Abnormalities in Beat-to-Beat Dynamics of Heart Rate Before the Spontaneous Onset of Life-Threatening Ventricular Tachyarrhythmias in Patients With Prior Myocardial Infarction

Huikuri, Heikki V.; Seppänen, Tapio; Koistinen, M. Juhani; Airaksinen, Juhani; Ikäheimo, Markku J.; Castellanos, Agustín; Myerburg, Robert J.

doi:10.1161/01.cir.93.10.1836

Cited by 227 publications

(158 citation statements)

References 31 publications

Supporting

Mentioning

148

Contrasting

Unclassified

Order By: Relevance

“…Huikuri et al used both 24-hour and hourly Poincaré plots to compare post-MI patients with either recorded ventricular tachycardia (VT) or VT inducible on EP study and post-MI patients who had neither with age-and gendermatched healthy controls (18). All of the VT patients had abnormal plots, which became more abnormal during the 1-hour period before the onset of VT. Complex patterns were seen in many VT patients, but in none of the other two groups.…”

Section: Discussionmentioning

confidence: 99%

Development of more erratic heart rate patterns is associated with mortality post–myocardial infarction

Stein

Domitrovich

2008

Journal of Electrocardiology

View full text Add to dashboard Cite

Cardiac patients often have sinus arrhythmia of non-respiratory origin [erratic sinus rhythm" (ESR)]. ESR was quantified using hourly Poincaré and power spectral HRV plots from normal-to-normal interbeat intervals (N-Ns) and hourly values of the short-term fractal scaling exponent and correlations of N-Ns in N=60 non-survivors and N=66 randomly-selected survivors in the Cardiac Arrhythmia Suppression Trial. Hours were coded (ABN) as normal (0), borderline (0.5) or ESR (1). T-tests compared ABN for N=2413 paired hours at baseline and on therapy. ABN was higher in nonsurvivors (0.38 ± 0.44 vs. 0.28 ± 0.40, baseline and 0.51 ± 0.45 vs. 0.34 ± 0.43, on therapy, p<0.001). Increased ABN with treatment was greater in non-survivors. Normal hours at baseline (RR=0.77, 095% CI=0.62−0.96, p=0.018) and on treatment (RR=0.47, 95%CI=0.39−0.58) were significantly associated with decreased mortality compared to ESR. Quantification of ESR may identify more vulnerable patients or help monitor the effects of pharmacological treatment. Keywordsheart rate; risk factor; mortality; post-MI; anti-arrhythmic The analysis of heart rate variability (HRV) provides information about cardiac autonomic function. However, we have found that many older subjects and patients with cardiovascular disease have an increased beat-to-beat variability that is irregular and does not reflect underlying respiratory sinus arrhythmia (1). We have called this erratic rhythm. The presence of erratic rhythm, which is frequently episodic, increases values for short-term HRV indices such as rMSSD [root mean square of successive differences of normal-to-normal (N-N) interbeat intervals in ms], pNN50 [the % of N-N intervals >50 ms different from the previous interval) and high frequency power (the amount of variance in N-N intervals at respiratory frequencies, i.e., 0.15−0.4 Hz) that quantify beat-to-beat variability. Thus, in the presence of erratic rhythm, increased short-term HRV does not, as it does for younger people, necessarily reflect greater parasympathetic control of heart rate. A high prevalence of erratic rhythm may also explain why HRV measures that are believed to reflect parasympathetic function have relatively little predictive value for outcomes. At the same time, some "non-linear" HRV measures like the short-term fractal scaling exponent, (DFA1), and (SD12), the ratio of the axes of an ellipse fitted to the Poincaré plot do capture the presence of erratic rhythm (2,3).

show abstract

Section: Discussionmentioning

confidence: 99%

Development of more erratic heart rate patterns is associated with mortality post–myocardial infarction

Stein

Domitrovich

2008

Journal of Electrocardiology

View full text Add to dashboard Cite

show abstract

“…The HR variability analysis techniques have been described elsewhere. 5,13,14,18,19 The methods are briefly described here.…”

Section: Ambulatory Ecg Recordingsmentioning

confidence: 99%

“…The quantitative 2-dimensional analysis of these plots has been described in detail previously. 18 Briefly, scattergrams of successive R-R intervals were plotted for the entire 24-hour period, and the SD of instantaneous R-R interval variability and the SD of continuous variability (SD2) were then analyzed…”

Section: Poincaré Plot Analysismentioning

confidence: 99%

Fractal Correlation Properties of R-R Interval Dynamics and Mortality in Patients With Depressed Left Ventricular Function After an Acute Myocardial Infarction

Huikuri

Mäkikallio²,

Peng³

et al. 2000

Circulation

Self Cite

592

475

View full text Add to dashboard Cite

MD; for the DIAMOND Study GroupBackground-Preliminary data suggest that the analysis of R-R interval variability by fractal analysis methods may provide clinically useful information on patients with heart failure. The purpose of this study was to compare the prognostic power of new fractal and traditional measures of R-R interval variability as predictors of death after acute myocardial infarction. Methods and Results-Time and frequency domain heart rate (HR) variability measures, along with short-and long-term correlation (fractal) properties of R-R intervals (exponents ␣ 1 and ␣ 2 ) and power-law scaling of the power spectra (exponent ␤), were assessed from 24-hour Holter recordings in 446 survivors of acute myocardial infarction with a depressed left ventricular function (ejection fraction Յ35%). During a meanϮSD follow-up period of 685Ϯ360 days, 114 patients died (25.6%), with 75 deaths classified as arrhythmic (17.0%) and 28 as nonarrhythmic (6.3%) cardiac deaths. Several traditional and fractal measures of R-R interval variability were significant univariate predictors of all-cause mortality. Reduced short-term scaling exponent ␣ 1 was the most powerful R-R interval variability measure as a predictor of all-cause mortality (␣ 1 Ͻ0.75, relative risk 3.0, 95% confidence interval 2.5 to 4.2, PϽ0.001). It remained an independent predictor of death (PϽ0.001) after adjustment for other postinfarction risk markers, such as age, ejection fraction, NYHA class, and medication. Reduced ␣ 1 predicted both arrhythmic death (PϽ0.001) and nonarrhythmic cardiac death (PϽ0.001). Conclusions-Analysis

show abstract

“…We find applications of the P oincaré plot in diverse fields such as astronomy, geophysics, meteorology, mathematical biology and medicine [Ott, 1993]. In medicine it was mainly used in HRV analyses [Woo et al, 1994;Huikuri et al, 1996]. The P oincaré plot is on the one hand a visual technique where the human eye can recognize different patterns, and on the other hand a quantitative one.…”

Section: Further Nonlinear Measuresmentioning

confidence: 99%

“…There are some parameters describing the shape of the plot. A ball-like or stick-like shape in the P oincaré plot has been linked to an adverse prognosis [Woo et al, 1994;Huikuri et al, 1996]. SD 1 and SD 2 visualized in Fig.…”

Section: Further Nonlinear Measuresmentioning

confidence: 99%

Nonlinear Methods of Cardiovascular Physics and Their Clinical Applicability

Wessel

Malberg²,

Bauernschmitt

et al. 2007

Int. J. Bifurcation Chaos

102

107

View full text Add to dashboard Cite

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

show abstract

Abnormalities in Beat-to-Beat Dynamics of Heart Rate Before the Spontaneous Onset of Life-Threatening Ventricular Tachyarrhythmias in Patients With Prior Myocardial Infarction

Cited by 227 publications

References 31 publications

Development of more erratic heart rate patterns is associated with mortality post–myocardial infarction

Development of more erratic heart rate patterns is associated with mortality post–myocardial infarction

Fractal Correlation Properties of R-R Interval Dynamics and Mortality in Patients With Depressed Left Ventricular Function After an Acute Myocardial Infarction

Nonlinear Methods of Cardiovascular Physics and Their Clinical Applicability

Contact Info

Product

Resources

About