[Calcified plaques of extracranial carotid arteries and left ventricular geometry as predictors of coronary artery disease].
METHODS
113 patients underwent cardiac catheterization with selective coronary angiography, ultrasound examination of carotid arteries, and echocardiography. Coronary angiograms were analyzed for disease severity and extent (number of main vessels with > 50% stenosis) carotid ultrasound for number and distribution of calcified plaques among the carotid arteries. Left ventricular diameter (LVEDD), interventricular septal thickness (IVS), and posterior wall thickness (LVPW) in end-diastole were measured echocardiographically. Left ventricular mass divided by body surface area (Q, normal < 150 g/m(2)) and left ventricular relative wall thickness (RWT = [IVS + LVPW]/LVEDD, normal < 0.44) were calculated. A normal left ventricular mass/body surface area with increased relative wall thickness was regarded as left ventricular concentric remodeling, while a hypertrophied left ventricle was denoted eccentric if the relative wall thickness was normal and concentric if the relative wall thickness was increased. Besides the traditional vascular risk factors hypertension, diabetes, smoking and hypercholesterolemia as well as body mass index, age and sex were analyzed.


RESULTS
Calcified plaques of carotid arteries were significantly correlated (r = 0.432, p < 0.001) with coronary artery stenoses as well as hypercholesterolemia (r = 0.434, p < 0.001), increasing age (r = 0.389, p < 0.001), diabetes (r = 0.273, p = 0.002), hypertension (r = 0.203, p = 0.015), and left ventricular hypertrophy (r = 0.188, p = 0.023) in contrast to smoking status, body mass index, and male sex. The number of calcified plaques was also significantly correlated (r = 0.504, p < 0.001) with severity and extent of coronary artery disease. Multiple stepwise regression analysis showed higher predictive values including calcified carotid plaques.


CONCLUSIONS
Thus, determination of calcified carotid plaques is useful to improve the predictive value of risk factor-based multivariate models.
Nossen
Joerg Michael
JM
Medizinische Klinik 1, Abteilung für Kardiologie und Angiologie, Erlangen. Jnossen@12move.de
Vierzigmann
Thomas
T
Lang
Erich
E
D000367:Age Factors; D000368:Aged; D015992:Body Mass Index; D001830:Body Surface Area; D002114:Calcinosis / Q000175:diagnosis* / Q000000981:diagnostic imaging; D006328:Cardiac Catheterization; D002340:Carotid Artery Diseases / Q000175:diagnosis* / Q000000981:diagnostic imaging; D017023:Coronary Angiography; D023921:Coronary Stenosis / Q000175:diagnosis* / Q000000981:diagnostic imaging; D048909:Diabetes Complications; D004452:Echocardiography; D005260:Female; D006801:Humans; D006937:Hypercholesterolemia / Q000150:complications; D006973:Hypertension / Q000150:complications; D017379:Hypertrophy, Left Ventricular / Q000175:diagnosis*; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D012044:Regression Analysis; D012307:Risk Factors; D012680:Sensitivity and Specificity; D012720:Severity of Illness Index; D012737:Sex Factors; D018615:Ultrasonography, Doppler, Color; D020257:Ventricular Remodeling