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Correlation dimension analysis of heart rate variability in patients with dilated cardiomyopathy

Raúl Carvajal1, Niels Wessel, Montserrat Vallverdú

  • 1Faculty of Computer Science, University of Sinaloa, 82017 Mazatlan, Mexico.

Computer Methods and Programs in Biomedicine
|April 26, 2005
PubMed

Insights

Correlation dimension analysis of heart rate variability (HRV) revealed significantly lower HRV complexity in dilated cardiomyopathy (DCM) patients compared to healthy controls. DCM patients also lost the normal day-night variation in HRV complexity.

Area of Science:

  • Cardiology
  • Nonlinear Dynamics
  • Biomedical Engineering

Background:

  • Dilated cardiomyopathy (DCM) is a severe heart condition affecting heart muscle function.
  • Heart rate variability (HRV) analysis offers insights into cardiac autonomic regulation.
  • Nonlinear methods, like correlation dimension (CD), can reveal complex dynamics in physiological signals.

Purpose of the Study:

  • To investigate the complexity of heart rate variability (HRV) in patients with dilated cardiomyopathy (DCM) using correlation dimension (CD) analysis.
  • To determine if CD analysis can differentiate between DCM patients and healthy individuals.
  • To explore the impact of circadian rhythms on HRV complexity in DCM.

Main Methods:

  • A correlation dimension (CD) analysis was applied to 24-hour RR time series data from 55 DCM patients and 55 healthy controls.
  • RR time series were segmented into 10,000 beats for CD calculation.
  • The influence of time delay (lag) on CD calculation was assessed, with lag values of 5 or greater showing good group discrimination (p<0.005).

Main Results:

  • CD values were significantly lower in DCM patients (8.4±1.9) compared to healthy controls (9.5±1.9).
  • Healthy individuals exhibited a circadian rhythm in HRV complexity, with higher CD values at night (10.6±1.8) than during the day (9.2±1.9).
  • DCM patients showed no significant difference in CD values between day (8.8±2.4) and night (8.9±2.1), indicating a loss of circadian rhythm.

Conclusions:

  • Correlation dimension analysis of HRV is a sensitive method for detecting altered cardiac autonomic regulation in DCM.
  • Reduced HRV complexity and the loss of circadian rhythm in DCM patients suggest impaired autonomic function.
  • These findings highlight the potential of nonlinear HRV analysis as a diagnostic or prognostic tool for DCM.

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