Abstract 14129: Identification of Highly Correlated Sub-Networks of Cardiovascular Ageing Imaging Markers With 10-Year Predicted Risk Scores

Introduction: While Framingham 10-year risk scores (FRS) estimates cardiovascular disease (CVD) risk in older adults, few studies have benchmarked these estimates against age-related changes in cardiac structure and function, which are complex and highly inter-related. We investigated associations between cardiovascular (CV) imaging markers and FRS, vascular age, calculated regression, and determined connectivity between them in a network analysis.

Methods: Participants recruited from a community-based cohort without CVD completed standardized questionnaires that collected baseline clinical factors, from which FRS, vascular age and calculated regression were derived. Cardiac structural and functional parameters were obtained via echocardiography.

Results: 202 participants (46.0% women, mean age 70.2 SD8.8) were included in this analysis. CV imaging markers correlated across a spectrum with FRS, vascular age and calculated regression. Predictive features and their associations by pearson correlation (nodes containing the variables; edges denoting links) (Fig 1) show significant associations. In ageing, this network showed that E/A ratio is inversely linked to FRS, vascular age and calculated regression while LVEF has a weak association with FRS and vascular age, without direct relationship with E/A ratio. While LAVI is associated with FRS and vascular age, LAVI is associated with E/E1 and not E/A ratio nor LVMI. Multivariate regression confirmed independent associations between FRS and vascular age with E/A ratio (b=-7.03, 95% CI -10.55, -3.52, p < 0.001; b= -15.13, 95% CI -19.33, -10.93, p < 0.001) and E/E prime ratio (b= 0.33, 95% CI 0.03 - 0.63, p = 0.033; b=0.66, 95% CI 0.30 - 1.02, p < 0.001).

Conclusion: This structural collation of associations depicted different sub networks of cardiovascular imaging features into context. FRS, vascular age and calculated regression were associated with imaging markers of CV ageing at various network levels.