Effect of Loss of Heart Rate Variability on T-Wave Heterogeneity and QT Variability in Heart Failure Patients: Implications in Ventricular Arrhythmogenesis

2017 ◽  
Vol 8 (2) ◽  
pp. 219-228 ◽  
Author(s):  
Sachin Nayyar ◽  
Muhammad A. Hasan ◽  
Kurt C. Roberts-Thomson ◽  
Thomas Sullivan ◽  
Mathias Baumert
2011 ◽  
pp. 52-61
Author(s):  
Anh Tien Hoang

Objectives: In reccent decades of research now link TWA with inducible and spontaneous clinical ventricular arrhythmias. This bench-tobedside foundation makes TWA a very plausible index of worsen of clinical status. Also with the heart rate variability. We research this study with 2 targets: 1. Prognosis value of TWA and HRV in heart failure. 2. Prognosis value of the combination of TWA and HRV in heart failure. Methods: Prospective study: 82 chronic heart failure patients were admitted to hospital from 2010 May to 2011 May and 50 healthy people were done treadmill test to caculate TWA, ECG, Holter ECG, echocardiography. Results: The combination of TWA and HRV to prognosic the worsen clinical status have the highest prognosis value with OR=102.13 (p<0.001) sensitivity: 80.49%, specificity: 98%, positive predict value: 98.51%, negative predict value: 75.38%. The combination of TWA and HRV to prognosic the ventricular arrythmia have the highest prognosis value with OR=46.25 (p<0.001) sensitivity: 83.33%, specificity: 90.24%, positive predict value: 89.74%, negative predict value: 84.09%. Conclusions: We should combine TWA and HRV in clinical to prognose heart failure patients.


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.


2018 ◽  
Vol 29 (9) ◽  
pp. 1257-1264 ◽  
Author(s):  
Shinya Yamada ◽  
Akiomi Yoshihisa ◽  
Yu Sato ◽  
Takamasa Sato ◽  
Masashi Kamioka ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document