Autonomic Nervous System Functioning Associated with Epileptic Seizures: Analysis of Heart Rate Variability (original) (raw)
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Objective: Psychogenic nonepileptic seizures (PNESs) resemble epileptic seizures but originate from psychogenic rather than organic causes. Patients with PNESs are often unable or unwilling to reflect on underlying emotions. To gain more insight into the internal states of patients during PNES episodes, this study explored the time course of heart rate variability (HRV) measures, which provide information about autonomic nervous system functioning and arousal. Methods: Heart rate variability measures were extracted from double-lead electrocardiography data collected during 1-7 days of video-electroencephalography monitoring of 20 patients with PNESs, in whom a total number of 118 PNESs was recorded. Heart rate (HR) and HRV measures in time and frequency domains (standard deviation of average beat-to-beat intervals (SDANN), root mean square of successive differences (RMSSD), high-frequency (HF) power, low-frequency (LF) power, and very low-frequency (VLF) power) were averaged over consecutive five-minute intervals. Additionally, quantitative analyses of Poincaré plot parameters (SD1, SD2, and SD1/SD2 ratio) were performed. Results: In the five-minute interval before PNES, HR significantly (p b 0.05) increased (d = 2.5), whereas SDANN (d = −0.03) and VLF power (d = −0.05) significantly decreased. During PNES, significant increases in HF power (d = 0.0006), SD1 (d = 0.031), and SD2 (d = 0.016) were observed. In the five-minute interval immediately following PNES, SDANN (d = 0.046) and VLF power (d = 0.073) significantly increased, and HR (d = −5.1) and SD1/SD2 ratio (d = −0.14) decreased, compared to the interval preceding PNES. Conclusion: The results suggest that PNES episodes are preceded by increased sympathetic functioning, which is followed by an increase in parasympathetic functioning during and after PNES. Future research needs to identify the exact nature of the increased arousal that precedes PNES.
Neurology Asia
Autonomic dysfunction is often associated with seizures in patients with epilepsy. Autonomic dysfunction during seizures can cause serious events like cardiac arrest and sudden unexplained death. Early detection of autonomic dysfunction is crucial to avoid such medical emergencies. In our study, we analyzed the heart rate variability (HRV) in physiological recording during the preictal, ictal and postictal periods. A total of 142 seizures with various semiologies recorded from 49 epilepsy patients were included. Time-domain measurements including mean hear rate (HR), RR interval (RRI), root-mean-square of successive R-R interval differences (RMSSD), The standard deviation of N-N intervals (SDNN) and percentage of successive RR intervals that differ by more than 50 ms(pNN50) were analyzed at different time points, 20 minutes before the seizure, 1 minute before the seizure, during the seizure and 20 minutes after the seizure. We observed there was a significant difference in HRV param...
Epilepsia, 2012
Purpose: Psychogenic nonepileptic seizures (PNES) superficially resemble epileptic seizures. Little is known about ictal autonomic nervous system (ANS) activity changes in epilepsy and PNES. This study compares ictal heart rate variability (HRV) parameters as a reflection of ANS tone in epileptic seizures and PNES, and explores differences between interictal and ictal ANS tone in both patient groups. Methods: Ictal HRV parameters were extracted from single-lead electrocardiography (ECG) data collected during video-electroencephalography (EEG) recordings of 26 patients with medically refractory temporal lobe epilepsy and 24 age-and sex-matched patients with PNES. One seizure per patient in a resting, wake, supine state was analyzed. Interictal ECG data were available for comparison from 14 patients in both groups. HRV parameters in time and frequency domains were analyzed (low frequency [LF], high frequency [HF], standard deviation of all consecutive normal R wave intervals [SDNN], square root of the mean of the sum of the squares of differences between adjacent normal R wave intervals [RMSSD]). CVI (cardiovagal index), CSI (cardiosympathetic index), and ApEn (approximate entropy) were calculated from Lorenz plots. Key Findings: There were significant differences between ictal HRV measures during epileptic and nonepileptic seizures in the time and frequency domains. CSI (p < 0.001) was higher in epileptic seizures. Time interval between two consecutive R waves in the ECG (RR interval) (p = 0.002), LF (p = 0.02), HF (p = 0.003), and RMSSD (p = 0.003) were significantly lower during epileptic seizures. Binary logistic
Electrophysiologic assessment of autonomic function in epilepsy
Seizure-european Journal of Epilepsy, 1998
Sudden unexpected death associated with epilepsy (SUDEP) is an important clinical problem. Peri-ictal autonomic dysfunction is thought to play a role in SUDEP and few means exist for clinical identification of patients at risk.
Medicinski podmladak
Epilepsy is a very prevalent neurological disorder. The gold standard in diagnosis of epilepsy is the EEG signal recorded during a seizure with characteristic ictal pattern. Automated systems for detection of seizures are a field of intensive research, in an attempt to create a reproducible, observer-independent mechanism for epilepsy diagnosis. Chronic therapy is a cornerstone of the epilepsy treatment, but the possibility to predict seizure onset and, consequently, to act with medications right before the seizure, instead of relying on everyday medications, is considered the holy grail of epilepsy research. Significant element of morbidity and mortality in epilepsy is sudden unexpected death in epilepsy (SUDEP) that occurs in roughly 1% of patients. Signal analysis techniques for EEG have been a staple in epilepsy research, but recently, with the rise of telemetric systems, heart rate variability (HRV) analysis derived from the ECG signal has been gaining importance. It has been found that perturbations in autonomic nervous system (ANS) regulation occur during, and even up to several minutes before, seizure onset allowing for changes in HRV to act in prediction, as well as detection, of seizures. Also, there is a compelling research exploring the extent of autonomic disbalance during seizures, as well as in the interictal periods in patients at risk for or that have had SUDEP. The focus of this review is to give a short crossection of research involving the utility HRV has in prediction and detection of seizure onset, as well as determining etiology classification and risk evaluation in SUDEP.
Anadolu Kardiyoloji Dergisi/The Anatolian Journal of Cardiology, 2013
Pre-ictal heart rate variability assessment of epileptic seizures by means of linear and non-linear analyses Doğrusal ve doğrusal olmayan analiz yoluyla epileptik nöbetlerin (iktal) kriz öncesi kalp hızı değişkenliği ile değerlendirilmesi ABSTRACT Objective: The purpose of the present study was to analyze the effects of epilepsy on the autonomic control of the heart in pre-ictal phase in order to find an algorithm of early detection of seizure onset. Methods: Overall 133 epileptic seizures were analyzed from 12 patients with epilepsy (seven males and five females; mean age 43.91 years, SD: 10.16) participated in this study. Single lead electrocardiogram recordings of epileptic patients were compiled. 240, 90-30, 30-10 and 5 minutes heart rate variability (HRV) signals of preseizure were chosen for analysis of heart rate. As HRV signals are non-stationary, a set of time and frequency domain features (Mean HR, Triangular Index, LF, HF, LF/HF) and nonlinear parameters (SD1, SD2 and SD2/SD1 indices derived from Poincaré plots) extracted from HRV is analyzed. Statistical analysis was performed using paired sample t-test for comparisons of the segments and differences between pre-ictal segments were evaluated by Tukey tests.
CARDIAC AUTONOMIC DYSFUNCTION IN PATIENTS WITH EPILEPSY
International Journal of Pharmacy and Pharmaceutical Sciences, 2023
Objective: The objective of this research was to appraise autonomic impairment through the examination of both time-domain and frequencydomain parameters of heart rate variability in individuals with epilepsy. Methods: Thirty epilepsy patients and thirty healthy subjects were enrolled in our study for evaluation of autonomic functions, which was assessed by comparing heart rate variability between epilepsy patients and healthy subjects. Results: There was no notable disparity observed in mean heart rate between the two groups. However, the frequency-domain metrics-LF Power, HF Power, and LF/HF ratio exhibited statistically noteworthy differences when comparing the patients to the control group (p-value<0.05). Conversely, parameters such as SDNN, RMSST, and pNN50 did not demonstrate statistically considerable differences in comparison to the controls (p-value>0.05). The parameters did not exhibit statistically significant distinctions between individuals with epilepsy for under 10 y and those diagnosed with epilepsy for over 10 y. Conclusion: Our investigation revealed a notable contrast in HRV metrics between the patient group and the group of individuals in good h ealth. The potential utilization of HRV as an indicator of susceptibility to SUDEP could enhance the quality of guidance provided to both patients and their families. Additional exploration is warranted, involving more extensive participant cohorts, and examining the impact of anti epileptic medications on HRV, within future studies.
Epilepsy & Behavior, 2011
Heart rate variability (HRV) metrics provide reliable information about the functioning of the autonomic nervous system (ANS) and have been discussed as biomarkers in anxiety and personality disorders. We wanted to explore the potential of various HRV metrics (VLF, LF, HF, SDNN, RMSSD, cardiovagal index, cardiosympathetic index, approximate entropy) as biomarkers in patients with psychogenic nonepileptic seizures (PNES). HRV parameters were extracted from 3-minute resting single-lead ECGs of 129 subjects (52 with PNES, 42 with refractory epilepsy and 35 age-matched healthy controls). Compared with healthy controls, both patient groups had reduced HRV (all measures P b 0.03). Binary logistic regression analyses yielded significant models differentiating between healthy controls and patients with PNES or patients with epilepsy (correctly classifying 86.2 and 93.5% of cases, respectively), but not between patients with PNES and those with epilepsy. Interictal resting parasympathetic activity and sympathetic activity differ between healthy controls and patients with PNES or those with epilepsy. However, resting HRV measures do not differentiate between patients with PNES and those with epilepsy.
Interictal autonomic dysfunction in patients with epilepsy
The Egyptian Journal of Neurology, Psychiatry and Neurosurgery, 2021
Background Autonomic nervous system (ANS) symptoms are frequently present in people with epilepsy (PwE). They are generally more prominent when they originate from the temporal lobe. We aim to investigate the alterations of autonomic functions during the interictal period in patient with temporal lobe epilepsy (TLE) and idiopathic generalized epilepsy (IGE) using heart-based tests, blood pressure (BP)-based tests and sympathetic skin response (SSR). Forty-eight PwE with disease duration ranging from 2 to 15 years and 51 healthy individuals were studied. Long-term electroencephalography (EEG) monitoring, the heart rate variability (HRV) during normal breathing, deep breathing, Valsalva maneuver and standing, BP responses during standing, to isometric hand grip and to mental arithmetic, and the SSR was recorded for all participants. Results 31 patients with TLE and 17 with IGE showed lower RR-IV values during deep breathing, Valsalva maneuver and standing, but not during rest, impaire...
Heart rate variability and vagus nerve stimulation in epilepsy patients
Translational Neuroscience, 2019
Background Vagus nerve stimulation (VNS) exerts a cortical modulating effect through its diffuse projections, especially involving cerebral structures related to autonomic regulation. The influence of VNS on cardiovascular autonomic function in drug-resistant epilepsy patients is still debated. We aimed to evaluate the impact of VNS on cardiovascular autonomic function in drug-resistant epilepsy patients, after three months of neurostimulation, using the heart rate variability (HRV) analysis. Methodology Multiple Trigonometric Regressive Spectral analysis enables a precise assessment of the autonomic control on the heart rate. We evaluated time and frequency-domain HRV parameters in resting condition and during sympathetic and parasympathetic activation tests in five epilepsy patients who underwent VNS procedure. Results We found appropriate cardiac autonomic responses to sympathetic and parasympathetic activation tests, described by RMSSD, pNN50, HF and LF/HF dynamics after three m...