A relevant question regarding these new measurements is: Does fractal analysis, such as the DFA method, have clinically predictive value, independent of conventional statistical indices? To answer this question, we have studied the predictive power of the DFA exponent in comparison with multiple conventional measures based on mean, variance and spectral analysis . We analyzed two-hour ambulatory ECG recordings of 69 participants (mean age years) in the Framingham Heart Study--a prospective, population-based study. The study population consisted of chronic congestive heart failure patients, and age- and sex-matched control subjects. Importantly, we found that this fractal measurement carried prognostic information about mortality not extractable from traditional methods of heart rate variability analysis (Fig. 7). Subsequent studies [29, 30, 31] have confirmed and extended these observations, suggesting that fractal scaling measures may have a practical use in bedside and ambulatory monitoring.
Figure: Assessment of patient survival rate by using an index (DFA index) derived from DFA analysis along with the information about the standard deviation of heart rate variability (SHR). In this population-based (Framingham Heart) study, we found, using multivariable analysis, that the DFA and SHR were the two most powerful independent heart rate variability predictors of mortality. Here, high and low DFA index (or SHR) refer to their median values. After .