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.

Can intravenous lorazepam prevent postictal generalized EEG suppression? A case report

Background

Postictal generalized electrographic suppression (PGES) may be considered an electrophysiological marker associated with an increased risk of sudden unexplained death in epilepsy (SUDEP).

Case Presentation

A case study is presented whereby a young man with focal to bilateral tonic-clonic seizures exhibited PGES after two spontaneously-aborted seizures; yet, after a third benzodiazepine-aborted seizure, PGES was absent.

Conclusion

This suggests that acutely administered benzodiazepines may offer direct anti-suppressive effects to prevent PGES, potentially reducing SUDEP risk.

Post-ictal Rhythmic Thalamic Activity of the Centromedian Nucleus

INTRODUCTION

Deep brain stimulation of the centromedian nucleus of the thalamus (CMN) to treat drug-resistant epilepsy has been of interest for decades. However, little is known about the electrophysiological activity of the CMN during seizures. We describe a novel CMN EEG finding associated with seizure: post-ictal rhythmic thalamic activity.

METHODS

Five patients with drug-resistant epilepsy of unknown etiology with focal onset seizures underwent stereoelectroencephalography monitoring as part of evaluation for potential resective surgery or neuromodulation. Two patients had previously undergone complete corpus callosotomy and vagus nerve stimulation. A standardized plan for implantation included targets in the bilateral CMN.

RESULTS

Each patient had frontal onset seizures, and two patients had additional insular, parietal, or mesial temporal onset seizures. Contacts of CMN were involved synchronously or rapidly after onset in most recorded seizures, particularly those with frontal onset. Focal onset hemiclonic and bilateral tonic-clonic seizures spread to involve cortical contacts with high-amplitude rhythmic spiking followed by abrupt offset with diffuse voltage attenuation. A post-ictal rhythmic 1.5 to 2.5 Hz delta frequency pattern, post-ictal rhythmic thalamic activity, emerged in CMN contacts amid the suppression of background activity in cortical contacts. In the two patients with corpus callosotomy, unilateral seizure spread and ipsilateral post-ictal rhythmic thalamic activity were observed.

CONCLUSIONS

We observed post-ictal rhythmic thalamic activity in five patients with stereoelectroencephalography monitoring of the CMN with convulsive seizures. This rhythm appears late in ictal evolution and may signal an important role of the CMN in seizure termination. Furthermore, this rhythm may help identify CMN involvement in the epileptic network.

Distinctive Amplitude-Integrated EEG Ictal Pattern and Targeted Therapy with Carbamazepine in KCNQ2 and KCNQ3 Neonatal Epilepsy: A Case Series

BACKGROUND

 Carbamazepine (CBZ) is effective in treating KCNQ2/3-related seizures, which may present with a distinctive amplitude-integrated electroencephalography (aEEG) pattern.

OBJECTIVE

 To assess how improved recognition of the distinctive aEEG ictal pattern associated with KCNQ2/3 variants has enabled early and effective targeted therapy with CBZ.

METHODS

 Retrospective descriptive study of five neonates with KCNQ2/3 pathogenic gene variants admitted at a level 3 neonatal intensive care unit (NICU) over an 8-year period.

RESULTS

 The distinctive ictal aEEG pattern was recognized in four neonates after an average of 61.5 hours (minimum 12 hours, maximum 120 hours) from the first electroclinical seizure and prompted the use of CBZ that was effective in all. The two most recently diagnosed patients could avoid polytherapy as they received CBZ as the first and second antiseizure medication, respectively. Three out of five patients with continuous normal voltage (CNV), sleep-wake cycling (SWC), and shorter postictal suppression had normal neurodevelopmental outcome. Regarding the remaining two infants, one was not trialed with CBZ and had a high seizure burden, both presented with a prolonged postictal suppression, no SWC, and had moderate-to-severe developmental delay. Genetic results became available after the neonatal period in all but one of the infants, who had a prenatal diagnosis.

CONCLUSION

 Recognition of the distinctive ictal aEEG pattern in the NICU allowed early and effective targeted therapy with CBZ in four neonates, well before genetic results became available. Furthermore, a CNV background pattern with SWC and short postictal suppression were associated with normal developmental outcomes.

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.

Sudden Unexpected Death in Epilepsy During Ambulatory Video-EEG Monitoring at Home

BACKGROUND AND OBJECTIVES

We report the recording of sudden unexpected death in epilepsy (SUDEP) in a 68-year-old man with recent onset cryptogenic epilepsy, captured by video-EEG monitoring, at home in the company of his wife while sitting in a chair. This was only the third seizure of his life, the first 2 occurring 19 days previously. This rare event is a novel case of SUDEP recorded with ambulatory video EEG at home. The video is included by permission.

METHODS

Electroclinical seizure and cardiorespiratory analysis was ascertained using a combination of video, EEG (Natus, standard 10-20 electrode), ECG, and sound. Respiratory rate was ascertained based on chest, abdominal, and facial respiratory movements, together with video and audio.

RESULTS

The unique video-EEG recording illustrates the time course of apnea and bradycardia leading to terminal apnea in conjunction with prolonged postictal generalized EEG suppression.

DISCUSSION

This case is illustrative of a wide spectrum of SUDEP cases, ranging from the highly intractable to the patient with newly diagnosed epilepsy with very few seizures. It illustrates that patients can succumb to SUDEP while awake and in the sitting position (1) very early in their epilepsy course, (2) without recognized risk factors other than generalized convulsive seizures, (3) even when accompanied.

Are we there yet? A critical evaluation of sudden and unexpected death in epilepsy models

Although animal models have helped to elaborate meaningful hypotheses about the pathophysiology of sudden and unexpected death in epilepsy (SUDEP), specific prevention strategies are still lacking, potentially reflecting the limitations of these models and the intrinsic difficulties of investigating SUDEP. The interpretation of preclinical data and their translation to diagnostic and therapeutic developments in patients thus require a high level of confidence in their relevance to model the human situation. Preclinical models of SUDEP are heterogeneous and include rodent and nonrodent species. A critical aspect is whether the animals have isolated seizures exclusively induced by a specific trigger, such as models where seizures are elicited by electrical stimulation, pharmacological intervention, or DBA mouse strains, or whether they suffer from epilepsy with spontaneous seizures, with or without spontaneous SUDEP, either of nongenetic epilepsy etiology or from genetically based developmental and epileptic encephalopathies. All these models have advantages and potential disadvantages, but it is important to be aware of these limitations to interpret data appropriately in a translational perspective. The majority of models with spontaneous seizures are of a genetic basis, whereas SUDEP cases with a genetic basis represent only a small proportion of the total number. In almost all models, cardiorespiratory arrest occurs during the course of the seizure, contrary to that in patients observed at the time of death, potentially raising the issue of whether we are studying models of SUDEP or models of periseizure death. However, some of these limitations are impossible to avoid and can in part be dependent on specific features of SUDEP, which may be difficult to model. Several preclinical tools are available to address certain gaps in SUDEP pathophysiology, which can be used to further validate current preclinical models.

Personalization of SUDEP risk: A survey of transient subclinical comorbid changes

OBJECTIVE

Preclinical data report within subject modifiable ailments emerge weeks prior to SUDEP, including sleep disorders and cardiorespiratory changes; findings which support anecdotal clinical data. Here, we bridge preclinical findings with future clinical/preclinical studies, and survey whether caretakers or family members of victims noticed transient changes prior to SUDEP. The aim of this pilot study is to identify potential modifiable changes that may synergistically increase SUDEP risk for future research.

METHODS

A mobile electronic survey was posted on SUDEP community websites. The survey queried whether changes in seizures, sleep, physical well-being, emotional well-being, cognition, breathing, or heart rate were noticed before SUDEP.

RESULTS

The most profound finding was that 85% of victims had multiple transient ailments prior to SUDEP. Changes in seizures (28/54), and sleep (30/58) occurred in more than 50% of the victims and represent the most influential changes identified. The second and third most influential changes were a reduction in physical well-being (25/57) and emotional well-being (26/56). Changes were observed within the last two months of life in approximately one third of the cases, and more than four months prior to SUDEP in approximately one third of cases, indicating a potential time frame for proactive preventative strategies. Respondents also noted changes in cognition (16/55), breathing (9/54) or heart rate (8/55). Data indicate these changes may be associated with increased SUDEP risk within subject. Study limitations include the responses were based on memory, there was a potential for data to be over reported, and caretakers were not prompted to observe changes a priori, thus some existing changes may have gone unnoticed.

SIGNIFICANCE

Data support the preclinical findings that transient, subclinical (i.e., not severe enough to require medical intervention), modifiable ailments may increase risk of SUDEP. This suggests that just as an epilepsy type can change over a lifetime and epilepsy type-specific treatments can reduce SUDEP risk, further personalization of SUDEP risk will improve our understanding as to whether variables contribute to risk differently across lifespan. Thus, with a dynamic capacity to change, differing factors may contribute to the distribution of risk probability within an individual at any given time. Understanding whether different combinations of transient changes are specific to epilepsy type, age, or sex needs to be determined to move the field forward in hopes of developing a personalized approach to preventative strategies.

A Water Nymph's Curse and the Serotonergic Mechanism of Postictal Breathing Dysfunction

Seizures Cause Prolonged Impairment of Ventilation, CO2 Chemoreception and Thermoregulation Teran FA, Sainju RK, Bravo E, Wagnon J, Kim Y, Granner A, Gehlbach BK, Richerson GB. J Neurosci . 2023;43(27):4959-4971. doi:10.1523/JNEUROSCI.0450-23.2023 . PMID: 37160367 Sudden unexpected death in epilepsy (SUDEP) has been linked to respiratory dysfunction, but the mechanisms underlying this association remain unclear. Here we found that both focal and generalized convulsive seizures (GCSs) in epilepsy patients caused a prolonged decrease in the hypercapnic ventilatory response (HCVR; a measure of respiratory CO2 chemoreception). We then studied Scn1a R1407X/+ (Dravet syndrome; DS) and Scn8a N1768D/+ (D/+) mice of both sexes, two models of SUDEP, and found that convulsive seizures caused a postictal decrease in ventilation and severely depressed the HCVR in a subset of animals. Those mice with severe postictal depression of the HCVR also exhibited transient postictal hypothermia. A combination of blunted HCVR and abnormal thermoregulation is known to occur with dysfunction of the serotonin (5-hydroxytryptamine; 5-HT) system in mice. Depleting 5-HT with para-chlorophenylalanine (PCPA) mimicked seizure-induced hypoventilation, partially occluded the postictal decrease in the HCVR, exacerbated hypothermia, and increased postictal mortality in DS mice. Conversely, pretreatment with the 5-HT agonist fenfluramine reduced postictal inhibition of the HCVR and hypothermia. These results are consistent with the previous observation that seizures cause transient impairment of serotonergic neuron function, which would be expected to inhibit the many aspects of respiratory control dependent on 5-HT, including baseline ventilation and the HCVR. These results provide a scientific rationale to investigate the interictal and/or postictal HCVR as noninvasive biomarkers for those at high risk of seizure-induced death, and to prevent SUDEP by enhancing postictal 5-HT tone.

Sudden Unexpected Death in Epilepsy and Respiratory Defects in a Mouse Model of DEPDC5-Related Epilepsy

OBJECTIVES

DEPDC5 is a common causative gene in familial focal epilepsy with or without malformations of cortical development. Its pathogenic variants also confer a significantly higher risk for sudden unexpected death in epilepsy (SUDEP), providing opportunities to investigate the pathophysiology intersecting neurodevelopment, epilepsy, and cardiorespiratory function. There is an urgent need to gain a mechanistic understanding of DEPDC5-related epilepsy and SUDEP, identify biomarkers for patients at high risk, and develop preventive interventions.

METHODS

Depdc5 was specifically deleted in excitatory or inhibitory neurons in the mouse brain to determine neuronal subtypes that drive epileptogenesis and SUDEP. Electroencephalogram (EEG), cardiac, and respiratory recordings were performed to determine cardiorespiratory phenotypes associated with SUDEP. Baseline respiratory function and the response to hypoxia challenge were also studied in these mice.

RESULTS

Depdc5 deletion in excitatory neurons in cortical layer 5 and dentate gyrus caused frequent generalized tonic-clonic seizures and SUDEP in young adult mice, but Depdc5 deletion in cortical interneurons did not. EEG suppression immediately following ictal offset was observed in fatal and non-fatal seizures, but low amplitude rhythmic theta frequency activity was lost only in fatal seizures. In addition, these mice developed baseline respiratory dysfunction prior to SUDEP, during which ictal apnea occurred long before terminal cardiac asystole.

INTERPRETATION

Depdc5 deletion in excitatory neurons is sufficient to cause DEPDC5-related epilepsy and SUDEP. Ictal apnea and respiratory dysregulation play critical roles in SUDEP. Our study also provides a novel mouse model to investigate the underlying mechanisms of DEPDC5-related epilepsy and SUDEP. ANN NEUROL 2023;94:812-824.

Further advances in epilepsy

In 2017, one of us reviewed advances in epilepsy (Manford in J Neurol 264:1811-1824, 2017). The current paper brings that review up to date and gives a slight change in emphasis. Once again, the story is of evolution rather than revolution. In recognition that most of our current medications act on neurotransmitters or ion channels, and not on the underlying changes in connectivity and pathways, they have been renamed as antiseizure (ASM) medications rather than antiepileptic drugs. Cenobamate is the one newly licensed medication for broader use in focal epilepsy but there have been a number of developments for specific disorders. We review new players and look forward to new developments in the light of evolving underlying science. We look at teratogenicity; old villains and new concerns in which clinicians play a vital role in explaining and balancing the risks. Medical treatment of status epilepticus, long without evidence, has benefitted from high-quality trials to inform practice; like buses, several arriving at once. Surgical treatment continues to be refined with improvements in the pre-surgical evaluation of patients, especially with new imaging techniques. Alternatives including stereotactic radiotherapy have received further focus and targets for palliative stimulation techniques have grown in number. Individuals' autonomy and quality of life continue to be the subject of research with refinement of what clinicians can do to help persons with epilepsy (PWE) achieve control. This includes seizure management but extends to broader considerations of human empowerment, needs and desires, which may be aided by emerging technologies such as seizure detection devices. The role of specialist nurses in improving that quality has been reinforced by specific endorsement from the International League against Epilepsy (ILAE).

Sudden unexpected death in epilepsy: A critical view of the literature

Sudden unexpected death in epilepsy (SUDEP) is a sudden, unexpected, witnessed or unwitnessed, non-traumatic and non-drowning death, occurring in benign circumstances, in an individual with epilepsy, with or without evidence for a seizure and excluding documented status epilepticus in which postmortem examination does not reveal other causes of death. Lower diagnostic levels are assigned when cases met most or all of these criteria, but data suggested more than one possible cause of death. The incidence of SUDEP ranged from 0.09 to 2.4 per 1000 person-years. Differences can be attributed to the age of the study populations (with peaks in the 20-40-year age group) and the severity of the disease. Young age, disease severity (in particular, a history of generalized TCS), having symptomatic epilepsy, and the response to antiseizure medications (ASMs) are possible independent predictors of SUDEP. The pathophysiological mechanisms are not fully known due to the limited data available and because SUDEP is not always witnessed and has been electrophysiologically monitored only in a few cases with simultaneous assessment of respiratory, cardiac, and brain activity. The pathophysiological basis of SUDEP may vary according to different circumstances that make that particular seizure, in that specific moment and in that patient, a fatal event. The main hypothesized mechanisms, which could contribute to a cascade of events, are cardiac dysfunction (included potential effects of ASMs, genetically determined channelopathies, acquired heart diseases), respiratory dysfunction (included postictal arousal deficit for the respiratory mechanism, acquired respiratory diseases), neuromodulator dysfunction, postictal EEG depression and genetic factors.

Progressive generalized tonic-clonic seizures in a transgenic mouse model of adult-onset epilepsy: Implications for morphological changes in cortico-limbic and brainstem structures

Video/cortical electroencephalography (EEG) is monitored to assess progressive severity of generalized tonic clonic seizures (GTCSs) in a transgenic mouse model of adult-onset epilepsy with increased death risk. The mice overexpress the brain derived neurotrophic factor (BDNF) in the forebrain under the calcium/calmodulin dependent protein kinase 2a (termed TgBDNF) and develop GTCSs in response to tail suspension/cage agitation stimulation at 3-4 months of age. With successive GTCSs (a total of 16 across 10 weeks of assessment), seizures became more severe as evidenced by increased duration of postictal generalized EEG suppression (PGES) associated with loss of posture/consciousness. Mice also developed spike wave discharges with behavioral arrest during the seizure recovery that increased in duration as a function of number of GTCSs. Overall seizure duration (from preictal spike to offset of PGES) and ictal spectral power (full spectra) were also increased. Half of the TgBDNF mice expired following a long period of PGES at the last recorded GTCS. Seizure-evoked general arousal impairment was associated with a striking decrease in total number of gigantocellular neurons of the brainstem nucleus pontis oralis along with increase in volumes of the anterior cingulate cortex and dorsal dentate gyrus in severely convulsive TgBDNF mice compared to litter-matched WT controls and non-convulsive TgBDNF mice. The latter effect was accompanied with an increase in total number of hippocampal granule neurons. These results provide structure-function associations in an animal model of adult-onset GTCSs that progressively increase in severity with clinical relevance for sudden unexpected death following generalized seizures.

Investigation of the effect and availability of ketamine on electroencephalography in cats with temporal lobe epilepsy

In recent years, electroencephalography (EEG) in veterinary medicine has become important not only in the diagnosis of epilepsy, but also in determining the epileptogenic focus. In cats, sedation and immobilization, usually with medetomidine or dexmedetomidine, are necessary to place the electrodes and to obtain stable scalp EEG recordings. In this study, we hypothesized that, for cats with temporal lobe epilepsy (TLE), ketamine, a sedative/anesthetic and N-methyl-D-aspartate (NMDA) antagonist that activates the limbic system and is also used to treat refractory status epilepticus in dogs, would induce sufficient sedation and immobilization for EEG, as well as induce interictal epileptiform discharges (IEDs) that are more pronounced than those induced with medetomidine. We obtained EEG recordings from TLE cats and healthy cats administered either ketamine or medetomidine alone (study 1) or ketamine after medetomidine sedation (study 2). In study 1, the frequency of IEDs showed no statistically significant difference between ketamine and medetomidine in both TLE and healthy cats. Seizures were observed in 75% (9/12) cats of the TLE group with ketamine alone. When ketamine was administered after sedation with medetomidine (study 2), 3/18 cats in the TLE group developed generalized tonic-clonic seizure and 1/18 cats showed subclinical seizure activity. However, no seizures were observed in all healthy cats in both study 1 and study 2. Slow wave activity at 2-4 Hz was observed in many individuals after ketamine administration regardless studies and groups, and quantitative analysis in study 2 showed a trend toward increased delta band activities in both groups. While there was no significant difference in the count of IEDs between medetomidine and ketamine, ketamine caused seizures in cats with TLE similar to their habitual seizure type and with a higher seizure frequency. Our results suggest that ketamine may activate epileptiform discharges during EEG recordings. However, caution should be used for cats with TLE.

Seizures Cause Prolonged Impairment of Ventilation, CO2 Chemoreception and Thermoregulation

Sudden unexpected death in epilepsy (SUDEP) has been linked to respiratory dysfunction, but the mechanisms underlying this association remain unclear. Here we found that both focal and generalized convulsive seizures (GCSs) in epilepsy patients caused a prolonged decrease in the hypercapnic ventilatory response (HCVR; a measure of respiratory CO2 chemoreception). We then studied Scn1a R1407X/+ (Dravet syndrome; DS) and Scn8a N1768D/+ (D/+) mice of both sexes, two models of SUDEP, and found that convulsive seizures caused a postictal decrease in ventilation and severely depressed the HCVR in a subset of animals. Those mice with severe postictal depression of the HCVR also exhibited transient postictal hypothermia. A combination of blunted HCVR and abnormal thermoregulation is known to occur with dysfunction of the serotonin (5-hydroxytryptamine; 5-HT) system in mice. Depleting 5-HT with para-chlorophenylalanine (PCPA) mimicked seizure-induced hypoventilation, partially occluded the postictal decrease in the HCVR, exacerbated hypothermia, and increased postictal mortality in DS mice. Conversely, pretreatment with the 5-HT agonist fenfluramine reduced postictal inhibition of the HCVR and hypothermia. These results are consistent with the previous observation that seizures cause transient impairment of serotonergic neuron function, which would be expected to inhibit the many aspects of respiratory control dependent on 5-HT, including baseline ventilation and the HCVR. These results provide a scientific rationale to investigate the interictal and/or postictal HCVR as noninvasive biomarkers for those at high risk of seizure-induced death, and to prevent SUDEP by enhancing postictal 5-HT tone.SIGNIFICANCE STATEMENT There is increasing evidence that seizure-induced respiratory dysfunction contributes to the pathophysiology of sudden unexpected death in epilepsy (SUDEP). However, the cellular basis of this dysfunction has not been defined. Here, we show that seizures impair CO2 chemoreception in some epilepsy patients. In two mouse models of SUDEP we found that generalized convulsive seizures impaired CO2 chemoreception, and induced hypothermia, two effects reported with serotonergic neuron dysfunction. The defects in chemoreception and thermoregulation were exacerbated by chemical depletion of serotonin and reduced with fenfluramine, suggesting that seizure-induced respiratory dysfunction may be due to impairment of serotonin neuron function. These findings suggest that impaired chemoreception because of transient inhibition of serotonergic neurons may contribute to the pathophysiology of SUDEP.

Sudden unexpected death in epilepsy (SUDEP): A bibliometric analysis

OBJECTIVE

The literature on sudden unexpected death in epilepsy (SUDEP) has been evolving at a staggering rate. We conducted a bibliometric analysis of the SUDEP literature with the aim of presenting its structure, performance, and trends.

METHODS

The Scopus database was searched in April 2023 for documents explicitly detailing SUDEP in their title, abstract, or keywords. After the removal of duplicate documents, bibliometric analysis was performed using the R package bibliometrix and the program VOSviewer. Performance metrics were computed to describe the literature's annual productivity, most relevant authors and countries, and most important publications. Science mapping was performed to visualize the relationships between research constituents by constructing a country collaboration network, co-authorship network, keyword co-occurrence network, and document co-citation network.

RESULTS

A total of 2140 documents were analyzed. These documents were published from 1989 onward, with an average number of citations per document of 25.78. Annual productivity had been on the rise since 2006. Out of 6502 authors, five authors were in both the list of the ten most productive and the list of the ten most cited authors: Devinsky O, Sander JW, Tomson T, Ryvlin P, and Lhatoo SD. The USA and the United Kingdom were the most productive and cited countries. Collaborations between American authors and European authors were particularly rich. Prominent themes in the literature included those related to pathophysiology (e.g., cardiac arrhythmia, apnea, autonomic dysfunction), epilepsy characteristics (e.g., epilepsy type, refractoriness, antiseizure medications), and epidemiology (e.g., incidence, age, sex). Emerging themes included sleep, genetics, epilepsy refractoriness, and non-human studies.

SIGNIFICANCE

The body of literature on SUDEP is rich, fast-growing, and benefiting from frequent international collaborations. Some research themes such as sleep, genetics, and animal studies have become more prevalent over recent years.

Sudden unexpected death in epilepsy

PURPOSE OF REVIEW

Sudden unexpected death in epilepsy (SUDEP) is a leading cause of death in patients with epilepsy. This review highlights the recent literature regarding epidemiology on a global scale, putative mechanisms and thoughts towards intervention and prevention.

RECENT FINDINGS

Recently, numerous population-based studies have examined the incidence of SUDEP in many countries. Remarkably, incidence is quite consistent across these studies, and is commensurate with the recent estimates of about 1.2 per 1000 patient years. These studies further continue to support that incidence is similar across the ages and that comparable factors portend heightened risk for SUDEP. Fervent research in patients and animal studies continues to hone the understanding of potential mechanisms for SUDEP, especially those regarding seizure-induced respiratory dysregulation. Many of these studies and others have begun to lay out a path towards identification of improved treatment and prevention means. However, continued efforts are needed to educate medical professionals about SUDEP risk and the need to disclose this to patients.

SUMMARY

SUDEP is a devastating potential outcome of epilepsy. More is continually learned about risk and mechanisms from clinical and preclinical studies. This knowledge can hopefully be leveraged into preventive measures in the near future.

Ictal ECG-based assessment of sudden unexpected death in epilepsy

Introduction

Previous case-control studies of sudden unexpected death in epilepsy (SUDEP) patients failed to identify ECG features (peri-ictal heart rate, heart rate variability, corrected QT interval, postictal heart rate recovery, and cardiac rhythm) predictive of SUDEP risk. This implied a need to derive novel metrics to assess SUDEP risk from ECG.

Methods

We applied Single Spectrum Analysis and Independent Component Analysis (SSA-ICA) to remove artifact from ECG recordings. Then cross-frequency phase-phase coupling (PPC) was applied to a 20-s mid-seizure window and a contour of −3 dB coupling strength was determined. The contour centroid polar coordinates, amplitude (alpha) and angle (theta), were calculated. Association of alpha and theta with SUDEP was assessed and a logistic classifier for alpha was constructed.

Results

Alpha was higher in SUDEP patients, compared to non-SUDEP patients (p < 0.001). Theta showed no significant difference between patient populations. The receiver operating characteristic (ROC) of a logistic classifier for alpha resulted in an area under the ROC curve (AUC) of 94% and correctly classified two test SUDEP patients.

Discussion

This study develops a novel metric alpha, which highlights non-linear interactions between two rhythms in the ECG, and is predictive of SUDEP risk.

Adherence patterns in antiseizure medications influencing risk of sudden unexplained death in epilepsy: A data linkage study using dispensed prescriptions

OBJECTIVE

Medication adherence is considered an important risk factor for sudden unexpected death in epilepsy (SUDEP), although measurement accuracy is difficult. Using prescription dispensations, this study aims to estimate antiseizure medication (ASM) adherence and identify adherence patterns that influence epilepsy mortality.

METHODS

This is a retrospective cohort study of tertiary epilepsy outpatients seen at St Vincent's Hospital Melbourne, Victoria, Australia, from January 1, 2012 until December 31, 2017. Privacy-preserving data linkage with the Australian national prescription, death, and coroner's databases was performed. We fitted a four-cluster longitudinal group-based trajectory model for ASM adherence from recurring 90-day windows of prescription dispensations during a 3-year "landmark period" from January 1, 2012 to December 31, 2014, using the AdhereR package. We estimated the risk of SUDEP and all-cause death for each adherence pattern during an "observation period" from January 1, 2015 to December 31, 2017. The Cox proportional hazards and logistic regression models were adjusted for age, sex, socioeconomic status, epilepsy duration, comorbidity, drug resistance, and inadequate seizure control.

RESULTS

One thousand one hundred eighty-seven participants were observed for a median of 3.2 years (interquartile range = 2.4-4.0 years). We observed 66 deaths with 10 SUDEP cases during the observation period. We identified four patterns of ASM adherence: good, 51%; declining, 24%; poor, 16%; and very poor, 9%. Declining adherence was associated with an increased risk for SUDEP, with hazard ratio (HR) = 8.43 (95% confidence interval [CI] = 1.10-64.45) at 1 year and HR = 9.17 (95% CI = 1.16-72.21) at 3 years. Compared to no ASM therapeutic change, the addition of a second to fourth ASM offered increased protection against SUDEP in patients with continuing drug-resistant epilepsy.

SIGNIFICANCE

ASM nonadherence was observed in half of outpatients with epilepsy. A declining pattern of adherence, observed in a quarter of patients, was associated with more than eight times increased risk of SUDEP. Any ongoing medication interventions must include strategies to maintain and improve ASM adherence if we are to reduce the risk of SUDEP.

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.

Perspectives on the basis of seizure-induced respiratory dysfunction

Epilepsy is an umbrella term used to define a wide variety of seizure disorders and sudden unexpected death in epilepsy (SUDEP) is the leading cause of death in epilepsy. Although some SUDEP risk factors have been identified, it remains largely unpredictable, and underlying mechanisms remain poorly understood. Most seizures start in the cortex, but the high mortality rate associated with certain types of epilepsy indicates brainstem involvement. Therefore, to help understand SUDEP we discuss mechanisms by which seizure activity propagates to the brainstem. Specifically, we highlight clinical and pre-clinical evidence suggesting how seizure activation of: (i) descending inhibitory drive or (ii) spreading depolarization might contribute to brainstem dysfunction. Furthermore, since epilepsy is a highly heterogenous disorder, we also considered factors expected to favor or oppose mechanisms of seizure propagation. We also consider whether epilepsy-associated genetic variants directly impact brainstem function. Because respiratory failure is a leading cause of SUDEP, our discussion of brainstem dysfunction focuses on respiratory control.

A hybrid unsupervised and supervised learning approach for postictal generalized EEG suppression detection

Sudden unexpected death of epilepsy (SUDEP) is a catastrophic and fatal complication of epilepsy and is the primary cause of mortality in those who have uncontrolled seizures. While several multifactorial processes have been implicated including cardiac, respiratory, autonomic dysfunction leading to arrhythmia, hypoxia, and cessation of cerebral and brainstem function, the mechanisms underlying SUDEP are not completely understood. Postictal generalized electroencephalogram (EEG) suppression (PGES) is a potential risk marker for SUDEP, as studies have shown that prolonged PGES was significantly associated with a higher risk of SUDEP. Automated PGES detection techniques have been developed to efficiently obtain PGES durations for SUDEP risk assessment. However, real-world data recorded in epilepsy monitoring units (EMUs) may contain high-amplitude signals due to physiological artifacts, such as breathing, muscle, and movement artifacts, making it difficult to determine the end of PGES. In this paper, we present a hybrid approach that combines the benefits of unsupervised and supervised learning for PGES detection using multi-channel EEG recordings. A K-means clustering model is leveraged to group EEG recordings with similar artifact features. We introduce a new learning strategy for training a set of random forest (RF) models based on clustering results to improve PGES detection performance. Our approach achieved a 5-second tolerance-based detection accuracy of 64.92%, a 10-second tolerance-based detection accuracy of 79.85%, and an average predicted time distance of 8.26 seconds with 286 EEG recordings using leave-one-out (LOO) cross-validation. The results demonstrated that our hybrid approach provided better performance compared to other existing approaches.

Toward automated prediction of sudden unexpected death in epilepsy

Sudden unexpected death in epilepsy (SUDEP) is a devastating yet overlooked complication of epilepsy. The rare and complex nature of SUDEP makes it challenging to study. No prediction or prevention of SUDEP is currently available in a clinical setting. In the past decade, significant advances have been made in our knowledge of the pathophysiologic cascades that lead to SUDEP. In particular, studies of brain, heart, and respiratory functions in both human patients at the epilepsy monitoring unit and animal models during fatal seizures provide critical information to integrate computational tools for SUDEP prediction. The rapid advances in automated seizure detection and prediction algorithms provide a fundamental framework for their adaption in predicting SUDEP. If a SUDEP can be predicted, then there will be a potential for medical intervention to be administered, either by their caregivers or via an implanted device automatically delivering electrical stimulation or medication, and finally save lives from fatal seizures. This article presents recent developments of SUDEP studies focusing on the pathophysiologic basis of SUDEP and computational implications of machine learning techniques that can be adapted and extended for SUDEP prediction. This article also discusses some novel ideas for SUDEP prediction and rescue including principal component analysis and closed-loop intervention.

Progressive slowing of clonic phase predicts postictal generalized EEG suppression

OBJECTIVE

Postictal generalized electroencephalography (EEG) suppression (PGES) is a surrogate marker of sudden unexpected death in epilepsy (SUDEP). It is still unclear which ictal phenomena lead to prolonged PGES and increased risk of SUDEP. Semiology features of generalized convulsive seizure (GCS type 1) have been reported as a predictor of prolonged PGES. Progressive slowing of clonic phase (PSCP) has been observed in GCSs, with gradually increasing inhibitory periods interrupting the tonic contractions. We hypothesized that PSCP is associated with prolonged PGES.

METHODS

We analyzed 90 bilateral convulsive seizures in 50 consecutive patients (21 female; age: 11-62 years, median: 31 years) recruited to video-EEG monitoring. Five raters, blinded to all other data, independently assessed the presence of PSCP. PGES and seizure semiology were evaluated independently. We determined inter-rater agreement (IRA) for the presence of PSCP, and we evaluated its association, as well as that of other ictal features, with the occurrence of PGES, prolonged PGES (≥20 s) and very prolonged PGES (≥50 s) using multivariate logistic regression analysis.

RESULTS

We found substantial IRA for the presence of PSCP (percent agreement: 80%; beyond-chance agreement coefficient: .655). PSCP was an independent predictor of the occurrence of PGES and prolonged PGES (p < .001). All seizures with very prolonged PGES had PSCP. GCS type 1 was an independent predictor of occurrence of PGES (p = .02) and prolonged PGES (p = .03) but not of very prolonged PGES. Only half of the seizures with very prolonged PGES were GCS type 1.

SIGNIFICANCE

PSCP predicts prolonged PGES, emphasizing the importance of gradually increasing inhibitory phenomena at the end of the seizures. Our findings shed more light on the ictal phenomena leading to increased risk of SUDEP. These phenomena may provide basis for algorithms implemented into wearable devices for identifying GCS with increased risk of SUDEP.

Serotonin receptor expression in hippocampus and temporal cortex of temporal lobe epilepsy patients by postictal generalized electroencephalographic suppression duration

OBJECTIVE

Prolonged postictal generalized electroencephalographic suppression (PGES) is a potential biomarker for sudden unexpected death in epilepsy (SUDEP), which may be associated with dysfunctional autonomic responses and serotonin signaling. To better understand molecular mechanisms, PGES duration was correlated to 5HT1A and 5HT2A receptor protein expression and RNAseq from resected hippocampus and temporal cortex of temporal lobe epilepsy patients with seizures recorded in preoperative evaluation.

METHODS

Analyses included 36 cases (age = 14-64 years, age at epilepsy onset = 0-51 years, epilepsy duration = 2-53 years, PGES duration = 0-93 s), with 13 cases in all hippocampal analyses. 5HT1A and 5HT2A protein was evaluated by Western blot and histologically in hippocampus (n = 16) and temporal cortex (n = 9). We correlated PGES duration to our previous RNAseq dataset for serotonin receptor expression and signaling pathways, as well as weighted gene correlation network analysis (WGCNA) to identify correlated gene clusters.

RESULTS

In hippocampus, 5HT2A protein by Western blot positively correlated with PGES duration (p = .0024, R2  = .52), but 5HT1A did not (p = .87, R2  = .0020). In temporal cortex, 5HT1A and 5HT2A had lower expression and did not correlate with PGES duration. Histologically, PGES duration did not correlate with 5HT1A or 5HT2A expression in hippocampal CA4, dentate gyrus, or temporal cortex. RNAseq identified two serotonin receptors with expression that correlated with PGES duration in an exploratory analysis: HTR3B negatively correlated (p = .043, R2  = .26) and HTR4 positively correlated (p = .049, R2  = .25). WGCNA identified four modules correlated with PGES duration, including positive correlation with synaptic transcripts (p = .040, Pearson correlation r = .52), particularly potassium channels (KCNA4, KCNC4, KCNH1, KCNIP4, KCNJ3, KCNJ6, KCNK1). No modules were associated with serotonin receptor signaling.

SIGNIFICANCE

Higher hippocampal 5HT2A receptor protein and potassium channel transcripts may reflect underlying mechanisms contributing to or resulting from prolonged PGES. Future studies with larger cohorts should assess functional analyses and additional brain regions to elucidate mechanisms underlying PGES and SUDEP risk.

Sudden Unexpected Death in Epilepsy: Pathogenesis, Risk Factors, and Prevention

Sudden unexpected death in epilepsy (SUDEP) is a tragic and unexpected cause of death in patients with a known diagnosis of epilepsy. It occurs in up to 6.3 to 9.3/1,000 patients with drug-resistant epilepsy. The main three risk factors associated with SUDEP are the presence of generalized tonic-clonic seizures, the presence of a seizure in the past year, and an intellectual disability. There are several mechanisms that can result in SUDEP. The most likely sequence of events appears to be a convulsive seizure, overactivation of the autonomic nervous system, cardiorespiratory dysfunction, and death. While the risk of SUDEP is relatively high in patients with drug-resistant epilepsy, studies indicate that more than 50% of patients and caregivers are unaware of the diagnosis. Counseling about the diagnosis and preventative measures at the time of diagnosis is important. There are numerous interventions that may reduce the risk of SUDEP, including conservative measures such as nocturnal surveillance with a bed partner (where applicable) and automated devices. Optimizing seizure control with antiseizure medications and surgical interventions can result in a reduced risk of SUDEP.

Quiescence during burst suppression and postictal generalized EEG suppression are distinct patterns of activity

OBJECTIVE

Periods of low-amplitude electroencephalographic (EEG) signal (quiescence) are present during both anesthetic-induced burst suppression (BS) and postictal generalized electroencephalographic suppression (PGES). PGES following generalized seizures induced by electroconvulsive therapy (ECT) has been previously linked to antidepressant response. The commonality of quiescence during both BS and PGES motivated trials to recapitulate the antidepressant effects of ECT using high doses of anesthetics. However, there have been no direct electrographic comparisons of these quiescent periods to address whether these are distinct entities.

METHODS

We compared periods of EEG quiescence recorded from two human studies: BS induced in 29 healthy adult volunteers by isoflurane general anesthesia and PGES in 11 patients undergoing right unilateral ECT for treatment-resistant depression. An automated algorithm allowed detection of EEG quiescence based on a 10-microvolt amplitude threshold. Spatial, spectral, and temporal analyses compared quiescent epochs during BS and PGES.

RESULTS

The median (interquartile range) voltage for quiescent periods during PGES was greater than during BS (1.81 (0.22) microvolts vs 1.22 (0.33) microvolts, p < 0.001). Relative power was greater for quiescence during PGES than BS for the 1-4 Hz delta band (p < 0.001), at the expense of power in the theta (4-8 Hz, p < 0.001), beta (13-30 Hz, p = 0.04) and gamma (30-70 Hz, p = 0.006) frequency bands. Topographic analyses revealed that amplitude across the scalp was consistently higher for quiescent periods during PGES than BS, whose voltage was within the noise floor.

CONCLUSIONS

Quiescent epochs during PGES and BS have distinct patterns of EEG signals across voltage, frequency, and spatial domains.

SIGNIFICANCE

Quiescent epochs during PGES and BS, important neurophysiological markers for clinical outcomes, are shown to have distinct voltage and frequency characteristics.

A multimodal clinical data resource for personalized risk assessment of sudden unexpected death in epilepsy

Epilepsy affects ~2-3 million individuals in the United States, a third of whom have uncontrolled seizures. Sudden unexpected death in epilepsy (SUDEP) is a catastrophic and fatal complication of poorly controlled epilepsy and is the primary cause of mortality in such patients. Despite its huge public health impact, with a ~1/1,000 incidence rate in persons with epilepsy, it is an uncommon enough phenomenon to require multi-center efforts for well-powered studies. We developed the Multimodal SUDEP Data Resource (MSDR), a comprehensive system for sharing multimodal epilepsy data in the NIH funded Center for SUDEP Research. The MSDR aims at accelerating research to address critical questions about personalized risk assessment of SUDEP. We used a metadata-guided approach, with a set of common epilepsy-specific terms enforcing uniform semantic interpretation of data elements across three main components: (1) multi-site annotated datasets; (2) user interfaces for capturing, managing, and accessing data; and (3) computational approaches for the analysis of multimodal clinical data. We incorporated the process for managing dataset-specific data use agreements, evidence of Institutional Review Board review, and the corresponding access control in the MSDR web portal. The metadata-guided approach facilitates structural and semantic interoperability, ultimately leading to enhanced data reusability and scientific rigor. MSDR prospectively integrated and curated epilepsy patient data from seven institutions, and it currently contains data on 2,739 subjects and 10,685 multimodal clinical data files with different data formats. In total, 55 users registered in the current MSDR data repository, and 6 projects have been funded to apply MSDR in epilepsy research, including three R01 projects and three R21 projects.

Sudden Unexpected Death in Epilepsy

Epilepsy is a complex neurological condition with numerous etiologies and treatment options. In a subset of these patients, sudden unexpected death can occur, and to date, there are numerous explanations as to the pathophysiological mechanisms and how to mitigate these catastrophic outcomes. Approximately 2.3 million Americans have epilepsy, and nearly 150,000 people develop the condition each year. Sudden unexpected death in epilepsy (SUDEP) accounts for 2–18% of all epilepsy-related deaths and this is equivalent to one death in 1000 person-years of diagnosed epilepsy. It is more common in young adults aged 20–45. Seizures in the past year; the absence of terminal remission in the last five years; increased seizure frequency, particularly GTCS; and nocturnal seizures are the most potent modifiable risk factors for SUDEP. Patients not receiving any antiepileptic drug therapy are at higher risk of SUDEP. Patient education on medication compliance; care plans for seizure clusters (rescue medicines); epilepsy self-management programs; and lifestyle changes to avoid seizure-triggering factors, including avoiding excessive alcohol use and sleep deprivation, should be provided by health care providers. Continued research into SUDEP will hopefully lead to effective interventions to minimize occurrences. At present, aggressive control of epilepsy and enhanced education for individuals and the public are the most effective weapons for combating SUDEP. This narrative review focuses on updated information related to SUDEP epidemiology; pathophysiology; risk factor treatment options; and finally, a discussion of important clinical studies. We seek to encourage clinicians who care for patients with epilepsy to be aggressive in controlling seizure activity and diligent in their review of risk factors and education of patients and their families about SUDEP.

Changes of oxygen saturation in patients with pure temporal lobe epilepsy

PURPOSE

Ictal hypoxemia is accepted as one of the mechanisms underlying sudden unexpected death in epilepsy (SUDEP). Although ictal hypoxemia is more common in generalized seizures, it also occurs in focal seizures with or without generalization. In this study, we aimed to show the relationship between clinical and electroencephalographic findings of seizures in patients with temporal lobe epilepsy (TLE) with periictal oxygen saturation.

METHODS

The data of 55 adult patients who were hospitalized in the Video EEG Monitoring Unit (VEMU) and operated on for drug-resistant TLE between January 2017 and December 2020 were examined. Forty-five seizures from 21 patients with ictal peripheral arterial saturation information and that were seizure-free for at least a year during the follow-up were included in the study.

RESULTS

The median patient age was 28 (IQR 25-39.5) years (women: 9, men: 12). Age at epilepsy onset was negatively correlated with saturation at seizure onset. Moreover, the age at VEMU admission was also negatively correlated with saturation at seizure onset and the lowest levels of saturation. The saturation at the end of the seizures and the lowest saturation measured in the periictal period with generalization of EEG were significantly lower than those without generalization. The onset of ictal EEG with the rhythmic theta pattern was significantly associated with the lowest level of saturation (<90%), postictal generalized electroencephalographic suppression (PGES), and the presence of generalization.

CONCLUSION

According to the study, rhythmic ictal theta activity, older age, nocturnal seizure, and generalization in ictal EEG might increase the potential risk of SUDEP. Further studies including a greater number of subjects and different epilepsy syndromes may provide more comprehensive information about potential biomarkers for SUDEP.

Risk of SUDEP during infancy

Risk of sudden unexpected death in epilepsy (SUDEP) in children is influenced by different factors such as etiology, seizure type and frequency, treatment, and environment. A greater severity of epilepsy, in terms of seizure frequency, seizures type, especially with nocturnal generalized tonic-clonic seizures (GTCS), and resistance to anti-seizure medication are predisposing factors to SUDEP. Potential mechanisms of SUDEP might involve respiratory, cardiovascular, and central autonomic dysfunctions, either combined or in isolation. Patients with epilepsy carrying mutations in cardiac channelopathy genes might be disposed to seizure-induced arrhythmias. Other than in channelopathies, SUDEP has been reported in further patients with genetic epilepsies due to mutations of genes such as DEPDC5, TBC1D24, FHF1, or 5q14.3 deletion. Age-related electro-clinical differences in GTCS may therefore be relevant in explaining differences in SUDEP between adults and children. Typical GTCS represent a rare seizure type in infants and toddlers, they are characterized by a shorter tonic phase and, in direct proportion, by shorter postictal generalized EEG suppression (PGES). The presence of night-time supervision has been found to reduce SUDEP risk, likely reducing SUDEP incidence in children. Reconsideration of safety protocols in epilepsy monitoring units with the aim of reducing the risk of SUDEP, and the use of devices for seizure detection, might contribute to reduce the risk of death in patients affected by epilepsy. This article is part of the Special Issue "Severe Infantile Epilepsies".

The role of monoaminergic neurons in modulating respiration during sleep and the connection with SUDEP

Sudden unexpected death in epilepsy (SUDEP) is the leading cause of death among epilepsy patients, occurring even more frequently in cases with anti-epileptic drug resistance. Despite some advancements in characterizing SUDEP, the underlying mechanism remains incompletely understood. This review summarizes the latest advances in our understanding of the pathogenic mechanisms of SUDEP, in order to identify possible targets for the development of new strategies to prevent SUDEP. Based on our previous research along with the current literature, we focus on the role of sleep-disordered breathing (SDB) and its related neural mechanisms to consider the possible roles of monoaminergic neurons in the modulation of respiration during sleep and the occurrence of SUDEP. Overall, this review suggests that targeting the monoaminergic neurons is a promising approach to preventing SUDEP. The proposed roles of SDB and related monoaminergic neural mechanisms in SUDEP provide new insights for explaining the pathogenesis of SUDEP.

Interictal EEG and ECG for SUDEP Risk Assessment: A Retrospective Multicenter Cohort Study

Objective

Sudden unexpected death in epilepsy (SUDEP) is the leading cause of epilepsy-related mortality. Although lots of effort has been made in identifying clinical risk factors for SUDEP in the literature, there are few validated methods to predict individual SUDEP risk. Prolonged postictal EEG suppression (PGES) is a potential SUDEP biomarker, but its occurrence is infrequent and requires epilepsy monitoring unit admission. We use machine learning methods to examine SUDEP risk using interictal EEG and ECG recordings from SUDEP cases and matched living epilepsy controls.

Methods

This multicenter, retrospective, cohort study examined interictal EEG and ECG recordings from 30 SUDEP cases and 58 age-matched living epilepsy patient controls. We trained machine learning models with interictal EEG and ECG features to predict the retrospective SUDEP risk for each patient. We assessed cross-validated classification accuracy and the area under the receiver operating characteristic (AUC) curve.

Results

The logistic regression (LR) classifier produced the overall best performance, outperforming the support vector machine (SVM), random forest (RF), and convolutional neural network (CNN). Among the 30 patients with SUDEP [14 females; mean age (SD), 31 (8.47) years] and 58 living epilepsy controls [26 females (43%); mean age (SD) 31 (8.5) years], the LR model achieved the median AUC of 0.77 [interquartile range (IQR), 0.73–0.80] in five-fold cross-validation using interictal alpha and low gamma power ratio of the EEG and heart rate variability (HRV) features extracted from the ECG. The LR model achieved the mean AUC of 0.79 in leave-one-center-out prediction.

Conclusions

Our results support that machine learning-driven models may quantify SUDEP risk for epilepsy patients, future refinements in our model may help predict individualized SUDEP risk and help clinicians correlate predictive scores with the clinical data. Low-cost and noninvasive interictal biomarkers of SUDEP risk may help clinicians to identify high-risk patients and initiate preventive strategies.

Duration of postictal impaired awareness after bilateral tonic-clonic seizures: EEG and patient characteristics

OBJECTIVE

Ictal and postictal phenomena that may impact the duration of postictal impaired awareness have not been well studied. Postictal unresponsiveness invariably occurs following bilateral tonic-clonic seizures (BTCS). Bilateral tonic-clonic seizures are a major risk factor for sudden unexpected death in epilepsy (SUDEP). We quantify the effects of seizure characteristics on postictal recovery of awareness following BTCS. Factors include: the total seizure duration, the duration of the tonic phase of a BTCS, presence of postictal generalized EEG suppression (PGES), duration of postictal tonic electromyographic discharge, peri-ictal respiratory dysfunction, patient age, duration of epilepsy, and gender.

METHODS

Fifty-eight patients admitted to the epilepsy monitoring unit with BTCS were studied. Forty-one had unilateral onset temporal seizures. The remainder had bitemporal onsets, extratemporal onsets, undetermined onsets, or were generalized at onset. Following the first BTCS, time to initial recovery of awareness and its possible association with patient and seizure characteristics as well as peri-ictal respiratory dysfunction were evaluated. The presence or absence of postictal agitation was noted.

RESULTS

The severity of respiratory dysfunction and seizure characteristics were not associated with time to initial recovery of awareness. A shorter time to recovery of awareness was significantly associated with a younger age (p = 0.007). Postictal agitation was more common in males (p = 0.023).

SIGNIFICANCE

Focal seizures may impair awareness by active inhibition of subcortical arousal mechanisms. Focal seizures progressing to bilateral tonic-clonic seizures (BTCS) result in further widespread cerebral dysfunction impacting postictal awareness. MRI studies show accelerated brain aging in patients with temporal lobe epilepsy. Our findings suggest that patient age, as a surrogate marker for the lifetime burden of seizures, results in a progressive worsening in time to recovery after BTCS by an increasing negative impact on networks involved in arousal.

Prolonged Video-EEG and Heart Rate Variability can Elucidate Autonomic Dysregulation in Infantile Apneic Seizures

BACKGROUND

Infantile apneic seizures (IASs) are unexpected life-threatening events. We aimed to determine the utility of prolonged video-electroencephalography (vEEG) and heart rate variability (HRV) in IAS.

METHODS

The study included seven infants with apneic seizures captured by vEEG, percutaneous oxygen saturation (SpO₂), and electrocardiography (ECG). Interictal, preictal, and postictal HRV of patients and N2 sleep HRV of 10 age-matched controls were determined.

RESULTS

We analyzed seven vEEGs (duration = 17 to 87 hours) of seven patients aged three to 13 months (mean onset age of apneic event = 6.3 months). Fifteen apneic seizures (one to five per infant) were captured. The initial apneic seizure was captured at 7.5 to 76 hours (mean = 36.6 hours) after vEEG initiation. Ictal rhythmic delta/theta/fast waves were seen over temporal (five patients), central (one), and diffuse areas (one). Ictal SpO₂ decreased between 1.5% and 90% (mean = 47.9%). Ictal decreased heart rate (HR) (six seizures) and ictal increased HR (14) was detected. Both decreased and increased HR was observed (five). The preictal low-frequency (LF)/high-frequency (HF) ratio was significantly higher than the interictal LF/HF ratio (P = 0.048). Preictal (P = 0.048), and postictal (P = 0.019) root mean square of successive differences (RMSSDs) of patients were lower than the sleep RMSSD of controls. These results indicated dominant sympathetic activity. RMSSD from interictal to preictal periods tended to be higher in IAS with decreased HR than in IAS with increased HR alone (P = 0.066). The postictal RMSSD showed tendency to be higher in IAS with decreased HR than in IAS with increased HR alone (P = 0.088). The decreased HR and increased RMSSD suggested not only sympathetic activity but also escalated parasympathetic activity in IAS.

CONCLUSIONS

Infants with unexpected apneic events should be monitored with prolonged vEEG, SpO₂, and ECG. Abnormal HRV in infants with apneic seizures might indicate additional autonomic dysregulation in IAS.

Sudden unexpected death in epilepsy: Respiratory mechanisms

Epilepsy is one of the most common chronic neurologic diseases, with a prevalence of 1% in the US population. Many people with epilepsy live normal lives, but are at risk of sudden unexpected death in epilepsy (SUDEP). This mysterious comorbidity of epilepsy causes premature death in 17%-50% of those with epilepsy. Most SUDEP occurs after a generalized seizure, and patients are typically found in bed in the prone position. Until recently, it was thought that SUDEP was due to cardiovascular failure, but patients who died while being monitored in hospital epilepsy units revealed that most SUDEP is due to postictal central apnea. Some cases may occur when seizures invade the amygdala and activate projections to the brainstem. Evidence suggests that the pathophysiology is linked to defects in the serotonin system and central CO₂ chemoreception, and that there is considerable overlap with mechanisms thought to be involved in sudden infant death syndrome (SIDS). Future work is needed to identify biomarkers for patients at highest risk, improve ascertainment, develop methods to alert caregivers when SUDEP is imminent, and find effective approaches to prevent these fatal events.

A Peri-Ictal EEG-Based Biomarker for Sudden Unexpected Death in Epilepsy (SUDEP) Derived From Brain Network Analysis

Sudden unexpected death in epilepsy (SUDEP) is the leading seizure-related cause of death in epilepsy patients. There are no validated biomarkers of SUDEP risk. Here, we explored peri-ictal differences in topological brain network properties from scalp EEG recordings of SUDEP victims. Functional connectivity networks were constructed and examined as directed graphs derived from undirected delta and high frequency oscillation (HFO) EEG coherence networks in eight SUDEP and 14 non-SUDEP epileptic patients. These networks were proxies for information flow at different spatiotemporal scales, where low frequency oscillations coordinate large-scale activity driving local HFOs. The clustering coefficient and global efficiency of the network were higher in the SUDEP group pre-ictally, ictally and post-ictally (p < 0.0001 to p < 0.001), with features characteristic of small-world networks. These results suggest that cross-frequency functional connectivity network topology may be a non-invasive biomarker of SUDEP risk.

OUP accepted manuscript

Sudden unexpected death in epilepsy is the most catastrophic outcome of epilepsy. Each year there are as many as 1.65 cases of such death for every 1000 individuals with epilepsy. Currently, there are no methods to predict or prevent this tragic event, due in part to a poor understanding of the pathologic cascade that leads to death following seizures. We recently identified enhanced seizure-induced mortality in four inbred strains from the genetically diverse Collaborative Cross mouse population. These mouse models of sudden unexpected death in epilepsy provide a unique tool to systematically examine the physiological alterations during fatal seizures, which can be studied in a controlled environment and with consideration of genetic complexity. Here, we monitored the brain oscillations and heart functions before, during, and after non-fatal and fatal seizures using a flurothyl-induced seizure model in freely moving mice. Compared with mice that survived seizures, non-survivors exhibited significant suppression of brainstem neural oscillations that coincided with cortical epileptic activities and tachycardia during the ictal phase of a fatal seizure. Non-survivors also exhibited suppressed delta (0.5–4 Hz)/gamma (30–200 Hz) phase-amplitude coupling in cortex but not in brainstem. A connectivity analysis revealed elevated synchronization of cortex and brainstem oscillations in the delta band during fatal seizures compared with non-fatal seizures. The dynamic ictal oscillatory and connectivity features of fatal seizures provide insights into sudden unexpected death in epilepsy and may suggest biomarkers and eventual therapeutic targets.

Does the type of seizure influence heart rate variability changes?

OBJECTIVE

Heart rate variability (HRV), an index of the autonomic cardiac activity, is decreased in patients with epilepsy, and a low HRV is associated with a higher risk of sudden death. Generalized tonic-clonic seizures are one of the most consistent risk factors for SUDEP, but the influence (and relative risk) of each type of seizure on cardiac function is still unknown. Our objective was to assess the impact of the type of seizure (focal to bilateral tonic-clonic seizure - FBTCS - versus non-FBTCS) on periictal HRV, in a group of patients with refractory epilepsy and both types of seizures.

METHODS

We performed a 48-hour Holter recording on 121 patients consecutively admitted to our Epilepsy Monitoring Unit. We only included patients with both FBTCS and non-FBTCS on the Holter recording and selected the first seizure of each type to analyze. To evaluate HRV parameters (AVNN, SDNN, RMSSD, pNN20, LF, HF, and LF/HF), we chose 5-min epochs pre- and postictally.

RESULTS

We included 14 patients, with a median age of 36 (min-max, 16-55) years and 64% were female. Thirty-six percent had cardiovascular risk factors, but no previously known cardiac disease. In the preictal period, there were no statistically significant differences in HRV parameters, between FBTCS and non-FBTCS. In the postictal period, AVNN, RMSSD, pNN20, LF, and HF were significantly lower, and LF/HF and HR were significantly higher in FBTCS. From preictal to postictal periods, FBTCS elicited a statistically significant rise in HR and LF/HF, and a statistically significant fall in AVNN, RMSSD, pNN20, and HF. Non-FBTCS only caused statistically significant changes in HR (decrease) and AVNN (increase).

SIGNIFICANCE/CONCLUSION

This work emphasizes the greater effect of FBTCS in autonomic cardiac function in patients with refractory epilepsy, compared to other types of seizures, with a significant reduction in vagal tonus, which may be associated with an increased risk of SUDEP.

Adrenal function during long-term ACTH therapy for patients with developmental and epileptic encephalopathy

Some patients with developmental and epileptic encephalopathy (DEE) respond to adrenocorticotropic hormone (ACTH) therapy but relapse soon after. While long‐term ACTH therapy (LT‐ACTH) has been attempted for these patients, no previous studies have carefully assessed adrenal function during LT‐ACTH. We evaluated the effectiveness of LT‐ACTH, as well as adverse effects (AE), including their adrenal function in three DEE patients. Patients underwent a corticotropin‐releasing hormone (CRH) stimulation test during LT‐ACTH, and those with peak serum cortisol below 15 μg/dL were considered to be at high risk of adrenal insufficiency (AI). Two of three responded, and their life‐threatening seizures with postgeneralized electroencephalogram (EEG) suppression decreased. Although no individuals had serious AE, CRH stimulation test revealed relatively weak responses, without reaching normal cortisol peak level (18 μg/dL). Hydrocortisone replacement during stress was prepared in a case with lower cortisol peak than our cutoff level. LT‐ACTH could be a promising treatment option for cases of DEE that relapse soon after effective ACTH treatment. The longer duration and larger cumulative dosage in LT‐ACTH than in conventional ACTH could increase the relative risk of AI. Careful evaluation with pediatric endocrinologists, including hormonal stimulation tests, might be useful for continuing this treatment safely.

Seizures induced in electroconvulsive therapy as a human epilepsy model: A comparative case study

OBJECTIVE

Standardized investigation of epileptic seizures and the postictal state may contribute to a better understanding of ictal and postictal phenomena. This comparative case study aims to assess whether electrically induced seizures in electroconvulsive therapy (ECT) show sufficient similarities with spontaneous seizures to serve as a human epilepsy model.

METHODS

We compared six EEG recordings, three ECT-induced seizures and three generalized tonic-clonic seizures, using quantitative electroencephalography (EEG) analyses. EEG recordings during and after ECT sessions (under general anesthesia and muscle paralysis) were collected prospectively, whereas epilepsy data were selected retrospectively. Time-frequency representations, dominant ictal frequencies, and postictal alpha-delta ratios were calculated.

RESULTS

In all EEG recordings, a decrease in dominant ictal frequency was observed, as well as postictal suppression. Postictal alpha-delta ratio indicated the same trend for all: a gradual increase from predominantly delta to alpha frequencies on timescales of hours after the seizure. Postictal spectral representation was similar. Muscle artifacts were absent in ECT-induced seizures and present in spontaneous seizures. Ictal amplitude was higher in epileptic than in ECT-induced seizures. Temporospectral ictal dynamics varied slightly between groups.

SIGNIFICANCE

We show that ictal and postictal characteristics in ECT and patients with generalized tonic-clonic seizures are essentially similar. ECT-induced seizures may be used to investigate aspects of ictal and postictal states in a highly predictable manner and well-controlled environment. This suggests that clinical and electrophysiological observations during ECT may be extrapolated to epilepsy with generalized tonic-clonic seizures.

Reducing Sudden Unexpected Death in Epilepsy: Considering Risk Factors, Pathophysiology and Strategies

Purpose of Review

Sudden Unexpected Death in Epilepsy (SUDEP) is the commonest cause of epilepsy-related premature mortality in people with chronic epilepsy. It is the most devastating epilepsy outcome. We describe and discuss risk factors and possible pathophysiological mechanisms to elucidate possible preventative strategies to avert SUDEP.

Recent Findings

Sudden death accounts for a significant proportion of premature mortality in people with epilepsy compared to the general population. Unmodifiable risk factors include a history of neurologic insult, younger age of seizure-onset, longer epilepsy duration, a history of convulsions, symptomatic epilepsy, intellectual disability, and non-ambulatory status. Modifiable risk factors include the presence of convulsive seizures, increased seizure frequency, timely and appropriate use of antiseizure medications, polytherapy, alcoholism, and supervision while sleeping. Pathophysiology is unclear, but several possible mechanisms such as direct alteration of cardiorespiratory function, pulmonary impairment, electrocerebral shutdown, adenosine dysfunction, and genetic susceptibility suggested.

Summary

Methods to prevent SUDEP include increasing awareness of SUDEP, augmenting knowledge of unmodifiable risk factors, obtaining full seizure remission, addressing lifestyle factors such as supervision and prone positioning, and enacting protocols to increase the detection of and intervention for SUDEP. Further studies are required to characterize precisely and comprehensively SUDEP risk factors and pathophysiological drivers and develop evidence-based algorithms to minimize SUDEP in people with epilepsy.

Phase-Amplitude Coupling Features Accurately Classify Multiple Sub-States Within a Seizure Episode

Epilepsy is frequently characterized by convulsive seizures, which are often followed by a postictal EEG suppression state (PGES). The ability to automatically detect and monitor seizure progression and postictal state can allow for early warning of seizure onset, timely intervention in seizures themselves, as well as identification of major complications in epilepsy such as status epilepticus and sudden unexpected death in epilepsy (SUDEP). To test whether it is possible to reliably differentiate these ictal and postictal states, we investigated 52 seizure records (both intracranial and scalp EEG) from 19 patients. Phase-amplitude cross-frequency coupling was calculated for each recording and used as an input to a convolutional neural network model, achieving the mean accuracy of 0.890.09 across all classes, with the worst class accuracy of 0.73 for one of the later ictal sub-states. When the trained model was applied to SUDEP patient data, it classified seizure recordings as primarily interictal and PGES-like state (70% and 26%, respectively), highlighting the fact that in SUDEP patients seizures primarily exist in postictal states and don't show the ictal sub-state evolution. These results suggest that using frequency coupling markers with a machine learning algorithm can reliably identify ictal and postictal sub-states, which can open up opportunities for novel monitoring and management approaches in epilepsy.

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.