Sudden unexpected death in epilepsy, periictal physiology, and the SUDEP-7 Inventory

Obstructive sleep apnea is associated with risk for sudden unexpected death in epilepsy (SUDEP) using rSUDEP-7

BACKGROUND AND OBJECTIVE

Evaluate relationships between PSG-confirmed OSA and SUDEP risk using the revised SUDEP Risk Inventory (rSUDEP-7).

METHODS

Identified adults with epilepsy (AWE) who underwent PSG 2004-2016 at Cleveland Clinic. OSA was defined as apnea-hypopnea index (AHI)- ≥-5/h sleep; moderate/severe OSA as AHI≥15. SUDEP risk was assessed using rSUDEP-7: higher rSUDEP-7 score, greater SUDEP risk. Associations between rSUDEP-7 score and OSA groups (AHI≥15 vs. <15) were evaluated using Wilcoxon rank-sum tests and multivariable linear models adjusting for age, sex, BMI, and smoking status. Spearman correlations measured relationships between rSUDEP-7 score with AHI and oxygen desaturation indices (ODI).

RESULTS

OSA was present in 134 (62.6 %) of 214 AWE; moderate/severe in 75 (35 %). AWE with AHI≥15 were more likely to be male and older, had higher BMI, greater frequency of tonic-clonic seizures (TCS), longer epilepsy duration, and more likely to have drug-resistant epilepsy (DRE) and sleep-related seizures (all p< 0.05). The median rSUDEP-7 score was 1 (0,3) but 37.4 % had a score ≥3 (high SUDEP risk), and 11.7 % ≥5 (highest SUDEP risk). rSUDEP-7 scores were higher in those with AHI≥15 (3 vs. 1, p = 0.001). Higher AHI and ODI 3% positively correlated with rSUDEP-7 (p=0.002 and p=0.016) while SpO2 nadir negatively correlated with rSUDEP-7 (p=0.007). After adjustments, AWE with AHI≥15 had mean rSUDEP-7 score 1.14 points (95% CI 0.55-1.72, p<0.001) higher than those with AHI<15.

DISCUSSION

AWE with PSG-confirmed moderate/severe OSA especially those who are older and have GTC had higher rSUDEP-7 scores potentially increasing their risk for SUDEP. Our findings support routine screening for OSA in AWE. Further studies confirming the significance and impact of OSA on SUDEP risk are needed.

Update review on SUDEP: Risk assessment, background & seizure detection devices

This review focusses on sudden unexpected death in epilepsy patients (SUDEP) and incorporates risk stratification (through SUDEP risk factors and SUDEP risk scores), hypotheses on the mechanism of SUDEP and eligible seizure detection devices (SDDs) for further SUDEP prevention studies. The main risk factors for SUDEP are the presence and the frequency of generalized tonic-clonic seizures (GTC). In Swedish population-based case control study, the Odds ratio of the presence of GTC in the absence of bedroom sharing is 67. SUDEP risk scoring systems express a score that represents the cumulative presence of SUDEP risk factors, but not the exact effect of their combination. We describe 4 of the available scoring systems: SUDEP-7 inventory, SUDEP-3 inventory, SUDEP-ClinicAl Risk scorE (SUDEP-CARE score) and Kempenhaeghe SUDEP risk score. Although they all include GTC, their design is often different. Three of 4 scoring systems were validated (SUDEP-7 inventory, SUDEP-3 inventory and SUDEP-CARE score). None of the available scoring systems has been sufficiently validated for the use in a general epilepsy population. Plausible mechanisms of SUDEP are discussed. In the MORTEMUS-study (Mortality in Epilepsy Monitoring Unit Study), SUDEP was a postictal cardiorespiratory arrest after a GTC. The parallel respiratory and cardiac dysfunction in SUDEP suggests a central dysfunction of the brainstem centers that are involved in the control of respiration and heart rhythm. In the (consequent) adenosine serotonin hypotheses SUDEP occurs when a postictal adenosine-mediated respiratory depression is not compensated by the effect of serotonin. Other (adjuvant) mechanisms and factors are discussed. Seizure detection devices (SDDs) may help to improve nocturnal supervision. Five SDDs have been validated in phase 3 studies for the detection of TC: Seizure Link®, Epi-Care®, NightWatch, Empatica, Nelli®. They have demonstrated a sensitivity of at least 90 % combined with an acceptable false positive alarm rate. It has not yet been proven that the use will actually lead to SUDEP prevention, but clinical experience supports their effectiveness.

Association of hyperventilation-induced heart rate variability and sudden unexpected death in epilepsy in drug-resistant epilepsy

BACKGROUND

 Within the general epilepsy population, the incidence of Sudden Unexpected Death in Epilepsy (SUDEP) ranges from approximately 0.35 to 2.3 per 1,000 individuals per year.

OBJECTIVE

 We aimed to evaluate the relationship between SUDEP risk factors and heart rate variability (HRV) parameters as a potential biomarker of SUDEP in patients with drug-resistant epilepsy (DRE).

METHODS

 There were 52 patients diagnosed with DRE and under follow-up, and controls including 45 healthy subjects, included in the study. Hyperventilation-induced HRV (HRVHV) parameters, including the standard deviation of all RR intervals (SDRR), mean heart rate (HR), root mean squares of successive differences (RMSSD), SD of mean NN intervals recordings (SDANN), and HRV triangular index, were assessed during resting. To predict the risk of SUDEP, the relationship between HRV parameters and SUDEP risks was evaluated using the Risk Assessment for Sudden Death in Epilepsy (SUDEP-7) Risk Inventory.

RESULTS

 No statistically significant difference was found in sympathetic skin response (SSR) latency and amplitudes between the patient and control groups. In comparing healthy control subjects with patients experiencing DRE, we observed significant decreases in SDRRHV and hyperventilation-induced RMSSD (RMSSDHV) values, specifically within HRVHV. Notably, a significant correlation emerged concerning the RMSSDHV values (p < 0.01), when examining the correlation between the SUDEP-7 inventory and HRVHV parameters.

CONCLUSION

 This correlation between RMSSDHV and the SUDEP-7 Risk Inventory in patients with DRE represents a novel and consequential finding, suggesting its potential as an indicator of SUDEP risk.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

SIGNIFICANCE

This autonomic dysfunction might contribute to SUDEP pathophysiology.

Derivation and validation of a new prediction model for sudden unexpected death in epilepsy based on a longitudinal prospective population-based cohort

OBJECTIVE

We conducted a population-based, prospective cohort study with a large sample size in Ningxia Province of the Northwest, a rural area in China, by developing a model to specifically assess risk factors of sudden unexpected death in epilepsy (SUDEP) in people with convulsive epilepsy by clinical variables.

METHODS

Participants with convulsive epilepsy were recruited from January 1, 2008, to April 28, 2022, in rural Northwest China. They received regular assessments and management of epilepsy at the primary healthcare level and were followed up monthly. Information on the cause of death and relevant clinical details was obtained from death certificates or neurologist-conducted verbal autopsies. Survival analysis was employed to identify potential risk factors associated with SUDEP.

RESULTS

Five variables were independently associated with SUDEP: generalized tonic-clonic seizures (GTCS) with ≥1 attack during the preceding month, GTCS with >3 attacks during the preceding year, body mass index (BMI) ≥24, age of onset ≤14 years, and duration >20 years. The area under receiver operator characteristic (ROC) curve (AUC) value (95% CI) of the model was 0.789 (0.735-0.843) in the derivation dataset and 0.830 (0.758-0.902) in the validation dataset. There was agreement between the observed and predicted probabilities of SUDEP.

CONCLUSIONS

This study establishes that high GTCS frequency, early age of onset, long duration of epilepsy, and being overweight are associated with an increased risk of SUDEP in individuals with convulsive epilepsy. The study also developed and validated a personalized prediction model to accurately assess the risk of SUDEP.

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

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

Seizure-related complication rate in a residential population with epilepsy and intellectual disability (ECOMRAID-trial)

INTRODUCTION

The aim of the ECOMRAID trial (Epileptic seizure related Complication RAte in residential population of persons with epilepsy and Intellectual Disability) was to study seizure-related complications (status epilepticus, respiratory complications, or other severe complications) in people with epilepsy and intellectual disability living in a residential setting. The results of the present study are a prerequisite for performing a prospective study into the effectiveness of nocturnal surveillance patients with high risk for Sudden unexpected death in epilepsy (SUDEP).

MATERIAL AND METHODS

A retrospective study was conducted in three general residential care institutions and one residential specialized epilepsy clinic. In this 5-year cohort, we collected the following data: age (at inclusion and in case of death), sex, type of residential care, different types of complications, rescue/emergency medication administration, transfers to another department (internal midcare / monitoring unit or general hospital) and a self-designed SUDEP risk score. Our primary research questions were to assess the number of patients who experienced seizure-related complications and their individual complication rates. The secondary research questions were to document the relationship of these complications with the SUDEP risk score, with the type of residential living, and with the frequency of interventions by caregivers.

RESULTS

We included 370 patients (1790 patient-years) and in 135 of them, we found 717 seizure-related complications. The following complication rates were found: all complications: at 36%, status epilepticus: at 13%, respiratory complications: at 5%, and other complications at 26%. In residential care institutions, we found fewer patients with complications compared to the specialized epilepsy clinic (all complications 24% vs 42%, OR 0.44, p < 0.01; status epilepticus 5% vs 17%, OR 0.27, p < 0.01; other: complications 19% vs 30%, OR 0.56, p < 0.05). In residential care institutions, we found more "other complications" than in the specialized epilepsy clinic (89% vs 71%, OR 3.13, p < 0.0001). The annual frequency of all complications together was higher in residential care institutions (range 0 to 21 vs 0 to 10, p < 0.05). Rescue medication was given to 75% of the patients, but more often in the specialized epilepsy clinic (median 2.6 vs 0.5 times/patient/year, p < 0.001). In the specialized epilepsy clinic, more patients were transferred to a midcare / monitoring unit or general hospital (56% vs 9%, OR 13.44, p < 0.0001) with higher yearly frequencies (median 0.2 vs 0.0, p < 0.001). There were no reported cases of SUDEP. The median SUDEP risk score was higher in the specialized epilepsy clinic (5 vs 4, p < 0.05) and was weakly correlated with the status epilepticus (ρ = 0.20, p < 0.001) and (total) complication rate (ρ = 0.18, p < 0.001).

CONCLUSION

We found seizure-related complications in more than one-third of the patients with epilepsy and intellectual disability living in a residential setting over a period of 5 years. The data also quantify seizure-related complications in patients with epilepsy and intellectual disability.

Gene mutations in comorbidity of epilepsy and arrhythmia

Epilepsy is one of the most common neurological disorders, and sudden unexpected death in epilepsy (SUDEP) is the most severe outcome of refractory epilepsy. Arrhythmia is one of the heterogeneous factors in the pathophysiological mechanism of SUDEP with a high incidence in patients with refractory epilepsy, increasing the risk of premature death. The gene co-expressed in the brain and heart is supposed to be the genetic basis between epilepsy and arrhythmia, among which the gene encoding ion channel contributes to the prevalence of "cardiocerebral channelopathy" theory. Nevertheless, this theory could only explain the molecular mechanism of comorbid arrhythmia in part of patients with epilepsy (PWE). Therefore, we summarized the mutant genes that can induce comorbidity of epilepsy and arrhythmia and the possible corresponding treatments. These variants involved the genes encoding sodium, potassium, calcium and HCN channels, as well as some non-ion channel coding genes such as CHD4, PKP2, FHF1, GNB5, and mitochondrial genes. The relationship between genotype and clinical phenotype was not simple linear. Indeed, genes co-expressed in the brain and heart could independently induce epilepsy and/or arrhythmia. Mutant genes in brain could affect cardiac rhythm through central or peripheral regulation, while in the heart it could also affect cerebral electrical activity by changing the hemodynamics or internal environment. Analysis of mutations in comorbidity of epilepsy and arrhythmia could refine and expand the theory of "cardiocerebral channelopathy" and provide new insights for risk stratification of premature death and corresponding precision therapy in PWE.

Sudden unexpected death in epilepsy in children

Sudden unexpected death in epilepsy (SUDEP) is the leading cause of epilepsy-related mortality in children and adults living with epilepsy. The incidence of SUDEP is comparable in both children and adults; it is approximately 1.2 per 1000 person years. The pathophysiology of SUDEP is not well understood but may involve mechanisms such as cerebral shutdown, autonomic dysfunction, altered brainstem function, and cardiorespiratory demise. Risk factors for SUDEP include the presence of generalized tonic-clonic seizures, nocturnal seizures, possible genetic predisposition, and non-adherence to antiseizure medications. Pediatric-specific risk factors are not fully elucidated. Despite recommendations from consensus guidelines, many clinicians still do not follow the practice of counseling their patients about SUDEP. SUDEP prevention has been an area of important research focus and includes several strategies, such as obtaining seizure control, optimizing treatment regimens, nocturnal supervision, and seizure detection devices. This review discusses what is currently known about SUDEP risk factors and reviews current and future preventive strategies for SUDEP.

Stratifying sudden death risk in adults with drug-resistant focal epilepsy: The SUDEP-CARE score

BACKGROUND AND PURPOSE

A clinical risk score for sudden unexpected death in epilepsy (SUDEP) in patients with drug-resistant focal epilepsy could help improve prevention.

METHODS

A case-control study was conducted including (i) definite or probable SUDEP cases collected by the French National Sentinel Mortality Epilepsy Network and (ii) control patients from the French national research database of epilepsy monitoring units. Patients with drug-resistant focal epilepsy were eligible. Multiple logistic regressions were performed. After sensitivity analysis and internal validation, a simplified risk score was developed from the selected variables.

RESULTS

Sixty-two SUDEP cases and 620 controls were included. Of 21 potential predictors explored, seven were ultimately selected, including generalized seizure frequency (>1/month vs. <1/year: adjusted odds ratio [AOR] 2.6, 95% confidence interval [CI] 1.25-5.41), nocturnal or sleep-related seizures (AOR 4.49, 95% CI 2.68-7.53), current or past depression (AOR 2.0, 95% CI 1.19-3.34) or the ability to alert someone of an oncoming seizure (AOR 0.57, 95% CI 0.33-0.98). After internal validation, a clinically usable score ranging from -1 to 8 was developed, with high discrimination capabilities (area under the receiver operating curve 0.85, 95% CI 0.80-0.90). The threshold of 3 has good sensitivity (82.3%, 95% CI 72.7-91.8), whilst keeping a good specificity (82.7%, 95% CI 79.8-85.7).

CONCLUSIONS

These results outline the importance of generalized and nocturnal seizures on the occurrence of SUDEP, and show a protective role in the ability to alert someone of an oncoming seizure. The SUDEP-CARE score is promising and will need external validation. Further work, including paraclinical explorations, could improve this risk score.

Analysis of forensic autopsy cases associated with epilepsy: Comparison between sudden unexpected death in epilepsy (SUDEP) and not-SUDEP groups

Background and aims

Epilepsy is a common and chronic neurological disorder characterized by seizures that increase the risk of mortality. SUDEP is the most common seizure-related category of death. The study aimed to evaluate the key characteristics between SUDEP and not-SUDEP death cases.

Methods

A retrospective study of forensic autopsy cases from 2002 to 2021, performed by the Academy of Forensic Science (Ministry of Justice, China), identified a total of 31 deaths associated with epilepsy. We compared the different characteristics between individuals who died of SUDEP (SUDEP group) and individuals with epilepsy died suddenly due to unrelated causes (not-SUDEP group).

Results and conclusions

13 cases met the general accepted definition of SUDEP; and 18 cases were classified as not-SUDEP. The mean age of the not-SUDEP group was significantly higher than that of the SUDEP groups (p < 0.05) and there were more cases without a clear cause of epilepsy in the SUDEP group than in the not-SUDEP group (p < 0.05). Death position differed significantly between the two groups, with more cases dying in the prone position in the SUDEP group (p < 0.05). Complete autopsies were performed in 24 of the 31 cases. There were no significant differences in heart, lungs and brain weights, or in ventricular thickness (p > 0.05) between the SUDEP and not-SUDEP groups. In addition, compared to the not-SUDEP group, the SUDEP group featured a significantly more cases with coronary lesions (grades 1-3, p < 0.05). Neuropathological lesions were identified in 12 of the 13 SUDEP cases (92.3%), cardiac lesions were present in 10 cases (76.9%) and pulmonary edema and pulmonary congestion were present in all cases. The primary cause of death in 13 of the 31 cases was seizure disorder or epilepsy. The primary mechanism of death in SUDEP group was mainly asphyxia while that in the not-SUDEP group was cardiopulmonary failure (p < 0.05). Patients in the prone position had a significantly higher risk of asphyxia than those who were not. Here, we investigated the key characteristics between SUDEP and not-SUDEP death cases, which may help to facilitate forensic diagnosis in presumed SUDEP cases.

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.

Relation of Brain Perfusion Patterns to Sudden Unexpected Death Risk Stratification: A Study in Drug Resistant Focal Epilepsy

To explore the role of the interictal and ictal SPECT to identity functional neuroimaging biomarkers for SUDEP risk stratification in patients with drug-resistant focal epilepsy (DRFE). Twenty-nine interictal-ictal Single photon emission computed tomography (SPECT) scans were obtained from nine DRFE patients. A methodology for the relative quantification of cerebral blood flow of 74 cortical and sub-cortical structures was employed. The optimal number of clusters (K) was estimated using a modified v-fold cross-validation for the use of K means algorithm. The two regions of interest (ROIs) that represent the hypoperfused and hyperperfused areas were identified. To select the structures related to the SUDEP-7 inventory score, a data mining method that computes an automatic feature selection was used. During the interictal and ictal state, the hyperperfused ROIs in the largest part of patients were the bilateral rectus gyrus, putamen as well as globus pallidus ipsilateral to the seizure onset zone. The hypoperfused ROIs included the red nucleus, substantia nigra, medulla, and entorhinal area. The findings indicated that the nearly invariability in the perfusion pattern during the interictal to ictal transition observed in the ipsi-lateral putamen F = 12.60, p = 0.03, entorhinal area F = 25.80, p = 0.01, and temporal middle gyrus F = 12.60, p = 0.03 is a potential biomarker of SUDEP risk. The results presented in this paper allowed identifying hypo- and hyperperfused brain regions during the ictal and interictal state potentially related to SUDEP risk stratification.

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.

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.

Distinct Patterns of Brain Metabolism in Patients at Risk of Sudden Unexpected Death in Epilepsy

Objective: To characterize regional brain metabolic differences in patients at high risk of sudden unexpected death in epilepsy (SUDEP), using fluorine-18-fluorodeoxyglucose positron emission tomography (¹⁸FDG-PET).

Methods: We studied patients with refractory focal epilepsy at high (n = 56) and low (n = 69) risk of SUDEP who underwent interictal ¹⁸FDG-PET as part of their pre-surgical evaluation. Binary SUDEP risk was ascertained by thresholding frequency of focal to bilateral tonic-clonic seizures (FBTCS). A whole brain analysis was employed to explore regional differences in interictal metabolic patterns. We contrasted these findings with regional brain metabolism more directly related to frequency of FBTCS.

Results: Regions associated with cardiorespiratory and somatomotor regulation differed in interictal metabolism. In patients at relatively high risk of SUDEP, fluorodeoxyglucose (FDG) uptake was increased in the basal ganglia, ventral diencephalon, midbrain, pons, and deep cerebellar nuclei; uptake was decreased in the left planum temporale. These patterns were distinct from the effect of FBTCS frequency, where increasing frequency was associated with decreased uptake in bilateral medial superior frontal gyri, extending into the left dorsal anterior cingulate cortex.

Significance: Regions critical to cardiorespiratory and somatomotor regulation and to recovery from vital challenges show altered interictal metabolic activity in patients with frequent FBTCS considered to be at relatively high-risk of SUDEP, and shed light on the processes that may predispose patients to SUDEP.

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

BACKGROUND AND OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

CLASSIFICATION OF EVIDENCE

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

Heart Rate Variability in Insulo-Opercular Epilepsy

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

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.

Severe autonomic nervous system imbalance in Lennox-Gastaut syndrome patients demonstrated by heart rate variability recordings

OBJECTIVE

Patients diagnosed with Lennox Gastaut syndrome (LGS), an epileptic encephalopathy characterized by usually drug resistant generalized and focal seizures, are often considered as candidates for vagus nerve stimulation (VNS). Recent research shows that heart rate variability (HRV) differs in epilepsy patients and is related to VNS treatment response. This study investigated pre-ictal HRV in generalized onset seizures of patients with LGS in correlation with their VNS response.

METHODS

In drug resistant epilepsy (DRE) patients diagnosed with LGS video-electroencephalography recording was performed during their pre-surgical evaluation. Six HRV parameters (time and-, frequency domain, non-linear parameters) were evaluated for every seizure in epochs of 10 min at baseline (60 to 50 min before seizure onset) and pre-ictally (10 min prior to seizure onset). The results were correlated to VNS response after one year of VNS therapy.

RESULTS

Seven patients and 31 seizures were included, two patients were classified as VNS responders (≥ 50 % seizure reduction). No difference in pre-ictal HRV parameters between VNS responders and VNS non-responders could be found, but high frequency (HF) power, reflecting the parasympathetic tone increased significantly in the pre-ictal epoch in both VNS responders and VNS non-responders (p = 0.017, p = 0.004).

SIGNIFICANCE

In this pilot data pre-ictal HRV did not differ in VNS responders compared to VNS non-responders, but showed a significant increase in HF power - a parasympathetic overdrive - in both VNS responders and VNS non-responders. This sudden autonomic imbalance might have an influence on the cardiovascular system in the ictal period. Generalized tonic-clonic seizures are regarded as the main risk factor for SUDEP and severe seizure-induced autonomic imbalance may play a role in the pathophysiological pathway.

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.

Risk of sudden unexpected death in people with epilepsy and obstructive sleep apnea

This study aimed to determine whether severity of newly diagnosed obstructive sleep apnea (OSA) in people with epilepsy is associated with elevated sudden unexpected death in epilepsy (SUDEP) risk as calculated by the revised SUDEP-7 Inventory (rSUDEP-7). To this aim, a retrospective cross-sectional study was conducted at a single academic center. Adults ≥18 years of age with epilepsy and newly diagnosed OSA were retrospectively identified via electronic health records. Analysis was performed for subjects with confirmed epilepsy, OSA, and complete diagnostic PSG and rSUDEP-7 data. OSA severity was categorized as mild, moderate or severe. Logistic regression analysis was used to determine the association between OSA severity and rSUDEP-7 scores, adjusting for significantly different baseline characteristics. Of 86 subjects, OSA severity was classified as mild 38(44.2 %), moderate 25(29.1 %), and severe 23(26.7 %). Multivariate logistic regression demonstrated that severe OSA was significantly associated with rSUDEP-7 ≥ 5 after adjusting for congestive heart failure and diabetes (OR:4.08,p = 0.046,CI:1.04-16.28), but was attenuated when male gender was added to the model (OR:3.91,p = 0.067,CI:0.91-16.77). In conclusion, severe OSA is associated with elevated SUDEP risk. As a treatable disorder, OSA may thus represent a modifiable SUDEP risk factor. However, future confirmatory studies involving the prospective, longitudinal evaluation of SUDEP from broader populations are required.

Improving prediction of sudden unexpected death in epilepsy: From SUDEP-7 to SUDEP-3

OBJECTIVE

Sudden unexpected death in epilepsy (SUDEP) is a significant cause of mortality in epilepsy. The aim of this study is to evaluate the validity of the SUDEP-7 inventory and its components as tools for predicting SUDEP risk, and to develop and validate an improved inventory.

METHODS

The study included 28 patients who underwent video-electroencephalography (EEG) monitoring and later died of SUDEP, and 56 age- and sex-matched control patients with epilepsy. The SUDEP-7 score, its individual components, and an alternative inventory were examined as predictors of SUDEP.

RESULTS

SUDEP-7 scores were significantly higher among SUDEP patients compared with controls, both at time of admission (p = 0.024) and most recent follow-up (p = 0.016). SUDEP-7 scores declined only among controls, who demonstrated reduced seizure frequency. Seizure freedom after epilepsy surgery was also associated with survival. Several components of the SUDEP-7 inventory were independently associated with higher risk of SUDEP, including more than three generalized tonic-clonic (GTC) seizures (p = 0.002), one or more GTC seizures (p = 0.001), or one or more seizures of any type within the last year (p = 0.013), and intellectual disability (p = 0.031). In stepwise regression models, SUDEP-7 scores did not enhance the prediction of SUDEP over either GTC seizure frequency or seizure frequency alone. A novel SUDEP-3 inventory comprising GTC seizure frequency, seizure frequency, and intellectual disability (p < 0.001) outperformed the SUDEP-7 inventory (p = 0.010) in predicting SUDEP.

SIGNIFICANCE

Our findings demonstrate the limitations of the SUDEP-7 inventory. We propose a new three-item SUDEP-3 inventory, which predicts SUDEP better than the SUDEP-7.

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

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

Sudden Unexpected Death in Epilepsy: A Personalized Prediction Tool

Objective

To develop and validate a tool for individualized prediction of sudden unexpected death in epilepsy (SUDEP) risk, we reanalyzed data from 1 cohort and 3 case–control studies undertaken from 1980 through 2005.

Methods

We entered 1,273 epilepsy cases (287 SUDEP, 986 controls) and 22 clinical predictor variables into a Bayesian logistic regression model.

Results

Cross-validated individualized model predictions were superior to baseline models developed from only average population risk or from generalized tonic-clonic seizure frequency (pairwise difference in leave-one-subject-out expected log posterior density = 35.9, SEM ± 12.5, and 22.9, SEM ± 11.0, respectively). The mean cross-validated (95% bootstrap confidence interval) area under the receiver operating curve was 0.71 (0.68–0.74) for our model vs 0.38 (0.33–0.42) and 0.63 (0.59–0.67) for the baseline average and generalized tonic-clonic seizure frequency models, respectively. Model performance was weaker when applied to nonrepresented populations. Prognostic factors included generalized tonic-clonic and focal-onset seizure frequency, alcohol excess, younger age at epilepsy onset, and family history of epilepsy. Antiseizure medication adherence was associated with lower risk.

Conclusions

Even when generalized to unseen data, model predictions are more accurate than population-based estimates of SUDEP. Our tool can enable risk-based stratification for biomarker discovery and interventional trials. With further validation in unrepresented populations, it may be suitable for routine individualized clinical decision-making. Clinicians should consider assessment of multiple risk factors, and not focus only on the frequency of convulsions.

Cardiac Autonomic Dysfunction and Risk of Sudden Unexpected Death in Epilepsy

OBJECTIVE

We aimed to test whether patients who died of sudden unexpected death in epilepsy (SUDEP) had an abnormal cardiac autonomic response to sympathetic stimulation by hyperventilation.

METHODS

We conducted a retrospective, observational, case-control study of a group of patients who died of SUDEP and controls who were matched to the patients for epilepsy type, drug resistance, sex, age at EEG recording, age at onset of epilepsy, and duration of epilepsy. We analyzed the heart rate (HR) and HR variability (HRV) at rest and during and after hyperventilation performed during the patient's last EEG recording before SUDEP. In each group, changes over time in HRV indexes were analyzed with linear mixed models.

RESULTS

Twenty patients were included in each group. In the control group, the HR increased and the root mean square of successive RR-interval differences (RMSSD) decreased during the hyperventilation and then returned to the baseline values. In the SUDEP group, however, the HR and RMSSD did not change significantly during or after hyperventilation. A difference in HR between the end of the hyperventilation and 4 minutes after its end discriminated well between patients with SUDEP and control patients (area under the receiver operating characteristic curve 0.870, sensitivity 85%, specificity 75%).

CONCLUSION

Most of patients with subsequent SUDEP have an abnormal cardiac autonomic response to sympathetic stimulation through hyperventilation. An index reflecting the change in HR on hyperventilation might be predictive of the risk of SUDEP and could be used to select patients at risk of SUDEP for inclusion in trials assessing protective measures.

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

OBJECTIVE

Postictal generalized suppression (PGES) may be associated with SUDEP risk. We aimed to study metabolic changes on ¹⁸Fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography (PET) in patients with focal to bilateral (generalized) seizures (GTCS) and PGES on stereoelectroencephalography (SEEG).

METHODS

We analyzed interictal brain metabolism in a group of 19 patients with widespread postictal suppression (PGES+) associated with SEEG-recorded GTCS. This group was compared to 25 patients without widespread suppression (PGES-) as defined by SEEG, matched for epilepsy localization and lateralization. Frequency of GTCS was observed to be higher in the PGES+ group (high risk group for SUDEP). Analysis of metabolic data was performed by statistical parametric mapping (SPM) on the whole-brain, and principal component analysis (PCA) on AAL (automated anatomical labeling) atlas.

RESULTS

Statistical parametric mapping showed right temporal pole hypometabolism in the PGES+ group (T-score = 3.90; p < 0.001; k = 185), in comparison to the PGES- group. Principal component analysis showed association between the metabolic values of certain regions of interest and PGES+/PGES- groups, confirmed by a significant difference (p < 0.05) in the values of the right dorsal temporal pole and of the left temporal pole between the two groups. Principal component analysis showed two dimensions significantly related to the PGES+/PGES- partition, involving the following regions: right temporal pole, right parahippocampal gyrus, right Rolandic operculum, bilateral paracentral lobule, right precuneus, right thalamus, right caudate and pallidum, bilateral cerebellum, left temporal pole, left Heschl's gyrus, left calcarine region, and left caudate, with loss of connection in PGES+ patients. Metabolic differences were independent of epilepsy localization and lateralization and persisted after correction for GTCS frequency.

SIGNIFICANCE

Interictal metabolic changes within a predominantly right-sided network involving temporal lobe and connected cortical and subcortical structures were seen in patients with frequent GTCS presenting widespread postictal suppression.

Near SUDEP during bilateral stereo-EEG monitoring characterized by diffuse postictal EEG suppression

Sudden unexpected death in epilepsy (SUDEP) is the most common cause of death in patients with refractory epilepsy. The pathophysiology of SUDEP is unknown. Postictal phenomena such as postconvulsive immobility (PI), postictal generalized electroencephalography (EEG) suppression (PGES), arousal deficits, cardiac arrhythmias, central apneas, and obstructive apneas due to laryngospasms have been suggested to contribute to SUDEP. We present, to our knowledge, the first case of a near-SUDEP event in a patient undergoing intracranial, stereotactic EEG (sEEG) monitoring. This case spotlights potential mediators of SUDEP, most notably the striking PGES and postictal apnea. The nature of the sEEG investigation illustrates the extent of cortical and subcortical postictal EEG suppression and showcases a transient return of cerebral activity likely to be missed on scalp-EEG recording. Critically, this case emphasizes the importance of continuous cardiorespiratory monitoring and underscores the importance of postictal arousal as a pathophysiological mechanism in SUDEP.

Cardiorespiratory and autonomic function in epileptic seizures: A video-EEG monitoring study

PURPOSE

Seizure-induced cardiorespiratory and autonomic dysfunction has long been recognized, and growing evidence points to its implication in sudden unexpected death in epilepsy (SUDEP). However, a comprehensive understanding of cardiorespiratory function in the preictal, ictal, and postictal periods are lacking.

METHODS

We examined continuous cardiorespiratory and autonomic function in 157 seizures (18 convulsive and 139 nonconvulsive) from 70 consecutive patients who had a seizure captured on concurrent video-encephalogram (EEG) monitoring and polysomnography between February 1, 2012 and May 31, 2017. Heart and respiratory rates, heart rate variability (HRV), and oxygen saturation were assessed across four distinct periods: baseline (120 s), preictal (60 s), ictal, and postictal (300 s). Heart and respiratory rates were further followed for up to 60 min after seizure termination to assess return to baseline.

RESULTS

Ictal tachycardia occurred during both convulsive and nonconvulsive seizures, but the maximum rate was higher for convulsive seizures (mean: 138.8 beats/min, 95% confidence interval (CI): 125.3-152.4) compared with nonconvulsive seizures (mean: 105.4 beats/min, 95% CI: 101.2-109.6; p < 0.001). Convulsive seizures were associated with a lower ictal minimum respiratory rate (mean: 0 breaths/min, 95% CI: 0-0) compared with nonconvulsive seizures (mean: 11.0 breaths/min, 95% CI: 9.5-12.6; p < 0.001). Ictal obstructive apnea was associated with convulsive compared with nonconvulsive seizures. The low-frequency (LF) power band of ictal HRV was higher among convulsive seizures than nonconvulsive seizures (ratio of means (ROM): 2.97, 95% CI: 1.34-6.60; p = 0.008). Postictal tachycardia was substantially prolonged, characterized by a longer return to baseline for convulsive seizures (median: 60.0 min, interquartile range (IQR): 46.5-60.0) than nonconvulsive seizures (median: 0.26 min, IQR: 0.008-0.9; p < 0.001). For postictal hyperventilation, the return to baseline was longer in convulsive seizures (median: 25.3 min, IQR: 8.1-60) than nonconvulsive seizures (median: 1.0 min, IQR: 0.07-3.2; p < 0.001). The LF power band of postictal HRV was lower in convulsive seizures than nonconvulsive seizures (ROM: 0.33, 95% CI: 0.11-0.96; p = 0.043). Convulsive seizures with postictal generalized EEG suppression (PGES; n = 12) were associated with lower postictal heart and respiratory rate, and increased HRV, compared with those without (n = 6).

CONCLUSIONS

Profound cardiorespiratory and autonomic dysfunction associated with convulsive seizures may explain why these seizures carry the greatest risk of SUDEP.

Postictal stertor: Associations with focal and bilateral seizure types

OBJECTIVE

The objective of the present study was to determine the association between respiratory stertor and focal and bilateral seizure types.

METHODS

We characterized ictal and postictal behaviors during symmetric bilateral tonic-clonic (TC) and asymmetric TC seizures in the Johns Hopkins University (JHU) epilepsy monitoring unit, comparing these to focal unaware seizures. We measured the presence and duration of postictal stertorous respirations, postictal generalized electroencephalographic suppression (PGES), immobility/motor dysfunction, and encephalopathy and determined their associations and relationship to seizure types.

RESULTS

In initial seizures recorded in 80 consecutive patients, bilateral symmetric TC seizures (N = 35) were strongly associated with PGES (97%, p < 0.001) and postictal stertorous respirations (89%, p < 0.001). Only 10% of the 20 patients with asymmetric TC seizures had brief PGES; focal unaware seizures (N = 25) were not associated with PGES or stertorous breathing. Some patients (24%) with asymmetric or bilateral symmetric TC seizures had severe postictal encephalopathy with stertor that was separate or extended beyond periods of PGES.

CONCLUSION

Bilateral symmetric TC seizures, but not focal unaware seizures, have postictal stertor during PGES. Severe postictal encephalopathy, however, is also associated with motor dysfunction and stertor. Stertor appears to be a compensatory postictal respiratory pattern for ictal/postictal hypoxemia and occurs with PGES or postictal encephalopathy.

Prone, lateral, or supine positioning at seizure onset determines the postictal body position: A multicenter video-EEG monitoring cohort study

PURPOSE

Most patients who die from sudden unexpected death in epilepsy (SUDEP) are found in the prone position. We evaluated whether changes in body position occur during generalized convulsive seizures (GCSs).

METHOD

GCSs in patients undergoing video-EEG-monitoring between 2007 and 2017 at epilepsy centers in Frankfurt and Marburg were analyzed in relation to changes in body position.

RESULTS

A total of 494 GCSs were analyzed among 327 patients. At seizure onset, positions included supine (48.2 %), right lateral (19.0 %), left lateral (15.6 %), sitting or standing (14.0 %), and prone (3.2 %). Between seizure onset and the start of generalization, 57.5 % of participants altered body positions. During four seizures, patients adopted a prone position, while, in five seizures, patients moved from a prone position. Patients who experienced GCS onset while in a nonprone position had a 2.1 % risk of entering the prone position by the end of their seizure. In contrast, 56.2 % of those in an initial prone position remained so at the end of the GCS, with an odds ratio for maintaining that position of 60.2 (95 % confidence interval: 29.1-124.3; p < 0.001). The likelihood of ending up in the prone position post-GCS did not vary among patients with different nonprone starting positions (p = 0.147).

CONCLUSIONS

Seizures in prone position occur during sleep and the highest risk for postictal prone positioning appears to be being in the prone position at GCS onset. Epilepsy patients should therefore be advised to go to sleep in a supine or lateral position to reduce their SUDEP risk.

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.

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.

C-Fos mapping and EEG characteristics of multiple mice brain regions in pentylenetetrazol-induced seizure mice model

Purpose: To confirm different local brain activities characterized in pentylenetetrazol (PTZ)-induced seizure model. Methods: we induced seizure response by a single dose of PTZ injection (45 mg/kg, i.p.). Local activity was recorded in different brain regions by EEG in time and c-Fos staining at different time points (0.5 h, 1 h, 2 h, 4 h) after PTZ treatment. Results: EEG recordings showed distinctive features of activation in different brain areas. With the aggravation of behavioral manifestations of seizures, the frequency and amplitude of the discharges on EEG were increasing gradually. The epileptic response on EEG immediately ended after reaching the maximum stage of seizures, followed by a short period of suppression. The labeling of c-Fos was enhanced in the medial prefrontal cortex, the piriform cortex, the amygdala, hippocampal CA1, CA3 and dentate gyrus, but inapparent in the striatum. The most potent changes in c-Fos were observed in cortex, amygdala nuclei, and dentate gyrus. EEG and c-Fos immunolabeling in neuronal activation showed discrepancies in the striatum. For each brain region, the maximum c-Fos labeling was observed at 2 h after injection and diminished at 4 h. The level of c-Fos immunoreactivity was even lower than the control group, which was accompanied by increased labeling of parvalbumin neurons (PVNs). Conclusions: These findings validated PTZ-induced seizure as a seizure model with a specific spatial-temporal profile. Neuronal activity was enhanced and then subsequently inhibited during seizure evolution. Abbreviations: AEDs: anti-epileptic drugs; AF: Alexa Fluor; CA1: Cornu Ammonis area 1; CA3: Cornu Ammonis area 3; DAB, 3: 3P-diaminobenzidine; DAPI: 4',6-diamidino-2-phenylindole; DG: dentate gyrus; EEG: electroencephalogram; GABA: gamma-aminobutyric acid; IEG: immediate early gene; mPFC: medial prefrontal cortex; NAc: nucleus accumbens; PB: phosphate buffer; PBS: phosphate buffered saline; PBST: phosphate buffered saline with Tween; PFA, paraformaldehyde; PTZ: pentylenetetrazol; PVN: parvalbumin neuron; ROI: regions of interest; SE: status epilepticus.