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

Cardiac arrhythmia and epilepsy genetic variants in sudden unexpected death in epilepsy

Introduction

Sudden Unexpected Death in Epilepsy (SUDEP) is the leading epilepsy-related cause of death, affecting approximately 1 per 1,000 individuals with epilepsy per year. Genetic variants that affect autonomic function, such as genes associated with cardiac arrhythmias, may predispose people with epilepsy to greater risk of both sudden cardiac death and SUDEP. Advances in next generation sequencing allow for the exploration of gene variants as potential biomarkers.

Methods

Genetic testing for the presence of cardiac arrhythmia and epilepsy gene variants was performed via genetic panels in 39 cases of SUDEP identified via autopsy by the Ontario Forensic Pathology Service. Variants were summarized by in-silico evidence for pathogenicity from 4 algorithms (SIFT, PolyPhen-2, PROVEAN, Mutation Taster) and allele frequencies in the general population (GnomAD). A maximum credible population allele frequency of 0.00004 was calculated based on epilepsy prevalence and SUDEP incidence to assess whether a variant was compatible with a pathogenic interpretation.

Results

Median age at the time of death was 33.3 years (range: 2, 60). Fifty-nine percent (n=23) were male. Gene panels detected 62 unique variants in 45 genes: 19 on the arrhythmia panel and 26 on the epilepsy panel. At least one variant was identified in 28 (72%) of decedents. Missense mutations comprised 57 (92%) of the observed variants. At least three in silico models predicted 12 (46%) cardiac arrhythmia panel missense variants and 20 (65%) epilepsy panel missense variants were pathogenic. Population allele frequencies were <0.00004 for 11 (42%) of the cardiac variants and 10 (32%) of the epilepsy variants. Together, these metrics identified 13 SUDEP variants of interest.

Discussion

Nearly three-quarters of decedents in this SUDEP cohort carried variants in comprehensive epilepsy or cardiac arrhythmia gene panels, with more than a third having variants in both panels. The proportion of decedents with cardiac variants aligns with recent studies of the disproportionate cardiac burden the epilepsy community faces compared to the general population and suggests a possible cardiac contribution to epilepsy mortality. These results identified 13 priority targets for future functional studies of these genes potential role in sudden death and demonstrates the necessity for further exploration of potential genetic contributions to SUDEP.

Predictors of unprovoked seizures in intracerebral hemorrhages

BACKGROUND

Seizures are a common complication of intracerebral hemorrhage (ICH). We aimed to identify predictors of unprovoked seizures (US) after ICH in a Chinese cohort.

METHODS

We retrospectively included patients with ICH admitted in the Second Hospital of Hebei Medical University between November 2018 and December 2020. Incidence and risk factors of US were identified with univariate and then multiple Cox regression analysis. We used χ2 test to compare incidence of US between groups with or without prophylactic anti-seizure medications (ASM) in patients with craniotomy.

RESULTS

A total of 488 patients were included in the cohort, 58 (11.9%) patients developed US within 3 years after ICH. Analysis on the 362 patients without prophylactic ASM showed that craniotomy (HR 8.35, 95% CI 3.80-18.31) and acute symptomatic seizures (ASS) (HR 13.76, 95% CI 3.56-53.17) are independent predictors of US. No significant effect of prophylactic ASM use was found on incidence of US in ICH patients with craniotomy (P = 0.369).

CONCLUSIONS

Craniotomy and acute symptomatic seizures were independent predictors for unprovoked seizures after ICH, suggesting that more attention should be paid for such patients during follow-up. Whether prophylactic ASM treatment benefits ICH patients underwent craniotomy remains uncertain.

Epilepsy-Related Mortality After Laser Interstitial Thermal Therapy in Patients With Drug-Resistant Epilepsy

OBJECTIVES

The purpose of this report was to study the incidence of sudden unexpected death in epilepsy (SUDEP) after laser interstitial thermal therapy (LITT) for drug-resistant epilepsy (DRE).

METHODS

A prospective observational study of consecutive patients treated with LITT between 2013 and 2021 was conducted. The primary outcome was the occurrence of SUDEP during postoperative follow-up. Surgical outcome was classified according to the Engel scale.

RESULTS

There were 5 deaths, including 4 SUDEPs, among 135 patients with a median follow-up duration of 3.5 (range 0.1-9.0) years and a total of 501.3 person-years at risk. The estimated incidence of SUDEP was 8.0 (95% CI 2.2-20.4) per 1,000 person-years. Three SUDEPs occurred in patients with poor seizure outcomes, whereas 1 patient was seizure-free. Compared with pooled historical data, SUDEP occurred at a higher rate than in cohorts treated with resective surgery and at a rate similar to nonsurgical controls.

DISCUSSION

SUDEP occurred early and late after mesial temporal LITT. The SUDEP rate was comparable with rates reported in epilepsy surgery candidates who did not receive intervention. These findings reinforce targeting seizure freedom to decrease SUDEP risk, including early consideration for further intervention.

CLASSIFICATION OF EVIDENCE

This study provides Class IV evidence that LITT is not effective in reducing SUDEP incidence in patients with DRE.

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.

ILAE Genetic Literacy Series: Postmortem Genetic Testing in Sudden Unexpected Death in Epilepsy

A 24-year-old man with non-lesional bitemporal lobe epilepsy since age 16 years was found dead in bed around midday. He was last seen the previous night when he was witnessed to have a tonic-clonic seizure. Before his death, he was experiencing weekly focal impaired awareness seizures and up to two focal-to-bilateral tonic-clonic seizures each year. He had trialed several antiseizure medications and was on levetiracetam 1500 mg/day, lamotrigine 400 mg/day, and clobazam 10 mg/day at the time of death. Other than epilepsy, his medical history was unremarkable. Of note, he had an older brother with a history of febrile seizures and a paternal first cousin with epilepsy. No cause of death was identified following a comprehensive postmortem investigation. The coroner classified the death as "sudden unexpected death in epilepsy" (SUDEP), and it would qualify as "definite SUDEP" using the current definitions.1 This left the family with many questions unanswered; in particular, they wish to know what caused the death and whether it could happen to other family members. Could postmortem genetic testing identify a cause of death, provide closure to the family, and facilitate cascade genetic testing of first-degree family members who may be at risk of sudden death? While grieving family members struggle with uncertainty about the cause of death, we as clinicians also face similar uncertainties about genetic contributions to SUDEP, especially when the literature is sparse, and the utility of genetic testing is still being worked out. We aim to shed some light on this topic, highlighting areas where data is emerging but also areas where uncertainty remains, keeping our case in mind as we examine this clinically important area.

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

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

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.

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.

Sudden unexpected death in epilepsy

PURPOSE OF REVIEW

Sudden unexpected death in epilepsy (SUDEP) is a major contributor to premature mortality in people with epilepsy. This review provides an update on recent findings on the epidemiology of SUDEP, clinical risk factors and potential mechanisms.

RECENT FINDINGS

The overall risk rate of SUDEP is approximately 1 per 1000 patients per year in the general epilepsy population and that children and older adults have a similar incidence. Generalized convulsive seizures (GCS), perhaps through their effects on brainstem cardiopulmonary networks, can cause significant postictal respiratory and autonomic dysfunction though other mechanisms likely exist as well. Work in animal models of SUDEP has identified multiple neurotransmitter systems, which may be future targets for pharmacological intervention. There are also chronic functional and structural changes in autonomic function in patients who subsequently die from SUDEP suggesting that some SUDEP risk is dynamic. Modifiable risks for SUDEP include GCS seizure frequency, medication adherence and nighttime supervision.

SUMMARY

Current knowledge of SUDEP risk factors has identified multiple targets for SUDEP prevention today as we await more specific therapeutic targets that are emerging from translational research studies.

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.

Interictal autonomic changes in persons with epilepsy (PWE) on carbamazepine (CBZ) versus other anti-seizure drug monotherapy: A cross-sectional study

OBJECTIVE

Epilepsy is one of the most prevalent neurological conditions and carbamazepine is a commonly used anti-seizure drug (ASD), especially in developing nations. There are reports of carbamazepine causing atrioventricular conduction defects and autonomic dysfunctions and its implication in Sudden Unexpected Death in Epilepsy (SUDEP) is controversial. We planned this study to assess the effect of carbamazepine (CBZ) on autonomic function compared to other ASDs in persons with epilepsy.

METHODS

In this cross-sectional study, we assessed the sympathetic and parasympathetic autonomic functions in persons with epilepsy (PWE) on CBZ versus other anti-seizure monotherapy using tests of heart rate variability including its time-, frequency- and non-linear domains, heart rate response to deep breathing, valsalva maneuver, and blood pressure response to isometric handgrip.

RESULTS

Persons with epilepsy on CBZ monotherapy did not show a significant reduction in the time domain parameter SDRR compared to other ASDs used as monotherapy (mean ± SD, 38.04 ± 18.75 ms vs 44.37 ± 20.35 ms; p = 0.125). However, PWE on CBZ had significantly lower time-domain measurements including RMSSD (mean ± SD 31.95 ± 17.29 ms vs 42.02 ± 22.29 ms; p = 0.018), SDSD (mean ± SD 31.91 ± 17.26 ms vs 41.96 ± 22.27 ms; p 0.018), and pNN50 [median (IQR) 05.45(0.69-25.37) vs 16.38(2.32-36.83); p = 0.030]. Frequency domain measures of HRV, heart rate responses to deep breathing, valsalva maneuver and tilt-testing and BP responses to valsalva and tilt-testing were not significantly different between the groups.

CONCLUSION

The findings of our study indicate reduced parasympathetic activity in persons on CBZ monotherapy compared to other ASDs, which may pose risk of SUDEP. Carbamazepine may thus be avoided in those at risk of autonomic dysfunction and SUDEP.

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.

Autonomic manifestations of epilepsy: emerging pathways to sudden death?

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

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

OBJECTIVE

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

METHODS

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

RESULTS

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

SIGNIFICANCE/CONCLUSION

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

Trend of Sudden Unexpected Death in Epilepsy Incidence Rate in Rural West China

Objectives: To explore the trend of sudden unexpected death in epilepsy (SUDEP) incidence rate over time in rural west China.

Methods: We scanned probable SUDEP patients from the epilepsy program between 2010 and 2019 in rural West China and performed a verbal autopsy for each eligible patient. We calculated the crude and sex-adjusted incidence rate of SUDEP per person-year over a calendar year and the year of follow-up. We calculated the incidence rate ratio with the Poisson model in STATA 12.0 and calculated the annual percentage change (APC) and average annual percentage change in Joinpoint Trend Analysis Software 4.8.0.1 to analyze the trend of SUDEP incidence rate.

Results: In 2010–2019, 44 probable SUDEPs were identified from 10,128 patients with a total person-year of 31,347. The crude and sex-adjusted incidence rates of SUDEP were 1.40 and 1.45%0. Twenty-five (56.8%) of the 44 probable SUDEPs had no generalized tonic-clonic seizure 3 months before their death. The incidence of probable SUDEP decreased significantly in the calendar year [APC = −11.7, 95% confidence interval (CI): −21.7 to −0.3] and in time of follow-up (average annual percentage change = −21.2, 95% CI: −34.3 to −5.4). Comparing the first 5 years in follow-up with the subsequent 3 years, the incidence rate of SUDEP decreased significantly (estimated incidence rate ratio = 0.4, 95% CI: 0.2 to 0.8).

Significance: SUDEP happened to 1.4 cases per thousand patient-years in convulsive epilepsy in rural west China between 2010 and 2019. The incidence rate of SUDEP presented a downward trend over the time of follow-up.

Commercially available seizure detection devices: A systematic review

IMPORTANCE

Epilepsy can be associated with significant morbidity and mortality. Seizure detection devices could be invaluable tools for both people with epilepsy, their caregivers, and clinicians as they could alert caretakers about seizures, reduce the risk of sudden unexpected death in epilepsy, and provide objective and more reliable seizure tracking to guide treatment decisions or monitor outcomes in clinical trials.

OBJECTIVE

To synthesize the characteristics of commercial seizure detection tools/devices currently available.

METHODS

We performed a systematic search utilizing a diverse set of resources to identify commercially available seizure detection products for consumer use. Performance data was obtained through a systematic review on commercially available products.

OBSERVATIONS

We identified 23 products marketed for seizure detection/alerting. Devices utilize a variety of mechanisms to detect seizures, including movement detectors, autonomic change detectors, electroencephalogram (EEG) based detectors, and other mechanisms (audio). The optimal device for a person with epilepsy depends on a variety of factors including the main purpose of the device, their age, seizure type and personal preferences. Only 8 devices have published peer-reviewed performance data and the majority for tonic-clonic seizures. An informed conversation between the clinician and the patient can help guide if a seizure detection device is appropriate.

CONCLUSIONS AND RELEVANCE

Seizure detection devices have a potential to reduce morbidity and mortality for certain people with epilepsy. Clinicians should be familiar with the characteristics of commercially available devices to best counsel their patients on whether a seizure detection device may be beneficial and what the optimal devices may be.

Sudden Unexpected Death in Epilepsy (SUDEP): A Review of Risk Factors and Possible Interventions in Children

Sudden unexpected death in epilepsy (SUDEP) is a serious and devastating, yet poorly understood outcome in epilepsy. This review discusses the current knowledge and understanding of SUDEP in children and adolescents. Established risk factors for SUDEP include history of generalized tonic-clonic seizures and nocturnal seizures. Other proposed risk factors include the use of multiple antiseizure medications and poor medication adherence. Possible prevention strategies for SUDEP include improved medication adherence, surgical interventions, nighttime safety, seizure detection devices, and diet. Pediatric providers have a great opportunity to educate families about SUDEP, assess medication adherence, and provide families with tools to improve medication adherence and learn about SUDEP in children and adolescents with epilepsy. Future research in SUDEP aims to further understand the etiology and risk factors of SUDEP, while developing more intervention strategies to prevent SUDEP.

The role of convulsive seizures in SUDEP

Convulsive seizures are the most consistently reported risk factor for SUDEP. However, the precise mechanisms by which convulsive seizures trigger fatal cardiopulmonary changes are still unclear. Additionally, it is not clear why some seizures cause death when most do not. This article reviews the physiologic changes that occur during and after convulsive seizures and how these may contribute to SUDEP. Seizures activate specific cortical and subcortical regions that can cause potentially lethal cardiorespiratory changes. Clinical factors, including sleep state, medication treatment and withdrawal, positioning and posturing during seizures, and underlying structural or genetic conditions may also affect specific aspects of seizures that may contribute to SUDEP. While seizure control, either through medication or surgical treatment, is the primary intervention that reduces SUDEP risk, unfortunately, seizures cannot be fully controlled despite maximal treatment in a significant proportion of people with epilepsy. Thus specific interventions to prevent adverse seizure-related cardiopulmonary consequences are needed. The potential roles of repositioning/stimulation after seizures, oxygen supplementation, cardiopulmonary resuscitation and clinical treatment options in reducing SUDEP risk are explored. Ultimately, understanding of these factors may lead to interventions that could reduce or prevent SUDEP.

Electrocardiographic Abnormalities and Mortality in Epilepsy Patients

Background and Objectives: People with epilepsy (PWE) have a 2–3 times higher mortality rate than the general population. Sudden unexpected death in epilepsy (SUDEP) comprises a significant proportion of premature deaths, whereas sudden cardiac death (SCD) is among the leading causes of sudden death in the general population. Cardiac pathologies are significantly more prevalent in PWE. Whether electrocardiographic (ECG) parameters are associated with remote death in PWE has yet to be elucidated. The study objective was to assess whether interictal ECG parameters are associated with mortality in the long-term. Materials and Methods: The study involved 471 epilepsy patients who were hospitalized after a bilateral tonic-clonic seizure(s). ECG parameters were obtained on the day of hospitalization (heart rate, PQ interval, QRS complex, QT interval, heart rate corrected QT interval (QTc), ST segment and T wave changes), as well as reported ECG abnormalities. Mortality data were obtained from the Latvian National Cause-of-Death database 3–11, mean 7.0 years after hospitalization. The association between the ECG parameters and the long-term clinical outcome were examined. Results: At the time of assessment, 75.4% of patients were alive and 24.6% were deceased. Short QTc interval (odds ratio (OR) 4.780; 95% confidence interval (CI) 1.668–13.698; p = 0.004) was associated with a remote death. After the exclusion of known comorbidities with high mortality rates, short QTc (OR 4.631) and ECG signs of left ventricular hypertrophy (OR 5.009) were associated with a remote death. Conclusions: The association between routine 12-lead rest ECG parameters—short QTc interval and a pattern of left ventricular hypertrophy—and remote death in epilepsy patients was found. To the best of our knowledge, this is the first study to associate rest ECG parameters with remote death in an epileptic population.

Probable Sudden Unexpected Death in Dogs With Epilepsy (pSUDED)

Sudden unexpected death in human epileptic patients (SUDEP) is defined as death related to recurrent unprovoked seizures, death occurring unexpectedly, and suddenly in a patient with reasonable state of health, without an obvious medical cause of death, trauma, asphyxia, or intractable status epilepticus, and in post mortem examination no obvious reason for death can be found. “Probable SUDEP” (pSUDEP) is defined as SUDEP not confirmed pathologically. The adapted abbreviation for dogs is used in the following: “pSUDED” (probable sudden unexpected death in dogs with epilepsy). The aim of the present monocentric retrospective study using an online questionnaire was to evaluate the occurrence of pSUDED. Data of canine patients presented with seizures between 01/1998 and 05/2018 were retrospectively analyzed and classified according to their etiology (n = 1,503). Owners were contacted by telephone to participate in answering a validated questionnaire. A total of 509 owners were reached, and 373 owners completed the questionnaire. In addition to signalement (e.g., breed), special attention was paid to the frequency and presentation of seizures and seizures in the context of death. Fifty-one percent (191/373) of the dogs were dead at the endpoint of the study. A large proportion of the dogs was euthanized (149/191) because of seizure severity or health problems unrelated to seizures. Idiopathic epilepsy (IE) was diagnosed in 19/34 dogs which died unexpectedly. Of these seven animals had to be excluded for further investigation of pSUDED because of status epilepticus or aspiration pneumonia as a result of the seizures. In 12 dogs with IE the last seizure event occurred between 6 h and ~3 months before death. pSUDED was suspected in these dogs and an occurrence rate of 4.5–10% was calculated. pSUDED appears in a similar occurrence rate as human SUDEP and should be considered as a possible complication in epileptic dogs. The results of this study suggest that dogs with IE but especially those with brachycephalic syndrome and cluster seizures have an increased risk to die of pSUDED. Owners of dogs with seizures should be educated about the risk of sudden death in dogs with epilepsy.

Can Big Data guide prognosis and clinical decisions in epilepsy?

Big Data is no longer a novel concept in health care. Its promise of positive impact is not only undiminished, but daily enhanced by seemingly endless possibilities. Epilepsy is a disorder with wide heterogeneity in both clinical and research domains, and thus lends itself to Big Data concepts and techniques. It is therefore inevitable that Big Data will enable multimodal research, integrating various aspects of "-omics" domains, such as phenome, genome, microbiome, metabolome, and proteome. This scope and granularity have the potential to change our understanding of prognosis and mortality in epilepsy. The scale of new discovery is unprecedented due to the possibilities promised by advances in machine learning, in particular deep learning. The subsequent possibilities of personalized patient care through clinical decision support systems that are evidence-based, adaptive, and iterative seem to be within reach. A major objective is not only to inform decision-making, but also to reduce uncertainty in outcomes. Although the adoption of electronic health record (EHR) systems is near universal in the United States, for example, advanced clinical decision support in or ancillary to EHRs remains sporadic. In this review, we discuss the role of Big Data in the development of clinical decision support systems for epilepsy care, prognostication, and discovery.

The effect of time-of-day and circadian phase on vulnerability to seizure-induced death in two mouse models

KEY POINTS

Sudden unexpected death in epilepsy (SUDEP) is the leading cause of premature death in patients with refractory epilepsy. SUDEP typically occurs during the night, although the reason for this is unclear. We found that, in normally entrained mice, time-of-day alters vulnerability to seizure-induced death. We found that, in free-running mice, circadian phase alters the vulnerability to seizure-induced death. These findings suggest that circadian rhythmicity may be responsible for the increased night-time prevalence of SUDEP ABSTRACT: Sudden unexpected death in epilepsy (SUDEP) is the leading cause of epilepsy-related death. SUDEP typically occurs during the night following a seizure. Many aspects of mammalian physiology are regulated by circadian rhythms in ways that might make seizures occuring during the night more dangerous. Using two mouse models of seizure-induced death, we demonstrate that time-of-day and circadian rhythms alter vulnerability to seizure-induced death. We exposed normally entrained DBA/1 mice to a potentially seizure-inducing acoustic stimulus at different times of day and compared the characteristics and outcomes of the seizures. Time-of-day did not alter the probability of a seizure but it did alter the probability of seizure-induced death. To determine whether circadian rhythms alter vulnerability to seizure-induced death, we induced maximal electroshock seizures in free-running C57BL/6J mice at different circadian time points at the same time as measuring breathing via whole body plethysmography. Circadian phase did not affect seizure severity but it did alter postictal respiratory outcomes and the probability of seizure-induced death. By contrast to our expectations, in entrained and free-running mice, vulnerability to seizure-induced death was greatest during the night and subjective night, respectively. These findings suggest that circadian rhythmicity may be responsible for the increased night-time prevalence of SUDEP and that the underlying mechanism is phase conserved between nocturnal and diurnal mammals. All of the seizures in the present study were induced during wakefulness, indicating that the effect of time point on vulnerability to seizure-induced death was not the result of sleep. Understanding why SUDEP occurs more frequently during the night may inform future preventative countermeasures.

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.

Sudden unexpected death after acute symptomatic seizures in a patient on mechanical ventilation

Background

The mechanism of sudden unexpected death in epilepsy remains poorly understood. Seizure induced cardiac arrhythmia, central and obstructive apneas have been proposed as possible causes of death. Here we report a unique case of seizure related sudden unexpected death in a patient whose airway was fully protected by intubation and mechanic ventilation in the absence of fatal cardiac arrhythmia.

Case presentation

A 70-year-old woman was undergoing mechanical ventilation and video-electroencephalography (EEG) monitoring following two convulsive seizures with ictal hypoventilation and hypoxemia. Several hours after intubation, she suffered another generalized tonic clonic seizure lasted for 3 min and developed postictal generalized EEG suppression in the presence of stable vital signs with SpO2 > 90%. EEG suppression persisted throughout the postictal phase. There was a significant fluctuation of systolic blood pressure between 50 and 180 mmHg with several bouts of hypotension < 60 mmHg. She remained unresponsive after the convulsive seizure and died of diffuse cerebral edema 12 h later. Autopsy revealed no clear cause of death, except for possible hypoxic and ischemic injury leading to the diffuse cerebral edema.

Conclusion

Given the reliable periictal airway protection, neither seizure induced central apnea nor obstructive apnea appeared to be the direct cause of death in this unique case. In the absence of fatal cardiac arrhythmia, diffuse cerebral edema secondary to seizure-induced autonomic dysfunction, hypotension and hypoxemia might be the cause of death, highlighting the etiological heterogeneity of sudden unexpected death in epilepsy.

Sudden death in epilepsy: There is room for intracranial pressure

INTRODUCTION

Sudden unexpected death in patients with epilepsy (SUDEP) remains a poorly understood entity, and it is unclear whether the same pathomechanisms underlie all sudden deaths occurring in patients with epilepsy. One aspect not included in current models of SUDEP is the role of increased intracranial pressure (ICP) which can be observed immediately upon seizure activity in neurosurgical practice.

METHODS

We conducted a systematic review of the occurrence of edema in patients with epilepsy reported to have died of sudden death who underwent brain autopsy or postmortem brain imaging and discuss how increased ICP may contribute to clinical features of SUDEP.

RESULTS

19 eligible studies comprising a total of 623 patients were identified. Edema-mostly mild or moderate-was reported in 17% of cases and 74% of studies. 1% (n = 6) of the overall cases were clearly identified as having Dravet syndrome or an SCN1A mutation. In these patients, edema was found in 4 (67%) of cases.

CONCLUSION

Edema is regularly found in patients with epilepsy classified to have died from SUDEP. We argue that seizures preceding SUDEP may in certain cases elicit acute edema which may represent an additional contributing factor in the cascade of events leading to sudden death of patients with epilepsy. Furthermore, we hypothesize that mild edema may especially progress to severe edema in patients with sodium channel mutations which may represent an important mechanism to investigate in the context of understanding the significantly elevated risk of SUDEP in patients with SCN1A mutations.

Sudden Unexplained Death in Childhood: A Neuropathology Review

Sudden Unexplained Death in Childhood (SUDC) is the unexpected death of a child over age 12 months that remains unexplained after a thorough case investigation, including review of the child's medical history, circumstances of death, a complete autopsy and ancillary testing (1). First defined in 2005, SUDC cases are more often male, with death occurring during a sleep period, being found prone, peak winter incidence, associated with febrile seizure history in ~28% of cases and mild pathologic changes insufficient to explain the death (1, 2). There has been little progress in understanding the causes of SUDC and no progress in prevention. Despite reductions in sudden unexpected infant death (SUID) and other causes of mortality in childhood, the rate of SUDC has increased during the past two decades (3-5). In Ireland, SUID deaths were cut in half from 1994 to 2008 while SUDC deaths more than doubled (4). Surveillance issues, including lack of standardized certification practices, affect our understanding of the true magnitude of unexplained child deaths. Mechanisms underlying SUDC, like SUID, remain largely speculative. Limited and inconsistent evidence implicates abnormalities in brainstem autonomic and serotonergic nuclei, critical for arousal, cardiorespiratory control, and reflex responses to life-threatening hypoxia or hypercarbia in sleep (6). Abnormalities in medullary serotonergic neurons and receptors, as well as cardiorespiratory brainstem nuclei occur in some SUID cases, but have never been studied in SUDC. Retrospective, small SUDC studies with non-standardized methodologies most often demonstrate minor hippocampal abnormalities, as well as focal cortical dysplasia and dysgenesis of the brainstem and cerebellum. The significance of these findings to SUDC pathogenesis remains unclear with some investigators and forensic pathologists labeling these findings as normal variants, or potential causes of SUDC. The development of preventive strategies will require a greater understanding of underlying mechanisms.

Proceedings of the 15th Antiepileptic Drug and Device Trials Meeting: State of the Science

On May 22-24, 2019, the 15th Antiepileptic Drug and Device (AEDD) Trials Conference was held, which focused on current issues related to AEDD development from preclinical models to clinical prognostication. The conference featured regulatory agencies, academic laboratories, and healthcare companies involved in emerging epilepsy therapies and research. The program included discussions around funding and support for investigations in epilepsy and neurologic research, clinical trial design and integrated outcome measures for people with epilepsy, and drug development and upcoming disease-modifying therapies. Finally, the conference included updates from the preclinical, clinical, and device pipeline. Summaries of the talks are provided in this paper, with the various pipeline therapeutics in the listed tables to be outlined in a subsequent publication.

Mechanisms and prevention of acid reflux induced laryngospasm in seizing rats

OBJECTIVE

Recent animal work and limited clinical data have suggested that laryngospasm may be involved in the cardiorespiratory collapse seen in sudden unexpected death in epilepsy (SUDEP). In previous work, we demonstrated in an animal model of seizures that laryngospasm and sudden death were always preceded by acid reflux into the esophagus. Here, we expand on that work by testing several techniques to prevent the acid reflux or the subsequent laryngospasm.

METHODS

In urethane anesthetized Long Evans rats, we used systemic kainic acid to acutely induce seizure activity. We recorded pH in the esophagus, respiration, electrocorticography activity, and measured the liquid volume in the stomach postmortem. We performed the following three interventions to attempt to prevent acid reflux or laryngospasm and gain insights into mechanisms: fasting animals for 12 h, severing the gastric nerve, and electrical stimulation of either the gastric nerve or the recurrent laryngeal nerve.

RESULTS

Seizing animals had significantly more liquid in their stomach. Severing the gastric nerve and fasting animals significantly reduced stomach liquid volume, subsequent acid reflux, and sudden death. Laryngeal nerve stimulation can reverse laryngospasm on demand. Seizing animals are more susceptible to death from stomach acid-induced laryngospasm than nonseizing animals are to artificial acid-induced laryngospasm.

SIGNIFICANCE

These results provide insight into the mechanism of acid production and sudden obstructive apnea in this model. These techniques may have clinical relevance if this model is shown to be similar to human SUDEP.

All-cause mortality and SUDEP in a surgical epilepsy population

Epilepsy surgery is considered to reduce the risk of epilepsy-related mortality, including sudden unexpected death in epilepsy (SUDEP), though data from existing surgical series are conflicting. We retrospectively examined all-cause mortality and SUDEP in a population of 590 epilepsy surgery patients and a comparison group of 122 patients with pharmacoresistant focal epilepsy who did not undergo surgery, treated at Columbia University Medical Center between 1977 and 2014. There were 34 deaths in the surgery group, including 14 cases of SUDEP. Standardized mortality ratio (SMR) for the surgery group was 1.6, and SUDEP rate was 1.9 per 1000 patient-years. There were 13 deaths in the comparison group, including 5 cases of SUDEP. Standardized mortality ratio for the comparison group was 3.6, and SUDEP rate was 4.6 per 1000 patient-years. Both were significantly greater than in the surgery group (p < 0.05). All but one of the surgical SUDEP cases, and all of the comparison group SUDEP cases, had a history of bilateral tonic-clonic seizures (BTCS). Of postoperative SUDEP cases, one was seizure-free, and two were free of BTCS at last clinical follow-up. Time to SUDEP in the surgery group was longer than in the comparison group (10.1 vs 5.9 years, p = 0.013), with 10 of the 14 cases occurring >10 years after surgery. All-cause mortality was reduced after epilepsy surgery relative to the comparison group. There was an early benefit of surgery on the occurrence of SUDEP, which was reduced after 10 years. A larger, multicenter study is needed to further investigate the time course of postsurgical SUDEP.

SeizureBank: A Repository of Analysis-ready Seizure Signal Data

Approximately 60 million people worldwide suffer from epileptic seizures. A key challenge in machine learning ap proaches for epilepsy research is the lack of a data resource of analysis-ready (no additional preprocessing is needed when using the data for developing computational methods) seizure signal datasets with associated tools for seizure data management and visualization. We introduce SeizureBank, a web-based data management and visualization system for epileptic seizures. SeizureBank comes with a built-in seizure data preparation pipeline and web-based interfaces for querying, exporting and visualizing seizure-related signal data. In this pilot study, 224 seizures from 115 patients were extracted from over one terabyte of signal data and deposited in SeizureBank. To demonstrate the value of this approach, we develop a feature-based seizure identification approach and evaluate the performance on a variety of data sources. The results can serve as a cross-dataset evaluation benchmark for future seizure identification studies.

Detection of Postictal Generalized Electroencephalogram Suppression: Random Forest Approach

BACKGROUND

Sudden unexpected death in epilepsy (SUDEP) is second only to stroke in neurological events resulting in years of potential life lost. Postictal generalized electroencephalogram (EEG) suppression (PGES) is a period of suppressed brain activity often occurring after generalized tonic-clonic seizure, a most significant risk factor for SUDEP. Therefore, PGES has been considered as a potential biomarker for SUDEP risk. Automatic PGES detection tools can address the limitations of labor-intensive, and sometimes inconsistent, visual analysis. A successful approach to automatic PGES detection must overcome computational challenges involved in the detection of subtle amplitude changes in EEG recordings, which may contain physiological and acquisition artifacts.

OBJECTIVE

This study aimed to present a random forest approach for automatic PGES detection using multichannel human EEG recordings acquired in epilepsy monitoring units.

METHODS

We used a combination of temporal, frequency, wavelet, and interchannel correlation features derived from EEG signals to train a random forest classifier. We also constructed and applied confidence-based correction rules based on PGES state changes. Motivated by practical utility, we introduced a new, time distance-based evaluation method for assessing the performance of PGES detection algorithms.

RESULTS

The time distance-based evaluation showed that our approach achieved a 5-second tolerance-based positive prediction rate of 0.95 for artifact-free signals. For signals with different artifact levels, our prediction rates varied from 0.68 to 0.81.

CONCLUSIONS

We introduced a feature-based, random forest approach for automatic PGES detection using multichannel EEG recordings. Our approach achieved increasingly better time distance-based performance with reduced signal artifact levels. Further study is needed for PGES detection algorithms to perform well irrespective of the levels of signal artifacts.

Risks and predictive biomarkers of sudden unexpected death in epilepsy patient

PURPOSE OF REVIEW

The current review updates our knowledge regarding sudden unexpected death in epilepsy patient (SUDEP) risks, risk factors, and investigations of putative biomarkers based on suspected mechanisms of SUDEP.

RECENT FINDINGS

The overall incidence of SUDEP in adults with epilepsy is 1.2/1000 patient-years, with surprisingly comparable figures in children in recently published population-based studies. This risk was found to decrease over time in several cohorts at a rate of -7% per year, for unknown reasons. Well established risk factors include frequency of generalized tonic-clonic seizures, while adding antiepileptic treatment, nocturnal supervision and use of nocturnal listening device appear to be protective. In contrast, recent data failed to demonstrate the predictive value of heart rate variability, periictal cardiorespiratory dysfunction, and postictal generalized electroencephalography suppression. Preliminary findings suggest that brainstem and thalamic atrophy may be associated with a higher risk of SUDEP. Novel experimental and human data support the primary role of generalized tonic-clonic seizure-triggered respiratory dysfunction and the likely contribution of altered brainstem serotoninergic neurotransmission, in SUDEP pathophysiology.

SUMMARY

Although significant progress has been made during the past year in the understanding of SUDEP mechanisms and investigation of numerous potential biomarkers, we are still missing reliable predictors of SUDEP beyond the well established clinical risk factors.

Clinical risk factors in SUDEP: A nationwide population-based case-control study

Objective

We conducted a nationwide case-control study in Sweden to test the hypothesis that specific clinical characteristics are associated with increased risk of sudden unexpected death in epilepsy (SUDEP).

Methods

The study included 255 SUDEP cases (definite and probable) and 1,148 matched controls. Clinical information was obtained from medical records and the National Patient Register. The association between SUDEP and potential risk factors was assessed by odds ratios (ORs) and 95% confidence intervals (CIs) and interaction assessed by attributable proportion due to interaction (AP).

Results

Experiencing generalized tonic-clonic seizures (GTCS) during the preceding year was associated with a 27-fold increased risk (OR 26.81, 95% CI 14.86–48.38), whereas no excess risk was seen in those with exclusively non-GTCS seizures (OR 1.15, 95% CI 0.54–48.38). The presence of nocturnal GTCS during the last year of observation was associated with a 15-fold risk (OR 15.31, 95% CI 9.57–24.47). Living alone was associated with a 5-fold increased risk of SUDEP (OR 5.01, 95% CI 2.93–8.57) and interaction analysis showed that the combination of not sharing a bedroom and having GTCS conferred an OR of 67.10 (95% CI 29.66–151.88), with AP estimated at 0.69 (CI 0.53–0.85). Among comorbid diseases, a previous diagnosis of substance abuse or alcohol dependence was associated with excess risk of SUDEP.

Conclusions

Individuals with GTCS who sleep alone have a dramatically increased SUDEP risk. Our results indicate that 69% of SUDEP cases in patients who have GTCS and live alone could be prevented if the patients were not unattended at night or were free from GTCS.

Why we urgently need improved epilepsy therapies for adult patients

PURPOSE

Up to a third of patients with epilepsy suffer from recurrent seizures despite therapeutic advances.

RESULTS

Current epilepsy treatments are limited by experiential data from treating different types of epilepsy. For example, we lack evidence-based approaches to efficacious multi-drug therapies or identifying potentially serious or disabling adverse events before medications are initiated. Despite advances in neuroscience and genetics, our understanding of epilepsy pathogenesis and mechanisms of treatment-resistance remains limited. For most patients with epilepsy, precision medicine for improved seizure control and reduced toxicity remains a future goal.

CONCLUSION

A third of epilepsy patients suffer from ongoing seizures and even more suffer from adverse effects of treatment. There is a critical need for more effective and safer therapies for epilepsy patients with frequent comorbitidies, including depression, anxiety, migraine, and cognitive impairments, as well as special populations (e.g., women, elderly). Advances from genomic sequencing techniques may identify new genes and regulatory elements that influence both the depth of the epilepsies' roots within brain circuitry as well as ASD resistance. Improved understanding of epilepsy mechanisms, identification of potential new therapeutic targets, and their assessment in randomized controlled trials are needed to reduce the burden of refractory epilepsy. This article is part of the special issue entitled 'New Epilepsy Therapies for the 21st Century - From Antiseizure Drugs to Prevention, Modification and Cure of Epilepsy'.

Brainstem spreading depolarization and cortical dynamics during fatal seizures in Cacna1a S218L mice

Sudden unexpected death in epilepsy (SUDEP) is a fatal complication of epilepsy in which brainstem spreading depolarization may play a pivotal role, as suggested by animal studies. However, patiotemporal details of spreading depolarization occurring in relation to fatal seizures have not been investigated. In addition, little is known about behavioural and neurophysiological features that may discriminate spontaneous fatal from non-fatal seizures. Transgenic mice carrying the missense mutation S218L in the α1A subunit of Cav2.1 (P/Q-type) Ca2+ channels exhibit enhanced excitatory neurotransmission and increased susceptibility to spreading depolarization. Homozygous Cacna1aS218L mice show spontaneous non-fatal and fatal seizures, occurring throughout life, resulting in reduced life expectancy. To identify characteristics of fatal and non-fatal spontaneous seizures, we compared behavioural and electrophysiological seizure dynamics in freely-behaving homozygous Cacna1aS218L mice. To gain insight on the role of brainstem spreading depolarization in SUDEP, we studied the spatiotemporal distribution of spreading depolarization in the context of seizure-related death. Spontaneous and electrically-induced seizures were investigated by video monitoring and electrophysiological recordings in freely-behaving Cacna1aS218L and wild-type mice. Homozygous Cacna1aS218L mice showed multiple spontaneous tonic-clonic seizures and died from SUDEP in adulthood. Death was preceded by a tonic-clonic seizure terminating with hindlimb clonus, with suppression of cortical neuronal activity during and after the seizure. Induced seizures in freely-behaving homozygous Cacna1aS218L mice were followed by multiple spreading depolarizations and death. In wild-type or heterozygous Cacna1aS218L mice, induced seizures and spreading depolarization were never followed by death. To identify temporal and regional features of seizure-induced spreading depolarization related to fatal outcome, diffusion-weighted MRI was performed in anaesthetized homozygous Cacna1aS218L and wild-type mice. In homozygous Cacna1aS218L mice, appearance of seizure-related spreading depolarization in the brainstem correlated with respiratory arrest that was followed by cardiac arrest and death. Recordings in freely-behaving homozygous Cacna1aS218L mice confirmed brainstem spreading depolarization during spontaneous fatal seizures. These data underscore the value of the homozygous Cacna1aS218L mouse model for identifying discriminative features of fatal compared to non-fatal seizures, and support a key role for cortical neuronal suppression and brainstem spreading depolarization in SUDEP pathophysiology.

[Sudden unexpected death in epilepsy (SUDEP) : Epidemiology, cardiac and other risk factors]

Sudden unexpected death in epilepsy (SUDEP) is one of the most frequent epilepsy-related causes of death. The incidence of SUDEP is estimated to be approximately 1.2/1000 person-years (PY); however, it varies considerably depending on disease-specific and demographic factors. The estimated incidence of SUDEP in children seems to be significantly lower (0.22/1000 PY) than in adults but recent studies in children (>12 years) indicated a similar incidence to that of adults. Based on these estimations, approximately 700 SUDEP cases would be expected in Germany annually but no reliable data or epidemiological studies on SUDEP are available. Various risk factors and predictors for SUDEP have been investigated, e.g. age, seizure frequency, number of antiepileptic drugs, non-compliance and comorbidities, with sometimes contradictory results. This is understandable given that the exact mechanisms of SUDEP are unclear; however, it is very likely that the frequency of (nocturnal) generalized tonic-clonic seizures is the most important risk factor. Nocturnal monitoring of seizures (using devices) or the presence of another person at night may represent important factors to reduce the risk of SUDEP. Thus, seizure control and seizure monitoring are, according to current knowledge, the most important factors to avoid SUDEP. Some recent studies have contributed to a better understanding of possible pathomechanisms of SUDEP; however, further research is needed to identify predictive clinical factors and biomarkers and in particular to prevent SUDEP.

Let's talk SUDEP

Sudden unexplained death in epilepsy (SUDEP) is a devastating complication of epilepsy which was under-recognized in the recent past despite its clear importance. In this review, we examine the definition of SUDEP, revise current pathophysiological theories, discuss risk factors and preventative measures, disclose tools for appraising the SUDEP risk, and last but not least dwell upon announcing and explaining the SUDEP risk to the patients and their caretakers. We aim to aid the clinicians in their responsibility of knowing SUDEP, explaining the SUDEP risk to their patients in a reasonable and sensible way and whenever possible, preventing SUDEP. Future studies are definitely needed to increase scientific knowledge and awareness related to this prioritized topic with malign consequences.

Postictal serotonin levels are associated with peri-ictal apnea

OBJECTIVE

To determine the relationship between serum serotonin (5-HT) levels, ictal central apnea (ICA), and postconvulsive central apnea (PCCA) in epileptic seizures.

METHODS

We prospectively evaluated video EEG, plethysmography, capillary oxygen saturation (SpO₂), and ECG for 49 patients (49 seizures) enrolled in a multicenter study of sudden unexpected death in epilepsy (SUDEP). Postictal and interictal venous blood samples were collected after a clinical seizure for measurement of serum 5-HT levels. Seizures were classified according to the International League Against Epilepsy 2017 seizure classification. We analyzed seizures with and without ICA (n = 49) and generalized convulsive seizures (GCS) with and without PCCA (n = 27).

RESULTS

Postictal serum 5-HT levels were increased over interictal levels for seizures without ICA (p = 0.01), compared to seizures with ICA (p = 0.21). In patients with GCS without PCCA, serum 5-HT levels were increased postictally compared to interictal levels (p < 0.001), but not in patients with seizures with PCCA (p = 0.22). Postictal minus interictal 5-HT levels also differed between the 2 groups with and without PCCA (p = 0.03). Increased heart rate was accompanied by increased serum 5-HT levels (postictal minus interictal) after seizures without PCCA (p = 0.03) compared to those with PCCA (p = 0.42).

CONCLUSIONS

The data suggest that significant seizure-related increases in serum 5-HT levels are associated with a lower incidence of seizure-related breathing dysfunction, and may reflect physiologic changes that confer a protective effect against deleterious phenomena leading to SUDEP. These results need to be confirmed with a larger sample size study.

Insular resection may lead to autonomic function changes

OBJECTIVE

The aim of this study was to determine if insular damage is associated with markers of autonomic dysfunction.

METHODS

We studied patients who underwent temporal lobe and/or insular resections for epilepsy surgery between April 2010 and June 2015 at University Hospitals Cleveland Medical Center (UHCMC). Presurgical T1-weighted MPRAGE, standard T1, T2 and FLAIR sequences were compared with postsurgical MRI by a neuroradiologist and classified as type 0 (no involvement of insula), type 1 (minimal involvement of insular margin), type 2 (insular involvement <25%), and type 3 (insular involvement ≥25%). Analysis of heart rate variability (HRV) was carried out in pre- and postoperative video-electroencephalography (vEEG) recording. Time-domain parameters were calculated: (mean of the RR intervals (MNN), root mean square difference of successive RR intervals (RMSSD), standard deviation of the RR intervals (SDNN), and coefficient of variation (CV)). In addition, frequency-domain parameters were calculated: low frequency (LF), high frequency (HF), and low frequency/high frequency (LF/HF).

RESULTS

Twenty-one patients (14 females) with mean age of 36.2 ± 14.4 years (30; 22-75) were studied. Insular involvement was classified as type 0 (4 patients [19%]), type 1 (9 [43%]), type 2 (7 [33%]), and type 3 (1 [5%]). Significant decrease in RMSSD (p = 0.025) and CV (p = 0.008) was seen in insular damage types 2 and 3 compared with no or minimal insular involvement (types 0 and 1). Right-sided resections were associated with increase in LF power (p = 0.010) and the LF/HF ratio (p = 0.017).

CONCLUSIONS

This study indicates that insular resection may lead to autonomic function changes.

SUDEP in the North American SUDEP Registry: The full spectrum of epilepsies

Objective

To obtain medical records, family interviews, and death-related reports of sudden unexpected death in epilepsy (SUDEP) cases to better understand SUDEP.

Methods

All cases referred to the North American SUDEP Registry (NASR) between October 2011 and June 2018 were reviewed; cause of death was determined by consensus review. Available medical records, death scene investigation reports, autopsy reports, and next-of-kin interviews were reviewed for all cases of SUDEP. Seizure type, EEG, MRI, and SUDEP classification were adjudicated by 2 epileptologists.

Results

There were 237 definite and probable cases of SUDEP among 530 NASR participants. SUDEP decedents had a median age of 26 (range 1–70) years at death, and 38% were female. In 143 with sufficient information, 40% had generalized and 60% had focal epilepsy. SUDEP affected the full spectrum of epilepsies, from benign epilepsy with centrotemporal spikes (n = 3, 1%) to intractable epileptic encephalopathies (n = 27, 11%). Most (93%) SUDEPs were unwitnessed; 70% occurred during apparent sleep; and 69% of patients were prone. Only 37% of cases of SUDEP took their last dose of antiseizure medications (ASMs). Reported lifetime generalized tonic-clonic seizures (GTCS) were <10 in 33% and 0 in 4%.

Conclusions

NASR participants commonly have clinical features that have been previously been associated with SUDEP risk such as young adult age, ASM nonadherence, and frequent GTCS. However, a sizeable minority of SUDEP occurred in patients thought to be treatment responsive or to have benign epilepsies. These results emphasize the importance of SUDEP education across the spectrum of epilepsy severities. We aim to make NASR data and biospecimens available for researchers to advance SUDEP understanding and prevention.

Brainstem atrophy in focal epilepsy destabilizes brainstem-brain interactions: Preliminary findings

Background

MR Imaging has shown atrophy in brainstem regions that were linked to autonomic dysfunction in epilepsy patients. The brainstem projects to and modulates the activation state of several wide-spread cortical/subcortical regions. The goal was to investigate 1. Impact of brainstem atrophy on gray matter connectivity of cortical/subcortical structures and autonomic control. 2. Impact on the modulation of cortical/subcortical functional connectivity.

Methods

11 controls and 18 patients with non-lesional focal epilepsy (FE) underwent heart rate variability (HRV) measurements and a 3 T MRI (T1 in all subjects, task-free fMRI in 7 controls/ 12 FE). The brainstem was extracted, and atrophy assessed using deformation-based-morphometry. The age-corrected z-scores of the mean Jacobian determinants were extracted from 71 5x5x5 mm grids placed in brainstem regions associated with autonomic function. Cortical and non-brainstem subcortical gray matter atrophy was assessed with voxel-based-morphometry and mean age corrected z-scores of the modulated gray matter volumes extracted from 380 cortical/subcortical rois. The profile similarity index was used to characterize the impact of brainstem atrophy on gray matter connectivity. The fMRI was preprocessed in SPM12/Conn17 and the BOLD signal extracted from 398 ROIs (16 brainstem). A dynamic task-free analysis approach was used to identify activation states. Connectivity HRV relationship were assessed with Spearman rank correlations.

Results

HRV was negatively correlated with reduced brainstem right hippocampus/parahippocampus gray matter connectivity in controls (p < .05, FDR) and reduced brainstem to right parietal cortex, lingual gyrus, left hippocampus/amygdala, parahippocampus, temporal pole, and bilateral anterior thalamus connectivity in FE (p < .05, FDR). Dynamic task-free fMRI analysis identified 22 states. The strength of the functional brainstem/cortical connectivity of state 15 was negatively associated with HRV (r = −0.5, p = .03) and positively with decreased brainstem-cortical (0.49, p = .03) gray matter connectivity.

Conclusion

The findings of this small pilot study suggest that impaired brainstem-cortex gray matter connectivity in FE negatively affects the brainstem's ability to control cortical activation.

•

Brainstem and cortical/subcortical gray matter (gm) connectivity is impaired in FE.

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FE is associated with an abnormal brain activation state in the interictal state.

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The severity of the gm impairment and of the abnormal brain state are correlated.

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GM connectivity impairment and abnormal brain activity affect HRV.

Time of Day and a Ketogenic Diet Influence Susceptibility to SUDEP in Scn1a R1407X/+ Mice

Sudden unexpected death in epilepsy (SUDEP) is a major cause of mortality in patients with drug-resistant epilepsy. Most SUDEP cases occur in bed at night and are preceded by a generalized tonic-clonic seizure (GTCS). Dravet syndrome (DS) is a severe childhood-onset epilepsy commonly caused by mutations in the SCN1A gene. Affected individuals suffer from refractory seizures and an increased risk of SUDEP. Here, we demonstrate that mice with the Scn1a^R1407X/+ loss-of-function mutation (DS) experience more spontaneous seizures and SUDEP during the early night. We also evaluate effects of long-term ketogenic diet (KD) treatment on mortality and seizure frequency. DS mice showed high premature mortality (44% survival by P60) that was associated with increased spontaneous GTCSs 1–2 days prior to SUDEP. KD treated mice had a significant reduction in mortality (86% survival by P60) compared to mice fed a control diet. Interestingly, increased survival was not associated with a decrease in seizure frequency. Further studies are needed to determine how KD confers protection from SUDEP. Moreover, our findings implicate time of day as a factor influencing the occurrence of seizures and SUDEP. DS mice, though nocturnal, are more likely to have SUDEP at night, suggesting that the increased incidence of SUDEP at night in may not be solely due to sleep.

Incidence, Recurrence, and Risk Factors for Peri-ictal Central Apnea and Sudden Unexpected Death in Epilepsy

Introduction: Peri-ictal breathing dysfunction was proposed as a potential mechanism for SUDEP. We examined the incidence and risk factors for both ictal (ICA) and post-convulsive central apnea (PCCA) and their relationship with potential seizure severity biomarkers (i. e., post-ictal generalized EEG suppression (PGES) and recurrence.

Methods: Prospective, multi-center seizure monitoring study of autonomic, and breathing biomarkers of SUDEP in adults with intractable epilepsy and monitored seizures. Video EEG, thoraco-abdominal excursions, capillary oxygen saturation, and electrocardiography were analyzed. A subgroup analysis determined the incidences of recurrent ICA and PCCA in patients with ≥2 recorded seizures. We excluded status epilepticus and obscured/unavailable video. Central apnea (absence of thoracic-abdominal breathing movements) was defined as ≥1 missed breath, and ≥5 s. ICA referred to apnea preceding or occurring along with non-convulsive seizures (NCS) or apnea before generalized convulsive seizures (GCS).

Results: We analyzed 558 seizures in 218 patients (130 female); 321 seizures were NCS and 237 were GCS. ICA occurred in 180/487 (36.9%) seizures in 83/192 (43.2%) patients, all with focal epilepsy. Sleep state was related to presence of ICA [RR 1.33, CI 95% (1.08–1.64), p = 0.008] whereas extratemporal epilepsy was related to lower incidence of ICA [RR 0.58, CI 95% (0.37–0.90), p = 0.015]. ICA recurred in 45/60 (75%) patients. PCCA occurred in 41/228 (18%) of GCS in 30/134 (22.4%) patients, regardless of epilepsy type. Female sex [RR 11.30, CI 95% (4.50–28.34), p < 0.001] and ICA duration [RR 1.14 CI 95% (1.05–1.25), p = 0.001] were related to PCCA presence, whereas absence of PGES was related to absence of PCCA [0.27, CI 95% (0.16–0.47), p < 0.001]. PCCA duration was longer in males [HR 1.84, CI 95% (1.06–3.19), p = 0.003]. In 9/17 (52.9%) patients, PCCA was recurrent.

Conclusion: ICA incidence is almost twice the incidence of PCCA and is only seen in focal epilepsies, as opposed to PCCA, suggesting different pathophysiologies. ICA is likely to be a recurrent semiological phenomenon of cortical seizure discharge, whereas PCCA may be a reflection of brainstem dysfunction after GCS. Prolonged ICA or PCCA may, respectively, contribute to SUDEP, as evidenced by two cases we report. Further prospective cohort studies are needed to validate these hypotheses.

Fenfluramine, a serotonin-releasing drug, prevents seizure-induced respiratory arrest and is anticonvulsant in the DBA/1 mouse model of SUDEP

OBJECTIVE

Prevention of sudden unexpected death in epilepsy (SUDEP) is a critical goal for epilepsy therapy. The DBA/1 mouse model of SUDEP exhibits an elevated susceptibility to seizure-induced death in response to electroconvulsive shock, hyperthermia, convulsant drug, and acoustic stimulation. The serotonin hypothesis of SUDEP is based on findings that treatments which modify serotonergic function significantly alter susceptibility to seizure-induced sudden death in several epilepsy models, including DBA/1 mice. Serotonergic abnormalities have also recently been observed in human SUDEP. Fenfluramine is a drug that enhances serotonin release in the brain. Recent studies have found that the addition of fenfluramine improved seizure control in patients with Dravet syndrome, which has a high incidence of SUDEP. Therefore, we investigated the effects of fenfluramine on seizures and seizure-induced respiratory arrest (S-IRA) in DBA/1 mice.

METHODS

The dose and time course of the effects of fenfluramine (i.p.) on audiogenic seizures (Sz) induced by an electric bell in DBA/1 mice were determined. Videos of Sz-induced behaviors were recorded for analysis. Statistical significance (P < 0.05) was evaluated using the chi-square test.

RESULTS

Sixteen hours after administration of 15 mg/kg of fenfluramine, a high incidence of selective block of S-IRA susceptibility (P < 0.001) occurred in DBA/1 mice without blocking any convulsive behavior. Thirty minutes after 20-40 mg/kg of fenfluramine, significant reductions of seizure incidence and severity, as well as S-IRA susceptibility occurred, which were long-lasting (≥48 hours). The median effective dose (ED₅₀ ) of fenfluramine for significantly reducing Sz at 30 minutes was 21 mg/kg.

SIGNIFICANCE

This study presents the first evidence for the effectiveness of fenfluramine in reducing seizure incidence, severity, and S-IRA susceptibility in a mammalian SUDEP model. The ability of fenfluramine to block S-IRA selectively suggests the potential usefulness of fenfluramine in prophylaxis of SUDEP. These results further confirm and extend the serotonin hypothesis of SUDEP.

Postconvulsive central apnea as a biomarker for sudden unexpected death in epilepsy (SUDEP)

OBJECTIVE

To characterize peri-ictal apnea and postictal asystole in generalized convulsive seizures (GCS) of intractable epilepsy.

METHODS

This was a prospective, multicenter epilepsy monitoring study of autonomic and breathing biomarkers of sudden unexpected death in epilepsy (SUDEP) in patients ≥18 years old with intractable epilepsy and monitored GCS. Video-EEG, thoracoabdominal excursions, nasal airflow, capillary oxygen saturation, and ECG were analyzed.

RESULTS

We studied 148 GCS in 87 patients. Nineteen patients had generalized epilepsy; 65 had focal epilepsy; 1 had both; and the epileptogenic zone was unknown in 2. Ictal central apnea (ICA) preceded GCS in 49 of 121 (40.4%) seizures in 23 patients, all with focal epilepsy. Postconvulsive central apnea (PCCA) occurred in 31 of 140 (22.1%) seizures in 22 patients, with generalized, focal, or unknown epileptogenic zones. In 2 patients, PCCA occurred concurrently with asystole (near-SUDEP), with an incidence rate of 10.2 per 1,000 patient-years. One patient with PCCA died of probable SUDEP during follow-up, suggesting a SUDEP incidence rate 5.1 per 1,000 patient-years. No cases of laryngospasm were detected. Rhythmic muscle artifact synchronous with breathing was present in 75 of 147 seizures and related to stertorous breathing (odds ratio 3.856, 95% confidence interval 1.395-10.663, p = 0.009).

CONCLUSIONS

PCCA occurred in both focal and generalized epilepsies, suggesting a different pathophysiology from ICA, which occurred only in focal epilepsy. PCCA was seen in 2 near-SUDEP cases and 1 probable SUDEP case, suggesting that this phenomenon may serve as a clinical biomarker of SUDEP. Larger studies are needed to validate this observation. Rhythmic postictal muscle artifact is suggestive of post-GCS breathing effort rather than a specific biomarker of laryngospasm.