Impact of glucose variability on coronary plaque vulnerability in patients with dysglycemia: A whole coronary analysis with multislice computed tomography. Issue 1 (January 2022)

• Record Type: Journal Article
• Authors: Ito, Tsuyoshi; Nakasuka, Kosuke; Fujita, Hiroshi; Yokoi, Masashi; Nakayama, Takafumi; Sugiura, Tomonori; Ohte, Nobuyuki; Seo, Yoshihiro
• Is Part Of: Journal of cardiology. Volume 79:Issue 1(2022)
• Page Start: 58
• Page End: 64
• Publication Date: 2022-01
• Subjects: Dysglycemia -- Glucose variability -- Computed tomography coronary angiography -- Coronary plaque vulnerability; Cardiology -- Periodicals; 616.12
• DOI: 10.1016/j.jjcc.2021.08.001
• Languages: English
• ISSNs: 0914-5087

Abstract

Highlights: Dysglycemia is associated with an increased risk of acute coronary syndrome. Acute coronary syndrome is caused by the disruption of vulnerable plaques. Computed tomography can evaluate coronary plaque vulnerability in the entire heart. Increased glycemic variability was associated with the presence and extent of vulnerable plaques. Abstract: Background: Dysglycemia is associated with an increased risk of acute coronary syndrome caused by the disruption of vulnerable plaques. The relationship between glycemic variability (GV), which is a component of impaired glucose metabolism, and coronary plaque vulnerability has not been fully elucidated. This study investigated the impact of GV on whole coronary plaque vulnerability using multislice computed tomography (MSCT). Methods: We analyzed 88 patients with dysglycemia who underwent 24 h blood glucose monitoring and MSCT. The mean amplitude of glycemic excursion (MAGE) was calculated as an index of the GV. We defined a CT-derived vulnerable plaque as a plaque with a remodeling index > 1.10 and a mean CT density < 30 HU. We calculated the percentage of low-attenuation plaque (% LAP) as the ratio of the low-attenuation component (CT density < 30HU) volume to the total vessel volume. Results: Vulnerable plaques were detected in 27 patients (31%). Patients with vulnerable plaques had higher MAGE (110.0 ± 40.7 vs. 71.7 ± 21.7, p < 0.01) than patients without vulnerable plaques. A univariate logistic regression analysis showed that vulnerable plaques were associated with the MAGE [odds ratio (OR) 1.04, 95% confidence interval (CI), 1.02–1.07, p < 0.01]. In a multivariate model, the MAGE (OR 1.05, 95% CI 1.02–1.07) remained a significant predictor of vulnerable plaque presence. Patients with multivessel-vulnerable plaques had higher MAGE values than those with single-vessel involvement or no vulnerable plaques (132.3 ± 39.4 vs. 102.2 ± 39.7, vs. 71.7 ± 21.7, p < 0.01). The regression analysis showed a positive correlation between MAGE levels and the % LAP ( r = 0.55, p < 0.01). In a multiple linear regression analysis, the MAGE was independently associated with the % LAP (β = 0.42, p < 0.01). Conclusions: Increased GV is associated with the presence and extent of vulnerable plaques. Graphical abstract: Image, graphical abstract