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01.Kynurenines in the Brain: From Experiments to Clinics
02.Trends in Exercise and Health Research
03.Psychiatric and Metabolic Disorders: Research Synthesis and Clinical Translation
04.Malnutrition in the 21st Century
05.Body Mass Index and Health
06.New Research on Morbid Obesity
07.Trends in Diabetes Mellitus Research
08.Neurochemistry of Metabolic Diseases: Lysosomal Storage Diseases, Phenylketonuria and Canavan Disease
09.Trends in Obesity Research
10.Global Dimensions of Childhood Obesity
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Cardiovascular Signals in Diabetes Mellitus: A New Tool to Detect Autonomic Neuropathy
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Authors: Michal Javorka, Ingrid Tonhajzerova, Zuzana Turianikova, Kamil Javorka (Comenius Univ., Slovak Republic); Natasa Honzikova (Masaryk Univ., Czech Republic); Mathias Baumert (Univ. of Adelaide, Australia) 
Book Description:
Early detection of subclinical autonomic dysfunction is of vital importance in patients with diabetes mellitus (DM) for the prevention of subsequent serious adverse consequences. Reduction in heart rate variability (HRV) is now regarded as the earliest indicator of cardiovascular dysregulation in DM. HRV has traditionally been quantified using linear measures, which describe the magnitude of RR interval oscillations, but are insufficient to characterize complex heart rate dynamics. While HRV is mostly mediated by parasympathetic nervous system, beat-to-beat blood pressure recordings may provide information regarding sympathetic activity. A variety of novel measures has been developed to quantify nonlinear features of cardiovascular signals, providing information on the complexity of the dynamical system involved in the genesis of these short-term fluctuations. In this book, it is demonstrated that novel nonlinear methods are often more sensitive to autonomic dysregulation than linear methods and therefore may improve the diagnostic power of cardiovascular variability analysis for cardiovascular autonomic neuropathy in DM. Our data indicate that cardiovascular dysregulation progresses in relatively short time frames, depending on the history of DM. Further, its progression appears to be associated with glycemic control. Different methods of cardiovascular variability analysis can provide mutually independent information and therefore should be used simultaneously for a comprehensive analysis of autonomic dysfunction to identify patients at risk for autonomic neuropathy.

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Table of Contents:

Section 1: Short-Term Heart Rate Complexity Analysis

Chapter 1. Background, pp. 3-4
Chapter 2. Methods, pp. 5-11
Chapter 3. Results, pp. 13-24
Chapter 4. Interpretation, pp. 25-29

Section 2: Recurrences in Heart Rate Dynamics

Chapter 5. Background, pp. 33
Chapter 6. Methods, pp. 35-38
Chapter 7. Results, pp. 39-41
Chapter 8. Interpretation, pp. 43-44

Section 3: Blood Pressure Oscillations- Linear and Multiscale Entropy Analysis

Chapter 9. Background, pp. 47-48
Chapter 10. Methods, pp. 49-51
Chapter 11. Results, pp. 53-56
Chapter 12. Interpretation, pp. 57-58

Section 4: Linear and Nonlinear Analysis of Baroreflex

Chapter 13. Background, pp. 61
Chapter 14. Methods, pp. 63-67
Chapter 15. Results, pp. 69-73
Chapter 16. Interpretation, pp. 75-77
Chapter 17. Conclusion, pp. 79-81


      Cardiology Research and Clinical Developments
   Binding: Softcover
   Pub. Date: 2010
   Pages: 6 x 9, 99pp.
   ISBN: 978-1-60876-788-5
   Status: AV
Status Code Description
AN Announcing
FM Formatting
PP Page Proofs
FP Final Production
EP Editorial Production
PR At Prepress
AP At Press
AV Available
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Cardiovascular Signals in Diabetes Mellitus: A New Tool to Detect Autonomic Neuropathy