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

• Published in: The American journal of cardiology Vol. 83; no. 6; pp. 880 - 884
• Main Authors: 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
• Language: English
• Published: Legacy CDMS Elsevier Inc 15-03-1999; Elsevier; Elsevier Limited
• Subjects: 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; Space life sciences; Ventricular Fibrillation - diagnosis; Ventricular Fibrillation - etiology; Ventricular Fibrillation - physiopathology; Non-Nasa Center; Nasa Discipline Cardiopulmonary; Human; 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
• DOI: 10.1016/S0002-9149(98)01068-6

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.