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European Journal of Heart Failure 2002 4(2):151-158; doi:10.1016/S1388-9842(01)00227-6
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© 2002 European Society of Cardiology

Fractal correlation properties of R-R interval dynamics in asymptomatic relatives of patients with dilated cardiomyopathy{star}

Niall G. Mahona,*, Antti E. Hedmanb, Mina Padulaa, Yi Ganga, Irina Savelievaa, Johan E.P. Waktarea, Marek M. Malika, Heikki V. Huikuric and William J. McKennaa

a Department of Cardiological Sciences St George's Hospital Medical School, London, UK
b Division of Cardiology Kuopio University Hospital, Kuopio, Finland
c Division of Cardiology, Department of Medicine University of Oulu, Oulu, Finland

* Corresponding author. Department of Cardiology/Section of Heart Failure and Transplantation, Cleveland Clinic Foundation, 9500 Euclid Avenue, Cleveland, OH 44195, USA; tel.: +1-216-444-2268; fax: +1-216-444-7155. E-mail address: mahonn{at}ccf.org


   Abstract
Top
 Notes
 Abstract
1. Introduction
 2. Methods
 3. Results
 4. Discussion
 5. Conclusion
 References
 
Background and aim: asymptomatic relatives of patients with familial dilated cardiomyopathy who have left ventricular enlargement [LVE] are at risk for progression to dilated cardiomyopathy. A novel index of the fractal correlation properties of heart rate variability (HRV), the short-term scaling component ({propto}1) in detrended fluctuation analysis, is a promising prognostic tool in left ventricular dysfunction. The aim of this study was to compare values of {propto}1 and conventional HRV indices in LVE relatives with dilated cardiomyopathy patients and normal controls.

Methods: time-domain and spectral HRV measures, and the short-term scaling component ({propto}1) were assessed from 24-h Holter recordings from 22 LVE relatives (left ventricular end-diastolic dimension >112% predicted, normal fractional shortening), 24 dilated cardiomyopathy patients and 14 controls.

Results: the time domain index SDNN was lower in dilated cardiomyopathy patients [101.8(±44.0)] than in LVE relatives [161.7(±53.9)] or controls [152.9(±51.4)], P = 0.01. Similarly, triangular index and spectral measures were reduced in dilated cardiomyopathy patients but not in LVE relatives or controls. In contrast, the short term scaling component ({propto}1) in detrended fluctuation analysis was reduced in both dilated cardiomyopathy patients [1.06(±0.33)] and in LVE relatives [1.15 (±0.20)], compared with controls [1.32(±0.16)], P = 0.01. Among DCM patients the short-term scaling component ({propto}1) was significantly associated with echocardiographic deterioration during follow-up (3.7±2.1 year) (P = 0.004).

Conclusion: the short-term scaling component ({propto}1) is reduced in asymptomatic relatives of dilated cardiomyopathy patients who have LVE.

Key Words: Dilated cardiomyopathy • Heart rate variability

Received May 18, 2001; Revised August 1, 2001; Accepted October 23, 2001


   1. Introduction
Top
 Notes
 Abstract
 1. Introduction
2. Methods
 3. Results
 4. Discussion
 5. Conclusion
 References
 
Idiopathic dilated cardiomyopathy (DCM) typically presents at an advanced stage of left ventricular dilatation and dysfunction and accounts for approximately 50% of all patients undergoing cardiac transplantation [1–3]. The recognition, through recent prospective family evaluation studies, that at least 25% of patients have familial disease [4] raises the possibility that prognosis might be improved by earlier diagnosis and treatment of relatives in a preclinical phase of the disorder. The ability to identify early disease would represent a significant advance in the current management of dilated cardiomyopathy and in addition would facilitate studies of its pathogenesis.

Evaluation of families of dilated cardiomyopathy patients has identified a subset of relatives who have left ventricular enlargement (LVE) (defined as a left ventricular diastolic dimension of >112% predicted for age and body surface area [5]) in the presence of normal systolic function and in the absence of an underlying cause such as hypertension or athletic training [24]. LVE in a relative of a dilated cardiomyopathy patient may be a marker of early or mild disease. Relatives with LVE have abnormal histology, with evidence of inflammation [6], a higher than expected frequency of circulating cardiac specific antibodies [7], elevated circulating cytokines and cardiac creatine kinase isoforms [8], and are at risk of progression to overt dilated cardiomyopathy during follow-up [9].

Heart rate variability is a reliable and reproducible quantitative marker of autonomic activity in cardiac health and disease. Traditional time-domain and spectral measures are of prognostic value in a variety of settings, including following myocardial infarction, congestive cardiac failure, cardiac transplantation and cardiomyopathies [10]. However, these measures make assumptions of harmonic or sinusoidal variations that may not be true of complex biological regulation systems [11]. More recently, interest has focussed on fractal measures based on non-linear system theory (‘chaos theory’), which are suggested to reflect periodic and non-periodic variations in heart rate that result from a variety of internal and environmental influences more accurately [12,13]. One of these indices, the short-term scaling component ({propto}1) in detrended fluctuation analysis, has supplanted clinical variables and linear measures of heart rate variability as a predictor of morbidity and/or mortality in an increasing variety of clinical contexts, including acute myocardial infarction with or without left ventricular dysfunction [14–17], coronary bypass surgery [18], among elderly subjects [19] and in congestive heart failure [20].

LVE relatives have autonomic and neuroendocrine abnormalities that could be expected to result in abnormal heart rate variability, including elevations in levels of natriuretic peptides [21] and reduced peak oxygen consumption on metabolic exercise testing, with evidence of an abnormal ventilatory response similar to that observed in heart failure patients [22]. The aim of this study was to determine whether the short-term scaling component ({propto}1) index heart rate variability is reduced in asymptomatic relatives with left ventricular enlargement.


   2. Methods
Top
 Notes
 Abstract
 1. Introduction
 2. Methods
3. Results
 4. Discussion
 5. Conclusion
 References
 
2.1. Subjects
Between January 1992 and December 1998, prospective cardiovascular evaluation of relatives was offered to 370 consecutive patients with DCM attending St. George's Hospital, London. One hundred ninety eight patients consented to participate in the study. Evaluation of asymptomatic relatives was performed following local ethics committee approval and has been described in detail elsewhere [9]. Evaluation included clinical assessment, 12-lead ECG and two-dimensional echocardiogram. Dilated cardiomyopathy was defined according to World Health Organization criteria [23].

Echocardiographic measurements were performed in a single plane in the two-dimensional parasternal long-axis view. LVE in a relative was defined as an unexplained left ventricular end-diastolic dimension of greater than 112% of predicted values in the presence of a shortening fraction of greater than 25% [9]. Predicted LV end diastolic dimension [left ventricular end-diastolic dimension (corrected)] was calculated according to the formula of Henry [5]: left ventricular end-diastolic dimension (corrected)=[45.3xBSA0.3]–[0.03xAge]–7.2 (BSA=body surface area). The measured left ventricular end-diastolic dimension was then expressed as a percent according to the ratio: left ventricular end-diastolic dimension (%)=left ventricular end-diastolic dimension/left ventricular end-diastolic dimension (corrected).

Patients with coronary disease, hypertension, valvular disease or a regular alcohol intake of >21 units/week in men and >14 units/week in women were excluded, as were individuals with metabolic or endocrine disease. Coronary angiography was performed in all patients over the age of 40 years and in younger patients if there were symptoms, signs or risk factors suggestive of coronary disease.

In total, 767 relatives met inclusion criteria. Of these, 552 (72%) were assessed as normal, 37 (5%) fulfilled WHO criteria for DCM [23], 25 (3%) had isolated depressed fractional shortening (<25%) and 104 (14%) had LVE, defined as an unexplained LVDD greater than 112% of predicted values in the presence of a shortening fraction of =25% [9].

Patients with DCM were followed at least annually or more frequently as dictated by clinical status. As part of the study protocol, patients with LVE were followed annually. All DCM patients underwent annual Holter monitoring as part of their clinical follow-up, while LVE patients underwent Holter monitoring, usually at baseline, for research purposes.

The present study was an observational pilot study with a case-control design. Holter tapes from patients with dilated cardiomyopathy and asymptomatic relatives with LVE were selected at random from over a 6-year period (1992–1998). Patients with atrial fibrillation (n=5) were excluded as were patients with poor quality high-noise level Holter recordings (n=4). In total tapes from 24 DCM patients and 22 LVE relatives were analysed.

Baseline clinical and echocardiographic data were taken from the time of the Holter monitor analysed and follow-up data from the most recent visit. Follow-up was available on all patients.

Fourteen healthy volunteer subjects with no evidence of cardiac disease, hypertension, endocrine or metabolic disease, or any acute or chronic illness were included as controls.

2.2. HRV analysis
For each patient, relative and control two channel recordings (modified lead II and CM5) were made using tracker recorders (Marquette Electronics or Reynolds Medical). All data were processed using a Holter analysis system (Marquette, Series 8000) and all recordings were carefully manually edited with deletion of premature ventricular ectopics and noise prior to generating RR beat interval files for subsequent HRV analysis. All patients had >18 h of ECG data including >90% of normal sinus beats. Automated HRV analysis was performed using custom-written software developed and validated by research groups of Harvard and Oulu University [24,25] (Hearts5 software package, Hearts Signal Co., Oulu, Finland) by an investigator blinded to the subject's clinical status. The standard deviation of all normal–normal RR intervals (SDNN) and geometric triangular index were computed from the entire recording period as standard time-domain indices of heart rate variability, according to the recommendations of the Task-Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology [10]. Spectral power was quantified by fast-Fourier transformation analysis in 2 frequency bands:<0.0033 Hz (ultra-low frequency) and 0.0033–0.04 Hz (very low frequency). Detrended fluctuation analysis was used to quantify the fractal scaling properties of RR interval data. The technique has been described in detail elsewhere [24,25]. Briefly, the root mean square fluctuation of integrated and detrended time series was measured for various observation windows and plotted against the size of the observation window on a log-log scale. From this plot the value of short-term scaling exponent ({alpha}1) was obtained. The cut point of 11 beats was chosen for the short term scaling exponent ({alpha}1) based on the previous findings of a ‘crossover point’ on the log–log plot [24,25]. The exponent value of a fractal-like signal is 1 and of a random signal is 0.5. A short-term scaling exponent value of <0.85 has previously been shown to be a predictor of adverse events [17].

2.3. Statistical analysis
Statistical analysis was performed using SPSS for Windows (SPSS Inc., Chicago, IL, USA). Unpaired Student's t-test, parametric and non-parametric analysis of variance, {chi}2 test and correlation coefficient were used where appropriate. A P value of less than 0.05 was considered significant. Results are expressed as mean±S.D.


   3. Results
Top
 Notes
 Abstract
 1. Introduction
 2. Methods
 3. Results
4. Discussion
 5. Conclusion
 References
 
3.1. Clinical characteristics
Seventeen (85%) of dilated cardiomyopathy patients were on ACE-inhibitors, 5(20%) on angiotensin II antagonists, 8(33%) on amiodarone, 6(25%) on beta-blockers, 8(33%) on digoxin, 8(33%) on diuretics and 14(60%) on warfarin. No LVE patient or control was taking any cardiac medication. There was a non-significant preponderance of male DCM patients in this study compared with the total population of DCM patients (86% vs. 69%, P=0.2). DCM patients in the present study were younger than the overall DCM population [31(27) vs. 42(15), P=0.008]; LVDD and FS were similar to the larger group [136(21) vs. 136(23), P=0.9) and [15(11)% vs. 18(9)%, P=0.1], respectively. Similarly, LVE patients in this study were younger than the remaining population of LVE patients [30.2(12.1) vs. 36.8(16.2), P<0.01]. Gender distribution was equivalent to that in the larger group (male 64% vs. 59%, P=0.67). LVDD and FS were similar in both groups [118(7)% vs. 117(7)%, P=0.8; 33(6)% vs. 32(6)%, P=0.3]. There were no significant age or gender differences between the LVE and control groups in this study [30(12) vs. 35 (3), 0.24; M/F 14/8 vs. 8/6, 0.48]. Control subjects did not undergo echocardiography.

3.2. HRV indices
The time domain index SDNN was lower in dilated cardiomyopathy patients [101.8(±44.0)] than in LVE relatives[161.7(±53.9)] or controls[152.9(±51.4)], P=0.01 (Table 1). Similarly, triangular index and spectral measures were reduced in dilated cardiomyopathy patients but not in LVE relatives or controls. In contrast, the short term scaling component {propto}1 in detrended fluctuation analysis was reduced in both dilated cardiomyopathy patients [1.06(±0.33)] and in LVE relatives [1.15(±0.20)], compared with controls [1.32(±0.16)], after correction for multiple testing (P=0.01).


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  		Table 1 Heart rate variability in dilated cardiomyopathy, LVE and controls

 
3.3. Follow-up: HRV, survival and progression
Patients and relatives were followed for a median of 3.7 years. During that time three patients died and two underwent cardiac transplantation. No LVE relative died or underwent transplantation. Among dilated cardiomyopathy patients, univariate predictors of death or cardiac transplantation were New York Heart Association class, SDNN and the short-term scaling component ({propto}1) (Table 2). Echocardiographic progression, defined as an increase in left ventricular end-diastolic dimension of >1 S.E. during follow-up, occurred in three LVE relatives and six dilated cardiomyopathy patients. Progressive enlargement among LVE relatives was associated in one case with intermittent exertional and rest dyspnoea and the commencement of ace-inhibitor therapy, but was asymptomatic in all other cases. Among dilated cardiomyopathy patients, of all clinical, echocardiographic, Holter and HRV variables, only the short-term scaling component ({propto}1) was significantly associated with disease progression during follow-up [0.78(deteriorating group) vs. 1.21(stable group), P=0.004] (Table 3). In Kaplan–Meier analysis, {propto}1<0.85 was a significant predictor of progressive ventricular enlargement (Fig. 1). No variable predicted deterioration among LVE relatives.


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  		Table 2 Univariate predictors of survival in dilated cardiomyopathy patients

 


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  		Table 3 Predictors of disease progression in dilated cardiomyopathy

 


Figure 1
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  		Fig. 1 Kaplan–Meier curve depicting freedom from progressive ventricular enlargement among DCM patients according to {alpha}1 values.

 

   4. Discussion
Top
 Notes
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
5. Conclusion
 References
 
The principal finding of this study is that the short-term scaling component ({propto}1) of heart rate variability is abnormal in asymptomatic relatives of dilated cardiomyopathy patients who have left ventricular enlargement. This adds to clinical, serologic and physiological evidence that LVE in the context of a family history of dilated cardiomyopathy may represent early or mild disease. The ability to detect early disease is of considerable potential clinical importance and may help avoid presentation at a late stage in the disease process with advanced heart failure or with a catastrophic event such as stroke or sudden cardiac death, as well as potentially facilitating genetic and pathogenetic research in dilated cardiomyopathy. The finding of an abnormal fractal index contrasts with the lack of detectable abnormalities in non-spectral and spectral analyses of HRV in this and in a previous study of relatives with LVE [26], suggesting that the short-term scaling component ({propto}1) may be more sensitive than linear measures for the detection of abnormalities of HRV in patients with mild or early disease. Fractal scaling is suggested to be more accurately reflective of the organising principles of physiologic structure and short-term variations than traditional linear measurements. The potential superiority of fractal analysis over conventional measures is supported by accumulating evidence from larger outcome studies in left ventricular dysfunction in which both conventional and fractal analyses have been employed. In a study of patients with LV dysfunction following myocardial infarction in the trandolapril cardiac evaluation (TRACE) study, the short-term scaling component ({propto}1) was the most powerful HRV index in predicting mortality [17]. Similarly the short-term scaling component ({propto}1) was the most powerful R-R interval variability measure predictive of both arrhythmic and non-arrhythmic death in patients with left ventricular dysfunction following myocardial infarction in patients enrolled in the Danish Investigations of Arrhythmia and Mortality on Dofetilide (DIAMOND-MI) trial [16]. More recently, in an analysis of 24 h Holter recordings in 499 patients with congestive heart failure and ejection fraction, <35% participating in the DIAMOND-CHF trial, {alpha}1 was the only index of heart rate variability that was independently predictive of mortality [20].

Several studies have examined HRV specifically in idiopathic dilated cardiomyopathy. In one study of 64 patients with dilated cardiomyopathy followed up over 20 months, SDNN was shown to predict the development of progressive heart failure [26]. In another study, SDNN was an independent predictor of all cause mortality [27]. The short-term scaling component ({propto}1) has not previously specifically been evaluated in dilated cardiomyopathy patients. A limitation of this study is the fact that it was not powered to evaluate HRV or other variables as a predictor of outcomes. However, the potential prognostic utility of fractal indices is suggested by the observation in this study of an association of short-term scaling component ({propto}1) with death or cardiac transplantation among dilated cardiomyopathy patients and by the fact that the short-term scaling component ({propto}1) was associated with deterioration in LV function during follow-up. The prognostic utility of the short-term scaling component ({propto}1) in this context warrants prospective evaluation in a larger trial with longer follow-up.

The physiological background of reduced fractal correlation properties of R-R interval dynamics is not completely understood. Clinical observations suggest that reduced scaling exponent results mainly from unstable, random beat-to-beat R-R interval dynamics [16], often observed in patients with congestive heart failure [24]. Increasing evidence also supports the role of the sympathetic activation behind this impairment. High norepinephrine levels, indicating sympatho-excitation, have been observed to be related to unstable, random beat-to-beat R-R interval dynamics in heart failure patients [28]. Furthermore, in young healthy adults, an intravenous infusion of physiologic doses of norepinephrine has been shown to lead to altered fractality of heart rate, demonstrated by sudden abrupt changes in short-term heart rate dynamics [29]. These observations suggest that high plasma levels of circulating catecholamines may play a role in altered fractal HR dynamics as well as in deterioration of left ventricular function in patients with familial cardiomyopathy and in asymptomatic relatives at risk of progression. Further experimental work will be needed to confirm this concept, however.

This pilot study has several limitations. Patients and LVE relatives randomly selected for evaluation in this study were younger than their counterparts in the overall population of DCM patients and LVE relatives. However, this difference would have actually militated against detecting reduction in {propto}1, since its value tends to be highest in young adults, decreasing from middle age onwards [30].

Analysis of outcomes was inevitably limited because there were insufficient events to perform multivariate analyses. However, in univariate analysis {propto}1 was the most significant predictor of progressive ventricular enlargement in DCM patients and this finding supports the accumulating body of evidence that this index may be superior to traditional prognostic instruments in congestive heart failure. This study was not designed to evaluate the prognostic value of this measure in asymptomatic relatives. Such an investigation will require prospective evaluation in a larger cohort with longer follow-up. The finding of reduced {propto}1 in asymptomatic relatives with LVE does not negate its association with poor outcomes among patients with established heart disease seen in many studies, since values for {alpha}1 observed among our cohort of DCM patients and in heart failure patients in other studies are quantitatively lower than in the asymptomatic relatives.

The influence of cardiac medications on {propto}1 has not been fully investigated, although any potential influences are relevant only to our DCM patients, since the LVE relatives were on no medications. There is evidence that {propto}1 in heart failure improves after a period of beta-blocker treatment [31]. In this study we did not find any baseline differences in {propto}1 between DCM patients receiving and not receiving beta-blockers.

Relatives in this study were 1st degree relatives, identified through family screening, of a patient with dilated cardiomyopathy. They were not necessarily related to the DCM patients in this study, as to do so would have risked a potential confounding effect of unknown genetic factors. For the same reason the controls were also unrelated. Genetic analysis of transmission of HRV traits is beyond the scope of this study.

The potential for heart rate variability to be used widely in clinical practice remains to be established. Despite well-established prognostic credentials in a variety of cardiac diseases, its clinical utility will be more apparent when interventions based on HRV are proven to be beneficial. Trials randomising patients to pharmacological or non-pharmacological interventions based on the results of a heart rate variability tests such as the Defibrillator in Acute Myocardial Infarction Trial are currently underway [32]. The accumulating evidence of the prognostic utility of {alpha}1 warrants consideration of its incorporation as an inclusion criterion in future studies. Another issue requiring further study that is particularly relevant to the potential utility of the {alpha}1measure in cardiac failure, is whether it can be employed in patients with atrial fibrillation or other arrhythmias.


   5. Conclusion
Top
 Notes
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
 5. Conclusion
References
 
The short-term scaling component ({propto}1) is abnormal in asymptomatic relatives of dilated cardiomyopathy patients who have LVE. This finding adds to clinical, serological and physiological evidence that LVE represents early or mild disease in familial dilated cardiomyopathy. In addition the short-term scaling component ({propto}1) is a predictor of progressive ventricular enlargement in dilated cardiomyopathy patients. The potential prognostic utility of {propto}1 in asymptomatic relatives of dilated cardiomyopathy patients warrants prospective evaluation.


   Acknowledgements
 
Supported in part by British Heart Foundation project grant PG98124.


   Notes
Top
 Notes
Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
 5. Conclusion
 References
 
{star} Presented in part at the American Heart Association Scientific Sessions, November 2000, New Orleans, Louisiana, USA. Back


   References
Top
 Notes
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
 5. Conclusion
 References
 

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