From Metabolic Dysfunction to Vascular Remodeling

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.

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Publication Details

Journal
Cardiology in Review
Published
2026-09-16
DOI
https://doi.org/10.1097/crd.0000000000001475
Primary Topic
Cardiovascular Health and Disease Prevention
Type
article
Field-Weighted Citation Impact
0.00
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article

From Metabolic Dysfunction to Vascular Remodeling

Zongtao Chen, Jing Ran
Cardiology in Review
Cardiovascular Health and Disease Prevention
article

From Metabolic Dysfunction to Vascular Remodeling

Zongtao Chen, Jing Ran
article en

Abstract

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.

Cardiology in Review
Army Medical University (CN), The Affiliated Yongchuan Hospital of Chongqing Medical University (CN), Southwest Hospital (CN), Chongqing Medical University (CN)
Good health and well-being
Openalex Percentile: Top 11%
Cardiovascular Health and Disease Prevention
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