Association Between Heart Rate Resting State Entropy and Heart Rate Dynamics Among Healthy Adults and Patients with Aortic Stenosis

Abstract

Introduction: Aortic Stenosis (AS) is a cardiovascular disease that restricts the blood flow from the left ventricle to the aorta and leads to a decline in physical activities in people with such conditions. Heart rate (HR) complexity has been implemented as a standard method to assess cardiac autonomic dysfunction in cardiovascular diseases. The HR complexity is derived from the electrocardiogram (ECG) signals while the participant rests for a minimum of five minutes. The focus of this study is to compare the HR complexity during a 5-minute resting period and the HR dynamics, which is a novel approach to measure HR changes during a 20-second physical activity among healthy young adults and older adults with AS.Methods: Healthy young adults (controls) aged 18-30 years and older adults (>60 years) with AS were recruited for this study. HR complexity was assessed by asking the participants to sit still with no interaction or movement, and HR was recorded for 5 minutes. HR dynamics were assessed when participants performed a physical task (20 seconds baseline, 20 seconds of rapid elbow flexion with the right arm, and 30 seconds recovery). HR was recorded using an ECG sensor attached to the left side of the chest and upper rib. The multiscale entropy (MSE) method with a selected scale factor of 20 was used to measure complexity during the 20 seconds physical task using time series of intervals between the heartbeats. HR dynamics parameters included percent change in HR during the activity and the recovery period after the arm flexion task. ANOVA models were used with the groups, age, BMI, and sex as independent and HR dynamics and the MSE values as dependent variables. Pearson correlations between MSE and HR dynamics were calculated. Results & Discussion: A total of 70 participants were recruited for this study, including 30 healthy controls (age=21±6 years) and 40 AS patients (age=71±11 years). There was a significant difference between HR dynamics (HR increase and decrease) between controls and AS patients, mean values of 41.46% and 15.70% for HR increase (p=0.0055) and mean values of -27.04% and -13.15% for HR decrease (p=0.0007), for controls and AS patients, respectively. The Pearson correlation between the HR dynamics and the MSE data among the two groups combined showed significant associations. Results suggest that the proposed HR dynamics can provide a quicker measure of autonomic control deficits in AS. Significance: Current findings suggest that HR outcomes obtained from a quick 20s test during physical activity can provide information on cardiac autonomic dysfunction in AS patients. AS is mainly associated with an increased risk of frailty in older adults. Frailty is a syndrome associated with low physiological reserve, which leads to muscle loss and autonomic dysfunction. Currently, there is no specific device or assessment tool available to detect frailty in AS patients. Hence, our current findings suggest that the HR dynamics outcomes obtained could provide information for assessing frailty in AS. For future investigations, we will develop an easy-to-use app on a smartwatch for identifying frailty with the use of simultaneous measures of HR dynamics and motor performance.