Visceral Adiposity and Subclinical Left Ventricular Remodeling
Bibliographic record
Abstract
Abstract Introduction Visceral adiposity is emerging as a key driver of cardio-metabolic risk factors and cardiovascular disease (CVD), but its relationship with cardiac structure and function is not well characterized across sexes. Using the Canadian Alliance for Healthy Heart and Minds (CAHHM), a large population-based cohort study, we sought to determine the association of visceral adipose tissue (VAT) on subclinical left ventricular (LV) remodeling in males and females. Methods As part of the CAHHM study, 6522 participants free of clinical CVD (mean age: 57.4 [8.8 SD] years; 3,671 females, 56%) underwent magnetic resonance imaging (MRI) in which LV parameters and VAT volume were measured. Information about demographic factors, CV risk factors, and anthropometric measurements were obtained. Subclinical cardiac remodelling was defined as altered LV concentricity, represented by increased LV mass-to-volume ratio (LVMV). Results Males had a higher VAT volume (80.8 mL; 95% CI: 74.6 t 86.9) compared to females (64.7 mL; 95% CI: 58.5 to 70.8), adjusted for age and height. Among both males and females, VAT was significantly associated with subclinical cardiac remodeling (increased LVMV), independent of other CV risk factors. In multiple regression models adjusted for cardiovascular risk factors, age, and height, every 1 sex-specific standard deviation increase in VAT corresponded to an increase of 0.037 g/mL in LVMV (95% CI: 0.032 to 0.041; p<0.001), which was consistent across both sexes. Notably, a 1 standard deviation increase in VAT is associated with a LVMV that is 20 times higher than what is observed with natural aging alone (0.0020 g/mL rise in LVMV (95% CI 0.0016 to 0.0025), and 1.5 times higher than the impact of an integrated measure of CV risk factors (0.024 g/mL; 95% CI: 0.020 to 0.028). Conclusion VAT significantly influences subclinical cardiac remodeling in both males and females, independent of other cardiovascular risk factors and age. Further research to understand the pathways by which VAT contributes to accelerated cardiac aging is needed.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".