Prediction of sudden cardiac death by fractal analysis of heart rate variability in elderly subjects

Mäkikallio, Timo H.; Huikuri, Heikki V.; Mäkikallio, Anne; Sourander, L.; Mitrani, Raul D.; Castellanos, Agustín; Myerburg, Robert J.

doi:10.1016/s0735-1097(01)01171-8

Cited by 214 publications

(163 citation statements)

References 28 publications

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“…It is noteworthy that the longer-term (alpha 2) rather than the short-term fractal component (alpha 1) showed predictive value for all-cause mortality. This result contrasts with most previous studies reporting that a short-term fractal component was a better predictor in different patient populations [1][2][3]. It should also be kept in mind that in this study, a predictive value was found for alpha 2E, corresponding to the last 10rain of ambulatory ECG monitoring, when deep breathing was repeated in a supine position.…”

Section: Discussioncontrasting

confidence: 99%

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Fractal analysis of heart rate variability and mortality in elderly community-dwelling people — Longitudinal Investigation for the Longevity and Aging in Hokkaido County (LILAC) study

Hotta

Otsuka

Murakami³

et al. 2005

Biomedicine & Pharmacotherapy

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Aim-Fractal analysis of heart rate (HR) variability (HRV) has been used as a new approach to evaluate the risk of mortality in various patient groups. Aim of this study is to examine the prognostic power of detrended fluctuation analysis (DFA) and traditional time-and frequency-domain analyses of HR dynamics as predictors of mortality among elderly people in a community.Methods-We examined 298 people older than 75 years (average age: 79.6 years) and 1-h ambulatory ECG was monitored. During the last 10 min, deep respiration (6-s expiration and 4-s inspiration) was repeated six times in a supine position. Time-domain and frequency-domain measures were determined by the maximum entropy method. Scaling exponents of short-term (<11 beats, alpha 1) and longer-term (>11 beats, alpha 2) were determined by the DFA method. Six estimates, obtained from 10-min segments, were averaged to derive mean values for the entire recording span. These average values were denoted Alpha 1 and Alpha 2, estimates obtained during the first 10-min segment Alpha 1 S and Alpha 2 S, and those during the last 10-min segment Alpha 1E and Alpha 2E, respectively. The LILAC study started on July 25, 2000 and ended on November Results-Gender, age and Alpha 2E showed a statistically significant association with all-cause mortality. In univariate analyses, gender was significantly associated with all-cause mortality, being associated with a RR of 3.59 (P = 0.00136). Age also significantly predicted all-cause mortality and a 5-year increase in age was associated with a RR of 1.49 (P = 0.01809). The RR of developing allcause mortality predicted by a 0.2-unit increase in Alpha 2E was 0.58 (P = 0.00390). Other indices of fractal analysis of HRV did not have predictive value. In multivariate analyses, when both Alpha 2E and gender were used as continuous variables in the same model, Alpha 2E remained significantly associated with the occurrence of all-cause mortality (P = 0.02999). After adjustment for both gender and age, a 0.2-unit increase in Alpha 2E was associated with a RR of 0.61 (95% CI: 0.424).90, P = 0.01151).Conclusion-An intermediate-term fractal-like scaling exponent of RR intervals was a better predictor of death than the traditional measures of HR variability in elderly community-dwelling people. It is noteworthy that the longer-term (alpha 2) rather than the short-term fractal component (alpha 1) showed predictive value for all-cause mortality, which suggests that an increase in the randomness of intermediate-term HR behavior may be a specific marker of neurohumoral and sympathetic activation and therefore may also be associated with an increased risk of mortality.

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Section: Discussioncontrasting

confidence: 99%

“…Fractal analysis of heart rate (HR) variability (HRV) has been used as a new approach to evaluate the risk of mortality in various patient groups [1][2][3]. Several new methods have been developed to quantify complex HR dynamics and to complement the conventional measures of HR variability.…”

Section: Introductionmentioning

confidence: 99%

Fractal analysis of heart rate variability and mortality in elderly community-dwelling people — Longitudinal Investigation for the Longevity and Aging in Hokkaido County (LILAC) study

Hotta

Otsuka

Murakami³

et al. 2005

Biomedicine & Pharmacotherapy

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“…Taken together, the evidence supporting an independent prognostic value of fractal HRV in heart failure patients is not very strong. The short-term scaling exponent has also been suggested to be a specific risk marker of cardiac death in the elderly (Mäkikallio et al 2001b). Interestingly, altered short-term fractal-like scaling properties of heart rate dynamics have been observed to precede the spontaneous onset of atrial fibrillation among patients without structural heart disease (Vikman et al 1999).…”

Section: Fractal Measures Of Hrvmentioning

confidence: 99%

Clinical impact of evaluation of cardiovascular control by novel methods of heart rate dynamics

Huikuri

Perkiömäki

Maestri

et al. 2009

Phil. Trans. R. Soc. A.

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Heart rate variability (HRV) has been conventionally analysed with time-and frequencydomain methods, which measure the overall magnitude of RR interval fluctuations around its mean value or the magnitude of fluctuations in some predetermined frequencies. Analysis of heart rate dynamics by novel methods, such as heart rate turbulence after ventricular premature beats, deceleration capacity of heart rate and methods based on chaos theory and nonlinear system theory, have gained recent interest. Recent observational studies have suggested that some indices describing nonlinear heart rate dynamics, such as fractal scaling exponents, heart rate turbulence and deceleration capacity, may provide useful prognostic information in various clinical settings and their reproducibility may be better than that of traditional indices. For example, the short-term fractal scaling exponent measured by the detrended fluctuation analysis method has been shown to predict fatal cardiovascular events in various populations. Similarly, heart rate turbulence and deceleration capacity have performed better than traditional HRV measures in predicting mortality in post-infarction patients. Approximate entropy, a nonlinear index of heart rate dynamics, which describes the complexity of RR interval behaviour, has provided information on the vulnerability to atrial fibrillation. There are many other nonlinear indices which also give information on the characteristics of heart rate dynamics, but their clinical usefulness is not as well established. Although the concepts of nonlinear dynamics, fractal mathematics and complexity measures of heart rate behaviour, heart rate turbulence, deceleration capacity in relation to cardiovascular physiology or various cardiovascular events are still far away from clinical medicine, they are a fruitful area for research to expand our knowledge concerning the behaviour of cardiovascular oscillations in normal healthy conditions as well as in disease states.

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“…Individuals with high levels of anxiety have reduced heart rate variability compared with normal subjects, 17 which has been shown to predict SCD in the elderly 18 and in patients with heart failure. 19 Also, acute attacks of anxiety or mental stress may trigger episodes of fatal ventricular arrhythmias in susceptible patients. It is well documented that acute increases in the incidence of SCD can occur in populations suffering acute psychological stressors such as …”

Section: Circulation February 1 2005mentioning

confidence: 99%

Phobic Anxiety and Risk of Coronary Heart Disease and Sudden Cardiac Death Among Women

Albert¹,

Chae²,

Rexrode³

2005

ACC Current Journal Review

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Prediction of sudden cardiac death by fractal analysis of heart rate variability in elderly subjects

Abstract: Altered short-term fractal scaling properties of HR indicate an increased risk for cardiac mortality, particularly sudden cardiac death, in the random population of elderly subjects.

Cited by 214 publications

References 28 publications

Fractal analysis of heart rate variability and mortality in elderly community-dwelling people — Longitudinal Investigation for the Longevity and Aging in Hokkaido County (LILAC) study

Fractal analysis of heart rate variability and mortality in elderly community-dwelling people — Longitudinal Investigation for the Longevity and Aging in Hokkaido County (LILAC) study

Clinical impact of evaluation of cardiovascular control by novel methods of heart rate dynamics

Phobic Anxiety and Risk of Coronary Heart Disease and Sudden Cardiac Death Among Women

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