Diabetes Metab J.  2024 May;48(3):449-462. 10.4093/dmj.2023.0197.

Harnessing Metabolic Indices as a Predictive Tool for Cardiovascular Disease in a Korean Population without Known Major Cardiovascular Event

• Kim HJ
• Kim BS
• Lee Y
• Ahn SB
• Kim DW
• Shin JH

• KMID: 2555776
• DOI: http://doi.org/10.4093/dmj.2023.0197

Abstract

Background
This study evaluated the usefulness of indices for metabolic syndrome, non-alcoholic fatty liver disease (NAFLD), and insulin resistance (IR), as predictive tools for cardiovascular disease in middle-aged Korean adults.
Methods
The prospective data obtained from the Ansan-Ansung cohort database, excluding patients with major adverse cardiac and cerebrovascular events (MACCE). The primary outcome was the incidence of MACCE during the follow-up period.
Results
A total of 9,337 patients were included in the analysis, of whom 1,130 (12.1%) experienced MACCE during a median follow-up period of 15.5 years. The metabolic syndrome severity Z-score, metabolic syndrome severity score, hepatic steatosis index, and NAFLD liver fat score were found to significantly predict MACCE at values above the cut-off point and in the second and third tertiles. Among these indices, the hazard ratios of the metabolic syndrome severity score and metabolic syndrome severity Z-score were the highest after adjusting for confounding factors. The area under the receiver operating characteristic curve (AUC) of the 10-year atherosclerotic cardiovascular disease (ASCVD) score for predicting MACCE was 0.716, and the metabolic syndrome severity Z-score had an AUC of 0.619.
Conclusion
The metabolic syndrome severity score is a highly reliable indicator and was closely associated with the 10-year ASCVD risk score in predicting MACCE in the general population. Given the specific characteristics and limitations of metabolic syndrome severity scores as well as the indices of NAFLD and IR, a more practical scoring system that considers these factors is essential to achieve greater accuracy in forecasting cardiovascular outcomes.

Keyword

Cardiovascular diseases; Insulin resistance; Non-alcoholic fatty liver disease; Metabolic syndrome; Middle aged

Figure

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  Fig. 1. Study population. BMI, body mass index; AST, aspartate aminotransferase; ALT, alanine aminotransferase; TG, triglyceride; GGT, gamma-glutamyl transferase; MACCE, major adverse cardiac and cerebrovascular events; CV, cardiovascular; MI, myocardial infarction; CAD, coronary artery disease; HF, heart failure; PAD, peripheral artery disease.

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  Fig. 2. Time-dependent receiver operating characteristic (ROC) curve for major adverse cardiac and cerebrovascular events (MACCE) for each index. ASCVD, atherosclerotic cardiovascular disease; NAFLD, non-alcoholic fatty liver disease; TyG, triglycerides; HOMA-IR, homeostatic model assessment of insulin resistance; AUC, area under the receiver operating characteristic curve; CI, confidence interval; PPV, positive predictive value; NPV, negative predictive value.

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  Fig. 3. Additional value of including other metabolic indices in the metabolic syndrome severity Z-score. IR, insulin resistance; AUC, area under the receiver operating characteristic curve; CI, confidence interval.

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