Seizure Termination Research Articles

Postictal EEG changes following focal seizures: Interrater agreement and comparison to frequency analysis

ObjectivesTo compare frequency analysis to human raters and determine the interrater agreement of postictal EEG changes after focal seizures. Methods24 focal seizures with and without impaired awareness recorded with scalp-EEG in the epilepsy monitoring unit were selected. Five board-certified neurophysiologists annotated seizure termination and end of postictal changes for all seizures. We assessed agreement using intraclass correlation, described the band-power changes by time-frequency analysis, and correlated these measures with the rater annotations. ResultsInterrater agreement on the duration of the postictal changes was moderate (0.64, 95% confidence interval: 0.36–0.82). The interrater agreement for seizure termination was excellent (1.00). Median duration of the postictal interval of seizures with impaired awareness was significantly shorter than for seizures with retained awareness (p = 0.0004). Mean postictal duration was 16.4 min. Seizure duration did not predict duration of the postictal changes. We found a strong correlation of 0.8 between the median human rater and the duration of the decrease in spectral edge frequency. ConclusionsThe agreement of neurophysiologists is moderate for duration of postictal changes and high for seizure termination. Rater determination of postictal duration is correlated with measures of EEG slowing. SignificanceDisagreement between neurophysiologists on postictal duration need to be considered.

Regional and temporal regulation and role of somatostatin receptor subtypes in the mouse brain following systemic kainate-induced acute seizures

Somatostatin reduces neuronal excitability via somatostatin receptors (Sst1-Sst5) and inhibits seizure activity. However, the expression status of the Sst subtypes in epileptic mice and their role in the antiepileptic effects of somatostatin remain unclear. Here, we show that the Sst subtypes are regulated differently by epileptic neuronal activity in mice. Systemic kainate injection rapidly and transiently elevated the Sst2 and Sst3 mRNA and reduced Sst1 and Sst4 mRNA in the hippocampus; however, among all the subtypes, only Sst2 mRNA was increased in the excitatory neurons of the basolateral amygdala, accompanied by a decrease in the level of Sst2 protein. Following kainate administration, recovery from seizure was delayed by reduced expression of Sst2 in the basolateral amygdala, but not in the dentate gyrus of the hippocampus; higher expression levels of Bdnf, a neuronal activity marker, were observed in both conditions. These results suggest that Sst2 contributes to seizure termination by feedback inhibition in the amygdala. This could be a potential therapeutic target for acute seizures.

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

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

Control Mechanisms on the Initiation of Cortical Wave Propagation Preceding Seizure Termination

Abstract Organized patterns of activity in the form of traveling waves are characteristic features observed in clinical data recorded in vivo preceding seizure termination. Understanding the exact biological mechanisms leading to this type of cortical wave propagation is an open challenge. Since these relatively simple brain phenomena appear rigth before seizure termination, it is interesting to understand the mechanisms that initiate such wave propagation. Knowing these mechanisms may help to understand how to shorten the length of a seizure and position the brain into a state of seizure termination sooner. In this paper, we present a minimum-time control mechanism for the initiation of traveling wave activity in an activity-based neural field model with features observed in clinical recordings.

Postictal clinical and electroencephalographic activity following intracranially recorded bilateral tonic-clonic seizures.

The dynamics of the postictal period, which may demonstrate such dramatic clinical phenomena as focal neurological deficits, prolonged coma and immobility, and even sudden death, are poorly understood. We sought to classify and characterize postictal phases of bilateral tonic-clonic seizures based on electroencephalographic (EEG) criteria and associated clinical features. We performed a detailed electroclinical evaluation of the postictal period in a series of 31 bilateral tonic-clonic seizures in 16 patients undergoing epilepsy surgery evaluations for focal pharmacoresistant epilepsy with intracranial electrodes and time-locked video. The postictal EEG demonstrated three clearly differentiated phases as follows: attenuation, a burst-attenuation pattern, and a return to continuous background, with abrupt, synchronized transitions between phases. Postictal attenuation was common, occurring in 84% of seizures in 94% of patients in this study. There was increased power in gamma frequencies (>25 Hz) during postictal attenuation periods relative to preictal baseline in 88% of seizures demonstrating the attenuation pattern (n = 25 seizures, P < 0.002). Such increases were seen in >90% of channels in 13 seizures (52%) and <10% of channels in three seizures (12%). Postictal immobility was seen in 87% of seizures, with either a flaccid (58%) or rigid/dystonic (29%) appearance. Clinical motor manifestations, including focal dystonic posturing, automatisms, head and eye deviation, and myoclonic jerking, continued or emerged within the first minute following seizure termination in 48% of seizures, regardless of EEG appearance. Intracranial postictal attenuation, which may be diffuse or focal, is so common that it should be regarded as a ubiquitous feature of bilateral tonic-clonic seizures, rather than an unusual event. The prominence of high-frequency activity coupled with emerging clinical features, including rigid immobility and semiologies such as automatisms, during the postictal period supports the presence of ongoing seizure-related neuronal activity in unrecorded brain regions.

Quantitative analysis and EEG markers of KCNT1 epilepsy of infancy with migrating focal seizures.

We aimed to characterize epilepsy of infancy with migrating focal seizures (EIMFS), a rare, severe early onset developmental epilepsy related to KCNT1 mutation, and to define specific electroencephalography (EEG) markers using EEG quantitative analysis. The ultimate goal would be to improve early diagnosis and to better understand seizure onset and propagation of EIMFS as compared to other early onset developmental epilepsy. EEG of 7 EIMFS patients with KCNT1 mutations (115 seizures) and 17 patients with other early onset epilepsies (30 seizures) was included in this study. After detection of seizure onset and termination, spatiotemporal characteristics were quantified. Seizure propagation dynamics were analyzed using chronograms and phase coherence. In patients with EIMFS, seizures started and were localized predominantly in temporal and occipital areas, and evolved with a stable frequency (4-10Hz). Inter- and intrahemispheric migrations were present in 60% of EIMFS seizures with high intraindividual reproducibility of temporospatial dynamics. Interhemispheric migrating seizures spread in 71% from temporal or occipital channels to the homologous contralateral ones, whereas intrahemispheric seizures involved mainly frontotemporal, temporal, and occipital channels. Causality links were present between ictal activities detected under different channels during migrating seizures. Finally, time delay index (based on delays between the different ictal onsets) and phase correlation index (based on coherence of ictal activities) allowed discrimination of EIMFS and non-EIMFS seizures with a specificity of 91.2% and a sensitivity of 84.4%. We showed that the migrating pattern in EIMFS is not a random process, as suggested previously, and that it is a particular propagation pattern that follows the classical propagation pathways. It is notable that this study reveals specific EEG markers (time delay and phase correlation) accessible to visual evaluation, which will improve EIMFS diagnosis.

Directional functional coupling during limbic seizures in rats revealed by nonlinear Granger causality

Subject and Purpose - Temporal lobe epilepsy is increasingly recognized to involve widespread network alterations. In this study the temporal dynamics of directional interactions between the frontal cortex, hippocampus, thalamus and midbrain during limbic seizures are analyzed in rats. Methods - Local field potentials were recorded in Wistar rats expressing generalized limbic seizures, Racine's stage 4-5. These spontaneous seizures occur during chronic treatment with a CB1 (cannabinoid receptor type 1) antagonist SLV326. Time-frequency analysis, time-varying adapted nonlinear Granger causality and mutual information were applied. The Granger causality and mutual information values estimated from seizure episodes were compared to those of seizure-free periods. Results - During the seizure, two stages were detected: a high frequency (15-20 Hz) stage followed by a low frequency (2 Hz) stage. At seizure onset, a drop in coupling between all recorded sites was found. After the seizure onset, coupling restored to normal levels in the midbrain - hippocampus pair, but remained reduced in all other studied channel pairs for at least 10 s after the onset. The transition between stages and the seizure termination were characterized by couplings increase in some pairs and by decrease in others. Conclusion - Spontaneous generalized limbic seizures can be considered as a result of pathological reorganization of coupling architecture between different brain structures, developing in time, and providing transitions between seizure stages. These findings bring together views, considering seizures as an increase of couplings in the brain, and hypotheses, regarding seizures rather as a decoupled state.

Acid-Sensing Ion Channels Structural Aspects, Pathophysiological Importance and Experimental Mutational Data Available Across Various Species to Target Human ASIC1.

The H+-gated (proton) currents are widely present in brain sensory neuronal system and various studies identified the structural units and deciphered the physiological and pathological function of ion channels. The normal neuron requires an optimal pH to carry out its functions. In acidosis, the ASICs (Acid-sensing Ion Channels) are activated in both the CNS (central nervous system) and PNS (peripheral nervous system). ASICs are related to degenerin channels (DEGs), epithelial sodium cation channels (ENaCs), and FMRF-amide (Phe-Met-Arg-Phe-NH2)-gated channels (FaNaC). Its activation leads physiologically to pain perception, synaptic plasticity, learning and memory, fear, ischemic neuronal injury, seizure termination, neuronal degeneration, and mechanosensation. It detects the level of acid fluctuation in the extracellular environment and responds to acidic pH by increasing the rate of membrane depolarization. It conducts cations like Na+ (Sodium) and Ca2+ (Calcium) ions across the membrane upon protonation. The ASICs subtypes are characterized by differing biophysical properties and pH sensitivities. The subtype ASIC1 is involved in various CNS diseases and therefore focusing on its specific functional properties will guide in drug design methods. The review highlights the cASIC1 (Chicken ASIC1) crystal structures, involvement in physiological environment and limitations of currently available inhibitors. In addition, it details the mutational data available to design an inhibitor against hASIC1 (Human ASIC1).

Treatment of early life status epilepticus: What can we learn from animal models?

SummaryTreatment of status epilepticus (SE) in infants and children is challenging. There is a recognition that a broad set of developmental processes need to be considered to fully appreciate the physiologic complexity of severe seizures, and seizure outcomes, in infants and children. The development and use of basic models to elucidate important mechanisms will help further our understanding of these processes. Here we review some of the key experimental models and consider several areas relevant to treatment that could lead to productive translational research. Terminating seizures quickly is essential. Understanding pharmacoresistance of SE as it relates to receptor trafficking will be critical to seizure termination. Once a severe seizure is terminated, how will the developing brain respond? Basic studies suggest that there are important acute and long‐term histopathologic, and pathophysiologic, consequences that, if left unaddressed, will produce long‐lasting deficits on the form and function of the central nervous system. To fully utilize the evidence that basic models produce, age‐ and development‐ and model‐specific frameworks have to be considered carefully. Studies have demonstrated that severe seizures can cause perturbations to developmental processes during critical periods of development that lead to life‐long deficits. Unfortunately, some of the drugs that are commonly used to treat seizures may also produce negative outcomes by enhancing Cl‐‐mediated depolarization, or by accelerating programmed cell death. More research is needed to understand these phenomena and their relevance to the human condition, and to develop rational drugs that protect the developing brain from severe seizures to the fullest extent possible.

Phase Synchronization Dynamics of Neural Network during Seizures.

Epilepsy has been considered as a network-level disorder characterized by recurrent seizures, which result from network reorganization with evolution of synchronization. In this study, the brain networks were established by calculating phase synchronization based on electrocorticogram (ECoG) signals from eleven refractory epilepsy patients. Results showed that there was a significant increase of synchronization prior to seizure termination and no significant difference of the transitions of network states among the preseizure, seizure, and postseizure periods. Those results indicated that synchronization might participate in termination of seizures, and the network states transitions might not dominate the seizure evolution.

Bioenergetic Mechanisms of Seizure Control.

Epilepsy is characterized by the regular occurrence of seizures, which follow a stereotypical sequence of alterations in the electroencephalogram. Seizures are typically a self limiting phenomenon, concluding finally in the cessation of hypersynchronous activity and followed by a state of decreased neuronal excitability which might underlie the cognitive and psychological symptoms the patients experience in the wake of seizures. Many efforts have been devoted to understand how seizures spontaneously stop in hope to exploit this knowledge in anticonvulsant or neuroprotective therapies. Besides the alterations in ion-channels, transmitters and neuromodulators, the successive build up of disturbances in energy metabolism have been suggested as a mechanism for seizure termination. Energy metabolism and substrate supply of the brain are tightly regulated by different mechanisms called neurometabolic and neurovascular coupling. Here we summarize the current knowledge whether these mechanisms are sufficient to cover the energy demand of hypersynchronous activity and whether a mismatch between energy need and supply could contribute to seizure control.

Ca2+ Signals in Astrocytes Facilitate Spread of Epileptiform Activity.

Epileptic seizures are associated with increased astrocytic Ca2+ signaling, but the fine spatiotemporal kinetics of the ictal astrocyte–neuron interplay remains elusive. By using 2-photon imaging of awake head-fixed mice with chronic hippocampal windows we demonstrate that astrocytic Ca2+ signals precede neuronal Ca2+ elevations during the initial bout of kainate-induced seizures. On average, astrocytic Ca2+ elevations preceded neuronal activity in CA1 by about 8 s. In subsequent bouts of epileptic seizures, astrocytes and neurons were activated simultaneously. The initial astrocytic Ca2+ elevation was abolished in mice lacking the type 2 inositol-1,4,5-trisphosphate-receptor (Itpr2−/−). Furthermore, we found that Itpr2−/− mice exhibited 60% less epileptiform activity compared with wild-type mice when assessed by telemetric EEG monitoring. In both genotypes we also demonstrate that spreading depression waves may play a part in seizure termination. Our findings imply a role for astrocytic Ca2+ signals in ictogenesis.

Mechanisms of status epilepticus: α-Amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor hypothesis.

Prolonged seizures of status epilepticus (SE) result from failure of mechanisms of seizure termination or activation of mechanisms that sustain seizures. Reduced γ-aminobutyric acid type A receptor-mediated synaptic transmission contributes to impairment of seizure termination. However, mechanisms that sustain prolonged seizures are not known. We propose that insertion of GluA1 subunits at the glutamatergic synapses causes potentiation of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic receptor (AMPAR)-mediated neurotransmission, which helps to spread and sustain seizures. The AMPAR-mediated neurotransmission of CA1 pyramidal neurons was increased in animals in SE induced by pilocarpine. The surface membrane expression of GluA1 subunit-containing AMPARs on CA1 pyramidal neurons was also increased. Blockade of N-methyl-d-aspartate receptors 10minutes after the onset of continuous electrographic seizure activity prevented the increase in the surface expression of GluA1 subunits. N-methyl-d-aspartate receptor antagonist MK-801 in conjunction with diazepam also terminated seizures that were refractory to MK-801 or diazepam alone. Future studies using mice lacking the GluA1 subunit expression will provide further insights into the role of GluA1 subunit-containing AMPAR plasticity in sustaining seizures of SE.

Enhanced thalamo-hippocampal synchronization during focal limbic seizures.

The key factors that promote the termination of focal seizures have not been fully clarified. The buildup of neuronal synchronization during seizures has been proposed as one of the possible activity-dependent, self-limiting mechanisms. We investigate if increased thalamo-cortical coupling contributes to enhance synchronization during the late phase of focal seizure-like events (SLEs) generated in limbic regions. Recordings were simultaneously performed in the nucleus reuniens of the thalamus, in the hippocampus and in the entorhinal cortex of the isolated guinea pig brain during focal bicuculline-induced SLEs with low voltage fast activity at onset. Spectral coherence and cross-correlation analysis demonstrated a progressive thalamo-cortical entrainment and synchronization in the generation of bursting activity that characterizes the final part of SLEs. The hippocampus is the first activated structure at the beginning of SLE bursting phase and thalamo-hippocampal synchronization is progressively enhanced as SLE develops. The thalamus takes the lead in generating the bursting discharge as SLE end approaches. As suggested by clinical studies performed during pre-surgical intracranial monitoring, our data confirm a role of the midline thalamus in leading the synchronous bursting activity at the end of focal seizures in the mesial temporal regions.

Neuro-Glial Network Model Of Postictal Generalized EEG Suppression (PGES).

Over the past couple of decades, glial cells have been highlighted as active agents in hyperexcitability of neuronal networks, specifically playing key roles in seizure onset and termination. In particular, microglia have been suggested to have both neuroprotective and neurotoxic effects on the brain. Investigation into seizure termination is of particular interest, as it is sometimes followed by a postictal generalized EEG suppression (PGES) - a low activity state that is potentially associated with sudden unexpected death in epilepsy. In this study, we attempt to link glial effects - synaptic pruning and astrocytic potassium clearance - to the duration of spontaneous epileptiform discharges (SEDs) as well as interSED intervals (iSEDs). We build upon an earlier model of a neuroglial network by translating it into the cortical paradigm and including microglial units. Preliminary findings of our model demonstrated that the duration of SEDs is largely determined by the astrocytic potassium clearance, whereas iSEDs significantly increased with microglial-driven synaptic pruning. In our model, astrocytic potassium clearance itself did not bring a PGES-like state, whereas microglial effects did, which suggests a potential biomarker for PGES phenomena.

Abstract PD-044: COMPARISON OF IV LEVETIRACETAM AND PHENYTOIN COMBINATION VERSUS IV PHENYTOIN- PLACEBO COMBINATION IN CHILDREN WITH BENZODIAZEPINE RESISTANT CONVULSIVE SE- DOUBLE BLIND RANDOMIZED CONTROLLED TRIAL

Aims & Objectives: Background and Aim Current guidelines recommend initial benzodiazepine followed by phenytoin to control status epilepticus (SE). However, with this regimen seizures may remain uncontrolled in 50–60% of cases. Prolongation of seizures makes it refractory. We therefore planned this study to see if combination therapy controls seizures early. Aims: To compare seizure control with phenytoin + levetiracetam versus phenytoin monotherapy. Methods Sixty children 3m-12years, presenting to pediatric emergency between January-December 2017 in SE not controlled with initial 2 doses of benzodiazepines were enrolled. They were randomized into Group A (phenytoin + levetiracetam) or Group B (phenytoin + placebo). Primary outcome was seizure termination within 30 minutes of therapy. Standard care was provided to all. Serum levels of phenytoin and/or levetiracetam were measured at 1 hour of infusion. Patients were monitored for drug related adverse events. Trial was registered in Clinical Trials Registry of India (CTRI/2017/17/011050). Nonparametric continuous data was analyzed with student t-test and categorical variables with Chi square test. Results Seizure control was achieved in 25/28 children (75%) in Group A and 23/32 children (72%) in Group B, p=0.77. One child (3.6%) had recurrence of seizure within 8 hour in Group A and 3 (9.4%) in Group B (RR 0.35 95% 0.035–3.65) p=0.616. Serum levels of levetiracetam and phenytoin levels were similar in both the groups. No significant drug adverse effects were noted Conclusions Trend towards better seizure control was seen in phenytoin + levetiracetam group as compared to phenytoin alone though results were not statistically significant due to small sample size.

The effect of inhibition on the existence of traveling wave solutions for a neural field model of human seizure termination.

In this paper we study the influence of inhibition on an activity-based neural field model consisting of an excitatory population with a linear adaptation term that directly regulates the activity of the excitatory population. Such a model has been used to replicate traveling wave data as observed in high density local field potential recordings (González-Ramírez et al. PLoS Computational Biology, 11(2), e1004065, 2015). In this work, we show that by adding an inhibitory population to this model we can still replicate wave properties as observed in human clinical data preceding seizure termination, but the parameter range over which such waves exist becomes more restricted. This restriction depends on the strength of the inhibition and the timescale at which the inhibition acts. In particular, if inhibition acts on a slower timescale relative to excitation then it is possible to still replicate traveling wave patterns as observed in the clinical data even with a relatively strong effect of inhibition. However, if inhibition acts on the same timescale as the excitation, or faster, then traveling wave patterns with the desired characteristics cease to exist when the inhibition becomes sufficiently strong.

S20. EEG features of nonconvulsive seizures in critically ill patients - Findings from the TRENdS trial

Introduction There is little data on the EEG features of seizures seen critically ill patients having nonconvulsive seizures (NCS). The Treatment of Recurrent Electrographic Nonconvulsive Seizures (TRENdS) study enrolled 74 such subjects and randomized them to treatment with lacosamide or fosphenytoin. This study evaluates the EEG features of a subset of these subjects. Methods EEG features of 36 of the 74 subjects enrolled in the TRENdS study were analyzed in detail. The extent of spread, onset frequency, offset frequency and morphology of the most common seizure type was assessed. Results In this cohort, the average number of seizures per subject was 35.9 (range 1–339). Seizures were limited to one quadrant (11, 30.6%) or hemispheric (11, 30.6%) in most subjects. Another 14 (38.8%) subjects had seizures that were generalized, bilateral but not generalized or spread to varying extent. Most subjects had seizures with delta frequency onset (18, 50%), while another 9 (25%) had theta frequencies at onset. Another 9 (25%) subjects had seizure onset frequencies in alpha or beta range, or had seizures with varying onset frequencies. At seizure termination, delta frequencies were noted in 29 (80.6%) subjects, while 7 (19.4%) had various other frequencies. The morphology of the seizures was a rhythmic discharge in 17 (47.2%) subjects, recurrent spike or sharp discharges in 5 (13.9%), recurrent spike and wave discharges in 5 (13.9%) and various other morphologies in 9 (25%) others. Conclusion NCS in this cohort of subjects were mostly limited to one hemisphere. The seizure onset frequencies were most often in the delta and theta range, while delta frequencies were noted most often at offset. Rhythmic discharges were the most common morphology.

BS02. Severity of unwitnessed seizures estimated using postictal single-channel electrocardiogram recordings

Introduction Epilepsy patients are often susceptible to cardiorespiratory adverse events during and immediately after the seizure. Unwitnessed seizures during sleep are associated with the highest rate of SUDEP - a common cause of mortality in epilepsy. To improve surveillance, different wearable sensors (like seizure warning watches) are developed for seizure advisory systems. These devices are restricted to detecting ictal events from heart rate variability, motion, and muscle activities. As the risk of cardiorespiratory complications extends beyond seizure to postictal period, it may be worthwhile to develop novel extracranial physiological biomarkers that can be used to estimate the severity of seizures from the postictal period. During a convulsive seizure, movement artifact often precludes reliable data interpretation, and hence the motivation of this study is to identify parameters at the post ictal period when artifact is expected to be less. Using advanced signal processing and machine learning tools we systematically analyzed multiple parameters obtained from a single-channel electrocardiogram to estimate the severity of seizure and epilepsy. Methods Patients admitted to a level-IV epilepsy center for video scalp EEG monitoring were included in this study. Only patients with confirmed seizures were selected. A single lead EKG was recorded simultaneously with video EEG (Natus Xltek system). Sampling frequency was 256 Hz. The EKG was analyzed in time-frequency and nonlinear domains - mean HR, standard HR, mean RR interval, RMSSD, HF, LF, approximate and sample entropy. Two minutes of epoch were selected for a baseline (at least 6 h apart from a seizure), pre seizure and post seizure. The study goal was to identify parameters following seizure termination hence seizure was not analyzed. ANOVA was performed to select features and machine learning tools (deep learning and SVM) were used for classification. Seizure severity was scored by using duration, type (focal vs. generalized seizure), Chalfont Scale and SUDEP score. Results Forty patients (M = 28) with a mean age of 32-years were included in this retrospective study. Seventy-eight seizures (49 focal seizures) were analyzed. In the postictal period, the mean and standard deviation of HR increased while the mean RR decreased significantly in comparison to baseline or pre-seizure state. Both sample and approximate entropy decreased significantly in the postictal state. Deep learning ML classified post ictal state from pre ictal or baseline with higher accuracy (>90%) by using combination of approximate entropy, mean RR. However, other features like LF, HF are still analyzed for higher accuracy and to estimate seizure severity. Conclusion In this novel study, we aim to identify physiological parameters that can estimate severity of seizures from post ictal EKG recordings. Our preliminary analyses shows post ictal mean RR, HR and approximate entropy as candidate reliable markers for estimating seizure severity.

Status epilepticus

Status epilepticus is a neurologic emergency manifested by prolonged seizure activity or multiple seizures without full recovery of previous condition in between. The most important aim of treatment is early seizure termination, because duration of status epilepticus correlates with a higher rate of morbidity and mortality. Based on evidence from clinical trials and guidelines strategies for management of status epilepticus are provided.