The presence of long-range (fractal) correlations for healthy heartbeat fluctuations has important implications for understanding and modeling neuroautonomic regulation, as discussed below. A corollary question is whether pathologic states and aging are associated with distinctive alterations in these scaling properties which could be of practical diagnostic and prognostic use.
Analysis of data from patients with congestive heart failure is likely to be particularly informative in assessing correlations under pathologic conditions since these individuals have abnormalities in both the sympathetic and parasympathetic control mechanisms that regulate beat-to-beat variability . Previous studies have demonstrated marked changes in short-range heart rate dynamics in heart failure compared to healthy function, including the emergence of intermittent relatively low frequency ( cycle/minute) heart rate oscillations associated with the well-recognized syndrome of periodic (Cheyne-Stokes) respiration, an abnormal breathing pattern often associated with low cardiac output [6, 22]. Of note is the fact that patients with congestive heart failure are at very high risk for sudden cardiac death.
Figure: Plot of vs for three interbeat interval time series: healthy young subject, elderly subject, and a subject with congestive heart failure. Compared with the healthy young subject, the heart failure and healthy elderly subjects show different patterns of altered scaling behavior (see text).
Figure 6 compares a representative result of fractal scaling analysis of representative 24-hour interbeat interval time series from a healthy subject and a patient with congestive heart failure. Notice that for large time scales (asymptotic behavior), the healthy subject shows almost perfect power-law scaling over more than two decades () with (i.e., 1/f noise), while for the heart failure data set, (closer to Brownian noise). This result indicates that there is a significant difference in the scaling behavior between healthy and diseased states, consistent with a breakdown in long-range correlations.
To systematically study the alteration of long-range correlations with life-threatening pathologies, we have analyzed cardiac interbeat data from three different groups of subjects [12, 23]: (i) 29 adults (17 male and 12 female) without clinical evidence of heart disease (age range: 20-64 years, mean 41), (ii) 10 subjects with fatal or near-fatal sudden cardiac death syndrome (age range: 35-82 years) and (iii) 15 adults with severe heart failure (age range: 22-71 years; mean 56). Data from each subject contained approximately 24 hours of ECG recording encompassing heartbeats.
For the normal control group, we observed (mean value S.D.). These results confirm that healthy heart rate fluctuations exhibit long-range power-law (fractal) correlation behavior over three decades, similar to that observed in many dynamical systems far from equilibrium [24, 25]. Furthermore, both pathologic groups showed significant deviation of the long-range correlations exponent from the normal value, . For the group of heart failure subjects, we found that , while for the group of sudden cardiac death syndrome subjects, we found that . Of particular note, we obtained similar results when we divided the time series into three consecutive subsets (of hours each) and repeated the above analysis. Therefore our findings are not simply attributable to different levels of daily activities.
Similar analysis was applied to study the effect of physiologic aging. Ten young (21-34 yr) and ten elderly (68-81 yr) healthy subjects underwent 2 hours of continuous supine resting ECG recording (Fig. 6). In healthy young subjects, the scaling exponent had an value close to 1.0. In the group of healthy elderly subjects, the interbeat interval time series showed two scaling regions. Over the short range, interbeat interval fluctuations resembled a random walk process (Brownian noise, ), whereas over the longer range they resembled white noise () Short-range () and long-range () exponents were significantly different in the elderly subjects compared with young . Of interest, the alterations of scaling behavior associated with physiologic aging exhibited different patterns compared to the changes associated with heart failure.