Why the study?
Does metabolic syndrome alter myocardial microstructure as measured by signal intensity coefficient on echocardiography in patients without existing cardiovascular disease?
Does metabolic syndrome alter myocardial microstructure as measured by signal intensity coefficient on echocardiography in patients without existing cardiovascular disease?
Metabolic syndrome and dyslipidemia are associated with preclinical alterations in myocardial microstructure detectable by a novel echocardiographic signal intensity algorithm.
OBJECTIVE: Metabolic syndrome (MetS) can lead to myocardial fibrosis, diastolic dysfunction, and eventual heart failure. This study evaluated alterations in myocardial microstructure in people with MetS by using a novel algorithm to characterize ultrasonic signal intensity variation. METHODS: Among 254 participants without existing cardiovascular disease (mean age 42 ± 11 years, 75% women), there were 162 with MetS, 47 with obesity without MetS, and 45 nonobese controls. Standard echocardiography was performed, and a novel validated computational algorithm was used to investigate myocardial microstructure based on sonographic signal intensity and distribution. The signal intensity coefficient (SIC [left ventricular microstructure]) was examined. RESULTS: The SIC was significantly higher in people with MetS compared with people with (P < 0.001) and without obesity (P = 0.04), even after adjustment for age, sex, body mass index, hypertension, diabetes mellitus, and the ratio of triglyceride (TG) to high-density lipoprotein (HDL) cholesterol (P < 0.05 for all). Clinical correlates of SIC included TG concentrations (r = 0.21, P = 0.0007) and the TG/HDL ratio (r = 0.2, P = 0.001). CONCLUSIONS: This study's findings suggest that preclinical MetS and dyslipidemia in particular are associated with altered myocardial signal intensity variation. Future studies are needed to determine whether the SIC may help detect subclinical diseases in people with metabolic disease, with the ultimate goal of targeting preventive efforts.
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Ho et al. (2017) studied this question.
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