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(Circulation. 1995;91:722-727.)
© 1995 American Heart Association, Inc.


Articles

Fractal Clustering of Ventricular Ectopy Correlates With Sympathetic Tone Preceding Ectopic Beats

Presented in part at the 66th Scientific Sessions of the American Heart Association, Atlanta, Ga, November 8-11, 1993.

Kenneth M. Stein, MD; Labros A. Karagounis, MD; Jeffrey L. Anderson, MD; Paul Kligfield, MD; Bruce B. Lerman, MD

From the Department of Medicine, Division of Cardiology, The New York Hospital–Cornell Medical Center, New York, NY, and the University of Utah, LDS Hospital, Salt Lake City, Utah (L.A.K., J.L.A.).


*    Abstract
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*Abstract
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down arrowResults
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Background Fractal geometric analysis of ventricular ectopy yields a fractal dimension, which can range from zero to one and is inversely related to clustering of ventricular premature contractions (VPCs). Low values of this fractal dimension, which reflect significantly nonuniform distributions of ventricular ectopy, are found in patients with life-threatening ventricular arrhythmias and predict adverse outcomes in selected patients with congestive heart failure and with mitral regurgitation. However, the physiological mechanism and correlates of the fractal dimension are unknown.

Methods and Results To explore the physiological correlates of clustered ventricular ectopy, we studied 30 patients with a history of sustained ventricular tachycardia or ventricular fibrillation who had inducible sustained monomorphic ventricular tachycardia during electrophysiological study and also underwent drug-free 24-hour ambulatory ECG. In addition to fractal dimension (determined by use of our previously described algorithm), we measured the mean RR interval (±SD) for all sinus beats preceding a sinus beat and for all sinus beats preceding a single VPC and the mean root-mean-square difference (RMSSD) of all windows of 15 successive RR intervals (excluding ectopic beats) preceding a sinus beat and preceding a single VPC. Based on the directional changes of mean RR (a measure of both sympathetic and parasympathetic tone) and of RMSSD (a measure of parasympathetic tone), each patient's inferred relative sympathetic tone preceding ventricular ectopy was classified as increased, unchanged, or decreased. If these values changed concordantly, relative sympathetic tone was indeterminate. Fractal dimension did not correlate with the mean RR interval, SD of the RR interval, or RMSSD preceding sinus beats or preceding VPCs (all P>.10). In 20 patients, fractal dimension was significantly lower among those with increased relative sympathetic tone (n=14) than those with unchanged or decreased sympathetic tone (n=6, P=.008). Ten patients had indeterminate relative sympathetic tone.

Conclusions Clustering of ventricular ectopy, as measured by the fractal dimension, is observed in patients at increased risk of sudden cardiac death. A low fractal dimension (clustered ventricular ectopy) is related to changes in heart rate and heart rate variability that are consistent with transient increases in cardiac sympathetic tone.


Key Words: ventricles • fractals • electrophysiology • ectopy


*    Introduction
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*Introduction
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Fractal geometry, the branch of chaos theory devoted to the mathematical analysis of irregularly irregular objects,1 can be used to analyze patterns of ventricular ectopy in patients with frequent ventricular premature contractions (VPCs).2 3 The technique yields the fractal dimension of a patient's distribution of VPCs; the resulting value can range from zero to one and is a measure of VPC clustering. Values near one reflect a uniform distribution of VPCs, whereas lower values reflect the presence of clustering (over time scales from 1 to 10 minutes). In patients with frequent VPCs, fractal dimensions <=0.93 are incompatible with a uniform random distribution,4 thus defining a clustered (nonuniform) distribution of ectopic beats.

We have previously found that spontaneous ventricular ectopy is significantly nonuniformly distributed over time in patients with congestive heart failure,3 chronic severe mitral regurgitation, and abnormal left ventricular function5 and in patients with a history of life-threatening arrhythmias and inducible ventricular tachycardia during electrophysiological study.4 However, although clustered ventricular ectopy may be associated with adverse outcome,3 5 the physiological determinants of clustered ventricular ectopy are unknown. We hypothesized that clustering of ventricular ectopy might be related to transient changes in cardiac autonomic tone. Therefore, we examined the physiological correlates of the fractal dimension by analyzing patterns of heart rate and heart rate variability preceding ectopic beats in patients with a history of sustained ventricular tachycardia or ventricular fibrillation and positive electrophysiological studies.


*    Methods
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up arrowIntroduction
*Methods
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Patient Population and Electrophysiological Study
We examined 30 patients with a history of ventricular tachycardia or ventricular fibrillation unrelated to acute myocardial infarction, QT prolongation, hypertrophic cardiomyopathy, or chronic renal failure who had inducible sustained monomorphic ventricular tachycardia by electrophysiological study in the drug-free state. Electrophysiological study was performed following an overnight fast after informed consent had been obtained. All antiarrhythmic agents were discontinued for at least five half-lives before study. Patients were locally anesthetized with 0.25% bupivacaine, and quadripolar catheters with a 10-mm interelectrode spacing (Bard Electrophysiology) were introduced percutaneously and advanced under fluoroscopic guidance to the high right atrium, right ventricular apex, and across the tricuspid valve to record a His bundle potential. Bipolar intracardiac electrograms were filtered at 40 to 400 Hz and displayed simultaneously with three surface ECG leads (I, aVF, and V1) on a multichannel oscilloscope. Real-time recordings were made with a paper recorder (Astro-Med Inc) at recording speeds of 50 to 200 mm/s. Programmed stimulation was performed with a programmable stimulator with an isolated constant current source (Bloom Associates). Stimuli were delivered as rectangular pulses of 2-ms duration at 2 to 3 times diastolic threshold. The stimulation protocol included rapid atrial and ventricular pacing at multiple cycle lengths and the introduction of single atrial extrastimuli and single, double, and triple ventricular extrastimuli at drive cycle lengths of 600, 500, and 400 ms. The end point of the stimulation protocol was the reproducible induction of sustained monomorphic ventricular tachycardia, defined as ventricular tachycardia with constant morphology lasting for >=15 seconds or requiring termination sooner by programmed ventricular stimulation or cardioversion because of hemodynamic deterioration. If sustained monomorphic ventricular tachycardia was not induced from the right ventricular apex, the catheter was repositioned to the right ventricular outflow tract and the stimulation protocol was repeated.

Electrocardiographic Analysis
All patients underwent ambulatory ECG recording in the drug-free state, which revealed at least 200 VPCs during the monitoring period. Ambulatory ECG recordings of bipolar leads CM1 and CM5 were scanned and digitized by a computer-based system (Marquette Laser XP, Marquette Electronics Inc), and the RR interval and beat-type listing were downloaded to a personal computer for further analysis. For a series of VPCs, D is the slope of the "correlation function" relating the logarithm of the probability that any two VPCs are separated by less than or equal to the time interval ({delta}) as a function of log ({delta}) (Fig 1Down). Overall fractal dimension at time scales between 1 and 10 minutes was determined as the median of the fractal dimensions for all consecutive windows of 200 VPCs, overlapped by 100 VPCs, according to our previously described algorithm2 3 4 implemented in a customized program written with the Visual Basic programming language (Visual Basic, Microsoft Corp).



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Figure 1. Schematic of the method of calculation of the fractal dimension of ventricular premature contractions (VPCs). A, First, a "correlation function" is computed, which describes the probability that any two VPCs are separated by a given time interval (or less) as a function of the duration of the time interval ({partial}). B, If an intermittent phenomenon fulfills certain criteria,1 then this function is linear after log-log transformation. Fractal dimension (D) is the slope of this line.

In addition, for every sinus beat recorded during ambulatory ECG, we determined the interval between two successive sinus beats immediately preceding a sinus beat [NN-(N)] and the root mean square of the successive differences of all sinus beats in the 15 beats preceding a sinus beat [RMSSD15(N)] (Fig 2Down). Similarly, for every VPC recorded, we determined the interval between two successive sinus beats immediately preceding a VPC [NN-(V)] and the RMSSD of all sinus beats in the 15 beats preceding a VPC [RMSSD15(V)]. In each individual patient, the mean and SD over the recording period of each of these four values was then determined.



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Figure 2. Schematic of quantitative analysis of heart rate and heart rate variability. NN-(N) is defined as the interval between two successive sinus beats immediately preceding a sinus beat, and NN-(V) is the interval between two successive sinus beats immediately preceding a ventricular premature contraction (VPC) (which may be a single VPC or the first beat of a repetitive form). RMSSD15(N) is the root mean square of the successive differences of all sinus beats in the 15 beats preceding a sinus beat, and RMSSD15(V) is the root mean square of the successive differences of all sinus beats in the 15 beats preceding a VPC.

Heart rate (and hence the NN interval) is modulated by integrated effects of both sympathetic and parasympathetic nervous systems on the sinoatrial node. In contrast, RMSSD is a measure of high-frequency ("respiratory") heart rate variability and correlates closely with power spectral measures of high-frequency heart rate variability.6 7 8 9 High-frequency heart rate variability, in turn, can be related most strongly to cardiac parasympathetic tone.10 11 12 13 14 15 16 17 Therefore, significant directional differences in mean heart rate (a function of combined sympathetic and parasympathetic tone) preceding VPCs versus sinus beats and the mean RMSSD15 (a function of parasympathetic tone) preceding VPCs versus sinus beats allow inferences to be drawn regarding changing cardiac autonomic tone preceding VPCs in comparison to sinus beats in each patient (TableDown). A relative increase in sympathetic tone preceding VPCs can be inferred when increased heart rate occurs in the absence of parasympathetic withdrawal (increased or unchanged high-frequency heart rate variability assessed by RMSSD) or when no change in heart rate occurs in the context of increased parasympathetic tone. In a similar manner, each patient can be described as having increased, decreased, or unchanged relative parasympathetic tone preceding VPCs and increased, decreased, unchanged, or indeterminate relative sympathetic tone preceding VPCs.


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Table 1. Inferences Regarding Relative Autonomic Tone Preceding VPCs

Statistical Methods
Results are expressed as mean±SD where appropriate. D values are not normally distributed; therefore, the Mann-Whitney test was used for comparison of unpaired group means. For all purposes, a value of P<.05 was required to reject the null hypothesis.


*    Results
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*Results
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The mean age of the patients (26 men and 4 women) was 66±12 years. The mean number of VPCs was 4993±8144 (median, 2132), and 9 patients had at least one episode of nonsustained ventricular tachycardia (>=6 consecutive VPCs) during monitoring. The underlying cardiac diagnosis was coronary artery disease in 27 patients, 23 of whom had evidence of prior myocardial infarction. The clinical arrhythmia was ventricular tachycardia in 27 patients and ventricular fibrillation in 3. All patients had inducible ventricular tachycardia with programmed ventricular stimulation, consistent with a reentrant mechanism.

Sixteen of 30 patients (53%) had a fractal dimension for ventricular ectopy <=0.93, reflecting a significantly nonuniform ("clustered") distribution of VPCs.4 The fractal dimension did not correlate with the mean NN interval, SD of the NN interval, or RMSSD15 preceding sinus beats or preceding VPCs (all P>.10) for the group as a whole.

Relative sympathetic tone preceding VPCs was inferred to be increased in 14 patients, unchanged or decreased in 6, and indeterminate in 10, according to the schema outlined in the TableUp. Relative sympathetic tone was unrelated to the number of single VPCs or the number of runs of nonsustained ventricular tachycardia in a given patient. Patients with increased sympathetic tone preceding VPCs did not differ from their counterparts in the mean RR interval preceding sinus beats [NN-(N), 859±89 versus 858±143 ms, P=.62] or VPCs [NN-(V), 840±84 versus 867±141 ms, P=.41], the SD of the RR interval preceding sinus beats (87±22 versus 85±15 ms, P=1.00) or VPCs (88±28 versus 85±25 ms, P=.80), or the RMSSD preceding sinus beats (23±11 versus 50±45 ms, P=.16) or VPCs (26±12 versus 51±44 ms, P=.25). By definition, patients with increased sympathetic tone preceding VPCs had a decreased mean RR interval preceding VPCs compared with sinus beats ({Delta}NN=-11±14 ms), whereas those without increased sympathetic tone preceding VPCs had an increased mean RR interval preceding VPCs compared with sinus beats ({Delta}NN=+4±4 ms, P=.0007). Similarly, patients with increased sympathetic tone preceding VPCs had an increased RMSSD preceding VPCs compared with sinus beats ({Delta}RMSSD=±5±4 ms), whereas those without increased sympathetic tone preceding VPCs tended to have a small decrease in RMSSD ({Delta}RMSSD=-1±3 ms, P=.004).

Relative parasympathetic tone preceding VPCs was inferred to be decreased in 3 patients and increased or unchanged in 27 patients. Relative parasympathetic tone was unrelated to the number of single VPCs or the number of runs of nonsustained ventricular tachycardia. Patients with reduced parasympathetic tone preceding VPCs did not differ from their counterparts in the mean RR interval preceding sinus beats [NN-(N), 847±205 versus 853±109 ms, P=.86] or VPCs [NN-(V), 804±163 versus 860±97 ms, P=.65], the SD of the RR interval preceding sinus beats (123±54 versus 98±31 ms, P=.47) or VPCs (112±56 versus 100±41 ms, P=.51), or the RMSSD preceding sinus beats (22±7 versus 38±34 ms, P=.70) or VPCs (20±5 versus 41±36 ms, P=.12). Patients with decreased parasympathetic tone preceding VPCs had a decreased mean RR interval preceding VPCs compared with sinus beats ({Delta}NN=-8±14 ms), whereas those without decreased parasympathetic tone preceding VPCs had an increased mean RR interval preceding VPCs compared with sinus beats ({Delta}NN=+6±27 ms), but this difference was not significant (P=.32). By definition, patients with decreased parasympathetic tone preceding VPCs had a decreased RMSSD preceding VPCs compared with sinus beats ({Delta}RMSSD=-5±1 ms), whereas those without decreased parasympathetic tone preceding VPCs had an increase in RMSSD ({Delta}RMSSD=+5±5 ms, P=.005).

Fractal D was significantly lower among those patients with increased relative sympathetic tone (0.88±0.08) than those with unchanged or decreased sympathetic tone (0.97±0.03, P=.008) (Fig 3Down), compatible with increased clustering of VPCs in these patients. The D values were intermediate (0.93±0.05) for patients with indeterminate sympathetic tone. There were no differences in D values according to relative parasympathetic tone preceding VPCs (Fig 4Down).



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Figure 3. Bar graph showing sympathetic tone and ventricular premature contraction (VPC) clustering: (+) S indicates inferred increase in sympathetic tone preceding VPCs (n=14); (i) S, indeterminate change in sympathetic tone preceding VPCs (n=10); and (-) S, inferred decrease or no change in sympathetic tone preceding VPCs (n=6). P values by Kruskal-Wallis test.



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Figure 4. Bar graph showing parasympathetic tone and ventricular premature contraction (VPC) clustering: (-) PS indicates inferred decreases in parasympathetic tone preceding VPCs (n=3); (+) PS, inferred increase or no change in parasympathetic tone preceding VPCs (n=27). P values by Kruskal-Wallis test.


*    Discussion
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up arrowAbstract
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*Discussion
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Chaos theory, which includes the overlapping disciplines of fractal geometry and nonlinear dynamics, provides new means for quantitative analysis of cardiovascular pathophysiology.18 19 We have previously demonstrated that it is feasible to measure a fractal dimension for a patient's temporal distribution of ventricular ectopy, that this measure is robust and reproducible from day to day, and that the measure is only weakly correlated with traditional measures of VPC complexity (eg, Lown grade, number of runs of nonsustained ventricular tachycardia, and number of beats of nonsustained ventricular tachycardia).2 3 4 As shown in Fig 1Up, the dimension depends on the relation that exists between the probability of finding two VPCs separated by a given time interval or less and the duration of the time interval chosen. Accordingly, fractal dimension is inversely related to the degree of clustering of VPCs. If ectopic beats are distributed homogeneously (ie, are uniformly random), then the number of VPC pairs separated by less than a given time will increase in proportion to the time interval, and the fractal dimension approaches 1.0. However, if events are densely clustered, then the rate of accumulation of VPC pairs with increasing time is less than proportional, and the fractal dimension is less than 1.0. With the present algorithm, a fractal dimension for ventricular ectopy <=0.93 has been shown to be incompatible (P<.05) with a uniform random distribution of VPCs.4

With this approach, we have shown that patients with severe congestive heart failure3 and mitral regurgitation,5 as well as patients with a history of life-threatening arrhythmias,4 have spontaneous ventricular ectopy that is significantly nonuniformly distributed over relatively short time periods and that clustered ventricular ectopy, defined in this way, is associated with an adverse prognosis in congestive heart failure3 and mitral regurgitation with abnormal ventricular function.5 However, the pathophysiological determinants of nonrandom ventricular ectopy have not been addressed previously. The major finding of the present study is that clustering of ventricular ectopy (in patients with sustained ventricular tachycardia or ventricular fibrillation referred for electrophysiological study) is associated with transient increases in sympathetic tone preceding the ectopy, although there are no differences in 24-hour measures of cardiac neurohumoral tone (SD, RMSSD). This observation suggests that dynamic changes in cardiac autonomic tone modulate ambient ventricular ectopy in patients with clustered ventricular ectopy and sustained ventricular arrhythmias and that these changes may be related to their increased risk of adverse outcome.

Consistent with our previous observations, there was a broad range of patterns of spontaneous VPCs in these patients, half of whom had a temporal distribution of VPCs that was significantly nonuniform over time scales from 1 to 10 minutes. It should be emphasized that this nonuniformity is distinct from that due to diurnal variation in VPC frequency, which occurs over much longer time scales, and also that this nonuniformity is not strongly related to the presence or number of runs of nonsustained ventricular tachycardia. Although temporal distributions of VPCs characterized by irregular bursts of ectopic activity on such short time scales appear random, careful analysis may reveal an underlying order. Patterns of ectopic beats are often closely associated with the underlying heart rate,20 and Goldberger and Rigney21 demonstrated that in some patients these clusters occur in tandem with low-frequency (0.02-Hz) fluctuations in sinus cycle length. This suggests a relation between VPC clusters and oscillations in neurohumoral tone, since low-frequency heart rate variability is modulated by combined effects of cardiac sympathetic and parasympathetic activity. In addition, VPCs themselves enhance sympathetic activity,22 possibly creating a positive feedback loop that ultimately results in VPC clustering.

Analysis of 24-hour mean heart rate variability gives an indication of the average cardiac neurohumoral inputs over the course of a day but does not give insight into dynamic changes in autonomic tone (which were apparent only when short-term measures of heart rate variability were analyzed). Thus, in the present patients, neither the 24-hour SD of the RR interval nor RMSSD alone correlated with clustering of ventricular ectopy, whereas a difference was apparent when measures of autonomic tone immediately preceding ectopic beats were compared with measures preceding sinus beats. Consequently, VPC clustering was associated with transiently, rather than tonically, elevated sympathetic tone. The dynamic nature of the changes in autonomic tone preceding VPCs in this subgroup of patients may explain the conflicting results of previous studies exploring the relation of long-term measures of heart rate variability to ventricular arrhythmogenesis. In a previous study of patients with congestive heart failure, ventricular ectopic beats were associated with increased low-frequency heart rate variability compared with baseline, a change consistent with increased sympathetic tone.23 In one group of patients with a history of life-threatening arrhythmias, heart rate variability was reduced over the hour before clinical episodes of sustained ventricular tachycardia.24 Patients with ventricular fibrillation during Holter monitoring have markedly lower heart rate variability than normal subjects,25 but time-domain measures of heart rate variability do not change immediately preceding ventricular fibrillation and do not differ from a matched control group with nonsustained ventricular tachycardia.26 However, although conventional measures of heart rate variability may be insensitive to the phenomenon, nonlinear dynamic techniques reveal a regularization of heartbeat dynamics preceding imminent ventricular fibrillation in animal models of ischemia-provoked arrhythmias27 and in humans.28

The previously observed interaction between abnormal ventricular function, frequent and complex ventricular arrhythmias, and clustered ventricular ectopy (low fractal D) in patients at increased risk of sustained arrhythmias suggests that transient increases in cardiac sympathetic tone might be triggers of sustained ventricular arrhythmias in patients with an abnormal "substrate" (scarring and fibrosis of the ventricular myocardium) and frequent and complex VPCs.29 30 Such a link is consistent with the observations that the combination of enhanced sympathetic tone and diminished parasympathetic tone facilitates arrhythmogenesis.31

It should be recognized that although the inferences regarding relative autonomic tone in these patients are reasonable, they remain inferential. Furthermore, although the patients in the present study had structural heart disease and a history of life-threatening ventricular arrhythmias and positive electrophysiological studies and thus, in the vast majority of cases, the clinical arrhythmia was consistent with reentry, the mechanism of the patients' spontaneous VPCs is nevertheless not defined. Any given patient's spontaneous single VPCs may thus have been due to reentry, triggered activity, automaticity, or a combination of phenomena. Therefore, the present data do not permit a distinction between two possible explanations: (1) that the mechanism of clustered ventricular ectopy is different from that of uniform ventricular ectopy and that this mechanism is more susceptible to modulation by neurohumoral influences or (2) that the mechanism of ventricular ectopy in all patients is modulated by neurohumoral influences but that patients with clustered ventricular ectopy have more variable autonomic tone than patients with a more uniform distribution of VPCs.

Clustering of ventricular ectopic activity can be quantified by measurement of the fractal dimension. This analysis permits the identification of a group of patients whose temporal distribution of VPCs is incompatible with a uniform random distribution. Although in comparison with patients with uniformly distributed VPCs there are no differences in measures of tonic (24-hour) sympathetic tone, transiently elevated sympathetic tone can be inferred from short-term measures of heart rate variability in patients with clustered ventricular ectopy preceding their VPCs. These results should stimulate further analysis of the relation between dynamic changes in autonomic tone and ventricular arrhythmias using techniques, such as microneurography, that permit direct measurement of sympathetic nerve activity.


*    Acknowledgments
 
This work was supported in part by a grant from the National Institutes of Health (RO1-44747). Dr Lerman is an Established Investigator of the American Heart Association.


*    Footnotes
 
Reprint requests to Kenneth M. Stein, MD, Division of Cardiology, Starr-4, The New York Hospital, 525 E 68th St, New York, NY 10021.

Received June 2, 1994; accepted September 23, 1994.


*    References
up arrowTop
up arrowAbstract
up arrowIntroduction
up arrowMethods
up arrowResults
up arrowDiscussion
*References
 
1. Mandelbrot BB. The Fractal Geometry of Nature. New York, NY: Freeman; 1983.

2. Stein KM, Kligfield P. Application of fractal geometry to the analysis of ventricular premature contractions. J Electrocardiol. 1990;23: S82-S84.

3. Stein KM, Kligfield P. Fractal clustering of ventricular ectopy in dilated cardiomyopathy. Am J Cardiol. 1990;65:1512-1515. [Medline] [Order article via Infotrieve]

4. Stein KM, Karagounis LA, Anderson JL, Kligfield P. Day-to-day reproducibility and deviations from uniformity of two fractal measures of VPC clustering in patients with life-threatening ventricular arrhythmias. Comput Cardiol. 1992;239-241.

5. Stein KM, Borer JS, Hochreiter C, Kligfield P. Fractal clustering of ventricular ectopy and sudden death in mitral regurgitation. J Electrocardiol. 1992;25:S178-S181.

6. Bigger JT Jr, Albrecht P, Steinman RC, Rolnitzky LM, Fleiss JL, Cohen RJ. Comparison of time- and frequency domain-based measures of cardiac parasympathetic activity in Holter recordings after myocardial infarction. Am J Cardiol. 1989;64:536-538. [Medline] [Order article via Infotrieve]

7. Bigger JT Jr, LaRovere MT, Steinman RC, Fleiss JL, Rottman JN, Rolnitzky LM, Schwartz PJ. Comparison of baroreflex sensitivity and heart period variability after myocardial infarction. J Am Coll Cardiol. 1989;14:1511-1518. [Abstract]

8. Stein KM, Borer JS, Hochreiter C, Okin PM, Herrold EM, Devereux RB, Kligfield P. Prognostic value and physiological correlates of heart rate variability in chronic severe mitral regurgitation. Circulation. 1993;88:127-135. [Abstract/Free Full Text]

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11. Eckberg DL. Human sinus arrhythmia as an index of vagal cardiac outflow. J Appl Physiol. 1983;54:961-966. [Abstract/Free Full Text]

12. Koizumi K, Terui N, Kollai M. Effect of cardiac vagal and sympathetic nerve activity on rhythmic fluctuations in heart rate. J Auton Nerv Syst. 1985;12:251-259. [Medline] [Order article via Infotrieve]

13. Fouad FM, Tarazi RC, Ferrario CM, Fighaly S, Alicandri C. Assessment of parasympathetic control of heart rate by a noninvasive method. Am J Physiol. 1984;246:H838-H842.

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16. 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 variabilities as a marker of sympatho-vagal interaction in man and conscious dog. Circ Res. 1986;59: 178-193.

17. Akselrod S, Gordon D, Madwed JB, Snidman NC, Shannon DC, Cohen RJ. Hemodynamic regulation: investigation by spectral analysis. Am J Physiol. 1985;249:H867-H875. [Abstract/Free Full Text]

18. Goldberger AL, Findley LJ, Blackburn MR, Mandall AJ. Nonlinear dynamics in heart failure: implications of long-wavelength cardiopulmonary oscillations. Am Heart J. 1984;107:612-615. [Medline] [Order article via Infotrieve]

19. Glass L. Complex cardiac rhythms. Nature. 1987;330:695-696. [Medline] [Order article via Infotrieve]

20. DePaola R, Wang H-X, Norwood WI. Fractal structure underlying patterns of premature heart beats. Am J Physiol. 1993;265: H1603-H1613.

21. Goldberger AL, Rigney DR. Nonlinear dynamics at the bedside. In: Glass L, Hunter P, McCulloch A, eds. Theory of Heart. New York, NY: Springer-Verlag; 1991:583-606.

22. Welch WJ, Smith ML, Rea RF, Bauernfeind RA, Eckberg DL. Enhancement of sympathetic nerve activity by single premature ventricular beats in humans. J Am Coll Cardiol. 1989;13:69-75. [Abstract]

23. Birkett CL, Kienzle MG, Myers GA. Mechanisms underlying alterations in power spectra of heart rate variability associated with ectopy. Comput Cardiol. 1992;391-394.

24. Huikuri HV, Valkama JO, Airaksinen KEJ, Seppanen T, Kessler KM, Takkunen JT, Myerburg RJ. Frequency domain measures of heart rate variability before the onset of nonsustained and sustained ventricular tachycardia in patients with coronary artery disease. Circulation. 1993;87:1220-1228. [Abstract/Free Full Text]

25. Martin GJ, Magid NM, Myers G, Barnett PS, Schaad JW, Weiss JS, Lesch M, Singer DH. Heart rate variability and sudden death secondary to coronary artery disease during ambulatory electrocardiographic monitoring. Am J Cardiol. 1987;60:86-89. [Medline] [Order article via Infotrieve]

26. Vybiral T, Glaeser DH, Goldberger AL, Rigney DR, Hess KR, Mietus J, Skinner JE, Francis M, Pratt CM. Conventional heart rate variability analysis of ambulatory electrocardiographic recordings fails to predict imminent ventricular fibrillation. J Am Coll Cardiol. 1993;22:557-565. [Abstract]

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