Which Arterial and Cardiac Parameters Best Predict Left Ventricular Mass?

Author:

Chen Chen-Huan1,Ting Chih-Tai1,Lin Shing-Jong1,Hsu Tsui-Lieh1,Ho Shuenn-Jiin1,Chou Pesus1,Chang Mau-Song1,O’Connor Frances1,Spurgeon Harold1,Lakatta Edward1,Yin Frank C. P.1

Affiliation:

1. From the Division of Cardiology, Veterans General Hospital, Taipei, Taiwan (C.-H.C., S.-J.L., T.-L.H., S.-J.H., M.-S.C.); the Division of Cardiology, Veterans General Hospital, Taichung, Taiwan and National Yang Ming University, Taiwan (C.-T.T.); the Institute of Public Health, National Yang-Ming University, Taiwan (P.C.); Gerontology Research Center, National Institute on Aging, Baltimore, Md (F.O., H.S., E.L.); and the Division of Cardiology, Johns Hopkins University School of Medicine, Baltimore,...

Abstract

Background —Many cardiovascular and noncardiovascular parameters are thought to be determinants of left ventricular mass (LVM). Complicated interactions necessitate the simultaneous measurement and consideration of each to determine their individual and collective impact on LVM. We undertook such a comprehensive study. Methods and Results —The influence of anthropometry, cardiac size and contractility, arterial structure and function, as well as indices of lifestyle, physical activity, and dietary salt intake on LVM (by two-dimensionally guided M-mode echocardiography) was analyzed in 1315 Chinese subjects who were either normotensive or had untreated hypertension. Effects of many cardiac and arterial factors were assessed. In univariate analysis, almost all measured noncardiovascular, cardiac, and arterial variables were significantly correlated with LVM. In multivariate linear regression analyses, when age, sex, body habitus, fasting serum C-peptide level, dietary salt, physical activity, and lifestyle were accounted for, the optimum multivariate linear regression main effects model had an adjusted model r 2 of 0.740, with 98% of the model variance accounted for by the 5 independent determinants of LVM: stroke volume (49.6%), systolic blood pressure (30.7%), contractility (14.7%), body mass index (1.8%), and aortic root diameter (1.6%). Other proposed arterial indices were significant independent determinants of LVM only when blood pressure was removed from the model and, even then, these indices not only resulted in less powerful prediction but also accounted for only a very small percentage of the total variance of LVM. Conclusions —In a large population, we (1) confirmed that age, body habitus, and some indexes of arterial structure and function are independent determinants of LVM; (2) found aortic diameter to be an independent structural determinant of LVM; (3) demonstrated that the effects of the derived measures of arterial function were small and provided no better predictive power than blood pressure alone; and (4) showed that when the best measures of cardiac and vascular load were included, the single most potent predictor was an index of left ventricular size.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Physiology (medical),Cardiology and Cardiovascular Medicine

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