Low serum magnesium concentrations are associated with a high prevalence of premature ventricular complexes in obese adults with type 2 diabetes
Bibliographic record
Abstract
BACKGROUND: Premature ventricular complexes (PVC) predict cardiovascular mortality among several adult populations. Increased arrhythmia prevalence has been reported during controlled magnesium (Mg) depletion studies in adults. We thus hypothesized that serum magnesium (sMg) concentrations are inversely associated with the prevalence of PVC in adults at high cardiovascular risk. METHODS: Anthropometric, demographic and lifestyle characteristics were assessed in 750 Cree adults, aged > 18 yrs, who participated in an age-stratified, cross-sectional health survey in Quebec, Canada. Holter electrocardiograms recorded heart rate variability and cardiac arrhythmias for two consecutive hours. Multivariate logistic regression was used to evaluate the associations between sMg and PVC. RESULTS: PVC prevalence in adults with hypomagnesemia (sMg ≤ 0.70 mmol/L) was more than twice that of adults without hypomagnesemia (50% vs. 21%, p = 0.015); results were similar when adults with cardiovascular disease history were excluded. All hypomagnesemic adults with PVC had type 2 diabetes (T2DM). Prevalence of PVC declined across the sMg concentration gradient in adults with T2DM only (p < 0.001 for linear trend). In multivariate logistic regressions adjusted for age, sex, community, body mass index, smoking, physical activity, alcohol consumption, kidney disease, antihypertensive and cholesterol lowering drug use, and blood docosahexaenoic acid concentrations, the odds ratio of PVC among T2DM subjects with sMg > 0.70 mmol/L was 0.24 (95% CI: 0.06-0.98) p = 0.046 compared to those with sMg ≤ 0.70 mmol/L. CONCLUSIONS: sMg concentrations were inversely associated with the prevalence of PVC in patients with T2DM in a dose response manner, indicating that suboptimal sMg may be a contributor to arrhythmias among patients with T2DM.
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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) | 0.000 | 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 | 0.000 | 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".