Low-Attenuation Coronary Plaque Volume and Cardiovascular Events in Patients with Distinct Metabolic Phenotypes with or without Diabetes

Rev Cardiovasc Med. 2023 Dec 25;24(12):361. doi: 10.31083/j.rcm2412361. eCollection 2023 Dec.

Abstract

Background: Diabetes mellitus (DM) plays a key role in the pathophysiology of metabolic syndrome (MetS). This study aimed to investigate the association among DM, low-attenuation plaque (LAP) volume, and cardiovascular outcomes across metabolic phenotypes in patients with suspected coronary artery disease (CAD) who underwent coronary computed tomography angiography (CCTA).

Methods: We included 530 patients who underwent CCTA. MetS was defined as the presence of a visceral adipose tissue area 100 cm 2 in patients with DM (n = 58) or two or more MetS components excluding DM (n = 114). The remaining patients were categorised as non-MetS patients with DM (n = 52) or without DM (n = 306). A CCTA-based high-risk plaque was defined as a LAP volume of > 4%. The primary endpoint was the presence of a major cardiovascular event (MACE), which was defined as a composite of cardiovascular death, acute coronary syndrome, and coronary revascularization.

Results: The incidence of MACE was the highest in the non-MetS with DM group, followed hierarchically by the MetS with DM, MetS without DM, and non-MetS without DM groups. In the multivariable Cox hazard model analysis, DM as a predictor was associated with MACE independent of LAP volume > 4% (hazard ratio, 2.68; 95% confidence interval, 1.16-6.18; p = 0.02), although MetS did not function as an independent predictor. A LAP volume > 4% functioned as a predictor of MACE, independent of each metabolic phenotype or DM.

Conclusions: This study demonstrated that DM, rather than MetS, is a predictor of coronary events independent of high-risk plaque volume in patients who underwent CCTA.

Keywords: acute coronary syndrome; adipose tissue; computed tomography angiography; coronary artery disease; diabetes mellitus.

Grants and funding

This work was partially supported by the JSPS Kakenhi Grants (Number 22K08109 to KO).