Abstract P120: Prevalence of Ventricular Premature Beats Decreases With Serum Magnesium in Adults with Type 2 Diabetes
Bibliographic record
Abstract
Introduction: Ventricular premature beats (VPB) predict cardiovascular mortality among several adult populations. Controlled dietary magnesium (Mg) depletion studies demonstrated that diminished Mg intake and status induced VPB and other arrhythmias. Thus, we hypothesized that the prevalence of VPB is closely associated with serum Mg concentrations in a general adult population at high cardiovascular risk. Methods: Anthropometric, demographic and lifestyle characteristics were assessed in 750 Cree adults, >18yrs, 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 potential associations between serum Mg and VPB. Results: VPB prevalence in adults with hypomagnesaemia (serum Mg ≤ 0.70mmol/L) was over twice that of adults without hypomagnesaemia (50% vs. 21%, p =0.015); results were not materially altered when adults with cardiovascular disease history were excluded. All hypomagnesaemic adults with VPB had type 2 diabetes. Prevalence of VPB declined across the serum Mg concentration gradient in adults with type 2 diabetes only ( p <0.001). 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 of VPB among diabetics with serum Mg > 0.70 mmol/L was 0.24 (95%CI: 0.06-0.98; p =0.046). Conclusions: Prevalence of VPB significantly declined across the serum Mg concentration gradient in adults with type 2 diabetes, indicating that future interventions to increase levels of serum Mg among adults with type 2 diabetes may confer protection against cardiac arrhythmia.
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".