Scoring system based on electrocardiogram features to predict the type of heart failure in patients with chronic heart failure
Abstract: Heart failure is
divided into heart failure with reduced ejection fraction (HFrEF) and heart
failure with preserved ejection fraction (HFpEF). Additional studies are
required to distinguish between these two types of HF. A previous study showed
that HFrEF is less likely when ECG findings are normal. This study aims to
create a scoring system based on ECG findings that will predict the type of HF.
Methods and Results: We performed a cross-sectional study analyzing ECG
and echocardiographic data from 110 subjects. HFrEF was defined as an ejection
fraction ≤40%. Fifty 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., LAH, QRS duration
>100 ms, RBBB, ST-T segment changes and prolongation of the QT interval.
Based on 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, 95%
positive predictive value, an 80% negative predictive value and an accuracy of
86%.
Conclusions: The 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.
Keywords: chronic heart
failure - scoring system - electrocardiogram features - type of heart failure
Author: Hendry Purnasidha
Bagaswoto, Lucia Kris Dinarti, Erika Maharani
Journal Code: jpkedokterangg160183