3.2. Multivariate binary logistic regression and nomogram construction
RA, dyspnea
REGRESSION, LBBB, DILATED CARDIOMYOPATHY
ECG parameters in the training dataset which were found statistically significant in univariate analyses were included in multivariate binary logistic regression using forward LN stepwise regression. After multivariate analysis, V1SA (odds ratio [OR]: 4.145, 95% confidence interval [CI] [2.286, 7.516], Independent screening indicators for DCM in the multivariate logistic analysis.CI = confidence interval, DCM = dilated cardiomyopathy, RA = the amplitude of R wave, SA = amplitude of S wave.The nomogram of the screening model.The use of nomogram consists of 3 simple steps. First, the point value of each variable is read on the point scale. Next, add up all the points obtained in the first step as the total point. Finally, the probability of DCM corresponding to the total point of the specific patient is read on the predicted value scale. For example, a patient with dyspnea was admitted to the cardiovascular department of our hospital, and the ECG was examined (paper speed = 25 mm/s and calibration = 10 mm/mV) immediately after admission and showed LBBB, as shown in Figure Admission ECG of a patient with dyspnea. ECG = electrocardiogram.