126 - Systolic Time Ratios via Hemotag and 2D Echocardiography: Correlations with Ejection Fraction and Implications for Clinical Practice

Abstract

Background: Cardiac time intervals (CTI) have been classically obtained with phonocardiography, though this technique has been overlooked since the advent of the 2D M-mode echocardiography. The “HemoTag” is a new technology that uses heart sounds and an ECG signal transduced via 3 thoracic electrodes to measure CTI and can potentially constitute a quick and cost effective means of assessing patient's left ventricular (LV) function. “HemoTag” indices were assessed as a predictor of bi-plane Simpson's ejection fraction as established echocardiographic measures of systolic dysfunction, using a variety of prediction models. Methods: 103 consecutive patients were recruited at an outpatient cardiology clinic from March to September 2016. CTI measurements were obtained for all patients using both conventional echocardiography and via “HemoTag”. Of interest were the Pre-Ejection Period (PEP) and LV ejection time (LVET), which were evaluated for correlation with LVET using the systolic time ratio (STR), STR = PEP/LVET. Results: The female to male ratio was 0.91 and the mean age was 70 ± 15 years. The mean systolic blood pressure was 129 ± 21 mmHg. Using a threshold-based model, a sensitivity of 100%, specificity of 83.33% and accuracy of 86.9% was noted. With a linear regression-based prediction model, a sensitivity of 86.7%, specificity of 80% and accuracy of 86.3% was noted. With a support vector machine (SVM)-based prediction model, a sensitivity of 97%, specificity of 92% and accuracy of 96.3% was noted. Patients were then randomly allocated into two subsets, one to drive the model and the other to validate it. Using a logistic regression, an ROC curve was employed to assess performance with an AUC of 0.75 in the validation set. Conclusion: “HemoTag” represents a cost effective and potentially widely applicable technology that can be used for the assessment of LV function. Larger studies are needed to reinforce the conclusions stated above.