Deterministic Chaos and Fractal Complexity in the Dynamics of Cardiovascular Behavior: Perspectives on a New Frontier

Physiological systems such as the cardiovascular system are capable of five kinds of behavior: equilibrium, periodicity, quasi-periodicity, deterministic chaos and random behavior. Systems adopt one or more these behaviors depending on the function they have evolved to perform. The emerging mathematical concepts of fractal mathematics and chaos theory are extending our ability to study physiological behavior. Fractal geometry is observed in the physical structure of pathways, networks and macroscopic structures such the vasculature and the His-Purkinje network of the heart. Fractal structure is also observed in processes in time, such as heart rate variability. Chaos theory describes the underlying dynamics of the system, and chaotic behavior is also observed at many levels, from effector molecules in the cell to heart function and blood pressure. This review discusses the role of fractal structure and chaos in the cardiovascular system at the level of the heart and blood vessels, and at the cellular level. Key functional consequences of these phenomena are highlighted, and a perspective provided on the possible evolutionary origins of chaotic behavior and fractal structure. The discussion is non-mathematical with an emphasis on the key underlying concepts

Plasma brain natriuretic peptide as a surrogate marker for cardioembolic stroke

<p>Abstract</p> <p>Background</p> <p>Cardioembolic stroke generally results in more severe disability, since it typically has a larger ischemic area than the other types of ischemic stroke. However, it is difficult to differentiate cardioembolic stroke from non-cardioembolic stroke (atherothrombotic stroke and lacunar stroke). In this study, we evaluated the levels of plasma brain natriuretic peptide in acute ischemic stroke patients with cardioembolic stroke or non-cardioembolic stroke, and assessed the prediction factors of plasma brain natriuretic peptide and whether we could differentiate between stroke subtypes on the basis of plasma brain natriuretic peptide concentrations in addition to patient's clinical variables.</p> <p>Methods</p> <p>Our patient cohort consisted of 131 consecutive patients with acute cerebral infarction who were admitted to Kagawa University School of Medicine Hospital from January 1, 2005 to December 31, 2007. The mean age of patients (43 females, 88 males) was 69.6 ± 10.1 years. Sixty-two patients had cardioembolic stroke; the remaining 69 patients had non-cardioembolic stroke (including atherothrombotic stroke, lacunar stroke, or the other). Clinical variables and the plasma brain natriuretic peptide were evaluated in all patients.</p> <p>Results</p> <p>Plasma brain natriuretic peptide was linearly associated with atrial fibrillation, heart failure, chronic renal failure, and left atrial diameter, independently (F_4,126= 27.6, p < 0.0001; adjusted R²= 0.45). Furthermore, atrial fibrillation, mitral regurgitation, plasma brain natriuretic peptide (> 77 pg/ml), and left atrial diameter (> 36 mm) were statistically significant independent predictors of cardioembolic stroke in the multivariable setting (Χ²= 127.5, p < 0.001).</p> <p>Conclusion</p> <p>It was suggested that cardioembolic stroke was strongly predicted with atrial fibrillation and plasma brain natriuretic peptide. Plasma brain natriuretic peptide can be a surrogate marker for cardioembolic stroke.</p

Comparison of heart rate variability analysis methods in patients with Parkinson's disease

The aim of the present study was to evaluate different analysis methods for revealing heart rate variability (HRV) differences between untreated patients with Parkinson's disease and healthy controls. HRV in standard cardiovascular reflex tests and during a 10 min rest period were measured by time- and frequency-domain and geometrical and non-linear analysis methods. Both frequency- and time-domain measures revealed abnormal HRV in the patients, whereas non-linear and geometrical measures did not. The absolute high-frequency spectral power of HRV was the strongest independent predictor to separate the patients from the controls (p = 0.001), when the main time-domain and absolute frequency-domain measures were compared with each other. When the corresponding normalised spectral units, instead of the absolute units, were used in the comparison, the two best single measures for separating the groups were the 30/15 ratio of the tilting test (p = 0.003) and the max/min ratio during deep breathing (p = 0.024). When the correlations between the different measures were estimated, the time-domain measures, fractal dimension and absolute spectral powers correlated with each other. The frequency- and time-domain analysis techniques of stationary short-term HRV recordings revealed significant differences in cardiovascular regulation between untreated patients with Parkinson's disease and the controls. This confirms cardiovascular regulation failure before treatment in the early stages of Parkinson's disease. The HRV spectral powers, in absolute units, were the most effective single parameters in segregating the two groups, emphasising the role of spectral analysis in the evaluation of HRV in Parkinson's disease