The yield of long-term electrocardiographic recordings in refractory focal epilepsy.

OBJECTIVE: To determine the incidence of clinically relevant arrhythmias in refractory focal epilepsy and to assess the potential of postictal arrhythmias as risk markers for sudden unexpected death in epilepsy (SUDEP). METHODS: We recruited people with refractory focal epilepsy without signs of ictal asystole and who had at least one focal seizure per month and implanted a loop recorder with 2-year follow-up. The devices automatically record arrhythmias. Subjects and caregivers were instructed to make additional peri-ictal recordings. Clinically relevant arrhythmias were defined as asystole ≥ 6 seconds; atrial fibrillation < 55 beats per minute (bpm), or > 200 bpm and duration > 30 seconds; persistent sinus bradycardia < 40 bpm while awake; and second- or third-degree atrioventricular block and ventricular tachycardia/fibrillation. We performed 12-lead electrocardiography (ECG) and tilt table testing to identify non-seizure-related causes of asystole. RESULTS: We included 49 people and accumulated 1060 months of monitoring. A total of 16 474 seizures were reported, of which 4679 were captured on ECG. No clinically relevant arrhythmias were identified. Three people had a total of 18 short-lasting (<6 seconds) periods of asystole, resulting in an incidence of 2.91 events per 1000 patient-months. None of these coincided with a reported seizure; one was explained by micturition syncope. Other non-clinically relevant arrhythmias included paroxysmal atrial fibrillation (n = 2), supraventricular tachycardia (n = 1), and sinus tachycardia with a right bundle branch block configuration (n = 1). SIGNIFICANCE: We found no clinically relevant arrhythmias in people with refractory focal epilepsy during long-term follow-up. The absence of postictal arrhythmias does not support the use of loop recorders in people at high SUDEP risk.

Dynamics of convulsive seizure termination and postictal generalized EEG suppression.

It is not fully understood how seizures terminate and why some seizures are followed by a period of complete brain activity suppression, postictal generalized EEG suppression. This is clinically relevant as there is a potential association between postictal generalized EEG suppression, cardiorespiratory arrest and sudden death following a seizure. We combined human encephalographic seizure data with data of a computational model of seizures to elucidate the neuronal network dynamics underlying seizure termination and the postictal generalized EEG suppression state. A multi-unit computational neural mass model of epileptic seizure termination and postictal recovery was developed. The model provided three predictions that were validated in EEG recordings of 48 convulsive seizures from 48 subjects with refractory focal epilepsy (20 females, age range 15-61 years). The duration of ictal and postictal generalized EEG suppression periods in human EEG followed a gamma probability distribution indicative of a deterministic process (shape parameter 2.6 and 1.5, respectively) as predicted by the model. In the model and in humans, the time between two clonic bursts increased exponentially from the start of the clonic phase of the seizure. The terminal interclonic interval, calculated using the projected terminal value of the log-linear fit of the clonic frequency decrease was correlated with the presence and duration of postictal suppression. The projected terminal interclonic interval explained 41% of the variation in postictal generalized EEG suppression duration (P < 0.02). Conversely, postictal generalized EEG suppression duration explained 34% of the variation in the last interclonic interval duration. Our findings suggest that postictal generalized EEG suppression is a separate brain state and that seizure termination is a plastic and autonomous process, reflected in increased duration of interclonic intervals that determine the duration of postictal generalized EEG suppression.

Postictal generalized EEG suppression is not associated with periictal cardiac autonomic instability in people with convulsive seizures.

PURPOSE: Postictal generalized EEG suppression (PGES) seems to be a pathophysiologic hallmark in ictal recordings of sudden unexpected death in epilepsy (SUDEP). It has recently been suggested that presence and duration of PGES might be a predictor of SUDEP risk. Little is known about the etiology of PGES. METHODS: We conducted a retrospective case-control study in 50 people with convulsive seizures (CS) recorded on digital video-electroencephalography (EEG). One CS per individual was reviewed for presence and duration of PGES by two independent observers: Preictal and postictal heart rate (HR) (1 min before seizure onset and 1, 3, 5, 15, and 30 min after seizure end) and frequency domain measures of heart rate variability (HRV), including the ratio of low frequency (LF) versus high frequency (HF) power, were analyzed. The relationship between PGES and periictal autonomic changes was evaluated, as well as its association with several clinical variables. KEY FINDINGS: Thirty-seven individuals (74%) exhibited PGES and 13 (26%) did not. CS resulted in a significant increase of periictal HR and the LF/HF ratio. PGES was associated with neither periictal HR (mean HR difference between PGES+ and PGES- seizures: -2 beats per minute [bpm], 95% confidence interval [CI] -10 to +6 bpm) nor HRV change. There was no association between the duration of PGES and periictal HR change. People with PGES were more likely to be asleep before seizure onset (odds ratio [OR] 4.7, 95% CI 1.2-18.3) and had a higher age of onset of epilepsy (median age 15 vs. 4 years). SIGNIFICANCE: PGES was not associated with substantial changes in measures of cardiac autonomic instability but was more prevalent in CS arising from sleep.

Sudden unexpected death in epilepsy: people with nocturnal seizures may be at highest risk.

PURPOSE: Most people with epilepsy who die suddenly and whose death is attributed to sudden unexpected death in epilepsy (SUDEP) are found in or by the bed for unknown reasons. We assessed whether those with sleep-related SUDEP were more likely to have nocturnal seizures, and whether seizure patterns (diurnal vs. nocturnal) differed from people dying suddenly and living controls with epilepsy. METHODS: Seizure patterns in a cohort of 154 people with epilepsy who died suddenly and after autopsy conformed to the definition of SUDEP and 616 controls living with epilepsy were classified as having "exclusively diurnal" or "nocturnal seizures." Comparisons were made between the groups. SUDEP was classified as sleep-related or non-sleep-related based on eyewitness accounts and the circumstances surrounding death. KEY FINDINGS: SUDEP was primarily a sleep-related (58%) and unwitnessed (86%) event. If sleep-related, SUDEP was more likely to be unwitnessed [odds ratio (OR) 4.4, 95% confidence interval (CI) 1.6-12]. Those with sleep-related SUDEP were more likely to have a history of nocturnal seizures than those who had non-sleep-related SUDEP (OR 3.6, 95% CI 1.4-9.4). Those who died were more likely to have a history of nocturnal seizures than living controls (OR 3.9, 95% CI 2.5-6.0). After correction for previously established SUDEP risk factors (Langan et al., 2005), the presence of nocturnal seizures remained significant (OR 2.6, 95% CI 1.3-5.0). SIGNIFICANCE: Nocturnal seizures seem to be an independent risk factor for SUDEP. These findings underscore the importance of preventive measures, which may include night supervision.

Automated Video Detection of Epileptic Convulsion Slowing as a Precursor for Post-Seizure Neuronal Collapse.

Automated monitoring and alerting for adverse events in people with epilepsy can provide higher security and quality of life for those who suffer from this debilitating condition. Recently, we found a relation between clonic slowing at the end of a convulsive seizure (CS) and the occurrence and duration of a subsequent period of postictal generalized EEG suppression (PGES). Prolonged periods of PGES can be predicted by the amount of progressive increase of interclonic intervals (ICIs) during the seizure. The purpose of the present study is to develop an automated, remote video sensing-based algorithm for real-time detection of significant clonic slowing that can be used to alert for PGES. This may help preventing sudden unexpected death in epilepsy (SUDEP). The technique is based on our previously published optical flow video sequence processing paradigm that was applied for automated detection of major motor seizures. Here, we introduce an integral Radon-like transformation on the time-frequency wavelet spectrum to detect log-linear frequency changes during the seizure. We validate the automated detection and quantification of the ICI increase by comparison to the results from manually processed electroencephalography (EEG) traces as "gold standard". We studied 48 cases of convulsive seizures for which synchronized EEG-video recordings were available. In most cases, the spectral ridges obtained from Gabor-wavelet transformations of the optical flow group velocities were in close proximity to the ICI traces detected manually from EEG data during the seizure. The quantification of the slowing-down effect measured by the dominant angle in the Radon transformed spectrum was significantly correlated with the exponential ICI increase factors obtained from manual detection. If this effect is validated as a reliable precursor of PGES periods that lead to or increase the probability of SUDEP, the proposed method would provide an efficient alerting device.

Complex SCN8A DNA-abnormalities in an individual with therapy resistant absence epilepsy.

BACKGROUND: De novo SCN8A missense mutations have been identified as a rare dominant cause of epileptic encephalopathy. We described a person with epileptic encephalopathy associated with a mosaic deletion of the SCN8A gene. METHODS: Array comparative genome hybridization was used to identify chromosomal abnormalities. Next Generation Sequencing was used to screen for variants in known and candidate epilepsy genes. A single nucleotide polymorphism array was used to test whether the SCN8A variants were in cis or in trans. RESULTS: We identified a de novo mosaic deletion of exons 2-14 of SCN8A, and a rare maternally inherited missense variant on the other allele in a woman presenting with absence seizures, challenging behavior, intellectual disability and QRS-fragmentation on the ECG. We also found a variant in SCN5A. CONCLUSIONS: The combination of a rare missense variant with a de novo mosaic deletion of a large part of the SCN8A gene suggests that other possible mechanisms for SCN8A mutations may cause epilepsy; loss of function, genetic modifiers and cellular interference may play a role. This case expands the phenotype associated with SCN8A mutations, with absence epilepsy and regression in language and memory skills.

Sudden cardiac arrest in people with epilepsy in the community: Circumstances and risk factors.

OBJECTIVE: To ascertain whether characteristics of ventricular tachycardia/fibrillation (VT/VF) differed between people with epilepsy and those without and which individuals with epilepsy were at highest risk. METHODS: We ascertained 18 people with active epilepsy identified in a community-based registry of sudden cardiac arrest (SCA) with ECG-confirmed VT/VF (cases). We compared them with 470 individuals with VT/VF without epilepsy (VT/VF controls) and 54 individuals with epilepsy without VT/VF (epilepsy controls). Data on comorbidity, epilepsy severity, and medication use were collected and entered into (conditional) logistic regression models to identify determinants of VT/VF in epilepsy. RESULTS: In most cases, there was an obvious (10/18) or presumed cardiovascular cause (5/18) in view of preexisting heart disease. In 2 of the 3 remaining events, near-sudden unexpected death in epilepsy (SUDEP) was established after successful resuscitation. Cases had a higher prevalence of congenital/inherited heart disease (17% vs 1%, p = 0.002), and experienced VT/VF at younger age (57 vs 64 years, p = 0.023) than VT/VF controls. VT/VF in cases occurred more frequently at/near home (89% vs 58%, p = 0.009), and was less frequently witnessed (72% vs 89%, p = 0.048) than in VT/VF controls. Cases more frequently had clinically relevant heart disease (50% vs 15%, p = 0.005) and intellectual disability (28% vs 1%, p < 0.001) than epilepsy controls. CONCLUSION: Cardiovascular disease rather than epilepsy characteristics is the main determinant of VT/VF in people with epilepsy in the community. SCA and SUDEP are partially overlapping disease entities.

[Sudden unexpected death in epilepsy: SUDEP]. / Plotse onverwachte dood bij epilepsie, ofwel 'SUDEP'.

Sudden unexpected death in epilepsy (SUDEP) is the most important direct epilepsy-related cause of death. Patients with refractory epilepsy are at especially high risk of SUDEP. SUDEP occurs predominantly at night and unwitnessed, and can best be regarded as a fatal tonic-clonic seizure. While its pathophysiology is incompletely understood, SUDEP is most probably triggered by a number of predisposing and precipitating factors, including seizure-induced respiratory depression and cardiac arrhythmia. Achieving seizure freedom is the best way to prevent SUDEP. Nocturnal supervision may be another alternative preventive strategy, but this requires further research.

Postictal generalized EEG suppression: an inconsistent finding in people with multiple seizures.

OBJECTIVE: To determine the consistency and facilitating cofactors of postictal generalized EEG suppression (PGES) of >20 seconds after convulsive seizures (CS), a suggested predictor of sudden unexpected death in epilepsy risk. METHODS: We retrospectively reviewed video-EEG data of people with ≥2 recorded CS. Presence and duration of PGES were assessed by 2 independent observers blinded to patient status. Intraindividual consistency of PGES >20 seconds was determined and correlations with clinical characteristics were analyzed after correction for individual effects and the varying number of seizures. RESULTS: One hundred fifty-four seizures in 59 people were analyzed. PGES >20 seconds was found in 37 individuals (63%) and 57 (37%) of CS. The proportion of persons in whom PGES occurred consistently (presence or absence of PGES >20 seconds in all CS) was lower in those with more CS. PGES of >20 seconds was more frequent in seizures arising from sleep (odds ratio 3.29, 95% confidence interval 1.21-8.96) and when antiepileptic medication was tapered (odds ratio 4.80, 95% confidence interval 1.27-18.14). CONCLUSION: Apparent PGES consistency was less frequent in people with more CS recorded, suggesting that PGES is an inconsistent finding in any one individual. Thus, we believe that PGES >20 seconds is not a reliable predictor of sudden unexpected death in epilepsy. Sleep and antiepileptic drug reduction appear to facilitate the occurrence of PGES.

Epilepsy is a risk factor for sudden cardiac arrest in the general population.

BACKGROUND: People with epilepsy are at increased risk for sudden death. The most prevalent cause of sudden death in the general population is sudden cardiac arrest (SCA) due to ventricular fibrillation (VF). SCA may contribute to the increased incidence of sudden death in people with epilepsy. We assessed whether the risk for SCA is increased in epilepsy by determining the risk for SCA among people with active epilepsy in a community-based study. METHODS AND RESULTS: This investigation was part of the Amsterdam Resuscitation Studies (ARREST) in the Netherlands. It was designed to assess SCA risk in the general population. All SCA cases in the study area were identified and matched to controls (by age, sex, and SCA date). A diagnosis of active epilepsy was ascertained in all cases and controls. Relative risk for SCA was estimated by calculating the adjusted odds ratios using conditional logistic regression (adjustment was made for known risk factors for SCA). We identified 1019 cases of SCA with ECG-documented VF, and matched them to 2834 controls. There were 12 people with active epilepsy among cases and 12 among controls. Epilepsy was associated with a three-fold increased risk for SCA (adjusted OR 2.9 [95%CI 1.1-8.0.], p=0.034). The risk for SCA in epilepsy was particularly increased in young and females. CONCLUSION: Epilepsy in the general population seems to be associated with an increased risk for SCA.