Cardiovascular Engineering and Technology

, Volume 1, Issue 4, pp 290–298 | Cite as

Segmented Symbolic Dynamics for Risk Stratification in Patients with Ischemic Heart Failure

  • Andreas Voss
  • Rico Schroeder
  • Pere Caminal
  • Montserrat Vallverdú
  • Helena Brunel
  • Iwona Cygankiewicz
  • Rafael Vázquez
  • Antoni Bayés de Luna
Article

Abstract

Chronic heart failure (CHF) is recognized as major and escalating public health problem. Approximately 69% of CHF patients suffer from cardiac death within 5 years after the initial diagnosis. Until now, no generally accepted ECG risk predictors in CHF patients are available. The objective of this study was to investigate the suitability of the new developed non-linear method segmented symbolic dynamics (SSD) for risk stratification in patients with ischemic cardiomyopathy (ICM) in comparison to other indices from time and frequency domain, non-linear dynamics, and clinical markers. Twenty-four hour Holter ECGs were recorded from 256 ICM patients. Heart rate variability (HRV) was analyzed from the filtered beat-to-beat interval time series. For calculating SSD, NN interval time series were segmented in 1 min overlapping windows with a window length of 30 min. For each window a symbol- and word-transformation was performed and probabilities of word type occurrences were calculated. Several indices from frequency domain and non-linear dynamics revealed high univariate significant differences (p < 0.01) discriminating low (n = 221) and high risk ICM patients (n = 35). For multivariate risk stratification in ICM patients the two optimal mixed parameter sets consisting of either two clinical and three non-clinical indices (two from SSD) or three clinical and two non-clinical indices (one from SSD) achieved 74 and 75% sensitivity and 79 and 76% specificity, respectively. These results suggest that the new SSD enhances considerably risk stratification in ICM patients. The multivariate analysis including SSD leads to an optimum accuracy of 81%.

Keywords

Risk stratification Non-linear dynamics Cardiovascular diseases Symbolic dynamics 

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Copyright information

© Biomedical Engineering Society 2010

Authors and Affiliations

  • Andreas Voss
    • 1
  • Rico Schroeder
    • 1
  • Pere Caminal
    • 2
  • Montserrat Vallverdú
    • 2
  • Helena Brunel
    • 2
  • Iwona Cygankiewicz
    • 3
  • Rafael Vázquez
    • 4
  • Antoni Bayés de Luna
    • 5
  1. 1.Department of Medical Engineering and BiotechnologyUniversity of Applied Sciences JenaJenaGermany
  2. 2.Biomedical Engineering Research CentreUniversitat Politècnica de Catalunya - Barcelona TechBarcelonaSpain
  3. 3.Department of ElectrocardiologySterling Memorial University Hospital, Medical University of LodzLodzPoland
  4. 4.Servicio de Cardiología, Puerta del Mar University HospitalCádizSpain
  5. 5.Institut Català Ciències Cardiovasculars, Hospital Sant PauBarcelonaSpain

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