Epicardial adipose tissue volume and myocardial ischemia in asymptomatic people living with diabetes: a cross-sectional study
Abstract
Background Epicardial adipose tissue (EAT) is considered a novel diagnostic marker for cardiometabolic disease. This study aimed to evaluate whether EAT volume was associated with stress-induced myocardial ischemia in asymptomatic people living with diabetes—independently of confounding factors—and whether it could predict this condition. Methods We included asymptomatic patients with diabetes and no coronary history, who had undergone both a stress a myocardial scintigraphy to diagnose myocardial ischemia, and a computed tomography to measure their coronary artery calcium (CAC) score. EAT volume was retrospectively measured from computed tomography imaging. Determinants of EAT volume and asymptomatic myocardial ischemia were evaluated. Results The study population comprised 274 individuals, including 153 men. Mean (± standard deviation) age was 62 ± 9 years, and 243, 23 and 8 had type 2, type 1, or another type of diabetes, respectively. Mean body mass index was 30 ± 6 kg/m 2 , and mean EAT volume 96 ± 36 cm 3 . Myocardial ischemia was detected in 32 patients (11.7%). EAT volume was positively correlated with age, body mass index and triglyceridemia, but negatively correlated with HbA1c, HDL- and LDL-cholesterol levels. Furthermore, EAT volume was lower in people with retinopathy, but higher in men, in current smokers, in patients with nephropathy, those with a CAC score > 100 Agatston units, and finally in individuals with myocardial ischemia (110 ± 37 cm 3 vs 94 ± 37 cm 3…
How strong is the evidence?
Evidence Hub reads this as a cross-sectional, done in people. Its evidence level is 4 of 5 (Low · observational). Observational designs can show an association but not prove cause. Reported size: 274 participants or records.
Read the paper
Related studies
- In silico toxicology protocols
- QM7-X, a comprehensive dataset of quantum-mechanical properties spanning the chemical space of small organic molecules
- Quantum Informed Machine-Learning Potentials for Molecular Dynamics Simulations of CO2's Chemisorption and Diffusion in Mg-MOF-74
- In-silico strategies in nano-drug design: Bridging nanomaterials and pharmacological applications
- mRNA codon optimization with quantum computers
- The computational power of the human brain
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.