From Metabolic Dysfunction to Vascular Remodeling: A Multi-Indicator Framework for Subclinical Cardiovascular Disease

Subclinical cardiovascular disease (SCVD) encompasses a spectrum of vascular abnormalities that emerge well before the onset of overt cardiovascular events. Although a wide range of metabolic, inflammatory, and vascular markers have been associated with SCVD, current assessment strategies remain largely dependent on individual indicators, limiting their ability to capture the multidimensional and dynamic nature of disease progression. Increasing evidence suggests that SCVD develops through a continuum of interconnected biological processes, beginning with metabolic dysregulation, progressing through chronic low-grade inflammation, and ultimately leading to vascular remodeling and calcification. Notably, many of these processes can be partially reflected by routinely available health examination data, providing an opportunity to move beyond traditional risk factor assessment toward a more integrated evaluation of vascular health. In this review, we summarize the pathophysiological basis of SCVD and discuss the stage-specific significance of commonly available examination indicators across metabolic, inflammatory, structural, and functional domains. We further examine emerging strategies for multi-indicator integration, including conventional risk models, expanded assessment frameworks, and machine learning-based approaches. Collectively, these observations support a shift from isolated marker interpretation toward dynamic and stage-oriented assessment frameworks that better reflect the biological complexity of SCVD progression.