Linear regression models for quantitative assessment of left ventricular function and structures using M-mode echocardiography
AbstractChanges in left ventricular structures and function have been reported in cardiomyopathies. No prediction models have been established in this environment. This study established regression models for prediction of left ventricular structures in normal subjects. A sample of normal subjects was drawn from a large urban population. Echocardiographic end diastolic diameters, end systolic diameters, posterior wall thicknesses in both systole and diastole, septal wall thicknesses in both systole and diastole were used to calculate left ventricular mass, left ventricular mass index, relative wall thickness and fractional shortening. Heights, weights, ages, and blood pressures of subjects were obtained. Pearson’s correlation coefficients were computed. Tests were two tailed with P < 0.05 indicating statistical significance. Three hundred and twenty two normal subjects of Ibo descent were enrolled in this study as volunteers between June, 2006 and April, 2007. Correlation coefficients between measured left ventricular structures and functions, and some anthropometric variables were computed. Linear regression models for the prediction of left ventricular structures were established. Prediction models for left ventricular structures have been established and could be useful in
assessing morbidity in cardiomyopathies.