Risk evaluation of diabetes mellitus by relation of chaotic globals to HRV

Abstract

This study's aim is to analyze heart rate dynamics in subjects with diabetes by measures of heart rate variability (HRV). The correlation of chaotic global parameters in the two cohorts is able to assess the probability of cardiac failure and other dynamical diseases. Adults (46) were divided into two equal groups. The autonomic evaluation consisted of measuring HRV for 30 min in supine position in absence of any physical, sensory, or pharmacological stimuli. Chaotic global parameters are able to statistically determine which series of electrocardiograph interpeak intervals in short time-series are diabetic and which are not. The chaotic forward parameter that applies all three parameters is suggested to be the most appropriate and robust algorithm. This was decided after tests for normality; followed by one-way analysis of variance (ANOVA1); (P < 0.09) and Kruskal–Wallis technique (P < 0.03). Principal component analysis implied two components represent 99.8% of total variance. Therefore, diabetes is a disease which reduces the chaotic response and, as such may be termed a dynamical condition such as are cardiac arrest, asthma, and epilepsy.