scholarly journals Prediction of Lethal Arrhythmic Events Through Remote Monitoring Using Heart Rate Variability Analysis in Patients with an Implantable Cardioverter Defibrillator

2020 ◽  
Vol 61 (5) ◽  
pp. 927-935
Author(s):  
Yuki Shirakawa ◽  
Shinichi Niwano ◽  
Jun Oikawa ◽  
Daiki Saito ◽  
Tetsuro Sato ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Implantable Cardioverter Defibrillator ◽  
Remote Monitoring ◽  
Heart Rate Variability Analysis ◽  
Cardioverter Defibrillator ◽  
Variability Analysis

scholarly journals Heart rate variability analysis obtained from implantable cardioverter defibrillator: A new diagnostic tool

EP Europace ◽  
2001 ◽  
Vol 2 (Supplement_1) ◽  
pp. A79-A79
Author(s):  
Arne Wieckhorst ◽  
Frank Zimmermann ◽  
Andreas Tiroke ◽  
Inken Langhans ◽  
Rudiger Simon
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Implantable Cardioverter Defibrillator ◽  
Diagnostic Tool ◽  
Heart Rate Variability Analysis ◽  
Cardioverter Defibrillator ◽  
Variability Analysis

scholarly journals Remote monitoring can predict lethal arrhythmic events through time-domain analysis of heart rate variability in patients with implantable cardioverter defibrillator

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
Y Shirakawa ◽  
S Niwano ◽  
J Oikawa ◽  
D Saito ◽  
T Sato ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Implantable Cardioverter Defibrillator ◽  
Time Domain ◽  
Remote Monitoring ◽  
Time Domain Analysis ◽  
Domain Analysis ◽  
Cardioverter Defibrillator ◽  
The Mean ◽  
Hrv Analysis

Abstract Background We prospectively collected device and heart rate data, i.e. heart rate variability (HRV), through remote monitoring (RM) of patients with implantable cardioverter defibrillator (ICD). Several studies have demonstrated usefulness of RM in implanted device patients, however, reports concerning the predictors of lethal ventricular arrhythmias are limited. Purpose The objective was to identify the predictors of lethal arrhythmic events (VT/VF). Methods Thirty-three patients (mean age: 50 years) with ICDs [with functionality of HRV analysis] were divided into 2 groups [VT/VF(+), VT/VF(−)]. Clinical, device (ventricular lead impedance; amplitude of ventricular electrogram), and HRV data were compared between the 2 groups. As the index of time-domain HRV analysis, NN intervals-index (SDNNi) was calculated for every 5 minutes, and the mean, maximum, and minimum SDNNi during the 24-hour period were used. Results During the observation period (median 12 months), 10 patients experienced VT/VF events. In HRV data, the mean, max, and min SDNNi were higher in VT/VF(+) than VT/VF(−) group (132.9±9.3 v.s. 93.5±6.1, p=0.0013; 214.6±10.6 v.s. 167.0±7.0, p=0.0007; 71.2±7.5 v.s. 43.9±4.9, p=0.0047). The other parameters did not exhibit significant difference. On logistic regression analysis, the mean SDNNi of 100.1, max SDNNi of 185.0 and min SDNNi of 52.0 as cut-off values for prediction of VT/VF event demonstrated significant receiver operating characteristics (ROC) curves (AUC=0.86, p=0.0007; AUC=0.84, p=0.0005; AUC=0.78, p=0.0030). Furthermore, in cases of VT/VF(+) group, the max ΔSDNNi, i.e., difference from baseline SDNNi, and min ΔSDNNi in 7 and 28 days preceding VT/VF events exhibited time course changes in comparison with baseline values. They were significant predictors of VT/VF events (max ΔSDNNi cut-off: 46.8, AUC=0.91, p=0.0002; min ΔSDNNi cut-off: −42.4, AUC=0.88, p=0.0014). Conclusion Time-domain analysis of HRV through RM may help identify patients at high risk of lethal arrhythmic events, and predict occurrence of such arrhythmic events. Funding Acknowledgement Type of funding source: None

scholarly journals Heart Rate Variability Analyses in Parkinson’s Disease: A Systematic Review and Meta-Analysis

2021 ◽  
Vol 11 (8) ◽  
pp. 959
Author(s):  
Konstantin G. Heimrich ◽  
Thomas Lehmann ◽  
Peter Schlattmann ◽  
Tino Prell
Keyword(s):  
Parkinson’S Disease ◽  
Heart Rate ◽  
Parkinson's Disease ◽  
Heart Rate Variability ◽  
Meta Analysis ◽  
Cardiac Activity ◽  
Heart Rate Variability Analysis ◽  
Short Term ◽  
Variability Analysis ◽  
Parasympathetic Regulation

Recent evidence suggests that the vagus nerve and autonomic dysfunction play an important role in the pathogenesis of Parkinson’s disease. Using heart rate variability analysis, the autonomic modulation of cardiac activity can be investigated. This meta-analysis aims to assess if analysis of heart rate variability may indicate decreased parasympathetic tone in patients with Parkinson’s disease. The MEDLINE, EMBASE and Cochrane Central databases were searched on 31 December 2020. Studies were included if they: (1) were published in English, (2) analyzed idiopathic Parkinson’s disease and healthy adult controls, and (3) reported at least one frequency- or time-domain heart rate variability analysis parameter, which represents parasympathetic regulation. We included 47 studies with 2772 subjects. Random-effects meta-analyses revealed significantly decreased effect sizes in Parkinson patients for the high-frequency spectral component (HFms2) and the short-term measurement of the root mean square of successive normal-to-normal interval differences (RMSSD). However, heterogeneity was high, and there was evidence for publication bias regarding HFms2. There is some evidence that a more advanced disease leads to an impaired parasympathetic regulation. In conclusion, short-term measurement of RMSSD is a reliable parameter to assess parasympathetically impaired cardiac modulation in Parkinson patients. The measurement should be performed with a predefined respiratory rate.

scholarly journals Heart rate variability: Analysis of time-domain indices in patients with chronic Chagas disease before and after an exercise program

2013 ◽  
Vol 32 (3) ◽  
pp. 219-227 ◽  
Author(s):  
Marcus Vinicius Amaral da Silva Souza ◽  
Carla Cristiane Santos Soares ◽  
Juliana Rega de Oliveira ◽  
Cláudia Rosa de Oliveira ◽  
Paloma Hargreaves Fialho ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Chagas Disease ◽  
Time Domain ◽  
Exercise Program ◽  
Heart Rate Variability Analysis ◽  
Variability Analysis ◽  
Before And After ◽  
Chronic Chagas Disease
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