No abstract

Detection of subclinical autonomic dysfunction in patients with diabetes mellitus (DM) is of vital importance for risk stratification and subsequent management. Heart rate variability (HRV) analysis is a sensitive tool for assessment of cardiovascular autonomic dysfunction. As the heart is controlled by non-linear deterministic system, the non-linear dynamics measures should be preferred. Recurrence plot (RP) is able to analyse recurrences within system dynamics. The aim of the study was to detect heart rate dysregulation in DM by RP and to ascertain which of the recurrence quantification analysis (RQA) measures are changed in patients with DM compared to control group. We analysed HRV recordings from 17 young patients with type 1 DM and 17 healthy matched control subjects. RQA was performed on RPs with a fixed value of recurrence points percentage. From RQA measures based on diagonal lines, we have found higher percentage of determinism in DM group (P=0.038). Trapping time measure was also higher in DM (P=0.022). RQA revealed changes in dynamics recurrences with reduced complexity of heart rate control in young diabetic patients. As RQA parameters are independent of overall HRV, parameters of RP should be used together with linear HRV parameters for better description of heart rate dysregulation in patients with diabetics.

Multiscale entropy (MSE) analysis provides information about complexity on various time scales. The aim of this study was to test whether MSE is able to detect autonomic dysregulation in young patients with diabetes mellitus (DM). We analyzed heart rate (HR) oscillations, systolic (SBP) and diastolic blood pressure (DBP) signals in 14 patients with DM type 1 and 14 age- and sex-matched healthy controls. SampEn values (scales 1-10) and linear measures were computed. HR: among the linear measures of heart rate variability significant differences between groups were only found for RMSSD (p = 0.043). MSE was significantly reduced on scales 2 and 3 in DM (p = 0.023 and 0.010, respectively). SBP and DBP: no significant differences were detected with linear measures. In contrast, MSE analysis revealed significantly lower SampEn values in DM on scale 3 (p = 0.039 for SBP; p = 0.015 for DBP). No significant correlations were found between MSE and linear measures. In conclusion, MSE analysis of HR, SBP and DBP oscillations is able to detect subtle abnormalities in cardiovascular control in young patients with DM and is independent of standard linear measures.

Obesity is associated with autonomic nervous system dysfunction. The aim of the study was to evaluate baroreflex sensitivity, an indicator of autonomic nervous function, in 20 obese children and adolescents in comparison with 20 age- and sex-matched nonobese subjects. All subjects were examined in the supine position over a period of 50 min. Systolic blood pressure (SBP) and RR intervals were monitored continuously. Baroreflex sensitivity was assessed by cross-spectral analysis of SBP and RR interval oscillations (BRS index) and SBP and heart rate oscillations (BRSf index) within the low frequency range (0.04-0.15 Hz). Sensitivity was determined in 3 time intervals of 3 min each to evaluate changes during rest. The BRS index was significantly lower in obese children and adolescents than in the nonobese control group (p = 0.002). Significant changes in the BRS index over time (p = 0.004) were found only in nonobese subjects. In contrast, the BRSf index increased over time in both groups (p = 0.01), and no significant between-group difference was detected. In conclusion, obese children and adolescents show decreased resting baroreflex sensitivity with less variation compared with nonobese subjects. The BRS and BRSf indices appear to be only partially correlated.