Association between Multiscale Entropy Characteristics of Heart Rate Variability and Ischemic Stroke Risk in Patients with Permanent Atrial Fibrillation

Abstract

Abstract:Multiscale entropy (MSE) profiles of heart rate variability (HRV) in patients with atrial fibrillation (AFib) provides clinically useful information for ischemic stroke risk assessment, suggesting that the complex properties characterized by MSE profiles are associated with ischemic stroke risk. However, the meaning of HRV complexity in patients with AFib has not been clearly interpreted, and the physical and mathematical understanding of the relation between HRV dynamics and the ischemic stroke risk is not well established. To gain a deeper insight into HRV dynamics in patients with AFib, and to improve ischemic stroke risk assessment using HRV analysis, we study the HRV characteristics related to MSE profiles, such as the long-range correlation and probability density function. In this study, we analyze the HRV time series of 173 patients with permanent AFib. Our results show that, although HRV time series in patients with AFib exhibit long-range correlation (1/f fluctuations)-as observed in healthy subjects-in a range longer than 90 s, these autocorrelation properties have no significant predictive power for ischemic stroke occurrence. Further, the probability density function structure of the coarse-grained times series at scales greater than 2 s is dominantly associated with ischemic stroke risk. This observation could provide valuable information for improving ischemic stroke risk assessment using HRV analysis.

Ischemic Stroke Risk Assessment by Multiscale Entropy Analysis of Heart Rate Variability in Patients with Persistent Atrial Fibrillation

“…For the afternoon recording, those with R (s) (1) ≥ 0.82 at the time scale of 240 s and R (s) (1) ≥ 0.81 at the time scale of 270 s had a higher risk of developing an ischemic stroke (the result for 270 s is shown in Figure 5b). On the contrary, we found that H Matsuoka et al [13] revealed that the probability distribution characteristic of MSE profiles in a wider range of scales of s ≥ 2 s is a useful measure for ischemic stroke risk assessment, while our result of H (s) D did not show any significant difference between the two groups. Furthermore, the previous study did not find any significant difference in the time correlation characteristic between the two groups, while the present study found that R (s) (1) at longer time scales might contribute to S (s) E .…”

“…Our morning recording result was in agreement with the previous studies that at large time scales were higher in ischemic stroke patients than in non-ischemic stroke patients [ 12 , 13 ], while our afternoon recording result was similar to reports from other studies that demonstrated a decrease in nonlinear behavior of the heart rate, which is associated with the worsening of pathological states [ 29 ]. It has been reported that healthy participants generate more complex dynamics than diseased participants [ 30 ].…”

“…The present study demonstrated that sample entropy (S We confirmed the presence of white noise-like fluctuations at shorter scales (less than approximately 100 s) and near-1/f fluctuations in longer scales (more than approximately 100 s) in the VRI time series of AFib patients (Figure 2) with α 1 = 0.64 and α 2 = 0.89, which is similar to the previous study [13]. Several findings have described the existence of white noise characteristics as an uncorrelated process (over short scales) and 1/f noise as a correlated process (over long scales) in the HRV of patients with AFib [11,26].…”

“…There are limited studies regarding the HRV features of patients with AFib before an ischemic stroke event. Previous studies have reported the use of multiscale entropy (MSE) analysis of HRV as a predictor of ischemic stroke in patients with AFib [ 12 , 13 ]. Watanabe et al [ 12 ] demonstrated that patients with AFib with a higher value of sample entropy at a time scale of 90 s ≤ s ≤ 300 s were more likely to develop ischemic stroke.…”

“…Furthermore, MSE profiles are affected by multiscale characterizations, such as time correlation and probability distribution characteristics. Matsuoka et al [ 13 ] reported that information entropy as the probability distribution characteristic at scales of 2 s and greater dominantly contribute to the risk assessment of ischemic stroke events. However, previous studies did not focus on stroke-naïve patients with AFib.…”