Scoring System Based on Electrocardiogram Features to Predict the Type of Heart Failure in Patients With Chronic Heart Failure.

Abstract

BackgroundHeart failure (HF) is divided into heart failure with reduced ejection fraction (HFrEF) and heart failure with preserved ejection fraction (HFpEF). Mortality from HF is inversely related to left ventricular function. Additional studies are required to distinguish between these two types of HF. A previous study showed that HFrEF is less likely when electrocardiogram (ECG) findings are normal. This study aims to create a scoring system based on ECG findings that will predict the type of HF.MethodsWe performed a cross-sectional study analyzing ECG and echocardiographic data from 110 subjects with chronic HF. HFrEF was defined as an ejection fraction ≤ 40%.ResultsFifty people were diagnosed with HFpEF and 60 people suffered from HFrEF. Multiple logistic regression analysis revealed certain ECG variables that were independent predictors of HFrEF, i.e., left atrial hypertrophy (LAH), QRS duration > 100 ms, right bundle branch block (RBBB), ST-T segment changes and prolongation of the QT interval. Based on receiver operating characteristic (ROC) curve analysis, we obtained a score for HFpEF of -1 to +3, while HFrEF had a score of +4 to +6 with 76% sensitivity, 96% specificity, a 95% positive predictive value, an 80% negative predictive value and an accuracy of 86%.ConclusionsThe scoring system derived from this study, including the presence or absence of LAH, QRS duration > 100 ms, RBBB, ST-T segment changes and prolongation of the QT interval can be used to predict the type of HF with satisfactory sensitivity and specificity.