Assessment of autonomic dysfunction in patients with type 2 diabetes using reactive hyperemia

Hsien Tsai Wu, Po Chun Hsu, Cheuk Kwan Sun, Hou Jun Wang, Cyuan Cin Liu, Hong Ruei Chen, An Bang Liu, Chieh Ju Tang, Men Tzung Lo

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

It is known that aging and type 2 diabetes mellitus contribute to atherosclerosis and autonomic dysfunction. By using the air pressure sensing system (APSS), peak-peak intervals (PPIs) of wrist arterial waveforms from baseline and reactive hyperemia (RH) were obtained. Through frequency domain analysis of heart rate variability (HRV) and nonlinear Poincaré method, the HRV of healthy young individuals (Group 1, n=25), healthy upper middle-aged individuals (Group 2, n=22), and patients with type 2 diabetes (Group 3, n=28) were assessed. By using the standard deviation (SD) of the instantaneous PPI variability (SD1)/the SD of the long PPI variability (SD2) ratio (SSR), PPIs of the same individuals before and after RH induction were compared. Reduced SSR1-10 was noted only in patients with diabetes. Moreover, a significient correlation between SSR1-10 and endothelial function was observed in all subjects (r=0.290, p=0.033) after RH. However, no correlation with low-frequency to high-frequency power ratio (LHR) was noted before and after RH. In conclusion, according to our results, campared to the baseline, there were more significant changes of SSR1-10 after RH in patients with diabetes; and, a significient correlation between SSR1-10 and endothelial function at the moment of RH was noted.

Original languageEnglish
Pages (from-to)9-17
Number of pages9
JournalJournal of Theoretical Biology
Volume330
DOIs
StatePublished - 7 Aug 2013

Keywords

  • Autonomic dysfunction
  • Poincaré method
  • Pulse rate variability
  • SD1/SD2 ratio (SSR)

Fingerprint

Dive into the research topics of 'Assessment of autonomic dysfunction in patients with type 2 diabetes using reactive hyperemia'. Together they form a unique fingerprint.

Cite this