NDLI: Heart rate variability and nonlinear dynamic analysis in patients with stress-induced cardiomyopathy

Content Provider	Springer Nature Link
Author	Krstacic, Goran Parati, Gianfranco Gamberger, Dragan Castiglioni, Paolo Krstacic, Antonija Steiner, Robert
Copyright Year	2012
Abstract	Complexity-based analyses may quantify abnormalities in heart rate variability (HRV). The aim of this study was to investigate the clinical and prognostic significances of dynamic HRV changes in patients with stress-induced cardiomyopathy Takotsubo syndrome (TS) by means of linear and nonlinear analysis. Patients with TS were included in study after complete noninvasive and invasive cardiovascular diagnostic evaluation and compared to an age and gender matched control group of healthy subjects. Series of R–R interval and of ST–T interval values were obtained from 24-h ECG recordings after digital sampling. HRV analysis was performed by ‘range rescaled analysis’ to determine the Hurst exponent, by detrended fluctuation analysis to quantify fractal long-range correlation properties, and by approximate entropy to assess time-series predictability. Short- and long-term fractal-scaling exponents were significantly higher in patients with TS in acute phases, opposite to lower approximate entropy and Hurst exponent, but all variables normalized in a few weeks. Dynamic HRV analysis allows assessing changes in complexity features of HRV in TS patients during the acute stage, and to monitor recovery after treatment, thus complementing traditional ECG and clinically analysis.
Starting Page	1037
Ending Page	1046
Page Count	10
File Format	PDF
ISSN	01400118
Journal	Medical and Biological Engineering and Computing
Volume Number	50
Issue Number	10
e-ISSN	17410444
Language	English
Publisher	Springer-Verlag
Publisher Date	2012-08-19
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Heart rate variability Nonlinear dynamics Chaos theory Stress-induced cardiomyopathy Takotsubo syndrome Human Physiology Computer Applications Imaging Radiology Biomedical Engineering
Content Type	Text
Resource Type	Article
Subject	Biomedical Engineering Computer Science Applications

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