Frailty has been defined as a geriatric syndrome that results in high vulnerability to health adverse outcomes. This increased vulnerability state results from dysregulation of multiple physiological systems and its complex interactions. Thus, assessment of physiological systems integrity and of its dynamic interactions seems to be useful in the context of frailty management. Heart rate variability (HRV) analysis provides information about autonomic nervous system (ANS) function, which is responsible to control several physiologic functions. This study investigated the cardiac autonomic modulation by HRV analysis in community-dwelling elderly women classified as non-frail, pre-frail and frail. Twenty-three elderly women were assigned to the following groups: non-frail (n = 8), pre-frail (n = 8) and frail (n = 7). HRV assessment was performed through linear and non-linear analysis of cardiac interval variability. It was observed a higher sympathetic and lower parasympathetic modulation in frail when compared with non-frail and pre-frail groups (p < 0.05) as indicated by frequency domain indices. Additionally, frail group had a decreased 2LV % pattern (that reflects parasympathetic modulation) in the symbolic analysis in comparison with non-frail group. These findings suggest that frail elderly women present an autonomic imbalance characterized by a shift towards sympathetic predominance. Thus, monitoring ANS function in the context of frailty management may be an important strategy to prevention, diagnosis and treatment of this syndrome and its consequences.

Spectral analysis of heart rate (HR) has been widely used to assess the autonomic cardiovascular control. A nonlinear approach, known as symbolic analysis, has been reported to be very useful to assess the autonomic control of cardiovascular system in humans, but very few studies reported on the differences between these two approaches on experimental models. Two distinct approaches were used to elicit autonomic changes in conscious Wistar rats: (1) pharmacological blockade of cardiac autonomic receptors with atenolol (ATE, N = 9) or methylatropine (ATR, N = 9) and (2) mild changes in arterial pressure (AP) induced by phenylephrine (PHE, N = 9) or sodium nitroprusside (NPS, N = 9). Series of cardiac interval (CI) and systolic AP (SAP) were assessed using spectral analysis and symbolic dynamics. Results show that, for spectral analysis, the power in high frequency band of CI and the power in low frequency band of SAP are the most reliable indices of vagal and sympathetic modulation, respectively. For symbolic analysis, results point 0V% and 1V% to be related to sympathetic and 2UV% to vagal modulation. Interestingly, the incidence of 1V patterns, hitherto with unknown meaning, was revealed the best index of sympathetic modulation in the rat and should be accounted for in the future studies.

Analysis of heart rate variability (HRV) by nonlinear approaches has been gaining interest due to their ability to extract additional information from heart rate (HR) dynamics that are not detectable by traditional approaches. Nevertheless, the physiological interpretation of nonlinear approaches remains unclear. Therefore, we propose long-term (60 min) protocols involving selective blockade of cardiac autonomic receptors to investigate the contribution of sympathetic and parasympathetic function upon nonlinear dynamics of HRV. Conscious male Wistar rats had their electrocardiogram (ECG) recorded under three distinct conditions: basal, selective (atenolol or atropine), or combined (atenolol plus atropine) pharmacological blockade of autonomic muscarinic or β-adrenergic receptors. Time series of RR interval were assessed by multiscale entropy (MSE) and detrended fluctuation analysis (DFA). Entropy over short (1 to 5, MSE) and long (6 to 30, MSE) time scales was computed, as well as DFA scaling exponents at short (α, 5 ≤ ≤ 15), mid (α, 30 ≤ ≤ 200), and long (α, 200 ≤ ≤ 1,700) window sizes. The results show that MSE is reduced under atropine blockade and MSE is reduced under atropine, atenolol, or combined blockade. In addition, while atropine expressed its maximal effect at scale six, the effect of atenolol on MSE increased with scale. For DFA, α decreased during atenolol blockade, while the α increased under atropine blockade. Double blockade decreased α and increased α Results with surrogate data show that the dynamics during combined blockade is not random. In summary, sympathetic and vagal control differently affect entropy (MSE) and fractal properties (DFA) of HRV. These findings are important to guide future studies. Although multiscale entropy (MSE) and detrended fluctuation analysis (DFA) are recognizably useful prognostic/diagnostic methods, their physiological interpretation remains unclear. The present study clarifies the effect of the cardiac autonomic control on MSE and DFA, assessed during long periods (1 h). These findings are important to help the interpretation of future studies.

The analysis of heart rate variability (HRV) by nonlinear methods has been gaining increasing interest due to their ability to quantify the complexity of cardiovascular regulation. In this study, multiscale entropy (MSE) and refined MSE (RMSE) were applied to track the complexity of HRV as a function of time scale in three pathological conscious animal models: rats with heart failure (HF), spontaneously hypertensive rats (SHR), and rats with sinoaortic denervation (SAD). Results showed that HF did not change HRV complexity, although there was a tendency to decrease the entropy in HF animals. On the other hand, SHR group was characterized by reduced complexity at long time scales, whereas SAD animals exhibited a smaller short- and long-term irregularity. We propose that short time scales (1 to 4), accounting for fast oscillations, are more related to vagal and respiratory control, whereas long time scales (5 to 20), accounting for slow oscillations, are more related to sympathetic control. The increased sympathetic modulation is probably the main reason for the lower entropy observed at high scales for both SHR and SAD groups, acting as a negative factor for the cardiovascular complexity. This study highlights the contribution of the multiscale complexity analysis of HRV for understanding the physiological mechanisms involved in cardiovascular regulation.

No abstract