scholarly journals Modulation of Autonomic Tone Assessed by Heart Rate Variability in Advanced Heart Failure Patients Treated with an Extra-Aortic Counterpulsation (EACP) System: A Single Center Experience

2016 ◽  
Vol 35 (4) ◽  
pp. S319
Author(s):  
A. Kao ◽  
D. Georgakopoulos ◽  
J. Smith ◽  
D. Pomfret ◽  
S. Aggarwal
1996 ◽  
Vol 5 (1) ◽  
pp. 34-41 ◽  
Author(s):  
MA Woo ◽  
WG Stevenson ◽  
DK Moser

BACKGROUND: Heart rate variability reflects autonomic tone and is used to assess progression and prognosis in a variety of illnesses. However, multiple heart rate variability methods exist and are not necessarily equivalent. OBJECTIVES: To compare four methods of heart rate variability in heart failure patients and healthy subjects. METHODS: Twenty-four-hour Holter recordings were obtained in 50 heart failure patients and 50 age- and gender-matched control patients. From these recordings, heart rate variability was assessed by histograms, standard deviation, Poincare plots, and spectral analysis. RESULTS: For R-R interval histograms, standard deviation, and Poincare plots, diminished heart rate variability was identified in 65% to 100% of heart failure patients versus 0% to 8% of controls. Agreement among these tests ranged from 69% to 96%. Spectral values varied greatly over the recording period, even in the same subject, possibly because of variations in activity. Only 16% of heart failure patients had spectral values that were identified as abnormal. Agreement between spectral analysis and the other methods ranged between 58% and 67%. CONCLUSIONS: Heart rate variability assessed over a 24-hour period with different techniques yields similar but not identical results. Heart rate variability assessed from spectral analysis of short periods of data varied markedly in a 24-hour period and should not be compared with measures obtained from 24-hour methods. Standardization of subject activity and recording time is necessary for comparison of spectral analysis of brief periods. Further research is required to determine if differences among methods assessing 24-hour heart rate variability yield complementary information.


2020 ◽  
Vol 2020 ◽  
pp. 1-10 ◽  
Author(s):  
Ping Cao ◽  
Bailu Ye ◽  
Linghui Yang ◽  
Fei Lu ◽  
Luping Fang ◽  
...  

Objective. The deceleration capacity (DC) and acceleration capacity (AC) of heart rate, which are recently proposed variants to the heart rate variability, are calculated from unevenly sampled RR interval signals using phase-rectified signal averaging. Although uneven sampling of these signals compromises heart rate variability analyses, its effect on DC and AC analyses remains to be addressed. Approach. We assess preprocessing (i.e., interpolation and resampling) of RR interval signals on the diagnostic effect of DC and AC from simulation and clinical data. The simulation analysis synthesizes unevenly sampled RR interval signals with known frequency components to evaluate the preprocessing performance for frequency extraction. The clinical analysis compares the conventional DC and AC calculation with the calculation using preprocessed RR interval signals on 24-hour data acquired from normal subjects and chronic heart failure patients. Main Results. The assessment of frequency components in the RR intervals using wavelet analysis becomes more robust with preprocessing. Moreover, preprocessing improves the diagnostic ability based on DC and AC for chronic heart failure patients, with area under the receiver operating characteristic curve increasing from 0.920 to 0.942 for DC and from 0.818 to 0.923 for AC. Significance. Both the simulation and clinical analyses demonstrate that interpolation and resampling of unevenly sampled RR interval signals improve the performance of DC and AC, enabling the discrimination of CHF patients from healthy controls.


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