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Published on: September 22, 2023
Exploring the Relationship Between Visceral Fat and Coronary Artery Calcification Risk Using Metabolic Score for
Jiun-Chi Huang1,2,3, Ya-Chin Huang4,5, Chia-Hsin Lu6
1Department of Internal Medicine, Kaohsiung Municipal Siaogang Hospital, Kaohsiung Medical University, Kaohsiung 812, Taiwan.
The Metabolic Score for Visceral Fat (METS-VF) effectively identifies coronary artery calcification (CAC) presence and severity. This novel indicator outperforms traditional anthropometric measures in predicting CAC.
Area of Science:
- Cardiology
- Metabolic Health
- Medical Diagnostics
Background:
- Coronary artery calcification (CAC) is a significant indicator of cardiovascular disease.
- Intra-abdominal fat estimation is crucial for assessing metabolic risk.
- The Metabolic Score for Visceral Fat (METS-VF) is a new metric for visceral fat, but its association with CAC is unknown.
Purpose of the Study:
- To investigate the relationship between the novel Metabolic Score for Visceral Fat (METS-VF) and coronary artery calcification (CAC).
- To compare the efficacy of METS-VF in predicting CAC against established anthropometric indices.
Main Methods:
- A cohort of 1217 participants underwent health checkups and computed tomography (CT) scans.
- Coronary artery calcium (CAC) scores were used to categorize CAC severity.
- Receiver operating characteristic (ROC) curves were employed to compare METS-VF with anthropometric indices for CAC prediction.
Main Results:
- METS-VF showed a significant positive association with the presence of CAC (OR, 1.506; p=0.001), independent of cardiometabolic factors.
- METS-VF was also associated with mild, moderate, and severe CAC categories.
- METS-VF demonstrated superior performance in estimating CAC presence and severity, achieving the highest Area Under Curve (AUC) values compared to other indices.
Conclusions:
- The Metabolic Score for Visceral Fat (METS-VF) is a robust, independent marker for detecting CAC.
- METS-VF surpasses traditional anthropometric indices in identifying CAC presence and varying severity levels.
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