Seizure Counts Research Articles

Detection of seizure clustering using ultralong-term subcutaneous EEG monitoring

AbstractEpileptic seizures usually occur unpredictably yet not necessarily at random times. Cyclical patterns of seizure recurrence have been broadly described. Long-term seizure documentation may reveal individual cyclical seizure patterns; however, seizure reporting by patients or their caregivers is often inaccurate. Modern technologies for at-home monitoring of epileptic seizures enable continuous EEG recording for objective seizure counts over long-term timescales. Here, we present the clinical case of a patient with temporal lobe epilepsy due to hippocampal sclerosis who underwent ultralong-term subcutaneous EEG recording over a 1-year period, which revealed the occurrence of seizure clusters at three- to four-weekly intervals. The case demonstrates the possibility of detection of subject-specific seizure timing using a minimally invasive subcutaneous EEG recorder for ultralong-term at-home seizure monitoring. Information about individual seizure timing may contribute to a more personalized chronotherapeutic treatment approach in which antiseizure medication can be maintained at low doses during the low-risk periods and increased briefly before the anticipated seizures.

Exogenous ketones exert antiseizure effects and modulate the gut microbiome and mycobiome in a clinically relevant murine model of epilepsy.

Despite growing interest in the potential use of exogenous ketones for the treatment of epilepsy, their impact on seizures and the gut microbiome and mycobiome remain unclear. Here, we examined the effects of both oral gavage and subcutaneous (SC) injection of a ketone ester (KE) in spontaneously epileptic Kcna1-null (KO) mice that model seminal aspects of human temporal lobe epilepsy. Electroencephalographic recordings and biochemical analyses were performed in KE-treated KO mice. Fecal microbial and fungal communities were profiled to determine whether the antiseizure activity of KE involves changes in the gut microbiome. We found that exogenous KE administration by SC injection was more effective than oral gavage in terms of rendering antiseizure effects while generating similar degrees of ketonemia. However, reductions in mean daily seizure counts were accompanied by overall alterations in the fecal bacterial microbiome. Either oral or SC injection imposed a greater impact on the microbiome in male than female mice. In males, oral KE decreased Bacteroidota phylum and genera of Ligilactobacillus and Muribaculaceae, whereas SC injection decreased Bacteroides, Lactobacillus, and Lachnospiraceae. The fecal mycobiome was affected by KE injection to a greater degree than by oral gavage, and more in females than in males, as reflected by an increase in Ascomycota and Saccharomyces. Correlation analysis between microbiome and seizure counts revealed that in mice receiving KE injection, the seizure count was positively correlated with an amplicon sequencing variant of Lactobacillus (Spearman rho = .64, p = .03) and tended toward a negative correlation with Saccharomyces (Spearman rho = -.57, p = .057). Our findings demonstrate that exogenous ketone administration alone can induce antiseizure effects equally via different routes of administration, and that they induce differential shifts in both the bacterial microbiome and mycobiome.

Demonstration of Group-Level and Individual-Level Efficacy Using Time-to-Event Designs for Clinical Trials of Antiseizure Medications.

Participants with treatment-resistant epilepsy who are randomized to add-on placebo and remain in a trial for the typical 3 to 5-month maintenance period may be at increased risk of adverse outcomes. A novel trial design has been suggested, time to prerandomization monthly seizure count (T-PSC), which would limit participants' time on ineffective therapy. We reanalyzed 11 completed trials to determine whether the primary efficacy conclusions at T-PSC matched each of the original, longer trials. A total of 11 double-blind, placebo-controlled trials of levetiracetam, brivaracetam, lacosamide, topiramate, and lamotrigine for either focal-onset or generalized-onset epilepsy were selected. We evaluated the group-level and individual-level efficacy of treatments including the median percent reduction (MPR) in seizure frequency and 50% responder rate (50RR) at T-PSC, time to second seizure, and time to first seizure compared with the full-length trial. The primary efficacy conclusions of 10 of the 11 trials would have been the same with a T-PSC design compared with the traditional design (the exception of lamotrigine had a very high initial placebo response). As a proportion of the full-length effect size, 90% of the MPR and 85% of the 50RR were seen at T-PSC (95% CI 73%-113% and 65%-110%, respectively). Using the T-PSC design, the time on blinded treatment was at least 312 participant-years shorter (40% of total duration) and 142,000 seizures occurred during this time (60% of total seizures). By contrast, the time to first or second seizure designs reproduced group-level effect size, but the primary efficacy conclusions of each trial and individual-level efficacy correspondence were fair to poor. These results support the use of this trial design for new epilepsy medication trials because this reanalysis of 11 randomized controlled trials demonstrated that observation until T-PSC was sufficient to demonstrate efficacy while potentially improving participant safety by reducing the time of exposure to placebo and inadequate treatment. Despite analysis of 11 trials including 3,619 participants, we did not observe a significant reduction in the group-level effect size, which is directly related to statistical power. The next step is to evaluate whether T-PSC is sufficient to evaluate safety as measured by adverse events.

Characterizing Seizure-Onset Patterns With the Responsive Neurostimulation System.

The responsive neurostimulation system (RNS) aims to improve seizures by delivering electrical stimulation in response to epileptiform patterns detected by electrocorticograms. Seizure-onset patterns (SOPs) correspond to outcomes in intracranial EEG (IC-EEG), although whether this is true for RNS is unknown. This study characterizes common RNS SOPs and correlates them with seizure outcomes. Among 40 patients with RNS implants, long-episode electrocorticogram characteristics of each patient's seizures were classified by visual analysis as one of the eight patterns previously described in IC-EEG. Correlation between each type of SOP and eventual seizure outcome was analyzed, with ≥50% improvement in a number of patient-reported seizure counts defined as a favorable outcome. Across 263 LEs analyzed, the most common SOP observed was low-voltage fast activity. There was no difference between the distribution of RNS SOPs and that of IC-EEG SOPs described in the literature (Kolmogorov-Smirnov test, P = 0.98). Additionally, there was no correlation between any particular SOP and favorable outcomes (Fisher's omnibus test, P = 0.997). This initial description of RNS SOPs finds them to be similar to previously described IC-EEG SOPs, which suggests similar prognostic/therapeutic potential. However, we found that RNS efficacy is independent of patient SOP, suggesting that RNS is likely an equally effective treatment for all SOPs. Future research on stimulation parameters for particular RNS SOPs and correlation with IC-EEG SOPs in the same patients would be instrumental in guiding personalized neurostimulation.

Time to prerandomization seizure count design sufficiently assessed the safety and tolerability of perampanel for the treatment of primary generalized tonic-clonic seizures.

Static assignment of participants in randomized clinical trials to placebo or ineffective treatment confers risk from continued seizures. An alternative trial design of time to exceed prerandomization monthly seizure count (T-PSC) has replicated the efficacy conclusions of traditionally designed trials, with shorter exposure to placebo and ineffective treatment. Trials aim to evaluate efficacy as well as safety and tolerability; therefore, we evaluated whether this T-PSC design also could replicate the trial's safety and tolerability conclusions. We retrospectively applied the T-PSC design to analyze treatment-emergent adverse events (TEAEs) from a blinded, placebo-controlled trial of perampanel for primary generalized tonic-clonic seizures (NCT01393743). The safety analysis set consisted of 81 and 82 participants randomized to perampanel and placebo arms, respectively. We evaluated the incidences of TEAEs, treatment-related TEAEs, serious TEAEs, and TEAEs of special interest that occurred before T-PSC relative to those observed during the full-length trial. Of the 67 and 59 participants who experienced TEAEs in the perampanel and placebo arms during full-length trial, 66 (99%) and 54 (92%) participants experienced TEAEs with onset occurring before T-PSC, respectively. When limited to treatment-related TEAEs, 55 of 56 (98%) and 32 of 37 (86%) participants reported treatment-related TEAEs that occurred before T-PSC in the perampanel and placebo arms, respectively. There were more TEAEs after T-PSC with placebo as compared to perampanel (Fisher exact odds ratio = 8.6, p = .035), which resulted in overestimation of the difference in TEAE rate. There was a numerical reduction in serious TEAEs (3/13 occurred after T-PSC, one in placebo and two in perampanel). Almost all TEAEs occurred before T-PSC. More treatment-related TEAEs occurred after T-PSC for participants randomized to placebo than perampanel, which may be due to either a shorter T-PSC or delayed time to TEAE for placebo.

Clinical correlates of negative health events and disparities among adults with epilepsy enrolled in a self-management clinical trial

AimsDespite advances in care, people with epilepsy experience negative health events (NHEs), such as seizures, emergency department (ED) visits and hospitalizations. This analysis using baseline data from an epilepsy self-management clinical trial targeting people from rural regions and other underserved populations assessed the relationship between demographic and clinical variables vs. NHEs. MethodsData to evaluate disparities and clinical correlates was collected using patient surveys from a baseline sample of 94 participants in a larger prospective study of 160 individuals with epilepsy who experienced an NHE within the last six months. Demographic characteristics, mental and physical functional status assessed using 36-Item Short Form Health Survey questionnaire version 2 (SF-36v2), depression assessed with the 9-item Patient Health Questionnaire (PHQ-9), quality of life assessed with the 10-item Quality of Life in Epilepsy Inventory (QOLIE-10), self-efficacy assessed the Epilepsy Self-Efficacy Scale (ESES), social support assessed with the Multidimensional Scale of Perceived Social Support (MSPSS), self-management assessed with the Epilepsy Self-Management Scale (ESMS), and stigma assessed with the Epilepsy Stigma Scale (ESS) were all examined in association with past 6-month total NHE frequency as well as NHE sub-categories of past 30-day and 6-month seizure counts, self-harm attempts, ED visits and hospitalizations. An exploratory evaluation of NHE correlates in relation to the Rural Urban Continuum Code (RUCC) residence classification compared 3 subgroups of increasing rurality. Descriptive statistics were generated for demographic and clinical variables and NHEs, and exploratory analyses compared the distribution of demographic, clinical, and NHE variables by RUCC categorization. ResultsThe mean age was 38.5 years (SD 11.9), predominantly female (N= 62, 66.0%) and white (N=81, 86.2%). Just a little under half (N=43, 45.7%) of participants had annual incomes of less than $25,000, and 40% (N=38) were rural residents (RUCC >3). The past 6-month NHEs count was 20.4 (SD 32.0). Seizures were the most common NHE with a mean 30-day seizure frequency = 5.4 (SD 11.8) and 6-month seizure frequency of 18.7 (SD 31.6). Other NHE types were less common with a past 6-month self-harm frequency of 0.16 (SD 1.55), ED visit frequency of 0.72 (SD 1.10), and hospitalization frequency of 0.28 (SD 1.02). There were few significant demographic and clinical correlates for total and sub-categories of NHEs. Worse physical health status, as measured by the physical component summary (PCS) of the SF-36v2, was significantly associated with 6-month seizure counts (p=.04). There were no significant differences between the 3 RUCC subgroups on demographic variables. However, past 30-day seizure count, past 6-month seizure count and total past 6-month NHE counts were all higher among individuals from more rural settings (p-values <.01 for each). ConclusionsRural adults with epilepsy were more likely to have a greater number of seizures and more epilepsy complications in general. Worse physical health function was also associated with more epilepsy complications. However, this analysis found few other demographic and clinical correlates of cumulative NHEs among adults with epilepsy. Additional efforts are needed to investigate health disparities among people with epilepsy who live in rural regions or who have poor physical health function.

Detection of seizures with ictal tachycardia, using heart rate variability and patient adaptive logistic regression machine learning methods: A hospital-based validation study.

Automated seizure detection of focal epileptic seizures is needed for objective seizure quantification to optimize the treatment of patients with epilepsy. Heart rate variability (HRV)-based seizure detection using patient-adaptive threshold with logistic regression machine learning (LRML) methods has presented promising performance in a study with a Danish patient cohort. The objective of this study was to assess the generalizability of the novel LRML seizure detection algorithm by validating it in a dataset recorded from long-term video-EEG monitoring (LTM) in a Brazilian patient cohort. Ictal and inter-ictal ECG-data epochs recorded during LTM were analyzed retrospectively. Thirty-four patients had 107 seizures (79 focal, 28 generalized tonic-clonic [GTC] including focal-to-bilateral-tonic-clonic seizures) eligible for analysis, with a total of 185.5 h recording. Because HRV-based seizure detection is only suitable in patients with marked ictal autonomic change, patients with >50 beats/min change in heart rate during seizures were selected as responders. The patient-adaptive LRML seizure detection algorithm was applied to all elected ECG data, and results were computed separately for responders and non-responders. The patient-adaptive LRML seizure detection algorithm yielded a sensitivity of 84.8% (95% CI: 75.6-93.9) with a false alarm rate of .25/24 h in the responder group (22 patients, 59 seizures). Twenty-five of the 26 GTC seizures were detected (96.2%), and 25 of the 33 focal seizures without bilateral convulsions were detected (75.8%). The study confirms in a new, independent external dataset the good performance of seizure detection from a previous study and suggests that the method is generalizable. This method seems useful for detecting both generalized and focal epileptic seizures. The algorithm can be embedded in a wearable seizure detection system to alert patients and caregivers of seizures and generate objective seizure counts helping to optimize the treatment of the patients.

A preliminary study on the association between prognostic nutritional index and neutrophil-to-lymphocyte ratio with nutritional status and inflammation in febrile children's susceptibility to seizures.

The aim of this study was to evaluate the association between nutritional status, inflammation, and susceptibility to seizures in febrile children. This observational single-center study was carried out from January 2020 to December 2023 with 324 children aged 6 months and 6 years; 106 were diagnosed with febrile seizure, 108 were febrile children, and 110 were healthy controls. The prognostic nutritional index and neutrophil-to-lymphocyte ratio were calculated, and the cutoff threshold was established through receiver operating characteristics. The study utilized correlation and univariate-multivariate logistic regression analysis. The comparison between simple and complex febrile seizure was conducted to analyze differences. The optimal cutoff values were identified as 61.25 for prognostic nutritional index and 1.04 for neutrophil-to-lymphocyte ratio. Our findings showed a significant negative association between febrile seizure and platelet count, high C-reactive protein, and high ferritin levels. Additionally, the febrile seizure group showed a significant positive correlation with high neutrophil-to-lymphocyte ratio values (≥1.04) and body temperature (≥38). Our findings revealed that high neutrophil-to-lymphocyte ratio, high C-reactive protein, and age less than 18 months were independently associated with seizure susceptibility in febrile children. High neutrophil-to-lymphocyte ratio values and low prognostic nutritional index scores may serve as novel surrogate independent factors for seizure susceptibility in febrile children. Febrile children who are less than 18 months old are more prone to experience seizures than older febrile children. Moreover, there was a correlation between febrile seizures and elevated C-reactive protein levels and neutrophil-to-lymphocyte ratio values.

Efficacy of highly purified cannabidiol (CBD) in typical absence seizures: A pilot study

ObjectivesClinical trials for typical absence seizures are notoriously difficult, because those seizures are clinically subtle and brief, so that seizure counts by caregivers are inaccurate. As a result, treatment options are limited. Currently, there are no published studies on the use of CBD in typical absence seizures. This pilot study aims to evaluate the efficacy of pharmaceutical grade CBD in typical absence seizures. MethodsWe prospectively enrolled 14 patients aged 6 years and older, diagnosed with typical absence seizures. A baseline 24-hour ambulatory EEG was conducted, followed by a second 24-hour EEG after 90 days of treatment. The outcome was an objective measure of spike-wave complexes (SWC) burden change from pre- to post- treatment. ResultsAfter taking CBD for 90 days, 9 (64.3%) patients had an increase in SWC (ranging from 8% to 2876.5%) and 5 (35.7%) had a decrease in SWC (ranging from 62.3% to 98.9%). Of the 5 patients who had a decrease, 3 (60%) were on concomitant ethosuximide (with or without other ASMs). All 3 patients on CBD and ethosuximide improved. ConclusionsAlthough based on a small subset of patients, our results suggest that CBD may not be effective for typical absence seizures. However, patients on concomitant ethosuximide or on CBD monotherapy were more likely to improve.

State Space Modeling of Event Count Time Series.

This paper proposes a class of algorithms for analyzing event count time series, based on state space modeling and Kalman filtering. While the dynamics of the state space model is kept Gaussian and linear, a nonlinear observation function is chosen. In order to estimate the states, an iterated extended Kalman filter is employed. Positive definiteness of covariance matrices is preserved by a square-root filtering approach, based on singular value decomposition. Non-negativity of the count data is ensured, either by an exponential observation function, or by a newly introduced "affinely distorted hyperbolic" observation function. The resulting algorithm is applied to time series of the daily number of seizures of drug-resistant epilepsy patients. This number may depend on dosages of simultaneously administered anti-epileptic drugs, their superposition effects, delay effects, and unknown factors, making the objective analysis of seizure counts time series arduous. For the purpose of validation, a simulation study is performed. The results of the time series analysis by state space modeling, using the dosages of the anti-epileptic drugs as external control inputs, provide a decision on the effect of the drugs in a particular patient, with respect to reducing or increasing the number of seizures.

Clinical efficacy and safety of anterior thalamic deep brain stimulation for intractable drug resistant epilepsy

BackgroundDeep brain stimulation of the anterior nucleus of the thalamus (ANT DBS) is a neuromodulation therapy for patients with refractory focal seizures evolving into bilateral tonic-clonic seizures when pharmacotherapy as well other neuromodulation techniques including vagus nerve stimulation or responsive neurostimulation have failed. ObjectiveWe performed a prospective single-center study investigating the clinical efficacy and exact ANT DBS lead location in patients with DRE. MethodsThe primary outcome measure was the proportion of patients with more than 50 % reduction in diary-recorded seizures when compared to three preoperative months (baseline seizure frequency). The close postoperative follow-up was performed every 3 months. The seizure frequency, stimulation settings and adverse events were closely monitored during follow-up visits. We also analyzed the seizure outcome with location of ANT DBS active contacts. ResultsBetween May 2020 and October 2022, 10 adult patients with a mean age of 38.5 years (range, 30–48 years) underwent bilateral ANT DBS surgery (mean duration of DRE 28.6 years, range 16–41 years). The median seizure count in three months period preceding surgery (baseline seizure count) was 43.2 (range, 4–150). Nine patients achieved more than 50 % seizure reduction at the last follow-up (mean range 3–33 13.6 months, months). ANT DBS caused seizure reduction 3 months after procedure as well as at last follow-up by 60.4 % and 73.3 %, respectively. Due to relatively small number of studying individuals we cannot precisely locate the area within ANT associated with good clinical outcome. Patients with temporal lobe epilepsy had a remarkable reduction of seizure frequency. No patient suffered transient or permanent neurological deficits. ConclusionsClinical efficacy of ANT DBS may support more widespread utilization of this neuromodulation technique especially for seizures originating from temporal lobes.

Drug regulations and trafficking: Synthetic cannabinoids and cathinones in Hungary

In principle, new psychoactive substances (NPSs) are produced to circumvent drug regulations. However, the mixed success of regulatory efforts suggests that the dynamics of marketing is incompletely understood. To address this issue, we conducted a comprehensive study on the marketing of all synthetic cannabinoids and cathinones present in Hungary over ten years. Market evaluation was based on drug seizure data and chemical analyses provided by the Hungarian Institute for Forensic Sciences. Over ten years, 18 synthetic cannabinoids and 11 cathinones were identified. Total seizure counts were 22,906 and 10,273, respectively. When new synthetic cannabinoids emerged, seizures increased exponentially, but rapidly declined after their banning. In parallel, new synthetic cannabinoids emerged on the market. The systematic monitoring of local legislation allowed large sales between market introduction and legal control. Cathinones were also marketed in successive waves, but trading intensity was not associated with local regulations. Sales remained low throughout, likely because the risks involved by the temporal mismatch between marketing and legal control. One can hypothesize that marketing was driven by general trends in EU regulations or by measures taken by large countries. Our findings imply the existence of two different strategies for NPS marketing. The choice between the two may depend on multiple factors from the availability of skills required by rapid marketing adjustments to cost/benefit evaluations for various market segments. Studying NPS market strategies in neighboring and distant EU countries may help analyzing and predicting market events.

Explainable AI for wearable seizure logging: Impact of data quality, patient age, and antiseizure medication on performance

ObjectiveObjective seizure count estimates are crucial for ambulatory epilepsy management. Wearables have shown promise for the detection of tonic-clonic seizures but may suffer from false alarms and undetected seizures. Seizure signatures recorded by wearables often occur over prolonged periods, including increased levels of electrodermal activity and heart rate long after seizure EEG onset, however, previous detection methods only partially exploited these signatures. Understanding the utility of these prolonged signatures for seizure count estimation and what factors generally determine seizure logging performance, including the role of data quality vs. algorithm performance, is thus crucial for improving wearables-based epilepsy monitoring and determining which patients benefit most from this technology. MethodsIn this retrospective study we examined 76 pediatric epilepsy patients during multiday video-EEG monitoring equipped with a wearable (Empatica E4; records of electrodermal activity, EDA, accelerometry, ACC, heart rate, HR; 1983 h total recording time; 45 tonic-clonic seizures). To log seizures on prolonged data trends, we applied deep learning on continuous overlapping 1-hour segments of multimodal data in a leave-one-subject-out approach. We systematically examined factors influencing logging performance, including patient age, antiseizure medication (ASM) load, seizure type and duration, and data artifacts. To gain insights into algorithm function and feature importance we applied Uniform Manifold Approximation and Projection (UMAP, to represent the separability of learned features) and SHapley Additive exPlanations (SHAP, to represent the most informative data signatures). ResultsPerformance for tonic-clonic seizure logging increased systematically with patient age (AUC 0.61 for patients 〈 11 years, AUC 0.77 for patients between 11–15 years, AUC 0.85 for patients 〉 15 years). Across all ages, AUC was 0.75 corresponding to a sensitivity of 0.52 and a false alarm rate of 0.28/24 h. Seizures under high ASM load or with shorter duration were detected worse (P=.025, P=.033, respectively). UMAP visualized discriminatory power at the individual patient level, SHAP analyses identified clonic motor activity and peri/postictal increases in HR and EDA as most informative. In contrast, in missed seizures, these features were absent indicating that recording quality but not the algorithm caused the low sensitivity in these patients. SignificanceOur results demonstrate the utility of prolonged, postictal data segments for seizure logging, contribute to algorithm explainability and point to influencing factors, including high ASM dose and short seizure duration. Collectively, these results may help to identify patients who particularly benefit from such technology.

Time-to-event clinical trial designs: Existing evidence and remaining concerns.

Well-designed placebo-controlled clinical trials are critical to the development of novel treatments for epilepsy, but their design has not changed for decades. Patients, clinicians, regulators, and innovators all have concerns that recruiting for trials is challenging, in part, due to the static design of maintaining participants for long periods on add-on placebo when there are an increasing number of options for therapy. A traditional trial maintains participants on blinded treatment for a static period (e.g., 12 weeks of maintenance), during which participants on placebo have an elevated risk of sudden unexpected death in epilepsy compared to patients on an active treatment. Time-to-event trials observe participants on blinded treatment until a key event occurs (e.g., post-randomization seizure count matches pre-randomization monthly seizure count). In this article, we review the evidence for these designs based on re-analysis of prior trials, one published trial that used a time-to-second seizure design, and experience from an ongoing blinded trial. We also discuss remaining concerns regarding time-to-event trials. We conclude that, despite potential limitations, time-to-event trials are a potential promising mechanism to make trials more patient friendly and reduce placebo exposure, which are urgent needs to improve safety and increase recruitment to trials.

Spike-microstates correlate with interictal epileptogenic discharges: a marker for hidden epileptic activity.

Objectively estimating disease severity and treatment success is a main problem in outpatient managing of epilepsy. Self-reported seizures diaries are well-known to underestimate the actual seizure count, and repeated EEGs might not show interictal epileptiform discharges (IEDs), although patients suffer from seizures. In this prospective study, we investigate the potential of microstate analysis to monitor epilepsy patients independently of their IED count. From our databank of candidates for epilepsy surgery, we included 18 patients who underwent controlled resting EEG sessions (with eyes closed, 30 min), at around the same time of the day, during at least four days (range: 4-8 days; mean: 5). Nine patients with temporal foci, six with extratemporal foci, and three with generalized epilepsy were included. Each patient's IEDs were marked and the topographic voltage maps of the IED peaks were averaged, and an individual average spike topography (AST) was created. The AST was then backfitted to each timepoint of the whole EEG resulting in the Spike-Microstate (SMS). The presence of the SMS in the residual EEG outside of the short IEDs epochs was determined for each recording session in each patient and correlated with the occurrence of the IEDs across all recording session, as well as with the drug charge of each day. Overall, SMS was much more represented in the routine EEG than the IEDs: they were identified 262 times more often than IEDs. The SMS time coverage correlated significantly with the IED occurrence rate (rho = 0.56; P < 0.001). If only patients with focal epilepsy were considered, this correlation was even higher rho = 0.69 (P < 0.001). Drug charge per day did not correlate with SMS. In this proof-of-concept study, the time coverage of SMS correlated strongly with the occurrence rate of the IEDs, they can be retrieved in the scalp EEG at a much higher occurrence rate. We conclude that SMS, once obtained for a given patient, are a more abundant marker of hidden epileptic activity than IEDs, in particular in focal epilepsy, and can be used also in absence of IEDs. Future larger studies are needed to verify its potential as monitoring tool and to determine cut-off values when drug protection becomes imperfect.

Second-line cannabis therapy in patients with epilepsy

Marijuana-based therapies (MBTs) have been shown to reduce seizure frequency in patients with severe and drug-resistant epilepsy (DRE). Pharmaceutical-grade CBD (EpidiolexⓇ) was approved by the FDA in 2018 for the treatments of Dravet Syndrome (DS) and Lennox-Gastaut Syndrome (LGS) and subsequently in 2020 for tuberous sclerosis complex (TSC). It is unclear what the utility would be in prescribing one type of MBT if a previous, alternative type failed. We conducted a retrospective study to determine if an alternative formulation of MBT reduces seizure frequency if the patient has not had a meaningful response from an initial MBT. We also investigated the clinical impact that a second MBT has on side effect profile. We reviewed the charts of patients with DRE who were at least 2 years old and who took at least 2 different formulations of MBT, including a pharmacologic formulation of CBD (EpidiolexⓇ), artisanal marijuana, and/or a hemp-based formulation. We reviewed medical records in patients 2 years of age and older; however, subjects' historical data, such as age of first seizure onset, may be prior to the age of 2 years. We extracted data on demographics, type of epilepsy, history of epilepsy, medication history, seizure count, and drug side effects. Seizure frequency, side effect profiles, and predictors of responder status were evaluated. Thirty patients were identified as taking more than 1 type of MBT. Our findings suggest that seizure frequencies do not change significantly from baseline to after the first MBT and to after the second MBT (p=.4). However, we did find that patients with greater baseline seizure frequency were significantly more likely to respond to treatment after the second MBT (p=.03). To our second endpoint of side effect profile, we found that patients who experienced side effects after a second MBT had significantly greater seizure frequency compared to those who did not (p=.04). We found no significant seizure frequency reduction from baseline to after a second MBT in patients who tried at least 2 different formulations of MBT. This suggests a low probability of seizure frequency reduction with a second MBT therapy in patients with epilepsy who tried at least two different MBTs. While these findings need to be replicated in a larger sample, they suggest that clinicians should not delay care by trying alternative MBT formulations after a patient has already tried one. Instead, it may be more prudent to attempt an alternative class of therapy.

A comparison of statistical versus clinical classifiers of seizure clustering in women with catamenial and noncatamenial epilepsy.

We assessed whether (1) women with statistical clustering of daily seizure counts (DSCs) or seizure intervals (SIs) also showed clinical clustering, defined separately by ≥2 (≥2-SC) and ≥3 (≥3-SC) seizures on any single day; and (2) how these classifiers might apply to catamenial epilepsy. This is a retrospective case-control analysis of data from 50 women with epilepsy (WWE). We assessed the relationships of the four classifiers to each other and to catamenial versus noncatamenial epilepsy using chi-squared, correlation, logistic regression, and receiver operating characteristic (ROC) analyses. ≥3-SC, not ≥2-SC, was more frequent in WWE who had statistical DSC clustering versus those who did not (21/25 [84.0%] vs. 11/25 [44.0%], p= .007). Logistic regression (p= .006) and ROC (p= .015) identified ≥3-SC, not ≥2-SC, as a predictor of statistical DSC clustering, but ≥4-SC was more accurate. ≥3-SC correlated with the average daily seizure frequencies (ADSFs) of the subjects (p= .01). ROC optimal sensitivity-specificity cut-point for ADSF prediction of ≥3-SC (.372) was 64.6% higher than for ≥2-SC (.226). SI clustering was more common in WWE who had catamenial versus noncatamenial epilepsy (p= .013). Logistic regression identified statistical SI clustering as the only significant classifier (p= .043). ROC analysis offered only marginal support (p= .056), because specificity was low (42.1%). The findings lend statistical support for (1) the utility of clinical ≥3-SC as a predictor of convulsive status epilepticus, (2) consideration of ADSFs in defining clustering, and (3) ≥4-SC as a more accurate clinical predictor of statistical DSC clustering. Statistical SI clustering occurred more frequently in women with catamenial than noncatamenial epilepsy (90.3% vs. 57.9%, p= .013). Although sensitivity was high (90.3%, 28/31), specificity was only 42.1% (8/19). Algorithms that test patterns and periodicities of clusters are more applicable.

BAYESIAN NON-HOMOGENEOUS HIDDEN MARKOV MODEL WITH VARIABLE SELECTION FOR INVESTIGATING DRIVERS OF SEIZURE RISK CYCLING.

A major issue in the clinical management of epilepsy is the unpredictability of seizures. Yet, traditional approaches to seizure forecasting and risk assessment in epilepsy rely heavily on raw seizure frequencies, which are a stochastic measurement of seizure risk. We consider a Bayesian non-homogeneous hidden Markov model for unsupervised clustering of zero-inflated seizure count data. The proposed model allows for a probabilistic estimate of the sequence of seizure risk states at the individual level. It also offers significant improvement over prior approaches by incorporating a variable selection prior for the identification of clinical covariates that drive seizure risk changes and accommodating highly granular data. For inference, we implement an efficient sampler that employs stochastic search and data augmentation techniques. We evaluate model performance on simulated seizure count data. We then demonstrate the clinical utility of the proposed model by analyzing daily seizure count data from 133 patients with Dravet syndrome collected through the Seizure Tracker™ system, a patient-reported electronic seizure diary. We report on the dynamics of seizure risk cycling, including validation of several known pharmacologic relationships. We also uncover novel findings characterizing the presence and volatility of risk states in Dravet syndrome, which may directly inform counseling to reduce the unpredictability of seizures for patients with this devastating cause of epilepsy.

Time to baseline seizure count in patients with focal seizures receiving adjunctive eslicarbazepine acetate in a phase IV clinical trial

BackgroundThe efficacy and tolerability of eslicarbazepine acetate (ESL), a once-daily, orally-administered, anti-seizure medication (ASM), have primarily been established in treatment-resistant epilepsy patients, the population most often enrolled in clinical trials of anti-seizure medications. More recently, ESL was also shown to be effective and well-tolerated as first adjunctive therapy in non-treatment-resistant patients in an open-label, non-randomized, Phase IV, 24-week study of ESL using standard efficacy parameters in adults with focal seizures. ObjectiveTo determine the time required to reach baseline seizure count, as an alternative method of assessing the efficacy of adjunctive ESL in patients with relatively low baseline monthly seizure frequencies. This additional analysis was undertaken, as subtle changes and improvements are difficult to analyze using standard efficacy parameters, such as standardized seizure frequency reduction when the baseline frequency of seizures is particularly low. MethodsThis was a post-hoc analysis of the Phase IV study data, which investigated time to baseline seizure count in patients aged ≥ 18 years with focal seizures as an alternative measure of anti-seizure efficacy. In the Phase IV trial, patients had been enrolled into 2 groups: Arm 1: ESL as first adjunctive therapy to levetiracetam (LEV) or lamotrigine (LTG), the two most commonly-prescribed ASMs, in patients with inadequate response to treatment; Arm 2: ESL as a later adjunctive therapy, following prior use of 1–2 ASMs in patients who required an additional therapeutic option. ResultsThe time to reach individual baseline seizure count was longer in patients with focal seizures receiving ESL as a first (Arm 1) versus later (Arm 2) adjunctive therapy (p = 0.005). Patients who received ESL as a first adjunctive therapy had a longer time to ESL discontinuation than patients who received ESL as a later adjunctive therapy (p = 0.04). In Arm 1, patients receiving concomitant LTG reported treatment-emergent adverse events (TEAEs) significantly earlier than those receiving LEV (p = 0.02). Compared to patients receiving concomitant LTG, a greater number of patients in Arm 1 who were taking concomitant LEV had a modal ESL dose > 1200 mg and completed the full maintenance period. A greater number of patients in Arm 1 who were receiving concomitant LEV and completed the 24-week maintenance period reached a maximum ESL dose of 1600 mg, compared to those taking LTG, who reached a maximum ESL dose of 1200 mg. ConclusionsThis analysis of the Phase IV clinical trial data provides an alternative way of assessing efficacy beyond standardized seizure frequency reduction, in the context of relatively low monthly median seizure frequencies at baseline (SSF 2.0–2.4). These results provide further support for the use of ESL as an earlier or later adjunctive therapy to LEV or LTG.

Effects of anterior thalamic nucleus DBS on interictal heart rate variability in patients with refractory epilepsy

ObjectiveHeart rate variability (HRV) changes were investigated by several studies after resective epilepsy surgery/vagus nerve stimulation. We examined anterior thalamic nucleus (ANT)-deep brain stimulation (DBS) effects on HRV parameters. MethodsWe retrospectively analyzed 30 drug-resistant epilepsy patients’ medical record data and collected electrocardiographic epochs recorded during video- electroencephalography monitoring sessions while awake and during N1- or N2-stage sleep pre-DBS implantation surgery, post-surgery but pre-stimulation, and after stimulation began. ResultsThe mean square root of the mean squared differences between successive RR intervals and RR interval standard deviation values differed significantly (p < 0.05) among time-points, showing increased HRV post-surgery. High (0.15–0.4 Hz) and very low frequency (<0.04 Hz) increased, while low frequency (0.04–0.15 Hz) and the LF/HF ratio while awake decreased, suggesting improved autonomic regulation post-surgery. Change of effect size was larger in patients where both activated contacts were located in the ANT than in those where only one or none of the contacts hit the ANT. ConclusionsIn patients with drug-resistant epilepsy, ANT-DBS might positively influence autonomic regulation, as reflected by increased HRV. SignificanceTo gain a more comprehensive outcome estimation after DBS implantation, we suggest including HRV measures with seizure count in the post-surgery follow-up protocol.