Epicardial adipose tissue and culprit lesions in acute chest pain. The EPIC-ACS study

Abstract

Abstract Background The amount of epicardial adipose tissue (EAT) is associated with prevalent and incident myocardial infarction. However, clinical studies, specifically designed to determine, how the assessment of EAT can affect patient management, are lacking. Within Epicardial adipose tissue thickness PredIcts obstructive Coronary artery disease in Acute Coronary Syndrome patients (EPIC-ACS) study we tested the hypothesis that EAT quantification improves the prediction of the presence of culprit lesions in patients presenting with acute chest pain to the emergency department. Methods In this observational cohort study, we prospectively included consecutive patients presenting to the emergency department with acute chest pain suggestive of acute coronary syndrome between December 2018 and August 2020. Patients with ST-elevation myocardial infarction, hemodynamic instability, or known coronary artery disease were excluded. As part of the initial workup, bedside echocardiography for quantification of EAT thickness was performed by a dedicated study physician, blinded to all patients' characteristics. Treating physicians remained unaware of the results of the EAT assessment. The primary endpoint was defined as presence of a culprit lesion, as detected in subsequent invasive coronary angiography within 90 days after initial presentation. Logistic regression analysis was performed in different models adjusted for traditional cardiovascular risk factors, cardiac biomarkers as well as established cardiovascular risk scores. Results Overall, 657 patients (mean age 58.06±18.04 years, 53% male) were included in our study. Patients reaching the primary endpoint had significantly more EAT than patients without culprit lesions (7.90±2.56mm vs. 3.96±1.91mm, p<0.0001, figure 1). In unadjusted regression analysis, 1mm increase in EAT thickness was associated with a nearby 2-fold increased odds of the presence of culprit lesions [1.98 (1.77–2.21), p<0.0001]. Effect sizes remained stable and highly significant, when controlling for age, gender, and BMI as well as when ancillary controlling for traditional cardiovascular risk factors and cardiac biomarkers [1.87 (1.64–2.12), p<0.0001]. Effect sizes for the association of EAT with presence of culprit lesions were similar in troponin-positive [1.85 (1.5–2.28), p<0.0001] and troponin-negative acute chest pain [1.94 (1.66–2.26), p<0.0001; p-value for interaction: 0.24]. Adding EAT to a multivariable model of GRACE score, cardiac biomarkers and traditional risk factors significantly improved the area under the receiver operating characteristics curve (0.759 to 0.901, p<0.0001). Conclusion EAT strongly and independently predicts the presence of culprit lesions in patients presenting with acute chest pain to the emergency department. Our results suggest that the bedside echocardiographic assessment including the quantification of EAT may improve diagnostic algorithms of patients with acute chest pain. Funding Acknowledgement Type of funding sources: None. Distribution of EAT thickness