Key result
Short-time scale DFA exponents (0.79, 0.95, 1.11, 1.35) hierarchically classified advanced CHF patients at baseline, 1 and 3 months post-atenolol, and healthy individuals, respectively.
Why the study?
The mechanisms driving distinct temporal cardiac properties in CHF remain unclear, and whether these parameters can finely classify CHF severity is uncertain.
Does atenolol therapy alter temporal cardiac dynamics and heart rate variability in patients with advanced congestive heart failure?
Observational
Does atenolol therapy alter temporal cardiac dynamics and heart rate variability in patients with advanced congestive heart failure?
Temporal cardiac properties derived from multiscale entropy and detrended fluctuation analysis can classify CHF severity and response to beta-blocker therapy, highlighting the critical role of respiratory sinus arrhythmia in heart rate variability.
DFA exponents may track beta-blocker effects in advanced CHF; hypothesis-generating and requires prospective validation before clinical use.
Temporal cardiac properties provide alternative information in analyzing heart rate variability (HRV), which may be disregarded by the standard HRV analyses. Patients with congestive heart failure (CHF) are known to have distinct temporal features from the healthy individuals. However, the underlying mechanism leading to the variation remains unclear. Whether or not these parameters can finely classify the severity for CHF patients is uncertain as well. In this work, an electrocardiogram was monitored in advanced CHF patients using 24-h Holter in four conditions, including baseline, one and three months after atenolol therapy, and healthy individuals. Slope and area under the curve (AUC) of multiscale entropy (MSE) curve over short (scales 1–5) and long (scales 6–20) scales, and detrended fluctuation analysis (DFA) scaling exponents at short (4–11 beats) and intermediate (>11 beats) window sizes were calculated. The results show that short-time scale MSE-derived parameters (slope: −0.08 ± 0.10, −0.03 ± 0.10, 0.02 ± 0.06, 0.08 ± 0.06; AUC: 4.03 ± 2.11, 4.69 ± 1.28, 4.73 ± 0.94, and 6.17 ± 1.23) and short-time scale DFA exponent (0.79 ± 0.16, 0.95 ± 0.22, 1.11 ± 0.19, and 1.35 ± 0.20) can hierarchically classify all four conditions. More importantly, simulated R-R intervals with different fractions and amplitude of respiratory sinus arrhythmia (RSA) components were examined to validate our hypothesis regarding the essentiality of RSA in the improvement of cardiovascular function, and its tight association with unpredictability and fractal property of HRV, which is in line with our hypothesis that RSA contributes significantly to the generation of the unpredictability and fractal behavior of HR dynamics. NEW & NOTEWORTHY Temporal cardiac properties provide useful diagnostic parameters for patients with congestive heart failure (CHF). Our study hierarchically classified CHF patients with β-blocker treatment by using multiscale entropy and detrended fluctuation analysis. Also, we provided the evidence to validate the critical role of respiratory sinus arrhythmia in the fractal properties of heart rate variability.
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Yeh et al. (2019) conducted an observational in Congestive heart failure. Atenolol therapy vs. Baseline and healthy individuals was evaluated on Short-time scale multiscale entropy (MSE)-derived parameters and detrended fluctuation analysis (DFA) scaling exponents. Short-time scale DFA exponents (0.79, 0.95, 1.11, 1.35) hierarchically classified advanced CHF patients at baseline, 1 and 3 months post-atenolol, and healthy individuals, respectively.
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