“…We show, in a large animal model of CHF: a morning surge in ventricular arrhythmias with CHF; a morning rise in HR at baseline that was attenuated in CHF; a morning rise in LF/HF (balance between sympathetic vs parasympathetic system) that was blunted in CHF; reduced chaos in CD, DFA α1 & α2 and SE in CHF; a loss of time-of-day dependence was found in LF/HF, CD, DFA α1 and SE in CHF; and a lack of enhanced chaos at the time of enhanced arrhythmia occurrence. Several unique features of this study include this being the first demonstration of time-of-day-dependent pattern of VT and PVCs in a large animal model of CHF, and this being the first study to characterize chaotic behavior of HRV and its changes with CHF in the canine heart and demonstrating findings similar to those shown in human CHF [30], [34], [35], [37], [38], [39], [40], [41].…”
Section: Discussionmentioning
confidence: 69%
“…CD is one of the nonlinear parameters reflecting cardiac chaos, a decrease of which can be detrimental [34]. Figure 5A shows that CHF provoked consistent progressive reductions in CD.…”
Patients with chronic heart failure (CHF) exhibit a morning surge in ventricular arrhythmias, but the underlying cause remains unknown. The aim of this study was to determine if heart rate dynamics, autonomic input (assessed by heart rate variability (HRV)) and nonlinear dynamics as well as their abnormal time-of-day-dependent oscillations in a newly developed arrhythmogenic canine heart failure model are associated with a morning surge in ventricular arrhythmias. CHF was induced in dogs by aortic insufficiency & aortic constriction, and assessed by echocardiography. Holter monitoring was performed to study time-of-day-dependent variation in ventricular arrhythmias (PVCs, VT), traditional HRV measures, and nonlinear dynamics (including detrended fluctuations analysis α1 and α2 (DFAα1 & DFAα2), correlation dimension (CD), and Shannon entropy (SE)) at baseline, as well as 240 days (240d) and 720 days (720d) following CHF induction. LV fractional shortening was decreased at both 240d and 720d. Both PVCs and VT increased with CHF duration and showed a morning rise (2.5-fold & 1.8-fold increase at 6 AM-noon vs midnight-6 AM) during CHF. The morning rise in HR at baseline was significantly attenuated by 52% with development of CHF (at both 240d & 720d). Morning rise in the ratio of low frequency to high frequency (LF/HF) HRV at baseline was markedly attenuated with CHF. DFAα1, DFAα2, CD and SE all decreased with CHF by 31, 17, 34 and 7%, respectively. Time-of-day-dependent variations in LF/HF, CD, DFA α1 and SE, observed at baseline, were lost during CHF. Thus in this new arrhythmogenic canine CHF model, attenuated morning HR rise, blunted autonomic oscillation, decreased cardiac chaos and complexity of heart rate, as well as aberrant time-of-day-dependent variations in many of these parameters were associated with a morning surge of ventricular arrhythmias.
“…We show, in a large animal model of CHF: a morning surge in ventricular arrhythmias with CHF; a morning rise in HR at baseline that was attenuated in CHF; a morning rise in LF/HF (balance between sympathetic vs parasympathetic system) that was blunted in CHF; reduced chaos in CD, DFA α1 & α2 and SE in CHF; a loss of time-of-day dependence was found in LF/HF, CD, DFA α1 and SE in CHF; and a lack of enhanced chaos at the time of enhanced arrhythmia occurrence. Several unique features of this study include this being the first demonstration of time-of-day-dependent pattern of VT and PVCs in a large animal model of CHF, and this being the first study to characterize chaotic behavior of HRV and its changes with CHF in the canine heart and demonstrating findings similar to those shown in human CHF [30], [34], [35], [37], [38], [39], [40], [41].…”
Section: Discussionmentioning
confidence: 69%
“…CD is one of the nonlinear parameters reflecting cardiac chaos, a decrease of which can be detrimental [34]. Figure 5A shows that CHF provoked consistent progressive reductions in CD.…”
Patients with chronic heart failure (CHF) exhibit a morning surge in ventricular arrhythmias, but the underlying cause remains unknown. The aim of this study was to determine if heart rate dynamics, autonomic input (assessed by heart rate variability (HRV)) and nonlinear dynamics as well as their abnormal time-of-day-dependent oscillations in a newly developed arrhythmogenic canine heart failure model are associated with a morning surge in ventricular arrhythmias. CHF was induced in dogs by aortic insufficiency & aortic constriction, and assessed by echocardiography. Holter monitoring was performed to study time-of-day-dependent variation in ventricular arrhythmias (PVCs, VT), traditional HRV measures, and nonlinear dynamics (including detrended fluctuations analysis α1 and α2 (DFAα1 & DFAα2), correlation dimension (CD), and Shannon entropy (SE)) at baseline, as well as 240 days (240d) and 720 days (720d) following CHF induction. LV fractional shortening was decreased at both 240d and 720d. Both PVCs and VT increased with CHF duration and showed a morning rise (2.5-fold & 1.8-fold increase at 6 AM-noon vs midnight-6 AM) during CHF. The morning rise in HR at baseline was significantly attenuated by 52% with development of CHF (at both 240d & 720d). Morning rise in the ratio of low frequency to high frequency (LF/HF) HRV at baseline was markedly attenuated with CHF. DFAα1, DFAα2, CD and SE all decreased with CHF by 31, 17, 34 and 7%, respectively. Time-of-day-dependent variations in LF/HF, CD, DFA α1 and SE, observed at baseline, were lost during CHF. Thus in this new arrhythmogenic canine CHF model, attenuated morning HR rise, blunted autonomic oscillation, decreased cardiac chaos and complexity of heart rate, as well as aberrant time-of-day-dependent variations in many of these parameters were associated with a morning surge of ventricular arrhythmias.
“…In cancer patients, ECOG score was widely applied for survival analysis in an advanced stage of cancer [18]. Indices of parasympathetic function are considered to be independent predictors of mortality in health and disease conditions including cancer [19][20][21][22]. However, no data are available on the relationship between cardiac vagal function and ECOG score in cancer patients.…”
Objective: To investigate the influence of cancer severity and functional status of cancer patients on cardiac parasympathetic indicators.
Methods:A total of 267 patients with a fresh clinical diagnosis of solid malignant tumor not yet put on cancer therapy and 250 controls matched for age, sex of study subjects were included. Severity of cancer was defined based on the American Joint Committee on Cancer staging. Accordingly, study subjects were subdivided into early stage (Stage I and II combined) and advanced stage (Stage III and IV combined). In cancer patients, the Eastern Cooperative Oncology Group (ECOG) performance score and the Faces Pain Scale score (FPS) was noted. Two indicators of vagal function, expiratory:inspiratory ratio (E:I ratio) and root mean square of successive N-N interval difference (r-MSSD) were included. E:I ratio during deep breathing at six respiratory cycles/minute and r-MSSD at rest was obtained from 1 minute lead II electrocardiogram. Data were analyzed by applying suitable statistical tests. p≤0.05 was considered significant.Results: R-MSSD and E:I ratio was significantly reduced in the early and advanced stage of cancer compared to controls (p≤0.0001). r-MSSD and E:I ratio was significantly reduced in advanced stage compared to the early stage of cancer (p≤0.0001). r-MSSD and E:I ratio was significantly different in subgroups of stages of cancer and controls (p≤0.0001). In cancer patients, r-MSSD was negatively correlated with ECOG and FPS score (p≤0.0278, p≤0.0100).
Conclusion:Severity of cancer affects vagal function. However, r-MSSD alone was associated with functional status (ECOG, FPS) of cancer patients.
“…The Simulator is free simulation software developed by PHYSIONET called as Kubios HRV analysis tool kit [10][11][12][13][14]. The result sheet generated by the simulator is shown in figure 1.…”
Section: Hrv Analysis Toolmentioning
confidence: 99%
“…HRV analysis is a very sensitive tool to assess many parameters in the changing physiological and pathological conditions [11][12][13]. HRV analysis study is the only tool that provides early diagnosis of changed diabetic pathology [5,6].…”
The complications of diabetes are manifold. Episode of cardiac deaths are more in diabetic subjects than the normal cohorts. Clinical symptoms of deterioration of cardiac health are not manifested at an early stage in current diagnostic practice. Early diagnosis of the same can control morbidity and mortality rate. The paper proposes an early, safe, easily deployable, cost effective and non-invasive technique that can be used as confirmative diagnostic tool obtained from 2-lead ECG sample collected for at least 3 minutes duration. The proposed tool provides a guideline to the echo-cardiologist and saves his time and also controls inter operator diagnostic variation. Also the test can be performed by paramedical personnel saving the echo-cardiologist's time. The proposed paper establishes correlation between HRV indices and echocardiogram finding of control group and diabetic subjects.
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