models were applied to explore the association between dietary magnesium intake, MDS, hyperuricemia, and all-cause mortality or cardiovascular mortality. The results were presented as hazard ratios (HRs) and 95% confidence intervals (CIs). The Kaplan-Meier survival curves were used to explore survival status relative to magnesium intake or MDS.ResultsAfter an average of 81 months of follow-up, 879 CHD patients died. After adjusting for covariates, MDS ≥2 (HR=1.34, 95% CI: 1.13-1.60) and hyperuricemia (HR=1.25, 95% CI: 1.01-1.55) were associated with increased odds of all-cause mortality. Moreover, MDS affected the association between hyperuricemia and all-cause mortality (HR=1.41, 95% CI: 1.09-1.84) or cardiovascular mortality (HR=1.44, 95% CI: 1.02-2.03) in CHD patients.ConclusionMDS influences mortality in patients with hyperuricemia, highlighting the potential importance of magnesium status in managing the risks associated with hyperuricemia in CHD 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".