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Could a high Epicardial Adipose Tissue Volume increase the ability of the Calcium Score to discriminate cardiovascular events in an asymptomatic population?
Session:
Comunicações Orais - Sessão 29 - Score cálcio coronário
Speaker:
Margarida Temtem
Congress:
CPC 2023
Topic:
B. Imaging
Theme:
03. Imaging
Subtheme:
03.2 Computed Tomography
Session Type:
Comunicações Orais
FP Number:
---
Authors:
Margarida Temtem; Maria Isabel Mendonça; João Adriano Sousa; Marco Serrão; Marina Santos; Débora Sá; Francisco Sousa; Sónia Freitas; Sofia Borges; Eva Henriques; Mariana Rodrigues; António Drumond; Ana Célia; Roberto Palma Dos Reis
Abstract
<p style="text-align:justify"><span style="font-size:11pt"><span style="font-family:Calibri,"sans-serif""><strong>Background:</strong> Evidence indicates that an elevated calcium score (CAC) is a risk marker for subclinical atherosclerosis and cardiovascular (CV) events in the asymptomatic population. Recent research has shown that high epicardial adipose tissue (EAT) volume is associated with coronary calcification and CV events It is unknown whether the association between the two risk markers improved the ability to predict CV events.</span></span></p> <p style="text-align:justify"><span style="font-size:11pt"><span style="font-family:Calibri,"sans-serif""><strong>Objective</strong>: Evaluate whether a high EAT volume added to the CAC score improves the predictive ability to discriminate CV events in an asymptomatic population without apparent cardiovascular disease (CVD). </span></span></p> <p style="text-align:justify"><span style="font-size:11pt"><span style="font-family:Calibri,"sans-serif""><strong>Methods</strong>: A prospective cohort was performed with 1024 participants (mean age 51.6±8.2 years, 75.6% male) selected from controls of the GENEMACOR Study. CAC score was performed by cardiac computed tomography, and CAC severity was reported as an absolute Agatston unit stratified for age and sex- percentile (according to the Hoff Nomogram). EAT volume was measured with a quantitative semi-automated procedure using a postprocessing workstation-TeraRecon Aquarius Workstation (version 4.4.7, TeraRecon, Inc., San Mateo, CA, USA). We evaluated the discriminative ability of the CAC model without (model 1) and with EAT volume (model 2) using the ROC curve along with respective AUC and Harrel C statistics. Categorical free Net Reclassification Improvement (cfNRI) and Integrated Discrimination Index (IDI) reclassified patients. </span></span></p> <p style="text-align:justify"><span style="font-size:11pt"><span style="font-family:Calibri,"sans-serif""><strong>Results:</strong> CAC model showed a C Index of 0.733 (95%CI 0.633-0.833), which increased to 0.756 (95%CI 0.638-0.874) when EAT volume was included in the model. The difference between the two C indexes was significant (delta C statistic=0.023; p=0.020). CfNRI reclassified 63.6% of the population (p=0.0003), and IDI <span style="background-color:white"> improved the discrimination when EAT was included in CAC model (IDI=0.011; p=0.015).</span> </span></span></p> <p style="text-align:justify"><span style="font-size:11pt"><span style="font-family:Calibri,"sans-serif""><strong>Conclusion:</strong> Our findings displayed that the CAC score associated with a high EAT volume increased the predictive and discriminative ability to event occurrence. Improving the identification of high-risk patients at a subclinical stage could avoid atherosclerosis progression and events occurrence through preventive measures.</span></span></p>
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