Abstract
INTRODUCTION: Cardiac autonomic dysfunction reduces the cardiac system's ability to respond to stressors and is prevalent in aging and diseases, especially cardiovascular diseases like aortic stenosis (AS). Heart rate variability (HRV) is a common measure for evaluating parasympathetic activity and cardiac autonomic function; similarly, heart rate (HR) changes during exercise are utilized in determining cardiac health. However, directly measuring HR parameters from an electrocardiogram (ECG) is difficult due to motion artifacts during exercise. METHOD: This study aimed to develop a method that assesses HR metrics while minimizing motion artifacts, using an upper-extremity function (UEF) test. We determined the effect of aging and AS on resting-state HR measures, while quantifying the relationship between HRV and HR dynamics. Seventy participants, including 21 young controls (age = 21.8 ± 3.2 years), 12 aging/older controls (age = 69.8 ± 4.0 years), and 37 aging/older adults with AS (age = 74.3 ± 10.4 years), performed a baseline rest followed by the UEF test consisting of 20 s of rapid elbow flexion-extension with the right arm; HR was measured using ECG from the left side of the chest. HRV outcomes included sample entropy (SampEn), root mean square of successive differences between heartbeats (RMSSD), percentage of successive NN intervals with differences of more than 25 ms (pNN25), and a Poincaré plot. HR dynamics were percentage HR increase during the UEF test and percentage HR decrease during post-task recovery. RESULTS: All resting-state HR measures, except SampEn, as well as HR increase and decrease due to UEF, were significantly lower in the aging/older adult control and AS groups compared to the young control group (p < 0.0072, effect size = 1.964 ± 0.399 for HRV and 1.534 ± 0.256 for HR dynamics). No significant differences were observed in HRV outcomes between the aging/older adult control and AS groups (p > 0.0706, effect size = 0.192 ± 0.082); however, HR decrease was significantly different between the two aging adult groups (p = 0.0440, effect size = 0.569). Across all groups, all HRV parameters correlated significantly with both HR dynamics measures (R2 = 0.233-0.463, p < 0.0001). CONCLUSION: Findings suggest that, compared to AS, aging has a more pronounced impact on HRV and HR dynamics. Further, HR dynamics, evaluated through a short physical test, may provide a potential measure of cardiac autonomic dysfunction, which is promising for future clinical applications.