scholarly journals Heart rate variability changes following catheter ablation for atrial fibrillation

2020 ◽  
Vol 78 (3) ◽  
pp. 179-180
Author(s):  
Alena Shantsila ◽  
Dhiraj Gupta ◽  
Gregory Y. H. Lip
Keyword(s):  
Atrial Fibrillation ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Catheter Ablation

scholarly journals Alterations of Heart Rate Variability After Radiofrequency Catheter Ablation of Focal Atrial Fibrillation Originating From Pulmonary Veins

Circulation ◽  
1999 ◽  
Vol 100 (22) ◽  
pp. 2237-2243 ◽  
Author(s):  
Ming-Hsiung Hsieh ◽  
Chuen-Wang Chiou ◽  
Zu-Chi Wen ◽  
Chieh-Hung Wu ◽  
Ching-Tai Tai ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Catheter Ablation ◽  
Radiofrequency Catheter Ablation ◽  
Pulmonary Veins

scholarly journals Heart Rate Variability and Clinical Features as Predictors of Atrial Fibrillation Recurrence After Catheter Ablation: A Pilot Study

2021 ◽  
Vol 12 ◽  
Author(s):  
Javier Saiz-Vivo ◽  
Valentina D. A. Corino ◽  
Robert Hatala ◽  
Mirko de Melis ◽  
Luca T. Mainardi
Keyword(s):  
Atrial Fibrillation ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Catheter Ablation ◽  
Success Rate ◽  
Search Algorithm ◽  
Support Vector ◽  
Ensemble Classifiers ◽  
K Nearest Neighbor ◽  
Af Recurrence

Single-procedure catheter ablation success rate is as low as 52% in atrial fibrillation (AF) patients. This study evaluated the feasibility of using clinical data and heart rate variability (HRV) features extracted from an implantable cardiac monitor (ICM) to predict recurrences in patients prior to undergoing catheter ablation for AF. HRV-derived features were extracted from the 500 beats preceding the AF onset and from the first 2 min of the last AF episode recorded by an ICM of 74 patients (67% male; 57 ± 12 years; 26% non-paroxysmal AF; 57% AF recurrence) before undergoing their first AF catheter ablation. Two types of classification algorithm were studied to predict AF recurrence: single classifiers including support vector machines, classification and regression trees, and K-nearest neighbor classifiers as well as ensemble classifiers. The sequential forward floating search algorithm was used to select the optimum feature set for each classification method. The optimum weighted voting method, which used an optimum combination of the single classifiers, was the best overall classifier (accuracy = 0.82, sensitivity = 0.76, and specificity = 0.87). Clinical and HRV features can be used to predict rhythm outcome using an ensemble classifier which would enable a more effective pre-ablation patient triage that could reduce the economic and personal burden of the procedure by increasing the success rate of first catheter ablation.

065 Heart Rate Variability is Associated With Procedural Outcome in Catheter Ablation For Atrial Fibrillation

2012 ◽  
Vol 28 (5) ◽  
pp. S110
Author(s):  
G.E. Seaborn ◽  
K. Todd ◽  
K.A. Michael ◽  
A. Baranchuk ◽  
H. Abdollah ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Catheter Ablation ◽  
Procedural Outcome

scholarly journals Heart Rate Variability and Procedural Outcome in Catheter Ablation for Atrial Fibrillation

2013 ◽  
Vol 19 (1) ◽  
pp. 23-33 ◽  
Author(s):  
Geoffrey E.J. Seaborn ◽  
Keith Todd ◽  
Kevin A. Michael ◽  
Adrian Baranchuk ◽  
Hoshiar Abdollah ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Catheter Ablation ◽  
Procedural Outcome

Effect of amiodarone on heart rate variability in patients with newly diagnosed atrial fibrillation (clinical observation)

2020 ◽  
pp. 81-85
Author(s):  
E. P. Popova ◽  
O. T. Bogova ◽  
S. N. Puzin ◽  
D. A. Sychyov ◽  
V. P. Fisenko
Keyword(s):  
Atrial Fibrillation ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Drug Therapy ◽  
Heart Function ◽  
Newly Diagnosed ◽  
Class Iii ◽  
Spectral Parameters ◽  
Patient Will ◽  
The Individual

Spectral analysis of heart rate variability gives an idea of the role of the autonomic nervous system in the regulation of chronotropic heart function. This method can be used to evaluate the effectiveness of drug therapy. Drug therapy should be carried out taking into account the individual clinical form of atrial fibrillation. Information about the vegetative status of the patient will undoubtedly increase the effectiveness of treatment. In this study, spectral parameters were studied in patients with newly diagnosed atrial fibrillation. The effect of antiarrhythmic drug class III amiodarone on the spectral parameters of heart rate variability was studied.

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