Asymmetrical cortical surface area decrease in epilepsy patients with postictal generalized electroencephalography suppression.

Postictal generalized electroencephalographic suppression is a possible electroencephalographic marker for sudden unexpected death in epilepsy. We aimed to investigate the cortical surface area abnormalities in epilepsy patients with postictal generalized electroencephalographic suppression. We retrospectively included 30 epilepsy patients with postictal generalized electroencephalographic suppression (PGES+), 21 epilepsy patients without postictal generalized electroencephalographic suppression (PGES-), and 30 healthy controls. Surface-based analysis on high-resolution T1-weighted images was conducted and cortical surface areas were compared among the three groups, alongside correlation analyses with seizure-related clinical variables. Compared with PGES- group, we identified reduced surface area in the bilateral insula with more extensive distribution in the right hemisphere in PGES+ group. The reduced right insular surface area was associated with younger seizure-onset age. When compared with healthy controls, PGES- group presented reduced surface area in the left caudal middle frontal gyrus; PGES+ group presented more widespread surface area reductions in the right posterior cingulate gyrus, left postcentral gyrus, middle frontal gyrus, and middle temporal gyrus. Our results suggested cortical microstructural impairment in patients with postictal generalized electroencephalographic suppression. The significant surface area reductions in the insular cortex supported the autonomic network involvement in the pathology of postictal generalized electroencephalographic suppression, and its right-sided predominance suggested the potential shared abnormal brain network for postictal generalized electroencephalographic suppression and sudden unexpected death in epilepsy.

The influence of risk factors, biomarkers and care settings on SUDEP counseling.

Although sudden unexpected death in epilepsy (SUDEP) is the most feared epilepsy outcome, there is a dearth of SUDEP counseling provided by neurologists. This may reflect limited time, as well as the lack of guidance on the timing and structure for counseling. We evaluated records from SUDEP cases to examine frequency of inpatient and outpatient SUDEP counseling, and whether counseling practices were influenced by risk factors and biomarkers, such as post-ictal generalized EEG suppression (PGES). We found a striking lack of SUDEP counseling despite modifiable SUDEP risk factors; counseling was limited to outpatients despite many patients having inpatient visits within a year of SUDEP. PGES was inconsistently documented and was never included in counseling. There is an opportunity to greatly improve SUDEP counseling by utilizing inpatient settings and prompting algorithms incorporating risk factors and biomarkers.

The value of EEG attenuation in the prediction of outcome in COVID-19 patients.

INTRODUCTION: During the COVID-19 pandemic, electroencephalography (EEG) proved to be a useful tool to demonstrate brain involvement. Many studies reported non-reactive generalized slowing as the most frequent pattern and epileptiform activity in a minority of patients. OBJECTIVE: To investigate the prevalence of diffuse unreactive background attenuation or suppression and its correlation with outcome in a cohort of COVID-19 patients. METHODS: The EEGs recorded during the first year of the COVID-19 pandemic were retrospectively evaluated to identify the main pattern and focus on the occurrence of a low-voltage background, either attenuated (10-20 µV) or suppressed (< 10 µV). We sought a correlation between in-hospital mortality and low-voltage EEG. In a subsample of patients, biomarkers of inflammation, hypoxemia and organ failure were collected. Brain imaging was also evaluated. RESULTS: Among 98 EEG performed in 50 consecutive patients, diffuse unreactive slowing was the most prevalent pattern (54%), followed by unreactive attenuation or suppression pattern (26%), being the latter significantly correlated with an unfavourable outcome (p = 0.0004). Survivors showed significantly lower interleukine-6 values compared to non-survivors. Patients with attenuated EEG and non-survivors also showed lower PaO2/FiO2 values. Neuroradiological findings were very heterogeneous with a prevalence of lesions suggestive of a microangiopathic substrate. CONCLUSIONS: EEG attenuation or suppression may be more frequent than previously reported and significantly associated with a poor outcome. SARS-CoV-2 infection may result in encephalopathy and reduced EEG voltage through mechanisms that are still unknown but deserve attention given its negative impact on prognosis.

Interictal 18F-FDG brain PET metabolism in patients with postictal EEG suppression.

OBJECTIVE: Postictal generalized suppression (PGES) may be associated with SUDEP risk. We aimed to study metabolic changes on 18Fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) in patients with focal to bilateral (generalized) seizures (GTCS) and PGES on stereoelectroencephalography (SEEG). METHODS: We analyzed interictal brain metabolism in a group of 19 patients with widespread postictal suppression (PGES+) associated with SEEG-recorded GTCS. This group was compared to 25 patients without widespread suppression (PGES-) as defined by SEEG, matched for epilepsy localization and lateralization. Frequency of GTCS was observed to be higher in the PGES+ group (high risk group for SUDEP). Analysis of metabolic data was performed by statistical parametric mapping (SPM) on the whole-brain, and principal component analysis (PCA) on AAL (automated anatomical labeling) atlas. RESULTS: Statistical parametric mapping showed right temporal pole hypometabolism in the PGES+ group (T-score = 3.90; p < 0.001; k = 185), in comparison to the PGES- group. Principal component analysis showed association between the metabolic values of certain regions of interest and PGES+/PGES- groups, confirmed by a significant difference (p < 0.05) in the values of the right dorsal temporal pole and of the left temporal pole between the two groups. Principal component analysis showed two dimensions significantly related to the PGES+/PGES- partition, involving the following regions: right temporal pole, right parahippocampal gyrus, right Rolandic operculum, bilateral paracentral lobule, right precuneus, right thalamus, right caudate and pallidum, bilateral cerebellum, left temporal pole, left Heschl's gyrus, left calcarine region, and left caudate, with loss of connection in PGES+ patients. Metabolic differences were independent of epilepsy localization and lateralization and persisted after correction for GTCS frequency. SIGNIFICANCE: Interictal metabolic changes within a predominantly right-sided network involving temporal lobe and connected cortical and subcortical structures were seen in patients with frequent GTCS presenting widespread postictal suppression.

Peri-ictal heart rate variability parameters as surrogate markers of seizure severity.

This study aims at defining objective parameters reflecting the severity of peri-ictal autonomic changes and their relation to post-ictal generalized electroencephalography (EEG) suppression (PGES), with the view that such changes could be detected by wearable seizure detection systems and prove useful to assess the risk of sudden unexpected death in epilepsy (SUDEP). To this purpose, we assessed peri-ictal changes in heart rate variability (HRV) and correlated them with seizure duration, intensity of electromyography-based ictal muscle activity, and presence and duration of post-ictal generalized EEG suppression (PGES). We evaluated 75 motor seizures from 40 patients, including 61 generalized tonic-clonic seizures (GTCS) and 14 other major motor seizure types. For all major motor seizures, HRV measurements demonstrated a significantly decreased parasympathetic activity and increased sympathetic activity in the post-ictal period. The post-ictal increased sympathetic activity was significantly higher for GTCS as compared with non-GTCS. The degree of peri-ictal decreased parasympathetic activity and increased sympathetic activity was associated with longer PGES (>20 s), longer seizure duration, and greater intensity of ictal muscle activity. Mean post-ictal heart rate (HR) was an independent predictor of PGES duration, seizure duration, and intensity of ictal muscle contraction. Our results indicate that peri-ictal changes in HRV are potential biomarkers of major motor seizure severity.

Autonomic dysregulation in children with epilepsy with postictal generalized EEG suppression following generalized convulsive seizures.

OBJECTIVE: Postictal generalized electroencephalographic suppression (PGES) has been associated with sudden unexpected death in epilepsy (SUDEP) in adults. Decreased heart rate variability (HRV) is one clinical marker of SUDEP in adults with epilepsy. The objective of this study was to analyze the characteristics of HRV associated with generalized convulsive seizures (GCS) ±â€¯PGES in children. METHODS: Nine hundred and seventy-seven consecutive children who underwent prolonged scalp video-EEG (vEEG) and 1-lead electrocardiogram (ECG) monitoring at the Hospital for Sick Children, Toronto, Ontario, Canada were reviewed retrospectively from 2009 to 2011. Thirty-five children had GCS captured during their vEEG with or without PGES and met inclusion criteria. Children were subdivided into three age groups and compared with age-matched controls: 3-6 years; 7-12 years; and 13-18 years. Interictal HRV was measured at 5 min during N2 sleep. Preictal HRV was measured at 1 h prior to GCS onset, and postictal HRV was measured at 3 min post-GCS cessation. Low frequency (LF: ms2, 0.04-0.15 Hz) and high frequency (HF: ms2, 0.15-0.4 Hz) bands of heart rate oscillations were analyzed during the interictal and preictal periods. The root mean square of successive differences (RMSSDs) was analyzed during the following time points: interictal; preictal; and postictal. RESULTS: Thirty-five children had GCS: 18 children with PGES [3-6 years (n = 2); 7-12 years (n = 6); 13-18 years (n = 10)] and 17 children without PGES [3-6 years (n = 6); 7-12 years (n = 5); 13-18 years (n = 6)]. Seventeen additional age-matched controls were identified [3-6 years (n = 3); 7-12 years (n = 5); 13-18 years (n = 9)]. Seventy-four GCS were captured consisting of 36 GCS + PGES and 38 GCS - PGES. There was no difference of interictal HRV among children with GCS ±â€¯PGES and controls. The preictal LF and HF in 36 GCS + PGES were significantly higher compared with 38 GCS - PGES (p < 0.01). The postictal RMSSD in 36 GCS + PGES was significantly higher compared with 38 GCS - PGES (p < 0.01). The pre- to postictal RMSSD change was significantly lower in children with GCS + PGES than in those with GCS - PGES (p = 0.035). CONCLUSIONS: In summary, the preictal HRV in GCS + PGES was significantly higher than in children with GCS - PGES. The higher remaining postictal RMSSD in children with GCS + PGES is a potential indicator of autonomic dysregulation. In certain children with epilepsy, autonomic dysregulation may contribute to poor recovery from a GCS with subsequent PGES, thereby contributing to SUDEP. Heart rate variability and autonomic regulation in children with epilepsy should be further studied prospectively in order to better understand the mechanism by which PGES may lead to SUDEP.

Automated detection of activity onset after postictal generalized EEG suppression.

BACKGROUND: Sudden unexpected death in epilepsy (SUDEP) is a leading cause of premature death in patients with epilepsy. If timely assessment of SUDEP risk can be made, early interventions for optimized treatments might be provided. One of the biomarkers being investigated for SUDEP risk assessment is postictal generalized EEG suppression [postictal generalized EEG suppression (PGES)]. For example, prolonged PGES has been found to be associated with a higher risk for SUDEP. Accurate characterization of PGES requires correct identification of the end of PGES, which is often complicated due to signal noise and artifacts, and has been reported to be a difficult task even for trained clinical professionals. In this work we present a method for automatic detection of the end of PGES using multi-channel EEG recordings, thus enabling the downstream task of SUDEP risk assessment by PGES characterization. METHODS: We address the detection of the end of PGES as a classification problem. Given a short EEG snippet, a trained model classifies whether it consists of the end of PGES or not. Scalp EEG recordings from a total of 134 patients with epilepsy are used for training a random forest based classification model. Various time-series based features are used to characterize the EEG signal for the classification task. The features that we have used are computationally inexpensive, making it suitable for real-time implementations and low-power solutions. The reference labels for classification are based on annotations by trained clinicians identifying the end of PGES in an EEG recording. RESULTS: We evaluated our classification model on an independent test dataset from 34 epileptic patients and obtained an AUreceiver operating characteristic (ROC) (area under the curve) of 0.84. We found that inclusion of multiple EEG channels is important for better classification results, possibly owing to the generalized nature of PGES. Of among the channels included in our analysis, the central EEG channels were found to provide the best discriminative representation for the detection of the end of PGES. CONCLUSION: Accurate detection of the end of PGES is important for PGES characterization and SUDEP risk assessment. In this work, we showed that it is feasible to automatically detect the end of PGES-otherwise difficult to detect due to EEG noise and artifacts-using time-series features derived from multi-channel EEG recordings. In future work, we will explore deep learning based models for improved detection and investigate the downstream task of PGES characterization for SUDEP risk assessment.

A lightweight convolutional neural network for assessing an EEG risk marker for sudden unexpected death in epilepsy.

BACKGROUND: Convolutional neural network (CNN) has achieved state-of-art performance in many electroencephalogram (EEG) related studies. However, the application of CNN in prediction of risk factors for sudden unexpected death in epilepsy (SUDEP) remains as an underexplored area. It is unclear how the trade-off between computation cost and prediction power varies with changes in the complexity and depth of neural nets. METHODS: The purpose of this study was to explore the feasibility of using a lightweight CNN to predict SUDEP. A total of 170 patients were included in the analyses. The CNN model was trained using clips with 10-s signals sampled from the original EEG. We implemented Hann function to smooth the raw EEG signal and evaluated its effect by choosing different strength of denoising filter. In addition, we experimented two variations of the proposed model: (1) converting EEG input into an "RGB" format to address EEG channels underlying spatial correlation and (2) incorporating residual network (ResNet) into the bottle neck position of the proposed structure of baseline CNN. RESULTS: The proposed baseline CNN model with lightweight architecture achieved the best AUC of 0.72. A moderate noise removal step facilitated the training of CNN model by ensuring stability of performance. We did not observe further improvement in model's accuracy by increasing the strength of denoising filter. CONCLUSION: Post-seizure slow activity in EEG is a potential marker for SUDEP, our proposed lightweight architecture of CNN achieved satisfying trade-off between efficiently identifying such biomarker and computational cost. It also has a flexible interface to be integrated with different variations in structure leaving room for further improvement of the model's performance in automating EEG signal annotation.

Epilepsy as a manifestation of a multistate network of oscillatory systems.

The human brain, largely accepted as the most complex biological system known, is still far from being understood in its parts or as a whole. More specifically, biological mechanisms of epileptic states and state transitions are not well understood. Here, we explore the concept of the epilepsy as a manifestation of a multistate network composed of coupled oscillatory units. We also propose that functional coupling between neuroglial elements is a dynamic process, characterized by temporal changes both at short and long time scales. We review various experimental and modelling data suggesting that epilepsy is a pathological manifestation of such a multistate network - both when viewed as a coupled oscillatory network, and as a system of multistate stable state attractors. Based on a coupled oscillators model, we propose a significant role for glial cells in modulating hyperexcitability of the neuroglial networks of the brain. Also, using these concepts, we explain a number of observable phenomena such as propagation patterns of bursts within a seizure in the isolated intact hippocampus in vitro, postictal generalized suppression in human encephalographic seizure data, and changes in seizure susceptibility in epileptic patients. Based on our conceptual model we propose potential clinical applications to estimate brain closeness to ictal transition by means of active perturbations and passive measures during on-going activity.

Tonic electromyographic activity following bilateral tonic-clonic seizures is associated with periictal respiratory dysfunction and postictal generalized EEG suppression.

OBJECTIVE: No biomarkers reliably predict risk for sudden unexpected death in epilepsy (SUDEP). Postictal generalized electroencephalography (EEG) suppression (PGES) is a possible biomarker for SUDEP risk. However, its utility in predicting SUDEP remains uncertain. We had observed that postictal tonic electromyography (PTEMG) activity follows some generalized convulsive seizures (GCS). PTEMG activity and PGES may have a common pathophysiologic basis. PGES is associated with periictal respiratory distress. There is evidence that tonic EMG occurs with brain hypoxia. Thus PTEMG activity may be related to seizure-associated hypoxemia. Pronounced variation occurs among expert clinicians in identifying PGES, thereby limiting its utility as a biomarker. Characteristics of PTEMG activity and its relationship to preceding GCS have not been explored. We studied PTEMG activity characteristics, its relationship to the preceding seizure and associated respiratory dysfunction. METHODS: We reviewed 145 GCS in 66 patients undergoing video-EEG telemetry (VET). The presence of PTEMG activity was defined when tonic EMG occurred for at least 3 seconds following seizure termination and was identified with filter settings at 5-200 Hz. Duration of PTEMG activity, the seizure, PGES, seizure-associated peripheral capillary oxygen saturation (SpO2 ) change, and end-tidal CO2 were analyzed. We compared data from GCS with and without PTEMG activity. RESULTS: Ninety of 145 seizures with GCS had PTEMG activity. The remainder had postictal slowing without PTEMG activity, and cessation of activity was followed by EEG slowing. Duration of the initial PTEMG discharge was 39.1 (mean) ± (standard deviation) 17.9 seconds. SpO2 nadir was lower (P = 0.005) in seizures with PTEMG activity than in those without (72% vs 77%). End-tidal CO2 was higher (P = 0.05) in seizures with PTEMG activity than in those without (63  vs 56 mm Hg). PGES duration was 35.6 ± 22.2 seconds and associated with duration of PTEMG activity (P < 0.001). SIGNIFICANCE: The novel finding is that PTEMG activity occurs following 62% of GCS and that seizures with PTEMG activity have greater severity of respiratory dysfunction than seizures without. PTEMG activity is readily discerned by visual analysis of VET at appropriate filter settings and has the potential of being a complementary or surrogate biomarker of PGES for assessing SUDEP risk.

Serum serotonin levels in patients with epileptic seizures.

Profound cardiovascular and/or respiratory dysfunction is part of the terminal cascade in sudden unexpected death in epilepsy (SUDEP). Central control of ventilation is mediated by brainstem rhythm generators, which are influenced by a variety of inputs, many of which use the modulatory neurotransmitter serotonin to mediate important inputs for breathing. The aim of this study was to investigate epileptic seizure-induced changes in serum serotonin levels and whether there are potential implications for SUDEP. Forty-one epileptic patients were pooled into 2 groups based on seizure type as (1) generalized tonic-clonic seizures (GTCS) of genetic generalized epilepsy and focal to bilateral tonic-clonic seizures (FBTCS; n = 19) and (2) focal seizures (n = 26) based on clinical signs using surface video-electroencephalography. Postictal serotonin levels were statistically significantly higher after GTCS and FBTCS compared to interictal levels (P = .002) but not focal seizures (P = .941). The change in serotonin (postictal-interictal) was inversely associated with a shorter duration of tonic phase of generalized seizures. The interictal serotonin level was inversely associated with a shorter period of postictal generalized electroencephalographic suppression. These data suggest that peripheral serum serotonin levels may play a role in seizure features and earlier postseizure recovery; these findings merit further study.

Postictal generalized EEG suppression and respiratory dysfunction following generalized tonic-clonic seizures in sleep and wakefulness.

OBJECTIVE: Sudden unexpected death in epilepsy (SUDEP) is a common cause of death in epilepsy and frequently occurs following generalized tonic-clonic seizures (GTCS) in sleep. Postictal generalized electroencephalography (EEG) suppression (PGES), postictal immobility, and periictal respiratory dysfunction are potential risk factors for SUDEP. We sought to determine whether there was a difference in respiratory dysfunction, PGES, and postictal immobility for GTCS occurring during wakefulness or sleep. METHODS: We retrospectively analyzed video-EEG telemetry data in the epilepsy-monitoring unit. Patients' state at seizure onset and seizure characteristics were identified. Respiratory parameters and heart rate were recorded. Presence and duration of PGES and time to first postictal nonrespiratory movement were recorded. RESULTS: There were 165 seizures in 67 patients. There was no significant difference in the duration of postictal immobility in GTCS occurring out of wakefulness or sleep (p = 0.280). Oxygen desaturation nadir (p = 0.572) and duration of oxygen desaturation were not significantly different for GTCS starting during sleep or wakefulness (p = 0.992). PGES occurred more frequently when seizure onset was in sleep than in wakefulness (p = 0.004; odds ratio [OR] 2.760). There was no difference in the duration of PGES between the two groups. SIGNIFICANCE: PGES occurs more commonly after GTCS in sleep than in wakefulness but, in the epilepsy-monitoring unit (EMU), a patient's state at seizure onset does not affect the degree of respiratory dysfunction or duration of postictal immobility. In sleep, outside the hospital setting, GTCS are likely to go unnoticed. Postictal immobility in prone patients prevents head repositioning and unimpeded air exchange. A positive feedback cycle ensues with increasing respiratory distress, potentiating postictal immobility and PGES and eventually leading to asystole. Our findings suggest that the high incidence of nocturnal SUDEP may be related to the unsupervised environment during sleep rather than the severity of sleep-related respiratory dysfunction or PGES duration in the immediate postictal period.

Nocturnal seizures are associated with more severe hypoxemia and increased risk of postictal generalized EEG suppression.

Patients with epilepsy have 20-fold risk of sudden death when compared to the general population. Uncontrolled seizures is the most consistent risk factor, and death often occurs at night or in relation to sleep. We examined seizure-related respiratory disturbances in sleep versus wakefulness, focusing on periictal oxygen saturation. Respiratory measures were examined in 48 recorded seizures (sleep, n = 23, wake, n = 25) from 20 adult patients with epilepsy. Seizures from sleep were associated with lower saturation, as compared to seizures from wakefulness, both during ictal (sleep median = 90.8, wake median = 95.5; p < 0.01) and postictal periods (sleep median = 94.3, wake median = 96.9; p = 0.05). Compared to wake-related seizures, seizures from sleep were also associated with a larger desaturation drop (sleep median = -4.2, wake median = -1.2; p = 0.01). Postictal generalized electroencephalography (EEG) suppression (PGES) occurred more frequently after seizures from sleep (39%), as compared to wake-related seizures (8%, p = 0.01). Our findings suggest that nocturnal seizures may entail a higher sudden unexpected death in epilepsy (SUDEP) severity burden, as they are associated with more severe and longer hypoxemia events, and more frequently followed by PGES, both factors implicated in sudden death.

Nonseizure SUDEP: Sudden unexpected death in epilepsy without preceding epileptic seizures.

OBJECTIVE: To describe the phenomenology of monitored sudden unexpected death in epilepsy (SUDEP) occurring in the interictal period where death occurs without a seizure preceding it. METHODS: We report a case series of monitored definite and probable SUDEP where no electroclinical evidence of underlying seizures was found preceding death. RESULTS: Three patients (two definite and one probable) had SUDEP. They had a typical high SUDEP risk profile with longstanding intractable epilepsy and frequent generalized tonic-clonic seizures (GTCS). All patients had varying patterns of respiratory and bradyarrhythmic cardiac dysfunction with profound electroencephalography (EEG) suppression. In two patients, patterns of cardiorespiratory failure were similar to those seen in some patients in the Mortality in Epilepsy Monitoring Units Study (MORTEMUS). SIGNIFICANCE: SUDEP almost always occur postictally, after GTCS and less commonly after a partial seizure. Monitored SUDEP or near-SUDEP cases without a seizure have not yet been reported in literature. When nonmonitored SUDEP occurs in an ambulatory setting without an overt seizure, the absence of EEG information prevents the exclusion of a subtle seizure. These cases confirm the existence of nonseizure SUDEP; such deaths may not be prevented by seizure detection-based devices. SUDEP risk in patients with epilepsy may constitute a spectrum of susceptibility wherein some are relatively immune, death occurs in others with frequent GTCS with one episode of seizure ultimately proving fatal, while in others still, death may occur even in the absence of a seizure. We emphasize the heterogeneity of SUDEP phenomena.

Postictal immobility and generalized EEG suppression are associated with the severity of respiratory dysfunction.

OBJECTIVE: The pathophysiology of sudden unexpected death in epilepsy (SUDEP) remains undetermined. Seizures are accompanied by respiratory dysfunction (RD). Postictal generalized electroencephalography (EEG) suppression (PGES) may follow generalized tonic-clonic seizures (GTCS). Following GTCS patients have impaired arousal and may be motionless. Patients with SUDEP are usually prone. Postictal immobility (PI) may contribute to SUDEP by not permitting repositioning of the head to allow unimpeded ventilation. To determine whether RD and/or ictal characteristics are associated with PI, we analyzed patients with GTCS in the epilepsy monitoring unit. METHOD: We investigated for associations between PI duration and PGES, ictal/postictal oxygen saturation (SpO2 ), end-tidal CO2 (ETCO2 ), seizure localization, duration, and tonic and total convulsive phase duration. We investigated for linkage between PGES and these measures. RESULTS: Seventy patients with 181 GTCS and available SpO2 and/or ETCO2 data were studied. Simple linear regression analysis by seizures showed that PI duration was associated with peak periictal ETCO2 (p = 0.03), duration of oxygen desaturation (p = 0.005) and with SpO2 nadir (p = 0.02). PI duration was not associated with tonic, convulsive phase or total seizure duration. Analysis by patients also showed significant association of PI with RD. Duration of PI was longer following seizures with PGES (p < 0.001). PGES was not associated with the tonic, convulsive phase or total seizure duration. SpO2 nadir was lower in seizures with PGES (p = 0.046), ETCO2 peak change (p = 0.003) was higher, and duration of ETCO2 elevation (p = 0.03) was longer. Multivariable regression analysis showed that PGES and severe RD were associated with PI duration. SIGNIFICANCE: The duration of PI and presence of PGES are associated with periictal RD. The duration of PI is also associated with the presence of PGES. Seizure duration or duration of the convulsive phase is not associated with PI or PGES. Interventions aimed at reversing impaired arousal and PI may reduce SUDEP risk.

Local brain activity persists during apparently generalized postictal EEG suppression.

OBJECTIVES: Postictal generalized EEG suppression (PGES) frequently occurs after generalized convulsive seizures (GCS) and may be involved in the pathophysiology of sudden unexpected death in epilepsy (SUDEP). It is usually determined using conventional scalp EEG which is likely to miss cerebral activity in deeper brain structures. Here, we examined intracranial EEG activity after GCS to unravel the pattern and extent of local brain activity during apparent PGES on scalp EEG (s-PGES). METHODS: We retrospectively reviewed electroencephalographic data of people with chronic epilepsy who had GCS during presurgical video-EEG monitoring using simultaneous intracranial and scalp EEG (10-20 system) electrodes. RESULTS: Twenty-five GCS (20 with s-PGES) of 15 patients with an average number of 88±42 intracranial electrode contacts were included. The majority of GCS with s-PGES (18 of 20) displayed persisting or reemerging intracranial EEG activity during apparent PGES on scalp EEG. Three patterns were identified: Pattern 1 (11 GCS, 6 patients) consisted of continuous local interictal activity; Pattern 2 (5 GCS, 5 patients) displayed suppressed EEG activity at all intracranial contacts in the early phase of s-PGES, but reemerging local brain activity before s-PGES dissolved; and Pattern 3 (2 GCS, 2 patients) showed persistent local ictal activity during s-PGES. Persisting intracranial EEG activity at PGES onset on scalp EEG was present in 10±14% (range: 0 to 42%) of all intracranial contacts and mostly in the temporal lobe. CONCLUSIONS: Our results reveal that, during apparently generalized postictal EEG suppression, local brain activity persists or reemerges in most GCS. Possible implications of this localized neuronal activity in the context of SUDEP are discussed in the paper.

Periictal autonomic dysfunction and generalized postictal EEG suppression in convulsive seizures arising from sleep and wakefulness.

Sleep appears to be an independent risk factor of sudden unexpected death in epilepsy (SUDEP). We retrospectively determined the periictal electrophysiological characteristics of nocturnal and diurnal generalized convulsive seizures (GCSs) in 109 patients. Our data showed that preictal heart rate (HR) was significantly lower in 46 patients with nocturnal GCSs than in 63 patients with diurnal GCSs (p=0.002). However, there was no significant difference in postictal HR and respiratory rate (RR), total seizure duration, total convulsive phase, tonic phase, and clonic phase. Meanwhile, postictal generalized EEG suppression (PGES) was observed in 52.4% of the patients with diurnal GCSs and 67.4% of the patients with nocturnal GCSs. Duration of PGES was 38.2±17.3s in patients with diurnal GCSs and 49.5±21.7s in patients with nocturnal GCSs. There was also no significant difference in the prevalence (p=0.118) and duration (p=0.044, Bonferroni-corrected significant level: α=0.00625) of PGES in the two patient groups. Therefore, there is no clear evidence to attribute the SUDEP risk associated with sleep to postictal autonomic dysfunction and PGES, as compared to wakefulness.

Comparison of cardiorespiratory and EEG abnormalities with seizures in adults and children.

Cardiopulmonary dysfunction and postictal generalized EEG suppression (PGES) are proposed as possible risk factors for the occurrence of SUDEP. The evolution of cardiorespiratory abnormalities with seizures has not been systematically studied for any age-related findings. Additionally, not many studies have looked into the possible effect of age-related brain maturation on PGES. The purpose of this study was to compare these SUDEP risk factors in adults versus children. We prospectively recorded cardiopulmonary abnormalities during seizures using pulse oximetry, EKG, and respiratory inductance plethysmography. Linear and logistic regression models adjusting for multiple seizures in a single patient were used to compare the cardiorespiratory and EEG findings between adults and children. We recorded 101 seizures in 26 children and 55 seizures in 22 adults. Ictal central apnea and bradycardia occurred more often in children than in adults (p=0.02 and p=0.008, respectively), while ictal tachycardia occurred more often in adults (p=0.001) than in children. Postictal generalized EEG suppression of longer duration occurred more often in adults (p=0.003) than in children. Minimum O2 saturation and seizure duration/generalization/lateralization did not significantly differ between adults and children (p>0.1). Children had more frontal lobe seizures, and adults had more temporal lobe seizures recorded (p=0.01). There may be an age-related effect on cardiorespiratory and EEG abnormalities associated with seizures, with higher rates of apnea and bradycardia in children and a much higher prevalence of PGES of longer duration in adults. This may indicate why, despite lower rates of cardiopulmonary dysfunction, adults die more frequently from SUDEP than children.

Age-specific periictal electroclinical features of generalized tonic-clonic seizures and potential risk of sudden unexpected death in epilepsy (SUDEP).

Generalized tonic-clonic seizure (GTCS) is the commonest seizure type associated with sudden unexpected death in epilepsy (SUDEP). This study examined the semiological and electroencephalographic differences (EEG) in the GTCSs of adults as compared with those of children. The rationale lies on epidemiological observations that have noted a tenfold higher incidence of SUDEP in adults. We analyzed the video-EEG data of 105 GTCS events in 61 consecutive patients (12 children, 23 seizure events and 49 adults, 82 seizure events) recruited from the Epilepsy Monitoring Unit. Semiological, EEG, and 3-channel EKG features were studied. Periictal seizure phase durations were analyzed including tonic, clonic, total seizure, postictal EEG suppression (PGES), and recovery phases. Heart rate variability (HRV) measures including RMSSD (root mean square successive difference of RR intervals), SDNN (standard deviation of NN intervals), and SDSD (standard deviation of differences) were analyzed (including low frequency/high frequency power ratios) during preictal baseline and ictal and postictal phases. Generalized estimating equations (GEEs) were used to find associations between electroclinical features. Separate subgroup analyses were carried out on adult and pediatric age groups as well as medication groups (no antiepileptic medication cessation versus unchanged or reduced medication) during admission. Major differences were seen in adult and pediatric seizures with total seizure duration, tonic phase, PGES, and recovery phases being significantly shorter in children (p<0.01). Generalized estimating equation analysis, using tonic phase duration as the dependent variable, found age to correlate significantly (p<0.001), and this remained significant during subgroup analysis (adults and children) such that each 0.12-second increase in tonic phase duration correlated with a 1-second increase in PGES duration. Postictal EEG suppression durations were on average 28s shorter in children. With cessation of medication, total seizure duration was significantly increased by a mean value of 8s in children and 11s in adults (p<0.05). Tonic phase duration also significantly increased with medication cessation, and although PGES durations increased, this was not significant. Root mean square successive difference was negatively correlated with PGES duration (longer PGES durations were associated with decreased vagally mediated heart rate variability; p<0.05) but not with tonic phase duration. This study clearly points out identifiable electroclinical differences between adult and pediatric GTCSs that may be relevant in explaining lower SUDEP risk in children. The findings suggest that some prolonged seizure phases and prolonged PGES duration may be electroclinical markers of SUDEP risk and merit further study.

Association between postictal EEG suppression, postictal autonomic dysfunction, and sudden unexpected death in epilepsy: Evidence from intracranial EEG.

OBJECTIVE: The association between postictal electroencephalogram (EEG) suppression (PES), autonomic dysfunction, and Sudden Unexpected Death in Epilepsy (SUDEP) remains poorly understood. We compared PES on simultaneous intracranial and scalp-EEG and evaluated the association of PES with postictal heart rate variability (HRV) and SUDEP outcome. METHODS: Convulsive seizures were analyzed in patients with drug-resistant epilepsy at 5 centers. Intracranial PES was quantified using the Hilbert transform. HRV was quantified using root mean square of successive differences of interbeat intervals, low-frequency to high-frequency power ratio, and RR-intervals. RESULTS: There were 64 seizures from 63 patients without SUDEP and 11 seizures from 6 SUDEP patients. PES occurred in 99% and 87% of seizures on intracranial-EEG and scalp-EEG, respectively. Mean PES duration in intracranial and scalp-EEG was similar. Intracranial PES was regional (<90% of channels) in 46% of seizures; scalp PES was generalized in all seizures. Generalized PES showed greater decrease in postictal parasympathetic activity than regional PES. PES duration and extent were similar between patients with and without SUDEP. CONCLUSIONS: Regional intracranial PES can be present despite scalp-EEG demonstrating generalized or no PES. Postictal autonomic dysfunction correlates with the extent of PES. SIGNIFICANCE: Intracranial-EEG demonstrates changes in autonomic regulatory networks not seen on scalp-EEG.