(Circulation. 1999;100:1416-1422.)
© 1999 American Heart Association, Inc.
Clinical Investigation and Reports |
Dynamic Behavior and Autonomic Regulation of Ectopic Atrial Pacemakers
From University of Miami School of Medicine, Miami, Fla (R.D.M., R.J.M., A.C.), and University of Oulu, Department of Medicine, Division of Cardiology, Oulu, Finland (H.V.H., A.-M.P., T.H.M., M.J.K., K.E.J.A.).
Correspondence to Heikki Huikuri, MD, Division of Cardiology, University of Oulu, Kajaanintie 50, 90220 Oulu, Finland. E-mail heikki.huikuri{at}oulu.fi
 |
Abstract |
|---|
 Top Abstract IntroductionMethodsResultsDiscussionReferences |
|---|
Background—Heart rate (HR) variability reflects the neural regulation of normal pacemaker tissue, but the autonomic nervous regulation of abnormal atrial foci originating outside the sinus node has not been well characterized. We compared the HR variability of tachycardias originating from the ectopic foci and the sinus node.
Methods and Results—R-R–interval variability was
analyzed from 24-hour Holter recordings in 12 patients
with incessant ectopic atrial tachycardia (average HR
107±14 bpm), 12 subjects with sinus tachycardia (average
HR 106±9 bpm), and 24 age- and sex-matched subjects with normal sinus
rhythm (average HR 72±8 bpm). Time- and frequency-domain HR
variability measures, along with approximate entropy, short- and
long-term correlation properties of R-R intervals (exponents
1 and 2), and power-law scaling (exponent
ß), were analyzed. Time- and frequency-domain measures of HR
variability did not differ between subjects with ectopic and sinus
tachycardia. Fractal scaling exponents and approximate
entropy were similar in sinus tachycardia and normal sinus
rhythm, but the short-term scaling exponent 1 was
significantly lower in ectopic atrial tachycardia
(0.71±0.16) than in sinus tachycardia (1.16±0.13;
P<0.001) or normal sinus rhythm (1.19±0.11;
P<0.001). Abrupt prolongations in R-R intervals due to
exit blocks from the ectopic foci or instability in beat-to-beat R-R
dynamics were the major reasons for altered short-term HR behavior
during ectopic tachycardias.
Conclusions—HR variability obtained by time- and frequency-domain methods does not differ between ectopic and sinus tachycardias, which suggests that abnormal atrial foci are under similar long-term autonomic regulation as normal pacemaker tissue. Short-term R-R–interval dynamics are altered toward more random behavior in ectopic tachycardia, which may result from a specific autonomic disturbance or an intrinsic abnormality of ectopic atrial pacemakers.
Key Words: tachycardia • arrhythmia • heart rate • intervals
|
Introduction |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
Heart rate (HR) is normally determined by the rate of depolarization of the dominant cardiac pacemaker. Because temporal changes in cardiac interbeat intervals are mediated by phasic vagal and sympathetic outflow, measurement of HR variability from long-term ECG recordings has considerable potential to assess the role of the autonomic nervous system in the regulation of pacemaker tissue.1 2 3 4 5 6 Beginning with the original observations of Akselrod et al1 on the typical spectral patterns of HR variability during normal sinus rhythm, a large amount of data has been published on the characteristics of HR variability in healthy subjects and patients with various cardiac diseases.2 3 4 5 6 Recently, analysis methods based on nonlinear dynamics have been developed to describe the complex behavior of cardiac interbeat intervals.7 8 9 10 11 The studies using these new methods have shown typical self-similar or fractal-like features in the R-R–interval dynamics of normal sinus rhythm9 10 11 12 13 and have also implicated abnormal HR behavior of patients with structural heart disease.10 11 12 13
The neural regulation and dynamics of the richly innervated sinus node are well characterized,1 2 3 4 5 6 9 10 11 12 13 but there is little information on the dynamic behavior of pacemakers originating outside the sinus node. Therefore, we studied the characteristics of HR variability of incessant ectopic atrial tachycardias. We also sought to determine whether there are differences in HR behavior between normal sinus rhythm, sinus tachycardia, and ectopic atrial tachycardia by analyzing the fractal correlation properties and complexity of R-R–interval variability.
|
Methods |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
Patient Population
Inpatients and outpatients of the Oulu University Hospital (n=19) and the University of Miami School of Medicine (n=5) with fast HR in standard 12-lead ECG and in 24-hour ambulatory ECG recordings were included in the study. All patients had elevated HRs observed incidentally (n=3) on a routine examination or brought to attention because of symptoms (n=21) causing referral to a hospital. Twelve patients had ectopic atrial tachycardia (6 women and 6 men, mean age 30±12 years), and 12 had inappropriate sinus tachycardia (9 women and 3 men, mean age 32±8 years). The characteristics of the patients are shown in Tables 1
and 2.
|
|
The control group with normal sinus rhythm consisted of healthy subjects without clinical or echocardiographic evidence of structural heart disease (12 women and 12 men, mean age 34±12 years). These subjects were enrolled from populations described in detail previously14 15 16 and were matched with respect to age and sex to the patients with ectopic atrial tachycardia. All patients and control subjects gave informed consent for 24-hour ECG recordings.
Definitions of Tachycardias
Incessant ectopic atrial tachycardia was defined
according to the following criteria: (1) a resting daytime HR >100
bpm, (2) an average HR of >90 bpm on 24-hour ECG recordings,
and (3) an abnormal p-wave axis and/or abnormal p-wave
morphology in 
2 precordial leads and in 1 bipolar limb lead on a
12-lead ECG. Inappropriate sinus tachycardia was defined as
a resting daytime HR >100 bpm with a normal p-wave morphology and axis
obtained from standard 12-lead ECGs recorded on 2 separate days
and an average HR of >90 bpm on 24-hour ECG recording. None of
the patients had a secondary cause for sinus tachycardia or
ectopic atrial tachycardia. The symptoms and duration of
arrhythmias are shown in Tables 1
and 2.
Electrophysiological Studies
Seven patients with a 12-lead ECG suggesting ectopic atrial
tachycardia and 4 with inappropriate sinus
tachycardia underwent a clinically indicated
electrophysiological study. Quadripolar
catheters (7F) were positioned in the lateral portion of the high right
atrium and the low septal right atrium to record a His bundle
electrogram, the coronary sinus, and the right
ventricular apex. In 4 cases with inappropriate sinus
tachycardia, a "halo" catheter consisting of 10 bipolar
pairs was positioned along the crista terminalis in the right atrium
with the tip of the catheter at the coronary sinus ostium.
Surface leads I, II, and V1 and intracardiac
electrograms, filtered from 30 to 250 Hz, were recorded on an
electrostatic paper at a paper speed of 100 mm/s or in a
computer-based digitized amplifier/recorder system with optical
disk storage (ART Inc).
Detailed mapping and ablation of the ectopic atrial tachycardias were performed with a 7F ablation catheter with a deflectable tip and a 4-mm distal-tip electrode (Mansfield/Webster). The earliest local intracardiac activation in relation to the p-wave on the surface ECG was used to select the target site for ablation. Radiofrequency energy was applied at the appropriate target sites in a range of 20 to 40 W power for 40 to 60 seconds until termination of ectopic atrial tachycardia.
Criteria of incessant ectopic atrial tachycardia during the electrophysiological study were as follows: (1) an endocardial activation sequence inconsistent with a sinus origin; (2) inability to terminate or reset the tachycardia with appropriately timed premature atrial extrastimuli or rapid atrial pacing; (3) exclusion of intra-atrial, AV, and AV nodal reentry; and (4) sudden restoration of sinus rhythm after radiofrequency ablation of the tachycardia. Inappropriate sinus tachycardia was defined by (1) an activation sequence consistent with a sinus origin (ie, earliest endocardial activation in the lateral high right atrium obtained with the halo catheter) and (2) exclusion of reentry by inability to terminate or reset the tachycardia by atrial extrastimuli or rapid atrial pacing.
Ambulatory ECG Recordings
All subjects were monitored for 24 hours with an ambulatory ECG
recorder with modified V1 and
V5 lead placement. All patients and control
subjects were nonmedicated at the time of the 24-hour ECG
recordings and were encouraged to continue with their normal
daily activities during the recordings. The data were sampled
digitally and transferred to a microcomputer for analysis of HR
variability. Before the R-R–interval tachograms were analyzed,
the recordings were edited to eliminate premature ectopic beats
in the sinus tachycardia patients, sinus cycles in the
patients with ectopic atrial tachycardia, and segments with
intermittent AV block. The editing process was performed by printing
full disclosure of the 24-hour ECG recordings at a paper speed
of 8 mm/s. All questionable segments with a change in p-wave
morphology or R-R intervals on full disclosure were then printed at a
paper speed of 25 mm/s to confirm the sinus or ectopic origin of
the beats, respectively. Changes in p-wave morphology or AV block were
noted and marked, and the corresponding R-R intervals were manually
edited from the R-R–interval tachograms before analysis of HR
variability. After the ECG data had been transferred to the
microcomputer, the R-R–interval series were also edited both manually
and automatically from the R-R–interval tachograms. Each R-R–interval
time series was passed through a filter to eliminate premature beats
and artifacts and to replace the filling gaps. Only recordings
with qualified beats for at least a 16-hour period and with >80% of
qualified ectopic or sinus beats, respectively, were included in the
analyses of HR variability. HR variability, by both traditional
and new measures, was analyzed by custom-made analysis
programs described in detail previously.12 13 14 15 16
Time- and Frequency-Domain Analysis of HR
Variability
The time- and frequency-domain measures of HR variability were
analyzed by the methods recommended by the Task Force of the
European Society of Cardiology.5 The SD of
all normal-to-normal R-R intervals (SDNN) and the difference between
the maximum and minimum hourly HR (circadian rhythm) were computed as
standard time-domain measures of HR variability. Spectral power was
quantified both by fast Fourier transform analysis and by
autoregressive analysis in 4 frequency bands15 16 :
<0.0033 Hz (ultralow frequency [ULF]), 0.0033 to 0.04 Hz (very-low
frequency [VLF]), 0.04 to 0.15 Hz (low frequency [LF]), and 0.15 to
0.40 Hz (high frequency [HF]). ULF and VLF spectral components were
computed over the entire recording interval by the fast Fourier
method.16 LF and HF components were computed from the
segments of 512 R-R intervals by the autoregressive method, and the
average values of the entire recording interval were calculated
for these components. The LF and HF components were calculated as both
absolute units and normalized units, which we obtained by dividing the
power of these components by the total variance from which the DC
component had been subtracted and multiplying this value by
100.4
Poincaré Plot Analysis
A Poincaré plot is a diagram in which each R-R interval is
plotted as a function of the previous R-R interval. Both visual
analysis of the graphic display and quantitative
analysis of the plots can be used to describe R-R–interval
dynamics. The quantitative 2D analysis of these plots has been
described in detail previously.15 The scattergrams of
successive R-R intervals were plotted for the entire 24-hour period,
and the SD of instantaneous R-R–interval variability (SD1) and of
continuous variability (SD2) were then analyzed. The shape of
the plot was also classified as complex, torpedo-shaped, or normal, as
described previously.15
Fractal Analysis of R-R–Interval Variability
The power-law relationship of R-R–interval variability was
calculated from the frequency range 10-4 to
10-2 Hz. The point power spectrum was
logarithmically smoothed in the frequency domain and the power
integrated into bins spaced 0.0167 log (Hz) apart. A robust
line-fitting algorithm of log (power) on log (frequency) was then
applied to the power spectrum between 10-4 and
10-2 Hz, and the slope of this line was
calculated (ß). This spectral range was chosen on the basis of
previous observations regarding the linear relationship between log
(power) and log (frequency) in this frequency band in human HR time
series data.10 The details of this method have been
described previously.10 16
The detrended fluctuation analysis technique was used to
quantify the fractal scaling properties of short- and intermediate-term
R-R–interval time series. This method is a modified root-mean-square
analysis of random walk that quantifies the presence or absence
of fractal correlation properties and has been validated for
nonstationary time series.7 In this method, the
root-mean-square fluctuation of integrated and detrended time series is
measured at each observation window and plotted against the size of the
observation window on a log-log scale. The fractal-like signal (1/f
signal spectrum) results in an exponent value of 1 (=1.0). The
details of this method have been described
elsewhere.7 11 13 In the present study, the HR
correlations were defined separately for short-term (<11 beats,
1) and longer-term (>11 beats,
2) R-R–interval data (scaling exponents) on
the basis of the previous finding of a crossover point on the log-log
plot. Both 1 and 2
were analyzed from segments of 8000 R-R intervals and averaged
to obtain mean values for the entire recording period.
Approximate Entropy
Approximate entropy is a measure that quantifies the regularity
of time series. The details of the method used have been described
previously.8 12 The parameters m and r of the
method must be fixed to calculate approximate entropy, and m=2 and
r=20% of the SD of the data sets were chosen on the basis of previous
findings of statistical validity. Approximate entropy values were
computed from 8000 R-R–interval segments and averaged to obtain a mean
value of approximate entropy characterizing the entire
recording.12
Intravenous Atropine
Intravenous atropine was given gradually at a dose
of 0.02 mg/kg to 11 patients with ectopic atrial
tachycardia and 8 patients with inappropriate sinus
tachycardia who gave their informed consent to the atropine
test. HR was continuously recorded at a paper speed of 25 mm/s
until no increase in the average HR was observed during the 2-minute
period. The difference between baseline HR and maximum HR after
atropine was calculated and compared with normal reference values
obtained in previous studies, ie, increase of 20% to 50% over the
control rate.17 18
Statistical Analysis
Results are expressed as mean±SD. Statistical analysis
was performed with 1-way ANOVA with Bonferroni post hoc tests to
compare data between the groups. SPSS for Windows version 7.5 was used
in the analyses. A value of P<0.05 was considered
to indicate statistical significance.
|
Results |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
Time- and Frequency-Domain Measures of HR Variability
Table 3
shows the time- and
frequency-domain measures of HR variability in the 3 study groups. None
of these measures differed between patients with ectopic atrial
tachycardia or sinus tachycardia. However, all
traditional HR variability measures expressed in absolute units,
including measures obtained by quantitative analysis of
Poincaré plots, were reduced in patients with ectopic and sinus
tachycardia compared with subjects with normal sinus rhythm
(see examples in Figure 1). Despite the
reduced overall HR variability, the Poincaré plots showed normal
comet-shaped characteristics in cases with ectopic and inappropriate
tachycardia (Figure 2). The LF/HF ratio or the LF and
HF components analyzed in normalized units did not differ from
normal in either ectopic tachycardia or sinus
tachycardia. There was also no difference between maximum
and minimum HRs (amplitude of the circadian rhythm) between the study
groups (Table 3).
|
|
|
Fractal and Complexity Measures of R-R–Interval
Variability
The short- and long-term scaling exponents
1, 2, the power-law
slope ß, and approximate entropy did not differ between subjects with
sinus tachycardia and those with normal sinus rhythm (Table 3 and Figure 1). Approximate entropy, the long-term
scaling exponent 2, and the power-law slope in
cases with ectopic atrial tachycardia also did not differ
from those with sinus rhythm. However, the short-term scaling exponent
1 was significantly lower in ectopic atrial
tachycardia than in either inappropriate sinus
tachycardia or normal sinus rhythm (Table 3; Figures 2 and 3).
|
Full disclosures of Holter recordings and ECG printouts of
patients with ectopic atrial tachycardia showed sudden,
abrupt prolongations in R-R intervals (exit blocks from ectopic foci)
without evidence of a change in p-wave morphology or AV block in 6
patients throughout the 24-hour recordings (Figure 4). In 5 cases with a low
1 value, no abrupt changes in R-R intervals
were observed, but the ectopic foci showed continuous instability in
beat-to-beat behavior during the entire recording period.
Unstable beat-to-beat R-R–interval behavior and exit blocks were more
commonly observed during sleep than in the daytime.
|
HR Responses to Intravenous Atropine
HR increased from 104±16 bpm to 134±11 bpm (P<0.001)
after intravenous atropine administration in patients with
ectopic tachycardia. The mean increase of HR was 30±14
beats (range 11 to 65 bpm). In 2 patients, the increase in HR was
smaller than the reference values reported for healthy subjects with
normal sinus rhythm (<20% increase from baseline). In subjects with
inappropriate sinus tachycardia, HR increased from 108±15
to 137±18 bpm. The mean increase of HR was 29±13 bpm (range 15 to 49
bpm). Two subjects with sinus tachycardia had a smaller
increase in HR than the normal reference range.
|
Discussion |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
HR variability values obtained by time- and frequency-domain analysis methods over a 24-hour period did not differ between ectopic atrial tachycardia and sinus tachycardia, which suggests that atrial arrhythmic foci are under similar long-term phasic regulation as the sinus node. It appears that autonomic regulation of cardiac rhythm is not limited to effects on those specialized pacemaker tissues richly innervated by vagal and sympathetic fibers but may also influence the abnormal atrial pacemaker tissue. In contrast, short-term correlation properties of R-R–interval behavior were not similar during sinus and ectopic tachycardia. These differences in short-term HR behavior may result from a specific autonomic disturbance that controls the discharge of the ectopic foci or from an intrinsic electrophysiological abnormality of these foci.
Abnormalities in Time- and Frequency-Domain HR Variability
Autonomic regulation of sinus tachycardia and ectopic
tachycardia can be compared by use of traditional
analysis methods because of the similar average HR between the
2 rhythms. The results suggest that vagal outflow both to ectopic foci
and to sinoatrial cells and their responsiveness to vagal input are
similar, because phasic vagal tone is the major factor in the genesis
of HR variability.1 2 3 4 5 6 This concept is also supported by
the observation that atropine resulted in a similar increase in average
HR during ectopic and sinus tachycardia.
HR variability analyzed in absolute units was reduced in both types of tachycardia compared with normal sinus rhythm. Reduced overall HR variability in inappropriate sinus tachycardia has also been reported previously.19 The mechanism for differences in overall HR variability is difficult to interpret, however, because traditional HR variability analysis methods may fail to reveal specific autonomic abnormalities in cases with markedly elevated HR.20 21 Several factors that increase HR itself, regardless of the cause of increase, reduce the overall HR variability.21 22 Therefore, the pattern of reduced overall R-R–interval variability in patients with inappropriate sinus tachycardia or ectopic tachycardia may result not only from a reduced vagal input but also from enhanced intrinsic automaticity of pacemaker cells or an elevated sympathetic input. The traditional methods of analyzing HR variability in absolute units may not be able to document the specific autonomic disturbance as a mechanism of arrhythmias in these cases. Notably, the LF/HF ratio and the LF and HF components analyzed in normalized units did not differ from normal either in ectopic or sinus tachycardia, which suggests that there are no marked abnormalities in the phasic influences of the autonomic nervous system on either ectopic foci or sinoatrial cells causing inappropriate sinus tachycardia. Recent studies in which direct muscle sympathetic nerve activity has been used as a reference index have suggested that the LF and HF spectral components analyzed in normalized units may provide information on sympathetic and vagal outflow, respectively, in subjects without structural heart disease.23 The increase in HR was within the normal limits after atropine in the majority of patients with sinus and ectopic tachycardias, which also suggests that abnormal vagal function may not be the predominant autonomic disturbance of these tachycardias.24
Abnormalities in Short-Term Correlation Properties of
R-R–Interval Dynamics
A potential advantage of the new methods of analyzing
R-R–interval variability based on complexity and fractal
analysis is that they can provide information on the autonomic
regulation of pacemaker tissue independent of the rate of pacemaker
firing.8 9 10 11 12 13 The fractal and complexity measures are not
related to moment statistics (means and variance), and they are able to
reveal subtle abnormalities in dynamic behavior that are undetectable
by traditional analysis techniques.8 9 10 11 12 13
Fractal-like correlation properties in R-R–interval dynamics, ie,
values of 
1.0 of all scaling exponents, were observed in the
present study during both normal sinus rhythm and sinus
tachycardia. Similar fractal-like behavior in R-R–interval
dynamics over different time scales has also been described in previous
studies of subjects with normal sinus rhythm.7 10 11 12
An increase in the randomness of short-term HR behavior, expressed as a reduction in the short-term scaling exponent, was a typical feature of the ectopic tachycardias and resulted either from abrupt prolongations in the R-R intervals or from continuous instability in the beat-to-beat behavior of R-R intervals. An ECG analysis of Holter recordings revealed that the prolongations in R-R intervals resulted from abrupt exit blocks from the ectopic foci. Anecdotal cases of exit blocks from ectopic atrial foci have also been reported previously in short-term ECG recordings.25
Two potential mechanisms may explain the unstable or random R-R–interval behavior of ectopic tachycardias. First, it is possible that the exit blocks from the ectopic foci result from a specific electrophysiological abnormality similar to that observed in the diseased sinus node. Second, there may be a specific autonomic mechanism behind this abnormality. Accentuated sympathovagal interaction caused by high sympathetic outflow together with a concomitant increase in phasic vagal outflow may result in uncorrelated short-term HR behavior. Experiments in healthy volunteers have shown that incremental doses of norepinephrine infusion with baroreflex-mediated vagal activation result in similar abrupt prolongations of sinus intervals as observed in the present study in patients with ectopic tachycardia.26 A reduced short-term scaling exponent and random beat-to-beat HR dynamics have also been observed in patients with heart failure with high levels of norepinephrine.11 27 A complex interaction between norepinephrine and acetylcholine at the presynaptic and postsynaptic levels of the target tissue has been described,28 which may facilitate the random firing of both normal and abnormal pacemakers. Unstable R-R–interval dynamics were most commonly observed in the present study during the sleeping hours, when vagal activity is high, which also supports the view that altered beat-to-beat dynamics in ectopic tachycardias result from increased phasic vagal outflow together with enhanced responsiveness to sympathetic influences of the ectopic foci.
Implications
Analysis of the fractal characteristics of cardiac
interbeat dynamics revealed abnormal dynamic behavior that was not
uncovered by the traditional analysis methods of HR
variability, which confirms that the new analysis methods based
on fractals and nonlinear dynamics add significantly to the
diagnostic performance of the conventional methods
used to assess abnormal HR behavior. Long-term ECG recordings
may also help to differentiate between inappropriate sinus
tachycardia and ectopic atrial tachycardia in
cases in which the 12-lead ECG does not yield a definitive
diagnosis.
|
Acknowledgments |
|---|
This research was supported by grants from the Academy of Science, Helsinki, Finland; the Finnish Foundation for Cardiovascular Research; and a contract with the Finnish Life and Pension Insurance Companies, Helsinki, Finland.
Received April 29, 1999; revision received June 10, 1999; accepted June 17, 1999.
|
References |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
1. Akselrod S, Gordon D, Ubel FA, Shannon DC, Barger MA, Cohen RJ. Power spectrum analysis of heart rate fluctuation. Science. 1981;213:220–222.
2.
Pomeranz B, Macaulay RJB, Caudill MA, Kutz I, Adam D,
Gordon D, Kilborn KM, Barger AC, Shannon DC, Cohen RJ, Benson H.
Assessment of autonomic function in humans by heart rate spectral
analysis. Am J Physiol. 1985;248:H151–H153.
3.
Eckberg DL. Human sinus arrhythmia as an index
of vagal cardiac outflow. J Appl Physiol. 1983;54:961–966.
4.
Pagani M, Lombardi F, Guzzetti S, Rimoldi O, Furlan R,
Pizzinelli P, Sandrone G, Malfatto G, Dell'Orto S, Piccaluga E, Turiel
M, Baselli G, Cerutti S, Malliani A. Power spectral analysis of
heart rate and arterial pressure variability as a marker of
sympatho-vagal interaction in man and conscious dog. Circ
Res. 1986;59:178–193.
5.
Task Force of the European Society of
Cardiology and the North American Society of Pacing and
Electrophysiology. Heart rate variability: standards of measurement,
physiological interpretation, and clinical use.
Circulation. 1996;93:1043–1065.
6.
Malliani A, Pagani M, Lombardi F, Cerutti F.
Cardiovascular neural regulation explored in the
frequency domain. Circulation. 1991;84:482–492.
7. Peng CK, Havlin S, Stanley HE, Goldberger AL. Quantification of scaling exponents and crossover phenomena in nonstationary heartbeat time series. CHAOS. 1995;1:82–87.
8.
Pincus SM. Approximate entropy as a measure of system
complexity. Proc Natl Acad Sci U S A. 1991;88:2297–2301.
9. Goldberger AL. Non-linear dynamics for clinicians: chaos theory, fractals, and complexity at the bedside. Lancet. 1996;347:1312–1314.[Medline] [Order article via Infotrieve]
10.
Bigger JT Jr, Steinman RC, Rolnitzky LM, Fleiss JL,
Albrecht P, Cohen RJ. Power law behavior of RR-interval variability in
healthy middle-aged persons, patients with recent acute myocardial
infarction, and patients with heart transplants.
Circulation. 1996;93:2142–2151.
11.
Ho KKL, Moody GB, Peng CK, Mietus JE, Larson MG, Levy
D, Goldberger AL. Predicting survival in heart failure cases and
controls using fully automated methods for deriving nonlinear and
conventional indices of heart rate dynamics. Circulation. 1997;96:842–848.
12. Mäkikallio TH, Seppänen T, Niemelä M, Airaksinen KEJ, Koistinen JM, Tulppo M, Huikuri HV. Abnormalities in beat to beat complexity of heart rate dynamics in patients with a previous myocardial infarction. J Am Coll Cardiol. 1996;28:1005–1011.[Abstract]
13. Mäkikallio TH, Seppänen T, Airaksinen KEJ, Koistinen JM, Tulppo MP, Peng CK, Goldberger AL, Huikuri HV. Dynamic analysis of heart rate may predict subsequent ventricular tachycardia after myocardial infarction. Am J Cardiol. 1997;80:779–783.[Medline] [Order article via Infotrieve]
14.
Huikuri HV, Niemelä MJ, Ojala S, Rantala A,
Ikäheimo MJ, Airaksinen KEJ. Circadian rhythms of frequency
domain measures of heart rate variability in healthy subjects and
patients with coronary artery disease. Circulation. 1994;90:121–126.
15.
Huikuri HV, Seppänen T, Koistinen MJ, Airaksinen
KEJ, Ikäheimo MJ, Castellanos A, Myerburg RJ. Abnormalities in
beat-to-beat dynamics of heart rate before the spontaneous onset of
life-threatening ventricular
tachyarrhythmias in patients with prior myocardial
infarction. Circulation. 1996;93:1836–1844.
16.
Huikuri HV, Mäkikallio TH, Airaksinen KEJ,
Seppänen T, Puukka P, Räihä IJ, Sourander LB.
Power-law relationship of heart rate variability as a predictor of
mortality in the elderly. Circulation. 1998;97:2031–2036.
17. Morton HJV, Thomas ET. Effects of atropine on the heart rate. Lancet. 1958;2:1313–1315.[Medline] [Order article via Infotrieve]
18. Jose AD, Taylor RR. Autonomic blockade by propranolol and atropine to study intrinsic myocardial function in man. J Clin Invest. 1969;48:2019–2031.
19. Castellanos A, Moleiro F, Chakko S, Acosta H, Huikuri H, Mitrani RD, Myerburg RJ. Heart rate variability in inappropriate sinus tachycardia. Am J Cardiol. 1998;82:531–533.[Medline] [Order article via Infotrieve]
20. Tsuji H, Venditti FJ Jr, Manders ES, Evans JC, Larson MG, Feldman CL, Levy D. Determinants of heart rate variability. J Am Coll Cardiol. 1996;28:1539–1546.[Abstract]
21. Ahmed MW, Kadish AH, Parker MA, Goldberger JJ. Effect of physiologic and pharmacologic adrenergic stimulation on heart rate variability. J Am Coll Cardiol. 1994;24:1082–1090.[Abstract]
22.
Tulppo MP, Mäkikallio TH, Takala TES,
Seppänen T, Huikuri HV. Quantitative beat-to-beat
analysis of heart rate dynamics during exercise. Am
J Physiol. 1996;271:H244–H252.
23.
Pagani M, Montano N, Porta A, Malliani A, Abboud FM,
Birkett C, Somers VK. The relationship between spectral components of
cardiovascular variabilities and direct measures of
muscle sympathetic activity in humans. Circulation. 1997;95:1441–1448.
24.
Morillo CA, Klein GJ, Thakur RK, Li H, Zardini M, Yee
R. Mechanism of "inappropriate" sinus tachycardia: role
of sympathovagal balance. Circulation. 1994;90:873–877.
25. Calvino JM, Azan L, Castellanos A Jr. Paroxysmal tachycardia with 2:1 exit block. Am Heart J. 1957;54:444–447.[Medline] [Order article via Infotrieve]
26.
Tulppo MP, Mäkikallio TH, Seppänen T,
Airaksinen KEJ, Huikuri HV. Heart rate dynamics during accentuated
sympathovagal interaction. Am J Physiol. 1998;274:H810–H816.
27. Woo MA, Stevenson WG, Moser DK, Middlekauff HR. Complex heart rate variability and serum norepinephrine levels in patients with advanced heart failure. J Am Coll Cardiol. 1994;23:565–569.[Abstract]
28.
Levy MN. Sympathetic-parasympathetic interactions in
the heart. Circ Res. 1971;29:437–445.
This article has been cited by other articles:
 |
|
 |
|
  H. V Huikuri, J. S Perkiomaki, R. Maestri, and G. D. Pinna Clinical impact of evaluation of cardiovascular control by novel methods of heart rate dynamics Phil Trans R Soc A, April 13, 2009; 367(1892): 1223 - 1238. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 M. Mase, M. Disertori, and F. Ravelli Cardiorespiratory interactions in patients with atrial flutter J Appl Physiol, January 1, 2009; 106(1): 29 - 39. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 D. Chamchad, G. Djaiani, H. J. Jung, L. Nakhamchik, J. Carroll, and J. C. Horrow Nonlinear Heart Rate Variability Analysis May Predict Atrial Fibrillation After Coronary Artery Bypass Grafting Anesth. Analg., November 1, 2006; 103(5): 1109 - 1112. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 F. Holmqvist, M. Stridh, J. E. P. Waktare, J. Brandt, L. Sornmo, A. Roijer, and C. J. Meurling Rapid fluctuations in atrial fibrillatory electrophysiology detected during controlled respiration Am J Physiol Heart Circ Physiol, August 1, 2005; 289(2): H754 - H760. [Abstract] [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||