Prediction of Left Ventricular Mass Index Using Electrocardiography in Essential Hypertension – A Multiple Linear Regression Model

• Published in: Medical devices (Auckland, N.Z.) Vol. 13; pp. 163 - 172
• Main Authors: Ahmed, Shah Newaz, Jhaj, Ratinder, Sadasivam, Balakrishnan, Joshi, Rajnish
• Format: Journal Article
• Language: English
• Published: New Zealand Dove Medical Press Limited 01.01.2020; Taylor & Francis Ltd; Dove; Dove Medical Press
• Subjects: Analysis; Blood pressure; Body mass index; Cardiovascular disease; Care and treatment; echocardiography; Electrocardiography; Heart; Heart hypertrophy; Hypertension; left ventricular hypertrophy; Original Research; Regression analysis; Womens health; India; left ventricular hypertrophy; echocardiography; electrocardiography
• ISSN: 1179-1470; 1179-1470
• DOI: 10.2147/MDER.S253792

Current electrocardiography (ECG) criteria indicate only the presence or absence of left ventricular hypertrophy (LVH). LVH is a continuum and a direct relationship exists between left ventricular mass (LVM) and cardiovascular event rate. We developed a mathematical model predictive of LVM index (LVMI) using ECG and non-ECG variables by correlating them with echocardiography determined LVMI. The model was developed in a cohort of patients on treatment for essential hypertension (BP>140/90 mm of Hg) who underwent concurrent ECG and echocardiography. One hundred and forty-seven subjects were included in the study (56.38±11.84 years, 66% males). LVMI was determined by echocardiography (113.76±33.06 gm/m ). A set of ECG and non-ECG variables were correlated with LVMI for inclusion in the multiple linear regression model. The model was checked for multicollinearity, normality and homogeneity of variances. The final regression equation formulated with the help of unstandardized coefficients and constant was =18.494+ 1.704 ( ) + 0.969 ( ) + 0.295 ( ) + 15.406 ( ) (aLL - sum of deflections in augmented limb leads; RaVL+SV3 - sum of deflection of (R wave in aVL + S wave in V3); MBP - mean blood pressure; IHD=1 for the presence of the disease, IHD=0 for the absence of the disease). In the model, 50.4% of the variability in LV mass is explained by the variables used. The findings warrant further studies for the development of better and validated models that can be incorporated in microprocessor-based ECG devices. The determination of LVMI with ECG only will be a cost-effective and readily accessible tool in patient care.