Heart rate variability measurement in epilepsy: How can we move from research to clinical practice?

Autonomic biosignals, seizure detection, and forecasting

Wearable devices have attracted significant attention in epilepsy research in recent years for their potential to enhance patient care through improved seizure monitoring and forecasting. This narrative review presents a detailed overview of the current clinical state of the art while addressing how devices that assess autonomic nervous system (ANS) function reflect seizures and central nervous system (CNS) state changes. This includes a description of the interactions between the CNS and the ANS, including physiological and epilepsy-related changes affecting their dynamics. We first discuss technical aspects of measuring autonomic biosignals and considerations for using ANS sensors in clinical practice. We then review recent seizure detection and seizure forecasting studies, highlighting their performance and capability for seizure detection and forecasting using devices measuring ANS biomarkers. Finally, we address the field's challenges and provide an outlook for future developments.

Exercise-induced central and peripheral sympathetic activity in a community-based group of epilepsy patients differ from healthy controls

Ictal and interictal activity within the autonomic nervous system is characterized by a sympathetic overshoot in people with epilepsy. This autonomic dysfunction is assumed to be driven by alterations in the central autonomic network. In this study, exercise-induced changes of the interrelation of central and peripheral autonomic activity in patients with epilepsy was assessed. 21 patients with epilepsy (16 seizure-free), and 21 healthy matched controls performed an exhaustive bicycle ergometer test. Immediately before and after the exercise test, resting state electroencephalography measurements (Brain Products GmbH, 128-channel actiCHamp) of 5 min were carried out to investigate functional connectivity assessed by phase locking value in source space for whole brain, central autonomic network and visual network. Additionally, 1-lead ECG (Brain products GmbH) was performed to analyze parasympathetic (root mean square of successive differences (RMSSD) of the heart rate variability) and sympathetic activity (electrodermal activity (meanEDA)). MeanEDA increased (p < 0.001) and RMSSD decreased (p < 0.001) from pre to post-exercise in both groups. Correlation coefficients of meanEDA and central autonomic network functional connectivity differed significantly between the groups (p = 0.004) after exercise. Both patients with epilepsy and normal control subjects revealed the expected physiological peripheral autonomic responses to acute exhaustive exercise, but alterations of the correlation between central autonomic and peripheral sympathetic activity may indicate a different sympathetic reactivity after exercise in patients with epilepsy. The clinical relevance of this finding and its modulators (seizures, anti-seizure medication, etc.) still needs to be elucidated.

Cardiac dysfunctions in children with drug-resistant epilepsy

Objective

There were reports of cardiac dysfunction that led to sudden unexpected death in epilepsy (SUDEP) in patients with epilepsy. Early detection of cardiac dysfunction can lead to early management to prevent sudden cardiac death in these patients. The objective of our study is to assess cardiac functions in children with drug-resistant epilepsy (DRE) compared with the normal population by using a standard echocardiogram (SE), tissue Doppler imaging (TDI) and myocardial strain evaluations (MSE).

Method

Twenty-seven children who have been diagnosed with DRE based on the International League against Epilepsy (ILAE) were included in the study, along with 27 children whose ages match those of the normal control group.

Results

Seventeen children, median age 12 years old, were using more than four anti-seizure medications. Structural brain lesions were the most common cause of epilepsy, 55.6% (15). Generalized tonic-clonic seizures were the most common seizure type, 55.6% (15). Children with DRE had a lower early mitral valve E wave inflow velocity compared with the control group (p < 0.05). They also had lowered early diastolic velocities (e') and myocardial performance index (MPI) when compared with the control group (p < 0.05). There was a statistically significant difference in left ventricular myocardial strain in children with DRE, with an average of -21.1 (IQR -23.5 and -19.4) and control, -25.5 (IQR -27.3 and -24.2).

Significance

Children with DRE have an impairment of left ventricular diastolic function and myocardial strain, which could indicate decreased myocardial deformation and contraction compared with controls. These cardiological assessments can be used to evaluate children with DRE for early diagnosis and management of their cardiac dysfunction.

The Interplay of Sports and Nutrition in Neurological Health and Recovery

This comprehensive review explores the dynamic relationship between sports, nutrition, and neurological health. Focusing on recent clinical advancements, it examines how physical activity and dietary practices influence the prevention, treatment, and rehabilitation of various neurological conditions. The review highlights the role of neuroimaging in understanding these interactions, discusses emerging technologies in neurotherapeutic interventions, and evaluates the efficacy of sports and nutritional strategies in enhancing neurological recovery. This synthesis of current knowledge aims to provide a deeper understanding of how lifestyle factors can be integrated into clinical practices to improve neurological outcomes.

Impaired post-sleep apnea autonomic arousals in patients with drug-resistant epilepsy

OBJECTIVE

Sudden and unexpected deaths in epilepsy (SUDEP) pathophysiology may involve an interaction between respiratory dysfunction and sleep/wake state regulation. We investigated whether patients with epilepsy exhibit impaired sleep apnea-related arousals.

METHODS

Patients with drug-resistant (N = 20) or drug-sensitive (N = 20) epilepsy and obstructive sleep apnea, as well as patients with sleep apnea but without epilepsy (controls, N = 20) were included. We explored (1) the respiratory arousal threshold based on nadir oxygen saturation, apnea-hypopnea index, and fraction of hypopnea among respiratory events; (2) the cardiac autonomic response to apnea/hypopnea quantified as percentages of changes from the baseline in RR intervals (RRI), high (HF) and low (LF) frequency powers, and LF/HF.

RESULTS

The respiratory arousal threshold did not differ between groups. At arousal onset, RRI decreased (-9.42%) and LF power (179%) and LF/HF ratio (190%) increased. This was followed by an increase in HF power (118%), p < 0.05. The RRI decrease was lower in drug-resistant (-7.40%) than in drug-sensitive patients (-9.94%) and controls (-10.91%), p < 0.05. LF and HF power increases were higher in drug-resistant (188%/126%) than in drug-sensitive patients (172%/126%) and controls (177%/115%), p < 0.05.

CONCLUSIONS

Cardiac reactivity following sleep apnea is impaired in drug-resistant epilepsy.

SIGNIFICANCE

This autonomic dysfunction might contribute to SUDEP pathophysiology.

Changes in heart rate variability over time from symptom onset of transient global amnesia

Transient global amnesia (TGA) often involves precipitating events associated with changes in autonomic nervous system (ANS), and heart rate variability (HRV) reflects the ANS state. This study aimed to investigate HRV changes after TGA. A retrospective analysis of HRV included patients diagnosed with TGA between January 2015 and May 2020. The time and frequency domains of HRV were compared among three groups: early (< 1 week after TGA, n = 19), late (1-4 weeks after TGA, n = 38), and healthy control (HC, n = 19). The Pearson's correlation between time and time-domain HRV was also examined. The standard deviation of NN intervals (SDNN) (early, 47.2; late, 35.5; HC, 41.5; p = 0.033) and root mean square of successive RR interval differences (RMSSD) (early, 38.5; late, 21.3; HC, 31.0; p = 0.006) differed significantly among the three groups. Post-hoc analysis showed statistically significant differences only in the early and late groups in both SDNN (p = 0.032) and RMSSD (p = 0.006) values. However, the frequency domain with total power, low-frequency and high-frequency powers, and low-frequency/high-frequency ratio did not differ. SDNN (Pearson correlation coefficient =- 0.396, p = 0.002) and RMSSD (Pearson correlation coefficient =- 0.406, p = 0.002) were negatively correlated with time after TGA. Changes in HRV occurred over time after the onset of TGA, with the pattern showing an increase in the first week and then a decrease within 4 weeks.

Feasibility of cardiac-based seizure detection and prediction: A systematic review of non-invasive wearable sensor-based studies

A reliable seizure detection or prediction device can potentially reduce the morbidity and mortality associated with epileptic seizures. Previous findings indicating alterations in cardiac activity during seizures suggest the usefulness of cardiac parameters for seizure detection or prediction. This study aims to examine available studies on seizure detection and prediction based on cardiac parameters using non-invasive wearable devices. The Embase, PubMed, and Scopus databases were used to systematically search according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. Human studies that evaluated seizure detection or prediction based on cardiac parameters collected using wearable devices were included. The QUADAS-2 tool and proposed standards for validation for seizure detection devices were used for quality assessment. Twenty-four articles were identified and included in the analysis. Twenty studies evaluated seizure detection algorithms, and four studies focused on seizure prediction. Most studies used either a wrist-worn or chest-worn device for data acquisition. Among the seizure detection studies, cardiac parameters utilized for the algorithms mainly included heart rate (HR) (n = 11) or a combination of HR and heart rate variability (HRV) (n = 6). HR-based seizure detection studies collectively reported a sensitivity range of 56%-100% and a false alarm rate (FAR) of 0.02-8/h, with most studies performing retrospective validation of the algorithms. Three of the seizure prediction studies retrospectively validated multimodal algorithms, combining cardiac features with other physiological signals. Only one study prospectively validated their seizure prediction algorithm using HRV extracted from ECG data collected from a custom wearable device. These studies have demonstrated the feasibility of using cardiac parameters for seizure detection and prediction with wearable devices, with varying algorithmic performance. Many studies are in the proof-of-principle stage, and evidence for real-time detection or prediction is currently limited. Future studies should prioritize further refinement of the algorithm performance with prospective validation using large-scale longitudinal data. PLAIN LANGUAGE SUMMARY: This systematic review highlights the potential use of wearable devices, like wristbands, for detecting and predicting seizures via the measurement of heart activity. By reviewing 24 articles, it was found that most studies focused on using heart rate and changes in heart rate for seizure detection. There was a lack of studies looking at seizure prediction. The results were promising but most studies were not conducted in real-time. Therefore, more real-time studies are needed to verify the usage of heart activity-related wearable devices to detect seizures and even predict them, which will be beneficial to people with epilepsy.

Heart Rate Variability as a Tool for Seizure Prediction: A Scoping Review

The most critical burden for People with Epilepsy (PwE) is represented by seizures, the unpredictability of which severely impacts quality of life. The design of real-time warning systems that can detect or even predict ictal events would enhance seizure management, leading to high benefits for PwE and their caregivers. In the past, various research works highlighted that seizure onset is anticipated by significant changes in autonomic cardiac control, which can be assessed through heart rate variability (HRV). This manuscript conducted a scoping review of the literature analyzing HRV-based methods for detecting or predicting ictal events. An initial search on the PubMed database returned 402 papers, 72 of which met the inclusion criteria and were included in the review. These results suggest that seizure detection is more accurate in neonatal and pediatric patients due to more significant autonomic modifications during the ictal transitions. In addition, conventional metrics are often incapable of capturing cardiac autonomic variations and should be replaced with more advanced methodologies, considering non-linear HRV features and machine learning tools for processing them. Finally, studies investigating wearable systems for heart monitoring denoted how HRV constitutes an efficient biomarker for seizure detection in patients presenting significant alterations in autonomic cardiac control during ictal events.

Can heart rate variability identify a high-risk state of upcoming seizure?

Heart rate variability (HRV) is an accessible and convenient means to assess the sympathetic/parasympathetic balance. Autonomic dysfunctions may reflect a pro-ictal state and occur before the seizure onset. Previous studies have reported HRV-based models to identify preictal states in continuous electrocardiogram (EKG) monitoring. Here, we evaluated the ability of HRV metrics extracted from daily single resting-state periods to estimate the risk of upcoming seizure(s) using probabilistic forecasts. Daily standardized 10-min vigilance-controlled EKG periods were recorded in 15 patients with drug-resistant focal epilepsy who underwent intracerebral electroencephalography (EEG). Analyses of a total of 156 periods, based on machine learning approaches, suggested that HRV features can identify preictal states with a median AUC of 0.75 [0.68;0.99]. Pseudoprospective daily forecasts yielded a median Brier score of 0.3 [0.18;0.48]. About 60% of preictal days were correctly forecasted, while false positive predictions were noticed in 24% of interictal days. Daily resting HRV seems to capture information on autonomic variations that may reflect a pro-ictal state. The method could be embedded in an ambulatory clinical seizure prediction device, but additional modalities (prodromes, EEG-based features, etc.) should be associated to improve its performance.

The Association of Nocturnal Seizures and Interictal Cardiac/Central Autonomic Function in Frontal Lobe Epilepsy: Heart Rate Variability and Central Autonomic Network Analysis

Purpose

Patients with epilepsy frequently experience autonomic dysfunction, closely related to sudden unexplained death in epilepsy (SUDEP). SUDEP occurs most often at night or during sleep, and frequent nocturnal seizures are an established risk factor. This study investigated the influence of nocturnal seizures on autonomic dysfunction in epilepsy.

Patients and Methods

This retrospective study enrolled frontal lobe epilepsy (FLE) patients who performed 24-hour EEG monitoring. All participants were divided into nocturnal FLE (NFLE, > 90% of seizures occurring during sleep) or diurnal FLE (DFLE) groups. EEG and ECG signals were simultaneously obtained during waking and sleep stages. EEG current density source and connectivity analysis of the autonomic network were performed. ECG was analyzed across time and frequency domains heart rate variability (HRV) analysis method was used. The obtained parameters were compared between the NFLE and DFLE groups.

Results

Fifteen NFLE and 16 DFLE patients were enrolled with no significant difference in age, sex, disease duration, seizure frequency, or the number of anti-seizure medications between the two groups. During sleep, a decrease in HRV parameters and an increase of the beta-1 (13-22 Hz) current source density power in the bilateral paracentral lobule (BA4,5,6), precuneus (BA7), and cingulate (BA31) were observed in the NFLE group compared to DFLE group. The NFLE group also showed hyperconnectivity in the central autonomic (12 edges distributed over 10 nodes), sympathetic (2 edges distributed over 3 nodes), and parasympathetic (4 edges distributed over 6 nodes) beta-1 frequency band networks during sleep. During wakefulness, central and cardiac autonomic variables were not significantly different between the NFLE and DFLE groups.

Conclusion

Interictal cardiac and central autonomic dysfunction occurred simultaneously and can be attributed to the brain-heart autonomic axis. Our findings suggest that nocturnal seizures may contribute to interictal autonomic dysfunction during sleep in people with epilepsy.

Is anti-seizure medication the culprit of SUDEP?

BACKGROUND

Heart rate variability (HRV) reduction is a potential biomarker for sudden cardiac death. This study aimed to study the effects of anti-seizure medications (ASMs), adjusted with reported factors associated with sudden unexpected death in epilepsy (SUDEP) on HRV parameters.

METHODS

We recruited patients who were admitted in our epilepsy monitoring unit between January 2013 and December 2021. Two 5-min electrocardiogram epochs during wakefulness and sleep were selected in each patient. HRV analysis with Python® software was performed. The imputed datasets were used for linear regression analysis to assess association between each ASM item and all HRV parameters. The effects of ASM on HRV parameters were subsequently adjusted with the significant clinical characteristics and the concomitant use of other ASMs, respectively.

RESULTS

Carbamazepine (CBZ), levetiracetam (LEV), lamotrigine (LTG), and clonazepam (CZP) were statistically significantly associated with changes of sleep HRV parameters. Only CBZ showed negative effects with reduction in HRV, evidenced as lower standard deviation of RR interval (SDNN), even when adjusted with concomitant use of other ASMs (p = 0.045) and had a trend of significance when adjusted with significant clinical characteristics of concurrent taking of beta-blocker drug (p = 0.052). LEV and CZP showed opposite effects with increased HRV even when adjusted with significant clinical characteristics and the concomitant use of other ASMs.

CONCLUSIONS

CBZ showed negative effects on HRV. We proposed that CBZ should be cautiously used in patients with known risks for SUDEP. In addition, HRV assessment should be performed prior to commencing CBZ and re-performed in follow-up in cases of prolonged use.

Peri-ictal heart rate changes in patients with epilepsy

Background

Heart rate (HR) changes associated with seizures are promising biomarkers in epilepsy.

Aims

The aim of our study is to reveal possible HR changes in the peri-ictal period.

Methods

Long-term video-EEG monitorization records of generalized and focal epilepsy patients were reviewed. HRs were calculated in the pre-ictal (2 min before the first seizure activity in EEG), ictal (the time from the first seizure activity on the EEG to the end of the seizure), and in the interictal period (at least 2 h before or 12 h after the seizure). Interictal, pre-ictal, and ictal HRs were compared with each other. In addition, it was investigated whether peri-ictal HR changes differ between generalized and focal seizure patients.

Results

Focal motor seizures were observed in 21, and generalized tonic-clonic seizures were observed in 18 of 39 (22 female and 17 male) patients studied. HRs in the pre-ictal and ictal periods were significantly higher than in the interictal period. This significant increase in HR was validated separately in both focal and generalized seizure groups and was not different between the two groups.

Conclusion

Our study supports previous studies showing the presence of increased peri-ictal HR and also provides new insights by comparing focal and generalized motor seizures. We think that our findings may contribute to the development of early warning signs in epilepsy patients.

Heart Rate Variability for Outcome Prediction in Intracerebral and Subarachnoid Hemorrhage: A Systematic Review

This systematic review presents clinical evidence on the association of heart rate variability with outcome prediction in intracerebral and subarachnoid hemorrhages. The literature search led to the retrieval of 19 significant studies. Outcome prediction included functional outcome, cardiovascular complications, secondary brain injury, and mortality. Various aspects of heart rate recording and analysis, based on linear time and frequency domains and a non-linear entropy approach, are reviewed. Heart rate variability was consistently associated with poor functional outcome and mortality, while controversial results were found regarding the association between heart rate variability and secondary brain injury and cardiovascular complications.

Exploring Autonomic Alterations during Seizures in Temporal Lobe Epilepsy: Insights from a Heart-Rate Variability Analysis

Epilepsy's impact on cardiovascular function and autonomic regulation, including heart-rate variability, is complex and may contribute to sudden unexpected death in epilepsy (SUDEP). Lateralization of autonomic control in the brain remains the subject of debate; nevertheless, ultra-short-term heart-rate variability (HRV) analysis is a useful tool for understanding the pathophysiology of autonomic dysfunction in epilepsy patients. A retrospective study reviewed medical records of patients with temporal lobe epilepsy who underwent presurgical evaluations. Data from 75 patients were analyzed and HRV indices were extracted from electrocardiogram recordings of preictal, ictal, and postictal intervals. Various HRV indices were calculated, including time domain, frequency domain, and nonlinear indices, to assess autonomic function during different seizure intervals. The study found significant differences in HRV indices based on hemispheric laterality, language dominancy, hippocampal atrophy, amygdala enlargement, sustained theta activity, and seizure frequency. HRV indices such as the root mean square of successive differences between heartbeats, pNN50, normalized low-frequency, normalized high-frequency, and the low-frequency/high-frequency ratio exhibited significant differences during the ictal period. Language dominancy, hippocampal atrophy, amygdala enlargement, and sustained theta activity were also found to affect HRV. Seizure frequency was correlated with HRV indices, suggesting a potential relationship with the risk of SUDEP.

Brain Connectivity Correlates of Breathing and Cardiac Irregularities in SUDEP: A Resting-State fMRI Study

Sudden unexpected death in epilepsy (SUDEP) is the leading cause of premature mortality among people with epilepsy. Evidence from witnessed and monitored SUDEP cases indicate seizure-induced cardiovascular and respiratory failures; yet, the underlying mechanisms remain obscure. SUDEP occurs often during the night and early morning hours, suggesting that sleep or circadian rhythm-induced changes in physiology contribute to the fatal event. Resting-state fMRI studies have found altered functional connectivity between brain structures involved in cardiorespiratory regulation in later SUDEP cases and in individuals at high-risk of SUDEP. However, those connectivity findings have not been related to changes in cardiovascular or respiratory patterns. Here, we compared fMRI patterns of brain connectivity associated with regular and irregular cardiorespiratory rhythms in SUDEP cases with those of living epilepsy patients of varying SUDEP risk, and healthy controls. We analysed resting-state fMRI data from 98 patients with epilepsy (9 who subsequently succumbed to SUDEP, 43 categorized as low SUDEP risk (no tonic-clonic seizures (TCS) in the year preceding the fMRI scan), and 46 as high SUDEP risk (>3 TCS in the year preceding the scan)) and 25 healthy controls. The global signal amplitude (GSA), defined as the moving standard deviation of the fMRI global signal, was used to identify periods with regular ('low state') and irregular ('high state') cardiorespiratory rhythms. Correlation maps were derived from seeds in twelve regions with a key role in autonomic or respiratory regulation, for the low and high states. Following principal component analysis, component weights were compared between the groups. We found widespread alterations in connectivity of precuneus/posterior cingulate cortex in epilepsy compared to controls, in the low state (regular cardiorespiratory activity). In the low state, and to a lesser degree in the high state, reduced anterior insula connectivity (mainly with anterior and posterior cingulate cortex) in epilepsy appeared, relative to healthy controls. For SUDEP cases, the insula connectivity differences were inversely related to the interval between the fMRI scan and death. The findings suggest that anterior insula connectivity measures may provide a biomarker of SUDEP risk. The neural correlates of autonomic brain structures associated with different cardiorespiratory rhythms may shed light on the mechanisms underlying terminal apnea observed in SUDEP.

A unified hypothesis of SUDEP: Seizure-induced respiratory depression induced by adenosine may lead to SUDEP but can be prevented by autoresuscitation and other restorative respiratory response mechanisms mediated by the action of serotonin on the periaqueductal gray

Sudden unexpected death in epilepsy (SUDEP) is a major cause of death in people with epilepsy (PWE). Postictal apnea leading to cardiac arrest is the most common sequence of terminal events in witnessed cases of SUDEP, and postconvulsive central apnea has been proposed as a potential biomarker of SUDEP susceptibility. Research in SUDEP animal models has led to the serotonin and adenosine hypotheses of SUDEP. These neurotransmitters influence respiration, seizures, and lethality in animal models of SUDEP, and are implicated in human SUDEP cases. Adenosine released during seizures is proposed to be an important seizure termination mechanism. However, adenosine also depresses respiration, and this effect is mediated, in part, by inhibition of neuronal activity in subcortical structures that modulate respiration, including the periaqueductal gray (PAG). Drugs that enhance the action of adenosine increase postictal death in SUDEP models. Serotonin is also released during seizures, but enhances respiration in response to an elevated carbon dioxide level, which often occurs postictally. This effect of serotonin can potentially compensate, in part, for the adenosine-mediated respiratory depression, acting to facilitate autoresuscitation and other restorative respiratory response mechanisms. A number of drugs that enhance the action of serotonin prevent postictal death in several SUDEP models and reduce postictal respiratory depression in PWE. This effect of serotonergic drugs may be mediated, in part, by actions on brainstem sites that modulate respiration, including the PAG. Enhanced activity in the PAG increases respiration in response to hypoxia and other exigent conditions and can be activated by electrical stimulation. Thus, we propose the unifying hypothesis that seizure-induced adenosine release leads to respiratory depression. This can be reversed by serotonergic action on autoresuscitation and other restorative respiratory responses acting, in part, via the PAG. Therefore, we hypothesize that serotonergic or direct activation of this brainstem site may be a useful approach for SUDEP prevention.

Heart rate variability modifications in adult patients with early versus late-onset temporal lobe epilepsy: A comparative observational study

OBJECTIVES

Temporal lobe epilepsy (TLE) is the most frequent form of focal epilepsy. TLE is associated with cardio-autonomic dysfunction and increased cardiovascular (CV) risk in patients over the fifth decade of age. In these subjects, TLE can be classified as early-onset (EOTLE; i.e., patients who had developed epilepsy in their youth) and late-onset (LOTLE; i.e., patients who developed epilepsy in adulthood). Heart rate variability (HRV) analysis is useful for assessing cardio-autonomic function and identifying patients with increased CV risk. This study compared changes in HRV occurring in patients over the age of 50, with EOTLE or LOTLE.

METHODS

We enrolled twenty-seven adults with LOTLE and 23 with EOTLE. Each patient underwent a EEG and EKG recording during 20-minutes of resting state and a 5-minutes hyperventilation (HV). Short-term HRV analysis was performed both in time and frequency domains. Linear Mixed Models (LMM) were used to analyze HRV parameters according to the condition (baseline and HV) and group (LOTLE and EOTLE groups).

RESULTS

Compared to the LOTLE group, the EOTLE group showed significantly decreased LnRMSSD (natural logarithm of the root mean square of the difference between contiguous RR intervals) (p-value=0.05), LnHF ms² (natural logarithm of high frequency absolute power) (p-value=0.05), HF n.u. (high frequency power expressed in normalized units) (p-value=0.008) and HF% (high frequency power expressed in percentage) (p-value=0.01). In addition, EOTLE patients exhibited increased LF n.u. (low frequency power expressed in normalized units) (p-value=0.008) and LF/HF (low frequency/high frequency) ratio (p-value=0.007). During HV, the LOTLE group exhibited a multiplicative effect for the interaction between group and condition with increased LF n.u. (p = 0.003) and LF% (low frequency expressed in percentage) (p = 0.05) values.

CONCLUSIONS

EOTLE is associated with reduced vagal tone compared to LOTLE. Patients with EOTLE may have a higher risk of developing cardiac dysfunction or cardiac arrhythmia than LOTLE patients.

Cardiac autonomic control in Rett syndrome: Insights from heart rate variability analysis

Rett syndrome (RTT) is a rare and severe neurological disorder mainly affecting females, usually linked to methyl-CpG-binding protein 2 (MECP2) gene mutations. Manifestations of RTT typically include loss of purposeful hand skills, gait and motor abnormalities, loss of spoken language, stereotypic hand movements, epilepsy, and autonomic dysfunction. Patients with RTT have a higher incidence of sudden death than the general population. Literature data indicate an uncoupling between measures of breathing and heart rate control that could offer insight into the mechanisms that lead to greater vulnerability to sudden death. Understanding the neural mechanisms of autonomic dysfunction and its correlation with sudden death is essential for patient care. Experimental evidence for increased sympathetic or reduced vagal modulation to the heart has spurred efforts to develop quantitative markers of cardiac autonomic profile. Heart rate variability (HRV) has emerged as a valuable non-invasive test to estimate the modulation of sympathetic and parasympathetic branches of the autonomic nervous system (ANS) to the heart. This review aims to provide an overview of the current knowledge on autonomic dysfunction and, in particular, to assess whether HRV parameters can help unravel patterns of cardiac autonomic dysregulation in patients with RTT. Literature data show reduced global HRV (total spectral power and R-R mean) and a shifted sympatho-vagal balance toward sympathetic predominance and vagal withdrawal in patients with RTT compared to controls. In addition, correlations between HRV and genotype and phenotype features or neurochemical changes were investigated. The data reported in this review suggest an important impairment in sympatho-vagal balance, supporting possible future research scenarios, targeting ANS.

Effects of anterior thalamic nucleus DBS on interictal heart rate variability in patients with refractory epilepsy

OBJECTIVE

Heart rate variability (HRV) changes were investigated by several studies after resective epilepsy surgery/vagus nerve stimulation. We examined anterior thalamic nucleus (ANT)-deep brain stimulation (DBS) effects on HRV parameters.

METHODS

We retrospectively analyzed 30 drug-resistant epilepsy patients' medical record data and collected electrocardiographic epochs recorded during video- electroencephalography monitoring sessions while awake and during N1- or N2-stage sleep pre-DBS implantation surgery, post-surgery but pre-stimulation, and after stimulation began.

RESULTS

The mean square root of the mean squared differences between successive RR intervals and RR interval standard deviation values differed significantly (p < 0.05) among time-points, showing increased HRV post-surgery. High (0.15-0.4 Hz) and very low frequency (<0.04 Hz) increased, while low frequency (0.04-0.15 Hz) and the LF/HF ratio while awake decreased, suggesting improved autonomic regulation post-surgery. Change of effect size was larger in patients where both activated contacts were located in the ANT than in those where only one or none of the contacts hit the ANT.

CONCLUSIONS

In patients with drug-resistant epilepsy, ANT-DBS might positively influence autonomic regulation, as reflected by increased HRV.

SIGNIFICANCE

To gain a more comprehensive outcome estimation after DBS implantation, we suggest including HRV measures with seizure count in the post-surgery follow-up protocol.

The connection between heart rate variability (HRV), neurological health, and cognition: A literature review

The heart and brain have bi-directional influences on each other, including autonomic regulation and hemodynamic connections. Heart rate variability (HRV) measures variation in beat-to-beat intervals. New findings about disorganized sinus rhythm (erratic rhythm, quantified as heart rate fragmentation, HRF) are discussed and suggest overestimation of autonomic activities in HRV changes, especially during aging or cardiovascular events. When excluding HRF, HRV is regulated via the central autonomic network (CAN). HRV acts as a proxy of autonomic activity and is associated with executive functions, decision-making, and emotional regulation in our health and wellbeing. Abnormal changes of HRV (e.g., decreased vagal functioning) are observed in various neurological conditions including mild cognitive impairments, dementia, mild traumatic brain injury, migraine, COVID-19, stroke, epilepsy, and psychological conditions (e.g., anxiety, stress, and schizophrenia). Efforts are needed to improve the dynamic and intriguing heart-brain interactions.

Modulation of Heart Rate Variability following PAP Ion Magnetic Induction Intervention in Subjects with Chronic Musculoskeletal Pain: A Pilot Randomized Controlled Study

Heart rate variability (HRV) analysis has emerged as a simple and non-invasive technique to indirectly evaluate the autonomic nervous system (ANS), and it is considered a sensible and advanced index of health status. Pulsed electromagnetic fields (PEMFs) are widely used in clinical settings for improving the health status of individuals with chronic musculoskeletal pain. The aim of the present single-blind, randomized, placebo-controlled parallel pilot study was to investigate the acute effect of a single session of PEMFs stimulation by a PAP ion magnetic induction (PAPIMI) device on ANS activity, as measured by HRV, in patients with chronic musculoskeletal pain, and compare such effect with that induced by a sham (control) PAPIMI inductor. Thirty-two patients were randomized into two groups: PAPIMI intervention (PAP) (n = 17) and sham PAPIMI intervention (SHAM-PAP) (n = 15). HRV was assessed before and following the interventions. The PAP group showed a significant increase in all values of the time-domain parameters (SDNN, RMSSD, NN50, and pNN50) and the HF component of HRV, suggesting a parasympathetic effect. In contrast, the SHAM-PAP group showed no significant differences in all HRV indices following the intervention. Preliminary findings suggested that PAPIMI inductor could influence ANS activity and provided initial evidence of the potential physiological response induced by the PAPIMI device.

The mechanism of sudden unexpected death in epilepsy: A mini review

Sudden unexpected death in epilepsy (SUDEP) is defined as a sudden, unexpected, non-traumatic, non-drowning death in a person with epilepsy. SUDEP is generally considered to result from seizure-related cardiac dysfunction, respiratory depression, autonomic nervous dysfunction, or brain dysfunction. Frequency of generalized tonic clonic seizures (GTCS), prone posture, and refractory epilepsy are considered risk factors. SUDEP has also been associated with inherited cardiac ion channel disease and severe obstructive sleep apnea. Most previous studies of SUDEP mechanisms have focused on cardiac and respiratory dysfunction and imbalance of the neural regulatory system. Cardiac-related mechanisms include reduction in heart rate variability and prolongation of QT interval, which can lead to arrhythmias. Laryngospasm and amygdala activation may cause obstructive and central apnea, respectively. Neural mechanisms include impairment of 5-HT and adenosine neuromodulation. The research to date regarding molecular mechanisms of SUDEP is relatively limited. Most studies have focused on p-glycoprotein, catecholamines, potassium channels, and the renin-angiotensin system, all of which affect cardiac and respiratory function.

EEG datasets for seizure detection and prediction- A review

Electroencephalogram (EEG) datasets from epilepsy patients have been used to develop seizure detection and prediction algorithms using machine learning (ML) techniques with the aim of implementing the learned model in a device. However, the format and structure of publicly available datasets are different from each other, and there is a lack of guidelines on the use of these datasets. This impacts the generatability, generalizability, and reproducibility of the results and findings produced by the studies. In this narrative review, we compiled and compared the different characteristics of the publicly available EEG datasets that are commonly used to develop seizure detection and prediction algorithms. We investigated the advantages and limitations of the characteristics of the EEG datasets. Based on our study, we identified 17 characteristics that make the EEG datasets unique from each other. We also briefly looked into how certain characteristics of the publicly available datasets affect the performance and outcome of a study, as well as the influences it has on the choice of ML techniques and preprocessing steps required to develop seizure detection and prediction algorithms. In conclusion, this study provides a guideline on the choice of publicly available EEG datasets to both clinicians and scientists working to develop a reproducible, generalizable, and effective seizure detection and prediction algorithm.

Unexpected cardiorespiratory findings postictally and at rest weeks prior to SUDEP

Introduction

Mechanisms underlying sudden unexpected death in epilepsy (SUDEP) are unclear, but autonomic disorders are thought to play a critical role. However, those dysfunctions have mainly been reported in the peri-ictal context of generalized tonic-clonic seizures. Here, we explored whether heart rate variability (HRV), heart rate (HR), and breathing rate (BR) changes could be observed perictally during focal seizures with or without impaired awareness as well as interictally to assess the risk of SUDEP. We report the case of a 33-year-old patient with drug-resistant bilateral temporal lobe epilepsy who died at home probably from an unwitnessed nocturnal seizure ("probable SUDEP").

Methods

Ictal and interictal HRV as well as postictal cardiorespiratory analyses were conducted to assess autonomic functions and overall SUDEP risk. The SUDEP patient was compared to two living male patients from our local database matched for age, sex, and location of the epileptic focus.

Results

Interictal HRV analysis showed that all sleep HRV parameters and most awake HRV parameters of the SUDEP patient were significantly lower than those of our two control subjects with bitemporal lobe epilepsy without SUDEP (p < 0.01). In two focal with impaired awareness seizures (FIAS) of the SUDEP patient, increased postictal mean HR and reduced preictal mean high frequency signals (HF), known markers of increased seizure severity in convulsive seizures, were seen postictally. Furthermore, important autonomic instability and hypersensitivity were seen through fluctuations in LF/HF ratio following two seizures of the SUDEP patient, with a rapid transition between sympathetic and parasympathetic activity. In addition, a combination of severe hypopnea (202 s) and bradycardia (10 s), illustrating autonomic dysfunction, was found after one of the SUDEP patient's FIAS.

Discussion

The unusual cardiorespiratory and HRV patterns found in this case indicated autonomic abnormalities that were possibly predictive of an increased risk of SUDEP. It will be interesting to perform similar analyses in other SUDEP cases to see whether our findings are anecdotal or instead suggestive of reliable biomarkers of high SUDEP risk in focal epilepsy, in particular focal with or without impaired awareness seizures.

Longitudinally tracking personal physiomes for precision management of childhood epilepsy

Our current understanding of human physiology and activities is largely derived from sparse and discrete individual clinical measurements. To achieve precise, proactive, and effective health management of an individual, longitudinal, and dense tracking of personal physiomes and activities is required, which is only feasible by utilizing wearable biosensors. As a pilot study, we implemented a cloud computing infrastructure to integrate wearable sensors, mobile computing, digital signal processing, and machine learning to improve early detection of seizure onsets in children. We recruited 99 children diagnosed with epilepsy and longitudinally tracked them at single-second resolution using a wearable wristband, and prospectively acquired more than one billion data points. This unique dataset offered us an opportunity to quantify physiological dynamics (e.g., heart rate, stress response) across age groups and to identify physiological irregularities upon epilepsy onset. The high-dimensional personal physiome and activity profiles displayed a clustering pattern anchored by patient age groups. These signatory patterns included strong age and sex-specific effects on varying circadian rhythms and stress responses across major childhood developmental stages. For each patient, we further compared the physiological and activity profiles associated with seizure onsets with the personal baseline and developed a machine learning framework to accurately capture these onset moments. The performance of this framework was further replicated in another independent patient cohort. We next referenced our predictions with the electroencephalogram (EEG) signals on selected patients and demonstrated that our approach could detect subtle seizures not recognized by humans and could detect seizures prior to clinical onset. Our work demonstrated the feasibility of a real-time mobile infrastructure in a clinical setting, which has the potential to be valuable in caring for epileptic patients. Extension of such a system has the potential to be leveraged as a health management device or longitudinal phenotyping tool in clinical cohort studies.

Electroencephalogram and heart rate variability features as predictors of responsiveness to vagus nerve stimulation in patients with epilepsy: a systematic review

INTRODUCTION

Vagus nerve stimulation (VNS) is a mainstay treatment in people with medically refractive epilepsy with a growing interest to identify biomarkers that are predictive of VNS efficacy. In this review, we looked at electroencephalography (EEG) and heart rate variability (HRV) parameters as potential biomarkers.

METHODOLOGY

A comprehensive search of several databases limited to the English language and excluding animal studies was conducted. Data was collected from studies that specifically reviewed preoperative EEG and HRV characteristics as predictive factors of VNS outcomes.

RESULTS

Ten out of 1078 collected studies were included in this review, of which EEG characteristics were reported in seven studies; HRV parameters were reported in two studies, and one study reported both. For EEG, studies reported a lower global rate of synchronization in alpha, delta, and gamma waves as predictors of the VNS response. The P300 wave, an evoked response on EEG, had conflicting results. Two studies reported high P300 wave amplitudes in nonresponders and low amplitudes in responders, whereas another study reported high P300 wave amplitudes in responders. For HRV, one study reported high-frequency power as the only parameter to be significantly lower in responders. In contrast, two studies from the same authors showed that HRV parameters were not different between responders and nonresponders.

CONCLUSION

HRV parameters and EEG characteristics including focal seizures and P300 wave have been reported as potential biomarkers for VNS outcomes in people with medically refractive epilepsy. However, the contradictory findings imply a need for validation through clinical trials.

Protocols for multimodal polygraphy for cardiorespiratory monitoring in the epilepsy monitoring unit. Part II - Research acquisition

Multimodal polygraphy including cardiorespiratory monitoring is a valuable tool for epilepsy and sudden unexpected death in epilepsy (SUDEP) research. Broader applications in research into stress, anxiety, mood and other domains exist. Polygraphy techniques used during video electroencephalogram (EEG) recordings provide information on cardiac and respiratory changes in the peri-ictal period. In addition, such monitoring in brain mapping during chronic intracranial EEG evaluations has helped the understanding of pathomechanisms that lead to seizure induced cardiorespiratory dysfunction. Our aim here is to provide protocols and information on devices that may be used in the Epilepsy Monitoring Unit, in addition to proposed standard of care data acquisition. These devices include oronasal thermistors, oronasal pressure transducers, capnography, transcutaneous CO2 sensors, and continuous noninvasive blood pressure monitoring. Standard protocols for cardiorespiratory monitoring simultaneously with video EEG recording, may be useful in the study of cardiorespiratory phenomena in persons with epilepsy.

Impaired Functional Homotopy and Topological Properties Within the Default Mode Network of Children With Generalized Tonic-Clonic Seizures: A Resting-State fMRI Study

Introduction

The aim of the present study was to examine interhemispheric functional connectivity (FC) and topological organization within the default-mode network (DMN) in children with generalized tonic-clonic seizures (GTCS).

Methods

Resting-state functional MRI was collected in 24 children with GTCS and 34 age-matched typically developing children (TDC). Between-group differences in interhemispheric FC were examined by an automated voxel-mirrored homotopic connectivity (VMHC) method. The topological properties within the DMN were also analyzed using graph theoretical approaches. Consistent results were detected and the VMHC values were extracted as features in machine learning for subject classification.

Results

Children with GTCS showed a significant decrease in VMHC in the DMN, including the hippocampal formation (HF), lateral temporal cortex (LTC), and angular and middle frontal gyrus. Although the patients exhibited efficient small-world properties of the DMN similar to the TDC, significant changes in regional topological organization were found in the patients, involving the areas of the bilateral temporal parietal junction, bilateral LTC, left temporal pole, and HF. Within the DMN, disrupted interhemispheric FC was found between the bilateral HF and LTC, which was consistent with the VMHC results. The VMHC values in bilateral HF and LTC were significantly correlated with clinical information in patients. Support vector machine analysis using average VMHC information in the bilateral HF and LTC as features achieved a correct classification rate of 89.34% for the classification.

Conclusion

These results indicate that decreased homotopic coordination in the DMN can be used as an effective biomarker to reflect seizure effects and to distinguish children with GTCSs from TDC.

Interictal Heart Rate Variability as a Biomarker for Comorbid Depressive Disorders among People with Epilepsy

Depressive disorders are common among people with epilepsy (PwE). We here aimed to report an unbiased automatic classification of epilepsy comorbid depressive disorder cases via training a linear support vector machine (SVM) model using the interictal heart rate variability (HRV) data. One hundred and eighty-six subjects participated in this study. Among all participants, we recorded demographic information, epilepsy states and neuropsychiatric features. For each subject, we performed simultaneous electrocardiography and electroencephalography recordings both in wakefulness and non-rapid eye movement (NREM) sleep stage. Using these data, we systematically explored the full parameter space in order to determine the most effective combinations of data to classify the depression status in PwE. PwE with depressive disorders exhibited significant alterations in HRV parameters, including decreased time domain and nonlinear domain values both in wakefulness and NREM sleep stage compared with without depressive disorders and non-epilepsy controls. Interestingly, PwE without depressive disorder showed the same level of HRV values as the non-epilepsy control subjects. The SVM classification model of PwE depression status achieved a higher classification accuracy with the combination of HRV parameters in wakefulness and NREM sleep stage. Furthermore, the receiver operating characteristic (ROC) curve of the SVM classification model showed a satisfying area under the ROC curve (AUC: 0.758). Intriguingly, we found that the HRV measurements during NREM sleep are particularly important for correct classification, suggesting a mechanistic link between the dysregulation of heart rate during sleep and the development of depressive disorders in PwE. Our classification model may provide an objective measurement to assess the depressive status in PwE.

Heart rate variability is reduced during the menstrual phase in women with catamenial C1-type temporal lobe epilepsy

INTRODUCTION

Temporal lobe epilepsy (TLE) is the most frequent focal epilepsy in adulthood. Catamenial C1-type TLE, is characterized by a cyclic seizure exacerbation during the menstrual phase. The heart rate variability (HRV) analysis assesses cardiac autonomic control and may represent a biomarker for Sudden Unexpected Death in Epilepsy (SUDEP). It is plausible that female sex hormones can influence HRV. These changes might be more pronounced in patients suffering from catamenial C1-type TLE where hormonal changes also increase seizure susceptibility. To that aim, we evaluated HRV changes during the menstrual phase of women suffering from catamenial C1-type TLE.

METHODS

We enrolled 12 adults with a diagnosis of catamenial C1-type TLE (Catamenial Group) and 12 age-, and seizure-frequency-matched controls with TLE (Non-Catamenial Group). Each patient underwent a 20-minute EEG + EKG recording in resting state during the menstrual phase. HRV parameters were calculated with a short-lasting analysis of EKG records. Time domain-related, frequency domain-related, as well as non-linear analysis parameters, were compared between the two groups.

RESULT

Compared to the Non-Catamenial Group, the Catamenial Group showed significant reductions in SDNN (p-value = 0.01), RMSSD (p-value = 0.04), pNN50 (p-value = 0.001), LnLF ms² (p-value = 0.05), LnHF ms² (p-value = 0.007), SD1 (p-value = 0.02), and SD2 (p-value = 0.01). These results were independent from age, disease duration, numbers of ASM, and seizure etiology.

CONCLUSION

Our data provide experimental evidence that vagal output is reduced during the menstrual phase in patients with catamenial C1-type TLE. These results indicate that, during the menstrual phase, patients with catamenial C1-type TLE may be at a higher risk of developing cardiac dysfunctions and SUDEP.

Association of Short-term Heart Rate Variability and Sudden Unexpected Death in Epilepsy

BACKGROUND AND OBJECTIVES

We compared heart rate variability (HRV) in sudden unexpected death in epilepsy (SUDEP) cases and living epilepsy controls.

METHODS

This international, multicenter, retrospective, nested case-control study examined patients admitted for video-EEG monitoring (VEM) between January 1, 2003, and December 31, 2014, and subsequently died of SUDEP. Time domain and frequency domain components were extracted from 5-minute interictal ECG recordings during sleep and wakefulness from SUDEP cases and controls.

RESULTS

We identified 31 SUDEP cases and 56 controls. Normalized low-frequency power (LFP) during wakefulness was lower in SUDEP cases (median 42.5, interquartile range [IQR] 32.6-52.6) than epilepsy controls (55.5, IQR 40.7-68.9; p = 0.015, critical value = 0.025). In the multivariable model, normalized LFP was lower in SUDEP cases compared to controls (contrast -11.01, 95% confidence interval [CI] -20.29 to 1.73; p = 0.020, critical value = 0.025). There was a negative correlation between LFP and the latency to SUDEP, where each 1% incremental reduction in normalized LFP conferred a 2.7% decrease in the latency to SUDEP (95% CI 0.95-0.995; p = 0.017, critical value = 0.025). Increased survival duration from VEM to SUDEP was associated with higher normalized high-frequency power (HFP; p = 0.002, critical value = 0.025). The survival model with normalized LFP was associated with SUDEP (c statistic 0.66, 95% CI 0.55-0.77), which nonsignificantly increased with the addition of normalized HFP (c statistic 0.70, 95% CI 0.59-0.81; p = 0.209).

CONCLUSIONS

Reduced short-term LFP, which is a validated biomarker for sudden death, was associated with SUDEP. Increased HFP was associated with longer survival and may be cardioprotective in SUDEP. HRV quantification may help stratify individual SUDEP risk.

CLASSIFICATION OF EVIDENCE

This study provides Class III evidence that in patients with epilepsy, some measures of HRV are associated with SUDEP.

Heart rate variability alterations in Dravet Syndrome: The role of status epilepticus and a possible association with mortality risk

PURPOSE

Preliminary data suggest that patients with Dravet Syndrome (DS) have a reduced heart rate variability (HRV). This seems particularly evident in patients who experienced sudden unexpected death in epilepsy (SUDEP). This study aims at confirming these findings in a larger cohort and at defining clinical, genetic or electroencephalographic predictors of HRV impairment in DS patients.

METHODS

DS patients followed at our Institution performed a 24h-ECG Holter to derive HRV parameters. We used as control population patients with epilepsy (PWEs) and healthy controls (HCs). In DS patients, we assessed the impact of different clinical, neurophysiological and genetic features on HRV alterations through multiple linear regression. After a mean follow-up of 7.4 ± 3.2 years since the HRV assessment, all DS patients were contacted to record death or life-threatening events.

RESULTS

56 DS patients had a significantly reduced HRV compared to both HCs and PWEs. A recent history of status epilepticus (SE) was the only significant predictor of lower HRV in the multivariate analysis. At follow-up, only one patient died; her HRV was lower than that of all the controls and was in the low range for DS patients.

CONCLUSION

We describe for the first time an association between SE and HRV alterations in DS. Further studies on other SCN1A-related phenotypes and other epilepsies with frequent SE will help clarify this finding. Compared to the literature, our cohort showed better HRV and lower mortality. Although limited, this observation reinforces the role of HRV as a biomarker for mortality risk in DS.

Interictal autonomic dysfunction in patients with epilepsy

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, impaired BP responses during standing, isometric hand grip, and mental arithmetic. Also, prolonged SSR latencies. Within PwE group, no difference was noticed between males and females, nor between the left and right temporal lobes.

Conclusion

Abnormal autonomic (sympathetic and parasympathetic) regulatory functions suggest that epilepsy may alter the autonomic function and this is not only in TLE but rather in IGE too. These autonomic changes are irrespective of the localization of epilepsy between the two hemispheres. The ANS changes in epileptic patients, particularly those with autonomic symptoms, confirm that electrophysiologic measures of autonomic function may be of value in preventing sudden unexpected death in epilepsy.

Cerebral and systemic hemodynamic effect of recurring seizures

The increase in neuronal activity induced by a single seizure is supported by a rise in the cerebral blood flow and tissue oxygenation, a mechanism called neurovascular coupling (NVC). Whether cerebral and systemic hemodynamics are able to match neuronal activity during recurring seizures is unclear, as data from rodent models are at odds with human studies. In order to clarify this issue, we used an invasive brain and systemic monitoring to study the effects of chemically induced non-convulsive seizures in sheep. Despite an increase in neuronal activity as seizures repeat (Spearman’s ρ coefficient 0.31, P < 0.001), ictal variations of cerebral blood flow remained stable while it progressively increased in the inter-ictal intervals (ρ = 0.06, P = 0.44 and ρ = 0.22; P = 0.008). We also observed a progressive reduction in the inter-ictal brain tissue oxygenation (ρ =  − 0.18; P = 0.04), suggesting that NVC was unable to compensate for the metabolic demand of these closely repeating seizures. At the systemic level, there was a progressive reduction in blood pressure and a progressive rise in cardiac output (ρ =  − 0.22; P = 0.01 and ρ = 0.22; P = 0.01, respectively), suggesting seizure-induced autonomic dysfunction.

Heart Rate Variability in Insulo-Opercular Epilepsy

Background: We aimed to evaluate heart rate variability (HRV) changes in insulo-opercular epilepsy (IOE) and after insulo-opercular surgery. Methods: We analyzed 5-min resting HRV of IOE patients before and after surgery. Patients’ SUDEP-7 risk inventory scores were also calculated. Results were compared with age- and sex-matched patients with temporal lobe epilepsy (TLE) and healthy individuals. Results: There were no differences in HRV measurements between IOE, TLE, and healthy control groups (and within each IOE group and TLE group) in preoperative and postoperative periods. In IOE patients, the SUDEP-7 score was positively correlated with pNN50 (percentage of successive RR intervals that differ by more than 50 ms) (p = 0.008) and RMSSD (root mean square of successive RR interval differences) (p = 0.019). We stratified IOE patients into those whose preoperative RMSSD values were below (Group 1a = 7) versus above (Group 1b = 9) a cut-off threshold of 31 ms (median value of a healthy population from a previous study). In group 1a, all HRV values significantly increased after surgery. In group 1b, time-domain parameters significantly decreased postoperatively. Conclusions: Our results suggest that in IOE, HRV may be either decreased in parasympathetic tone or increased globally in both sympathetic and parasympathetic tones. We found no evidence that insulo-opercular surgeries lead to major autonomic dysfunction when a good seizure outcome is reached. The increase in parasympathetic tone observed preoperatively may be of clinical concern, as it was positively correlated with the SUDEP-7 score.

SUDEP risk and autonomic dysfunction in genetic epilepsies

The underlying pathophysiology of sudden unexpected death in epilepsy (SUDEP) remains unclear. This phenomenon is likely multifactorial, and there is considerable evidence that genetic factors play a role. There are certain genetic causes of epilepsy in which the risk of SUDEP appears to be increased relative to epilepsy overall. For individuals with pathogenic variants in genes including SCN1A, SCN1B, SCN8A, SCN2A, GNB5, KCNA1 and DEPDC5, there are varying degrees of evidence to suggest an increased risk for sudden death. Why the risk for sudden death is higher is not completely clear; however, in many cases pathogenic variants in these genes are also associated with autonomic dysfunction, which is hypothesized as a contributing factor to SUDEP. We review the evidence for increased SUDEP risk for patients with epilepsy due to pathogenic variants in these genes, and also discuss what is known about autonomic dysfunction in these contexts.

Autonomic manifestations of epilepsy: emerging pathways to sudden death?

Epileptic networks are intimately connected with the autonomic nervous system, as exemplified by a plethora of ictal (during a seizure) autonomic manifestations, including epigastric sensations, palpitations, goosebumps and syncope (fainting). Ictal autonomic changes might serve as diagnostic clues, provide targets for seizure detection and help us to understand the mechanisms that underlie sudden unexpected death in epilepsy (SUDEP). Autonomic alterations are generally more prominent in focal seizures originating from the temporal lobe, demonstrating the importance of limbic structures to the autonomic nervous system, and are particularly pronounced in focal-to-bilateral and generalized tonic-clonic seizures. The presence, type and severity of autonomic features are determined by the seizure onset zone, propagation pathways, lateralization and timing of the seizures, and the presence of interictal autonomic dysfunction. Evidence is mounting that not all autonomic manifestations are linked to SUDEP. In addition, experimental and clinical data emphasize the heterogeneity of SUDEP and its infrequent overlap with sudden cardiac death. Here, we review the spectrum and diagnostic value of the mostly benign and self-limiting autonomic manifestations of epilepsy. In particular, we focus on presentations that are likely to contribute to SUDEP and discuss how wearable devices might help to prevent SUDEP.

Heart rate variability in patients with refractory epilepsy: The influence of generalized convulsive seizures

OBJECTIVE

Patients with epilepsy, mainly drug-resistant, have reduced heart rate variability (HRV), linked to an increased risk of sudden death in various other diseases. In this context, it could play a role in SUDEP. Generalized convulsive seizures (GCS) are one of the most consensual risk factors for SUDEP. Our objective was to assess the influence of GCS in HRV parameters in patients with drug-resistant epilepsy.

METHODS

We prospectively evaluated 121 patients with refractory epilepsy admitted to our Epilepsy Monitoring Unit. All patients underwent a 48-hour Holter recording. Only patients with GCS were included (n = 23), and we selected the first as the index seizure. We evaluated HRV (AVNN, SDNN, RMSSD, pNN50, LF, HF, and LF/HF) in 5-min epochs (diurnal and nocturnal baselines; preictal - 5 min before the seizure; ictal; postictal - 5 min after the seizure; and late postictal - >5 h after the seizure). These data were also compared with normative values from a healthy population (controlling for age and gender).

RESULTS

We included 23 patients, with a median age of 36 (min-max, 16-55) years and 65% were female. Thirty percent had cardiovascular risk factors, but no previously known cardiac disease. HRV parameters AVNN, RMSSD, pNN50, and HF were significantly lower in the diurnal than in the nocturnal baseline, whereas the opposite occurred with LF/HF and HR. Diurnal baseline parameters were inferior to the normative population values (which includes only diurnal values). We found significant differences in HRV parameters between the analyzed periods, especially during the postictal period. All parameters but LF/HF suffered a reduction in that period. LF/HF increased in that period but did not reach statistical significance. Visually, there was a tendency for a global reduction in our patients' HRV parameters, namely AVNN, RMSSD, and pNN50, in each period, comparing with those from a normative healthy population. No significant differences were found in HRV between diurnal and nocturnal seizures, between temporal lobe and extra-temporal-lobe seizures, between seizures with and without postictal generalized EEG suppression, or between seizures of patients with and without cardiovascular risk factors.

SIGNIFICANCE/CONCLUSION

Our work reinforces the evidence of autonomic cardiac dysfunction in patients with refractory epilepsy, at baseline and mainly in the postictal phase of a GCS. Those changes may have a role in some SUDEP cases. By identifying patients with worse autonomic cardiac function, HRV could fill the gap of a lacking SUDEP risk biomarker.

Pre- and postoperative heart rate variability and vagus nerve stimulation in patients with drug-resistant epilepsy - A meta-analysis

OBJECTIVE

The effect of vagus nerve stimulation (VNS), an important auxiliary therapy for treating drug-resistant epilepsy (DRE), on autonomic nerve function is still controversial. Heart rate variability is a widely used indicator of autonomic nerve function. To clarify the relationship between VNS and heart rate variability (HRV), we performed a meta-analysis to systematically evaluate the effect of VNS on HRV in patients with epilepsy.

METHODS

We performed a systematic review by searching the following online databases: PubMed, Web of Science, EMBASE and the Cochrane Library. The key search terms were "vagal nerve stimulation," "epilepsy" and "heart rate variability". Other features of VNS in patients with epilepsy include postoperative changes in low-frequency (LF), high-frequency (HF) and low-frequency/high-frequency (LF/HF) heart rate variability, which were used as evaluation indices, and the Newcastle-Ottawa Quality Assessment Scale and Stata 14.0 statistical software were used for literature quality evaluation and meta-analysis.

RESULTS

Twelve studies published in English were obtained, and 229 patients with epilepsy who underwent VNS were ultimately included after elimination of duplicate articles and those that did not meet the inclusion criteria. Regarding LF heart rate variability, in the response subgroup, patients with DRE with VNS presented a lower value (-0.58) before surgery than after surgery, with a 95% confidence interval (CI) ranging from -1.00 to -0.15. For HF heart rate variability, patients with DRE with VNS had a lower value (-0.45) before surgery than after surgery in the response subgroup, with a 95% CI ranging from -0.74 to -0.17. No differences were found for LF/HF values or the LF and HF values of other subgroups.

CONCLUSION

VNS has little effect on the balance of sympathetic and parasympathetic nerve activity and would not be expected to cause cardiovascular autonomic dysfunction in patients with DRE. For patients with DRE, VNS can control seizures and has little effect on autonomic nervous function.

Altered cardiac structure and function is related to seizure frequency in a rat model of chronic acquired temporal lobe epilepsy

OBJECTIVE

This study aimed to prospectively examine cardiac structure and function in the kainic acid-induced post-status epilepticus (post-KA SE) model of chronic acquired temporal lobe epilepsy (TLE), specifically to examine for changes between the pre-epileptic, early epileptogenesis and the chronic epilepsy stages. We also aimed to examine whether any changes related to the seizure frequency in individual animals.

METHODS

Four hours of SE was induced in 9 male Wistar rats at 10 weeks of age, with 8 saline treated matched control rats. Echocardiography was performed prior to the induction of SE, two- and 10-weeks post-SE. Two weeks of continuous video-EEG and simultaneous ECG recordings were acquired for two weeks from 11 weeks post-KA SE. The video-EEG recordings were analyzed blindly to quantify the number and severity of spontaneous seizures, and the ECG recordings analyzed for measures of heart rate variability (HRV). PicroSirius red histology was performed to assess cardiac fibrosis, and intracellular Ca²⁺ levels and cell contractility were measured by microfluorimetry.

RESULTS

All 9 post-KA SE rats were demonstrated to have spontaneous recurrent seizures on the two-week video-EEG recording acquired from 11 weeks SE (seizure frequency ranging from 0.3 to 10.6 seizures/day with the seizure durations from 11 to 62 s), and none of the 8 control rats. Left ventricular wall thickness was thinner, left ventricular internal dimension was shorter, and ejection fraction was significantly decreased in chronically epileptic rats, and was negatively correlated to seizure frequency in individual rats. Diastolic dysfunction was evident in chronically epileptic rats by a decrease in mitral valve deceleration time and an increase in E/E` ratio. Measures of HRV were reduced in the chronically epileptic rats, indicating abnormalities of cardiac autonomic function. Cardiac fibrosis was significantly increased in epileptic rats, positively correlated to seizure frequency, and negatively correlated to ejection fraction. The cardiac fibrosis was not a consequence of direct effect of KA toxicity, as it was not seen in the 6/10 rats from separate cohort that received similar doses of KA but did not go into SE. Cardiomyocyte length, width, volume, and rate of cell lengthening and shortening were significantly reduced in epileptic rats.

SIGNIFICANCE

The results from this study demonstrate that chronic epilepsy in the post-KA SE rat model of TLE is associated with a progressive deterioration in cardiac structure and function, with a restrictive cardiomyopathy associated with myocardial fibrosis. Positive correlations between seizure frequency and the severity of the cardiac changes were identified. These results provide new insights into the pathophysiology of cardiac disease in chronic epilepsy, and may have relevance for the heterogeneous mechanisms that place these people at risk of sudden unexplained death.

Exploring factors associated with interictal heart rate variability in patients with medically controlled focal epilepsy

PURPOSE

Heart rate variability (HRV) reflects the balance between the functional outputs of the sympathetic and parasympathetic nervous systems. It is lower in patients with epilepsy than in the healthy controls. However, HRV has been inadequately studied in different patient subgroups with medically controlled epilepsy. Hence, this study aimed to investigate factors associated with interictal HRV in patients with medically controlled epilepsy.

METHODS

This retrospective cohort study included 54 patients (24 males and 30 females) with medically controlled focal epilepsy who only received monotherapy to eliminate the confounding effect of different antiseizure medications (ASMs). Patients with major systemic or psychiatric disorder comorbidities were excluded. For HRV analysis, electroencephalography and 5-minute well-qualified electrocardiogram segment recording were conducted during stage N1 or N2 sleep. In addition, the association between age, gender, seizure onset type, ASMs, and the time domain and frequency-domain HRV measures was analyzed.

RESULTS

HRV negatively correlated with advanced age. Patients with focal to bilateral tonic-clonic seizure (FBTCS) had a significantly lower HRV than focal impaired awareness seizures (FIAS). HRV was not associated with any gender and ASMs.

CONCLUSIONS

HRV negatively correlated with age, and patients with FBTCS had a decreased HRV. Thus, these patients may have a declining autonomic function. Therefore, different seizure types may carry different risks of autonomic dysfunction in patients with medically controlled focal epilepsy.

Left ventricular dysfunction and cardiac autonomic imbalance in children with drug-resistant epilepsy

BACKGROUND

Resistance to antiepileptic drug treatment increases the risk of comorbidities and mortality due to a cardio-autonomic imbalance and left ventricular (LV) dysfunction.

OBJECTIVE

To assess the prevalence of LV dysfunction and cardio-autonomic imbalance in children with drug-resistant epilepsy (DRE).

PATIENTS AND METHODS

This cross-sectional study included 40 children with DRE and 40 healthy age- and sex-matched controls. LV function was evaluated by M-mode, two-dimensional, pulse-wave Doppler echocardiography, and tissue Doppler imaging (TDI). Cardio-autonomic function was assessed by 24 -h Holter monitoring of heart rate variability.

RESULTS

All time domain measures were significantly lower in the epilepsy group than in the control group (all Ps<0.01). Additionally, the mean high frequency (HF) parameters were significantly lower (P = 0.035), whereas the mean low frequency (LF) parameters and the LF/HF ratio were significantly higher (P < 0.001) in the epilepsy group than in the control group. LV function did not differ between groups regarding all standard echocardiographic parameters. There was evidence of subclinical LVdysfunction by tissue doppler among the epileptic group, as evidenced by the elevated Myocardial Performance Index, isovolumetric relaxation time and mitral E/Em ratio. There was no significant correlation between the duration of epilepsy or seizure frequency with any cardiac abnormality.

CONCLUSIONS

Children with DRE exhibited cardio-autonomic and subclinical LV dysfunction, independent of the duration of epilepsy, frequency, and seizure type.

Comparing Ictal Cardiac Autonomic Changes in Patients with Frontal Lobe Epilepsy and Temporal Lobe Epilepsy by Ultra-Short-Term Heart Rate Variability Analysis

Background and Objectives: Abnormal epileptic discharges in the brain can affect the central brain regions that regulate autonomic activity and produce cardiac symptoms, either at onset or during propagation of a seizure. These autonomic alterations are related to cardiorespiratory disturbances, such as sudden unexpected death in epilepsy. This study aims to investigate the differences in cardiac autonomic function between patients with temporal lobe epilepsy (TLE) and frontal lobe epilepsy (FLE) using ultra-short-term heart rate variability (HRV) analysis around seizures. Materials and Methods: We analyzed electrocardiogram (ECG) data recorded during 309 seizures in 58 patients with epilepsy. Twelve patients with FLE and 46 patients with TLE were included in this study. We extracted the HRV parameters from the ECG signal before, during and after the ictal interval with ultra-short-term HRV analysis. We statistically compared the HRV parameters using an independent t-test in each interval to compare the differences between groups, and repeated measures analysis of variance was used to test the group differences in longitudinal changes in the HRV parameters. We performed the Tukey-Kramer multiple comparisons procedure as the post hoc test. Results: Among the HRV parameters, the mean interval between heartbeats (RRi), normalized low-frequency band power (LF) and LF/HF ratio were statistically different between the interval and epilepsy types in the t-test. Repeated measures ANOVA showed that the mean RRi and RMSSD were significantly different by epilepsy type, and the normalized LF and LF/HF ratio significantly interacted with the epilepsy type and interval. Conclusions: During the pre-ictal interval, TLE patients showed an elevation in sympathetic activity, while the FLE patients showed an apparent increase and decrease in sympathetic activity when entering and ending the ictal period, respectively. The TLE patients showed a maintained elevation of sympathetic and vagal activity in the pos-ictal interval. These differences in autonomic cardiac characteristics between FLE and TLE might be relevant to the ictal symptoms which eventually result in SUDEP.

Altered Relationship Between Heart Rate Variability and fMRI-Based Functional Connectivity in People With Epilepsy

Background: Disruptions in central autonomic processes in people with epilepsy have been studied through evaluation of heart rate variability (HRV). Decreased HRV appears in epilepsy compared to healthy controls, suggesting a shift in autonomic balance toward sympathetic dominance; recent studies have associated HRV changes with seizure severity and outcome of interventions. However, the processes underlying these autonomic changes remain unclear. We examined the nature of these changes by assessing alterations in whole-brain functional connectivity, and relating those alterations to HRV. Methods: We examined regional brain activity and functional organization in 28 drug-resistant epilepsy patients and 16 healthy controls using resting-state functional magnetic resonance imaging (fMRI). We employed an HRV state-dependent functional connectivity (FC) framework with low and high HRV states derived from the following four cardiac-related variables: 1. RR interval, 2. root mean square of successive differences (RMSSD), 4. low-frequency HRV (0.04-0.15 Hz; LF-HRV) and high-frequency HRV (0.15-0.40 Hz; HF-HRV). The effect of group (epilepsy vs. controls), HRV state (low vs. high) and the interactions of group and state were assessed using a mixed analysis of variance (ANOVA). We assessed FC within and between 7 large-scale functional networks consisting of cortical regions and 4 subcortical networks, the amygdala, hippocampus, basal ganglia and thalamus networks. Results: Consistent with previous studies, decreased RR interval (increased heart rate) and decreased HF-HRV appeared in people with epilepsy compared to healthy controls. For both groups, fluctuations in heart rate were positively correlated with BOLD activity in bilateral thalamus and regions of the cerebellum, and negatively correlated with BOLD activity in the insula, putamen, superior temporal gyrus and inferior frontal gyrus. Connectivity strength in patients between right thalamus and ventral attention network (mainly insula) increased in the high LF-HRV state compared to low LF-HRV; the opposite trend appeared in healthy controls. A similar pattern emerged for connectivity between the thalamus and basal ganglia. Conclusion: The findings suggest that resting connectivity patterns between the thalamus and other structures underlying HRV expression are modified in people with drug-resistant epilepsy compared to healthy controls.

Cardiorespiratory findings in epilepsy: A recent review on outcomes and pathophysiology

Epilepsy is a debilitating disorder of uncontrollable recurrent seizures that occurs as a result of imbalances in the brain excitatory and inhibitory neuronal signals, that could stem from a range of functional and structural neuronal impairments. Globally, nearly 70 million people are negatively impacted by epilepsy and its comorbidities. One such comorbidity is the effect epilepsy has on the autonomic nervous system (ANS), which plays a role in the control of blood circulation, respiration and gastrointestinal function. These epilepsy-induced impairments in the circulatory and respiratory systems may contribute toward sudden unexpected death in epilepsy (SUDEP). Although, various hypotheses have been proposed regarding the role of epilepsy on ANS, the linking pathological mechanism still remains unclear. Channelopathies and seizure-induced damages in ANS-control brain structures were some of the causal/pathological candidates of cardiorespiratory comorbidities in epilepsy patients, especially in those who were drug resistant. However, emerging preclinical research suggest that neurotransmitter/receptor dysfunction and synaptic changes in the ANS may also contribute to the epilepsy-related autonomic disorders. Thus, pathological mechanisms of cardiorespiratory dysfunction should be elucidated by considering the modifications in anatomy and physiology of the autonomic system caused by seizures. In this regard, we present a comprehensive review of the current literature, both clinical and preclinical animal studies, on the cardiorespiratory findings in epilepsy and elucidate the possible pathological mechanisms of these findings, in hopes to prevent SUDEP especially in patients who are drug resistant.

The brain-heart interaction in epilepsy: implications for diagnosis, therapy, and SUDEP prevention

The influence of the central nervous system and autonomic system on cardiac activity is being intensively studied, as it contributes to the high rate of cardiologic comorbidities observed in people with epilepsy. Indeed, neuroanatomic connections between the brain and the heart provide links that allow cardiac arrhythmias to occur in response to brain activation, have been shown to produce arrhythmia both experimentally and clinically. Moreover, seizures may induce a variety of transient cardiac effects, which include changes in heart rate, heart rate variability, arrhythmias, asystole, and other ECG abnormalities, and can trigger the development of Takotsubo syndrome. People with epilepsy are at a higher risk of death than the general population, and sudden unexpected death in epilepsy (SUDEP) is the most important direct epilepsy-related cause of death. Although the cause of SUDEP is still unknown, cardiac abnormalities during and between seizures could play a significant role in its pathogenesis, as highlighted by studies on animal models of SUDEP and registration of SUDEP events. Recently, genetic mutations in genes co-expressed in the heart and brain, which may result in epilepsy and cardiac comorbidity/increased risk for SUDEP, have been described. Recognition and a better understanding of brain-heart interactions, together with new advances in sequencing techniques, may provide new insights into future novel therapies and help in the prevention of cardiac dysfunction and sudden death in epileptic individuals.