P1.12: Predictive Combined Role of Calcium Score and Carotidimt in Coronary Artery Disease

• Published in: Artery research Vol. 7; no. 3-4; p. 114
• Main Authors: Meani, P., Cesana, F., Fallanca, A., Valsecchi, C., Musca, F., Campadello, P., Soriano, F., Faggiano, P., Rigo, F., Moreo, A., Muiesan, M. L., Paini, A., Mureddu, G. F., Gaibazzi, N., Giannattasio, C.
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 2013; Springer Nature B.V; BMC
• Subjects: Cardiovascular disease; Conference Abstract; Coronary vessels; Vein & artery diseases; United States > US
• ISSN: 1872-9312; 1876-4401; 1876-4401
• DOI: 10.1016/j.artres.2013.10.043

Objectives up to date the assessment of coronary artery disease (CAD) risk is based mainly on the presence of CV risk factors. However, many markers of subclinical atherosclerosis has been demonstrated as powerful predictors of CV events. Aim of our study was to evaluate if non invasive US parameters, such as carotid properties and heart calcifications, are able to add information to the prediction of CAD. Methods In 405 in-patients with a clinical indication (overt angina and/or positive exercise test) for coronary angiography (CA), we measured blood pressures (BP), carotid intima-media thickness (IMT), local PWV and distensibility and quantified cardiac calcification by means of Calcium Score (CaS). After CA we divided the group in G1 (N=240) (patients with at least one coronary stenosis >50%), and G0 (N=165) (unaffected coronaries). Results G0 and G1 patients differed in age (67±10 vs 64±11yrs,p=0,01), but not in BMI (26±3.5 vs 28±16 kg/m2,p=0,03); G1 had higher BP (130±21/74±10 vs 136±18/77±11mmHg, p<0.02), carotid-IMT (705,4±155 vs 775,2±164mcm, p<0.0001), local PWV (8,9±2.8 vs 9,5±2,7m/s, p<0.01) and CaS(1,51±1,45 vs 2,56±1,86,p?). Among the considered US parameters, IMT and CaS were the best predictors of CAD, after adjusting for Framingham Risk Score (CaS: OD=1, p<,001; IMT: OD=1,p=0,06). Conclusions: Integrated US of heart and carotid artery can be very useful to detect subclinical ATS in medium-high risk patients, predicting significant CAD and adding qualitative information for better stratify the CV risk and improve clinical management.