Nonlinear analysis of heart rate dynamics in hyperthyroidism

Jin Long Chen, Yin Jiun Tseng, Hung Wen Chiu, Tzu Chien Hsiao, Woei Chyn Chu

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

Studies on the physiology of the cardiovascular system suggested that the generation of the heart rate signal is governed by nonlinear chaotic dynamics. No study investigated the nonlinear dynamics of heart rate in hyperthyroidism. We examined whether the heart rate dynamics of hyperthyroid patients is different from normal controls by the nonlinear analysis of heart rate variability (HRV) with correlation dimension (CD). Thirty-three hyperthyroid Graves' disease patients (30 females and 3 males; age 31 ± 1 years, means ± SE) and 33 sex-, age-, and body mass index-matched normal controls were recruited to receive one-channel electrocardiogram recording for 30 min. The CD, an index of complexity, was computed from the sequence of normal R-R intervals by the Grassberger and Procaccia algorithm. Compared to the normal controls, the hyperthyroid patients showed significant reductions (P <0.001) in the mean R-R interval (hyperthyroid 616 ± 15 versus control 868 ± 16 ms), the standard deviation of R-R intervals (25 ± 2 versus 54 ± 4 ms) and CD (5.02 ± 0.11 versus 6.42 ± 0.16). Our study demonstrated for the first time that hyperthyroid patients and normal controls could be distinguished by CD analysis of HRV. In addition, the decreased CD in hyperthyroid patients implies reduced complexity and impaired tolerance to cardiovascular stresses in hyperthyroidism. This finding helps to explain exercise intolerance and irritability manifested by the hyperthyroid patients.

Original languageEnglish
Article number008
Pages (from-to)427-437
Number of pages11
JournalPhysiological Measurement
Volume28
Issue number4
DOIs
Publication statusPublished - Apr 1 2007

Keywords

  • Chaos
  • Complexity
  • Correlation dimension
  • Heart rate variability
  • Hyperthyroidism
  • Nonlinear dynamics

ASJC Scopus subject areas

  • Physiology (medical)
  • Biophysics
  • Physiology
  • Biomedical Engineering

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