Fractal analysis and time- and frequency-domain measures of heart rate variability as predictors of mortality in patients with heart failure

Mäkikallio, Timo H.; Huikuri, Heikki V.; Hintze, Ulrik; Videbæk, J; Mitrani, Raul D.; Castellanos, Agustín; Myerburg, Robert J.; Møller, Mogens

doi:10.1016/s0002-9149(00)01312-6

Cited by 223 publications

(171 citation statements)

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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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“…Also, several recent observations have emerged linking unfavourable cardiovascular outcomes to cardiac dysautonomia in various pathological conditions that affect the autonomic nervous system [47][48][49][50][51][52][53] . …”

Section: Cardiac Autonomic Nervous System In Chagas Diseasementioning

confidence: 99%

“…However, this was the sole index evaluated in this study and was derived from series of ECG R-R intervals employing the 24h Holter monitoring, which methodologically show some restrictions limiting the heart rate variability analysis and interpretation. To this regard, it should be reinforced that there are abundant data supporting the prognostic significance and the role as risk marker of some classical linear and newer non-linear measures of heart variability in different clinical conditions other than Chagas disease [48][49][50][51][52]69,71 . But, several factors influence the prognostic value of heart rate variability measurements when they are used in risk stratification, which among the more important are: a) the type and combination of indexes, b) the nature of the autonomic modulation that the indexes reflect, if overall or parasympathetic or sympathetic exclusive or balanced one, c) the circadian rhythm of heart rate variability, d) the epoch of evaluation during the development of the clinical, functional or pathological condition analysed, e) the severity of left ventricular dysfunction, f) the method employed to achieve, process and editing the ECG R-R intervals series, if derived from 5min short-term recording in controlled experimental setting, or long-term ambulatory 24h Holter recording under uncontrolled interfering factors and non-stationary data series, g) the nature of the selected adverse outcome 50,51,69,71 .…”

Section: Dysautonomic Arrhythmogenesis -A Working Hypothesismentioning

confidence: 99%

Insights into the clinical and functional significance of cardiac autonomic dysfunction in Chagas disease

Junqueira Junior

2012

Rev. Soc. Bras. Med. Trop.

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INTRODUCTION: Exclusive or associated lesions in various structures of the autonomic nervous system occur in the chronic forms of Chagas disease. In the indeterminate form, the lesions are absent or mild, whereas in the exclusive or combined heart and digestive disease forms, they are often more pronounced. Depending on their severity these lesions can result mainly in cardiac parasympathetic dysfunction but also in sympathetic dysfunction of variable degrees. Despite the key autonomic effect on cardiovascular functioning, the pathophysiological and clinical significance of the cardiac autonomic dysfunction in Chagas disease remains unknown. METHODS: Review of data on the cardiac autonomic dysfunction in Chagas disease and their potential consequences, and considerations supporting the possible relationship between this disturbance and general or cardiovascular clinical and functional adverse outcomes. RESULTS: We hypothesise that possible consequences that cardiac dysautonomia might variably occasion or predispose in Chagas disease include: transient or sustained arrhythmias, sudden cardiac death, adverse overall and cardiovascular prognosis with enhanced morbidity and mortality, an inability of the cardiovascular system to adjust to functional demands and/or respond to internal or external stimuli by adjusting heart rate and other hemodynamic variables, and immunomodulatory and cognitive disturbances. CONCLUSIONS: Impaired cardiac autonomic modulation in Chagas disease might not be a mere epiphenomenon without significance. Indirect evidences point for a likely important role of this alteration as a primary predisposing or triggering cause or mediator favouring the development of subtle or evident secondary cardiovascular functional disturbances and clinical consequences, and influencing adverse outcomes.

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“…Altered fractal correlation properties have been associated with mortality in heart failure patients [Ho et al, 1997]. The investigation of a relatively large population with CHF suggests that reduced short-term scaling exponent is closely related to the risk of mortality [Makikallio et al, 2001a]. The short-term scaling exponent also has been suggested to be a specific risk marker of cardiac death in the elderly [Makikallio et al, 2001b].…”

Section: Further Applicationsmentioning

confidence: 99%

Nonlinear Methods of Cardiovascular Physics and Their Clinical Applicability

Wessel

Malberg²,

Bauernschmitt

et al. 2007

Int. J. Bifurcation Chaos

102

107

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In this tutorial we present recently developed nonlinear methods of cardiovascular physics and show their potentials to clinically relevant problems in cardiology. The first part describes methods of cardiovascular physics, especially data analysis and modeling of noninvasively measured biosignals, with the aim to improve clinical diagnostics and to improve the understanding of cardiovascular regulation. Applications of nonlinear data analysis and modeling tools are various and outlined in the second part of this tutorial: monitoring-, diagnosis-, course and mortality prognoses as well as early detection of heart diseases. We show, that these data analyses and modeling methods lead to significant improvements in different medical fields.Keywords: Cardiovascular physics; nonlinear data analysis and modeling; heart rate and blood pressure variability; baroreflex sensitivity. List of Abbreviations

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Fractal analysis and time- and frequency-domain measures of heart rate variability as predictors of mortality in patients with heart failure

Cited by 223 publications

References 20 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

Insights into the clinical and functional significance of cardiac autonomic dysfunction in Chagas disease

Nonlinear Methods of Cardiovascular Physics and Their Clinical Applicability

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