Correlation between aortic valve stenosis severity and heart rate variability indices based on recurrence quantification analysis

Aortic valve stenosis (AVS) is a progressive disease characterized by inflammation, lipid infiltration, and calcification, ultimately leading to impaired valvular function. Heart rate variability (HRV) has been associated with autonomic impairment in AVS, yet prior ambulatory studies have reported inconsistent associations between this imbalance and AVS severity. Moreover, the relationship between nonlinear HRV indices, particularly those derived from recurrence quantification analysis (RQA) and echocardiographic parameters under controlled short-term conditions, remains insufficiently explored. This cross-sectional study investigated the correlation between linear and nonlinear RQA-derived HRV indices with the AVS severity. 26 patients (57.7% male, 42.3% female; mean age 63 ± 6 years) with moderate-to-severe AVS underwent 5-min supine ECG recordings under spontaneous breathing. Time and frequency-domain HRV indices, as well as RQA indices, were computed using standardized embedding parameters. Pearson correlations were computed to assess associations of the indices with echocardiographic and demographic variables. RQA indices (including determinism, Shannon entropy, and laminarity) showed significant correlations with echocardiographic markers of AVS: mean pressure gradient (mPG), indexed aortic valve area (AVAi), and peak jet velocity ( V max ), all with p < 0.05. These correlations revealed that as AVS progresses toward more severe stages, there is a significant shift in cardiovascular dynamics, suggesting that the heart rate signal becomes increasingly characterized by periodic, rigid, and laminar states. Notably, while age correlated primarily with linear HRV indices, most RQA indices remained independent of age, systolic blood pressure, and left ventricular ejection fraction. Among the nonlinear metrics, specific associations were observed for body mass index with recurrence time type 1. Both linear and nonlinear HRV indices correlate with established echocardiographic parameters of AVS severity (mPG, AVAi, and V max ). These findings suggest that short-term HRV analysis, including RQA, may serve as a valuable non-invasive tool for assessing the disease progression in patients with aortic valve stenosis.