Abstract 15117: Estimating Ejection Fraction From the 12 Lead Electrocardiogram in Acute Heart Failure

Abstract

Introduction: The 2022 AHA Guidelines for the Management of Heart Failure (HF) emphasized initiating guideline-directed medical therapy (GDMT) as early as possible during acute hospitalization. GDMT significantly differs between HF patients with reduced and preserved ejection fraction (EF). The electrocardiogram (ECG) is one of the first tests performed to assess cardiac function among HF patients. Purpose: To develop a linear model to estimate EF using the ECG and clinical covariates. Methods: Medical record data from 2020-21 of HF patients > 18 years and positive Framingham Heart Failure Diagnostic Criteria excluding those with ventricular assist devices were extracted. Demographics, NYHA class, EF, and comorbidities, 12-lead ECG closest to the time of the echocardiogram were analyzed. We extracted 312 different features from the ECG using the Philips DXL Algorithm. Recursive LASSO regression was used to identify a subset of features in domain blocks. All analyses were completed in RStudio (4.3.0). Results: Among 126 patients (age 69.4 + 15.5 years; BMI 31.2 + 8.2 kg/m 2 ; EF 40 + 19%; the time between ECG-echocardiogram 13.30 + 40.67 hours: minutes), the predominant cardiac rhythm (70%, n=88) was sinus. Among the 312 ECG features, 39 (13%) were significant; the final linear model included 9 (3%) features: S Duration V1, QRS Duration III, Horizontal T Angle, Mean Heart Rate, Q Duration aVL, Maximum QRS Angle, R Duration V3, S Amplitude V3, and P amplitude V3. The final linear model achieved an R 2 =0.498 and adjusted R 2 =0.459. We adjusted the model for age, body mass index, and sex, and model performance improved by R 2 =0.107 adjusted R 2 =0.104. The addition of time between ECG-echocardiogram to the model did not significantly change performance. From the predicted values, 50% (n=63) were within the margin of error, and the correlation between predicted and true values was moderate (r=0.629 [95%CI, 0.510-0.724]). The mean difference between predicted and true EF values varied between + 12.06%. Conclusions: Our initial results demonstrate the ability to estimate EF using a 12-lead ECG. While the results are limited due to the small sample size and significant time between ECG and echocardiogram, these preliminary results support the feasibility of future research.