Heart rate dynamics before spontaneous onset of ventricular fibrillation in patients with healed myocardial infarcts

The traditional methods of analyzing heart rate (HR) variability have failed to predict imminent ventricular fibrillation (VF). We sought to determine whether new methods of analyzing RR interval variability based on nonlinear dynamics and fractal analysis may help to detect subtle abnormalities in...

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Veröffentlicht in:The American journal of cardiology Jg. 83; H. 6; S. 880 - 884
Hauptverfasser: Mäkikallio, Timo H, Koistinen, Juhani, Jordaens, Luc, Tulppo, Mikko P, Wood, Nicholas, Golosarsky, Boris, Peng, Chung-Kang, Goldberger, Ary L, Huikuri, Heikki V
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Legacy CDMS Elsevier Inc 15.03.1999
Elsevier
Elsevier Limited
Schlagworte:
Aged
Biological and medical sciences
Cardiac arrhythmia
Cardiac Pacing, Artificial
Cardiology
Cardiology. Vascular system
Case-Control Studies
Coronary heart disease
Electrocardiography, Ambulatory
Female
Fractals
Heart
Heart attacks
Heart Rate
Humans
Life Sciences (General)
Male
Medical sciences
Middle Aged
Myocardial Infarction - complications
Nonlinear Dynamics
Regression Analysis
Retrospective Studies
Ventricular Fibrillation - diagnosis
Ventricular Fibrillation - etiology
Ventricular Fibrillation - physiopathology
Support, U.s. Gov't, Non-P.h.s
Human
Heart Rate
Support, Non-U.s. Gov't
Nasa Discipline Cardiopulmonary
Myocardial Infarction/complications
Support, U.s. Gov't, P.h.s
Middle Aged
Non-Nasa Center
Male
Fractals
Cardiac Pacing, Artificial
Ventricular Fibrillation/diagnosis/etiology/physiopathology
Case-Control Studies
Regression Analysis
Female
Retrospective Studies
Aged
Nonlinear Dynamics
Electrocardiography, Ambulatory
Prognosis
Arrhythmia
Infarct
Variability
Cardiovascular disease
Coronary heart disease
Myocardial disease
Excitability disorder
Ventricular fibrillation
Heart rate
Heart disease
Myocardium
Complication
NASA Discipline Cardiopulmonary
Non-NASA Center
ISSN:0002-9149, 1879-1913
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Zusammenfassung:The traditional methods of analyzing heart rate (HR) variability have failed to predict imminent ventricular fibrillation (VF). We sought to determine whether new methods of analyzing RR interval variability based on nonlinear dynamics and fractal analysis may help to detect subtle abnormalities in RR interval behavior before the onset of life-threatening arrhythmias. RR interval dynamics were analyzed from 24-hour Holter recordings of 15 patients who experienced VF during electrocardiographic recording. Thirty patients without spontaneous or inducible arrhythmia events served as a control group in this retrospective case control study. Conventional time- and frequency-domain measurements, the short-term fractal scaling exponent (α) obtained by detrended fluctuation analysis, and the slope (β) of the power-law regression line (log power − log frequency, 10 −4 −10 −2 Hz) of RR interval dynamics were determined. The short-term correlation exponent α of RR intervals (0.64 ± 0.19 vs 1.05 ± 0.12; p <0.001) and the power-law slope β (−1.63 ± 0.28 vs −1.31 ± 0.20, p <0.001) were lower in the patients before the onset of VF than in the control patients, but the SD and the low-frequency spectral components of RR intervals did not differ between the groups. The short-term scaling exponent performed better than any other measurement of HR variability in differentiating between the patients with VF and controls. Altered fractal correlation properties of HR behavior precede the spontaneous onset of VF. Dynamic analysis methods of analyzing RR intervals may help to identify abnormalities in HR behavior before VF.
Bibliographie:CDMS
Legacy CDMS
ISSN: 0002-9149
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ISSN:0002-9149
1879-1913
DOI:10.1016/S0002-9149(98)01068-6