Autonomic cardiac control in animal models of cardiovascular diseases. I. Methods of variability analysis

Cerebral ischemia during hemodialysis-finding the signal in the noise

Hemodialysis patients have multiple risk factors for small vessel cerebrovascular disease and cognitive dysfunction. Hemodialysis itself may cause clinically significant neurological injury through repetitive cerebral ischemia. However, supporting evidence to date consists of epidemiological associations, expert opinion, and small, single-centre studies of variable methodological quality. Isolating the impact of intra-dialytic hemodynamic instability from underlying renal and vascular disease on clinically relevant functional outcomes would require very large, controlled studies, given the heterogeneity and confounding comorbidities of the population, and the complex relationship between blood pressure and cerebral oxygen delivery. There has been an increase in complementary physiological studies looking directly at intra-dialytic cerebral oxygen balance, which have provided supporting evidence for the occurrence of cerebral ischemia, often independently of hemodynamics. Data suggesting a relationship between these measures of oxygen balance and functional outcomes is only hypothesis-generating at this stage. We advocate the testing of interventions that aim to reduce intra-dialytic cerebral hypoxia (rather than hypotension) in sufficiently powered studies, followed by correlation with validated, longitudinal assessment of clinically relevant neurological damage.

Quantifying Effects of Pharmacological Blockers of Cardiac Autonomous Control Using Variability Parameters

Objective: The aim of this study was to identify the most sensitive heart rate and blood pressure variability (HRV and BPV) parameters from a given set of well-known methods for the quantification of cardiovascular autonomic function after several autonomic blockades.

Methods: Cardiovascular sympathetic and parasympathetic functions were studied in freely moving rats following peripheral muscarinic (methylatropine), β1-adrenergic (metoprolol), muscarinic + β1-adrenergic, α1-adrenergic (prazosin), and ganglionic (hexamethonium) blockades. Time domain, frequency domain and symbolic dynamics measures for each of HRV and BPV were classified through paired Wilcoxon test for all autonomic drugs separately. In order to select those variables that have a high relevance to, and stable influence on our target measurements (HRV, BPV) we used Fisher's Method to combine the p-value of multiple tests.

Results: This analysis led to the following best set of cardiovascular variability parameters: The mean normal beat-to-beat-interval/value (HRV/BPV: meanNN), the coefficient of variation (cvNN = standard deviation over meanNN) and the root mean square differences of successive (RMSSD) of the time domain analysis. In frequency domain analysis the very-low-frequency (VLF) component was selected. From symbolic dynamics Shannon entropy of the word distribution (FWSHANNON) as well as POLVAR3, the non-linear parameter to detect intermittently decreased variability, showed the best ability to discriminate between the different autonomic blockades.

Conclusion: Throughout a complex comparative analysis of HRV and BPV measures altered by a set of autonomic drugs, we identified the most sensitive set of informative cardiovascular variability indexes able to pick up the modifications imposed by the autonomic challenges. These indexes may help to increase our understanding of cardiovascular sympathetic and parasympathetic functions in translational studies of experimental diseases.

Complexity of cardiovascular regulation in small animals

Oscillations of heart rate and blood pressure are related to the activity of the underlying control mechanism. They have been investigated mostly with linear methods in the time and frequency domains. Also, in recent years, many different nonlinear analysis methods have been applied for the evaluation of cardiovascular variability. This review presents the most commonly used nonlinear methods. Physiological understanding is obtained from various results from small animals.

Autonomic cardiac control in animal models of cardiovascular diseases II. Variability analysis in transgenic rats with α-tropomyosin mutations Asp175Asn and Glu180Gly

Animal models of cardiovascular diseases allow to investigate relevant pathogenetic mechanisms in detail. In the present study, the mutations Asp175Asn and Glu180Gly in alpha-tropomyosin (TPM1), known cause familiar hypertrophic cardiomyopathy (FHC) were studied for changes in hemodynamic parameters and spontaneous baroreflex regulation in transgenic rats in comparison to transgenic and non-transgenic controls by telemetry. Heart rate variability (HRV) and blood pressure variability (BPV) were analyzed using time- and frequency domain, as well as non-linear measures. The dual sequence method was used for the estimation of the baroreflex regulation. In transgenic rats harboring mutated TPM1, changes in HRV were detected during exercise, but not at rest. Both mutations, Asp175Asn and Glu180Gly, caused increased low frequency power. In addition, in animals with mutation Asp175Asn a reduced total HRV was observed. BPV did not show any differences between all transgenic animal lines. During exercise, a strong increase in the number of bradycardic and tachycardic fluctuations accompanied with decreased baroreflex sensitivity (BRS) was detected in animals with either TPM1 mutation, Asp175Asn or Glu180Gly. These data suggest, that the analysis of cardiac autonomic control, particularly of baroreflex regulation, represents a powerful non-invasive approach to investigate the effects of subtle changes in sarcomeric architecture on cardiac physiology in vivo. In case of mutations Asp175Asn or Glu180Gly in TPM1, early detection of alterations in autonomic cardiac control could help to prevent sudden cardiac death in affected persons.