Fractal analysis of heart rate variability as a predictor of mortality: A systematic review and meta-analysis

Abstract

Previous studies have suggested benefits of applying fractal analysis to intervals between R waves in electrocardiography as an additional prognostic marker. The aim of this study was to investigate whether fractal analysis can provide an independent predictor of cardiac mortality or all-cause mortality. Prognostic cohort studies reporting fractal heart rate variability results from 24-h Holter monitor recordings were selected for comparison. Populations were subdivided into four groups-post-myocardial infarction, left ventricular dysfunction, other cardiac, and non-cardiac patients-and analysed using ANOVA, Forest plots (using pooled mean difference), and Funnel plots. The most significant mean differences were recorded in short-term fractal self-similarity (α) (-0.17, 95% CI [-0.21, -0.13], p < 0.00001) and the traditional measure called standard deviation of NN intervals (SDNN) (-13.31, 95% CI [-18.89, -7.73], p < 0.00001) between the deceased and survivor groups. Fractal measures of long-term fractal self-similarity (α), 1/f scaling (β), and traditional heart rate variability measures of high frequency to low frequency ratio show promise. This review indicated that fractal measure α and traditional measure SDNN could be potential predictors of mortality, but require further assessment to determine appropriate thresholds for clinical significance and additional targeted prognostic studies to properly define their applicability as prognostic markers. Therefore, clinicians should interpret fractal and traditional measures with caution since such measures have yet to be fully described as biomarkers for clinical application.

Heart Rate Variability and Exceptional Longevity

“…A classic example is high resting HR (Zhang et al, 2015). Additionally, a recent meta-analysis has established LF/HF ratio and SDNN as two of the variables with greater potential as predictors of mortality (Sen and McGill, 2018). Shimizu et al (2002) have also observed the relevance of LF/ HF ratio in a cohort of 27 centenarians.…”

Fractal correlations and linear analyses of heart rate variability in healthy young people with different levels of physical activity

“…These techniques have been shown to be powerful tools for the characterisation of complex systems, like the complexity and fractal scaling properties of the cardiac beat-to-beat series. 46 Silva et al 47 and Sen and McGill 48 reported that although α2 is less reported in the literature, it is related to a decrease in the oxygen desaturation index and cardiovascular disease, 47 and is strongly related to mortality. 48 Detrended fluctuation analysis calculates the fluctuation of the mean square root of the integral and purifies the time series, allowing the detection of the intrinsic autosomillarity embedded in the non-stationary time series.…”

“…46 Silva et al 47 and Sen and McGill 48 reported that although α2 is less reported in the literature, it is related to a decrease in the oxygen desaturation index and cardiovascular disease, 47 and is strongly related to mortality. 48 Detrended fluctuation analysis calculates the fluctuation of the mean square root of the integral and purifies the time series, allowing the detection of the intrinsic autosomillarity embedded in the non-stationary time series. The detrended fluctuation analysis graph is not strictly linear, but consists of two distinct regions of distinct curves, separated by one point, suggesting that there is a short-term fractal scale exponent (α1) during periods of 4-11 beats (or 4-13), and a long-term exponent (α2) for longer periods (>11 beats).…”

New Directions in Exercise Prescription: Is There a Role for Brain-Derived Parameters Obtained by Functional Near-Infrared Spectroscopy?

“…A promising indicator of the state of the autonomous nervous system is the HRV, which is operationalized by the beat-to-beat variations of the heart rate over a specific time period (e.g., during a resting state or during physical exercises) [45,[241][242][243][244][245]. HRV is considered to be a proxy of the actual health state [246][247][248][249] and stress level [247,250] of an individual. HRV also reflects, at least partly, the fitness level and daily readiness [243,244,[251][252][253][254][255] of an individual, as well as the organismic demands [256][257][258][259][260].…”