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Objective: To evaluate the incidence and prevalence of drug-resistant epilepsy (DRE) as well as its predictors and correlates, we conducted a systematic review and meta-analysis of observational studies., Methods: Our protocol was registered with PROSPERO, and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses and Meta-analysis of Observational Studies in Epidemiology reporting standards were followed. We searched MEDLINE, Embase, and Web of Science. We used a double arcsine transformation and random-effects models to perform our meta-analyses. We performed random-effects meta-regressions using study-level data., Results: Our search strategy identified 10,794 abstracts. Of these, 103 articles met our eligibility criteria. There was high interstudy heterogeneity and risk of bias. The cumulative incidence of DRE was 25.0% (95% confidence interval [CI]: 16.8-34.3) in child studies but 14.6% (95% CI: 8.8-21.6) in adult/mixed age studies. The prevalence of DRE was 13.7% (95% CI: 9.2-19.0) in population/community-based populations but 36.3% (95% CI: 30.4-42.4) in clinic-based cohorts. Meta-regression confirmed that the prevalence of DRE was higher in clinic-based populations and in focal epilepsy. Multiple predictors and correlates of DRE were identified. The most reported of these were having a neurologic deficit, an abnormal EEG, and symptomatic epilepsy. The most reported genetic predictors of DRE were polymorphisms of the ABCB1 gene., Conclusions: Our observations provide a basis for estimating the incidence and prevalence of DRE, which vary between populations. We identified numerous putative DRE predictors and correlates. These findings are important to plan epilepsy services, including epilepsy surgery, a crucial treatment option for people with disabling seizures and DRE., (© 2021 American Academy of Neurology.)

Purpose of Review: Caffeine is the most widely consumed central nervous stimulant. For people with epilepsy, it is often unclear whether drinking coffee carries a risk of triggering seizures., Recent Findings: The relationship between caffeine, seizures, epilepsy, and anti-seizure drugs is not fully understood. Clinical studies are scarce. In animal models, caffeine can increase seizure susceptibility but can also protect from seizures. Effects seem dose-dependent and are influenced by the duration of intake and the developmental stage at which caffeine exposure started. Caffeine reduces the efficacy of several anti-seizure medications, especially topiramate. It is unclear how these findings, mainly from animal studies, can be translated to the clinical condition. At present, there is no evidence to advise people with epilepsy against the use or overuse of caffeine. Until clinical studies suggest otherwise, caffeine intake should be considered as a factor in achieving and maintaining seizure control in epilepsy.

Objective: We assessed motor phenomena in syncope and convulsive seizures to aid differential diagnosis and understand the pathophysiologic correlates., Methods: We studied video-EEG recordings of tilt-induced syncope and convulsive seizures in participants aged 15 years and older. Syncope was defined as (1) loss of consciousness (video-assessed), (2) circulatory changes (accelerating blood pressure decrease with or without bradycardia/asystole), and (3) EEG changes ("slow" or "slow-flat-slow"). We assessed myoclonic jerks and tonic postures of the arms and noted time of occurrence, laterality, synchrony, and rhythmicity (mean consecutive differences of interclonic intervals)., Results: Video-EEG records of 65 syncope cases and 50 convulsive seizures were included. In syncope, postures occurred in 42 cases (65%) and jerks in 33 (51%). Fewer jerks occurred in syncope (median 2, range 1-19) compared to convulsive seizures (median 48, range 20-191; p < 0.001). Jerks were more rhythmic in seizures compared to syncope ( p < 0.001). Atonia was seen in all syncope cases, while this was not observed in any seizure. Jerks predominantly occurred during the slow and postures during the flat EEG phase., Conclusions: Jerks and tonic postures were common in syncope, but semiology differed from convulsive seizures. The lack of overlap in the number of jerks suggests that less than 10 indicates syncope and more than 20 a convulsive seizure: the "10/20 rule." Loss of tone strongly favors syncope. The EEG correlates imply that jerks in syncope are likely of cortical origin, whereas tonic postures may result from brainstem disinhibition., (© 2018 American Academy of Neurology.)

Purpose: Caffeine is the most commonly used central nervous system (CNS) stimulant. The relationship between caffeine, seizures, epilepsy, and antiepileptic drugs (AEDs) is complex and not fully understood. Case reports suggest that caffeine triggers seizures in susceptible people. Our systematic review reports on the relationship between caffeine, seizures, and drugs in animal and human studies. Quantitative analyses were also done on animal studies regarding the effects of caffeine on AEDs., Methods: PubMed was searched for studies assessing the effects of caffeine on seizure susceptibility, epilepsy, and drug interactions in people and in animal models. To quantify the interaction between AEDs and caffeine, the data of six animal studies were pooled and analyzed using a general linear model univariate analysis or One-way Analysis of Variance (ANOVA)., Results: In total, 442 items were identified from which we included 105 studies. Caffeine can increase seizure susceptibility and protect from seizures, depending on the dose, administration type (chronic or acute), and the developmental stage at which caffeine exposure started. In animal studies, caffeine decreased the antiepileptic potency of some drugs; this effect was strongest in topiramate., Conclusion: Preclinical studies suggest that caffeine increases seizure susceptibility. In some cases, chronic use of caffeine may protect against seizures. Caffeine lowers the efficacy of several drugs, especially topiramate. It is unclear how these findings in models can be translated to the clinical condition. Until clinical studies suggest otherwise, caffeine intake should be considered as a factor in achieving and maintaining seizure control in epilepsy., (Copyright © 2017 Elsevier Inc. All rights reserved.)

It is not fully understood how seizures terminate and why some seizures are followed by a period of complete brain activity suppression, postictal generalized EEG suppression. This is clinically relevant as there is a potential association between postictal generalized EEG suppression, cardiorespiratory arrest and sudden death following a seizure. We combined human encephalographic seizure data with data of a computational model of seizures to elucidate the neuronal network dynamics underlying seizure termination and the postictal generalized EEG suppression state. A multi-unit computational neural mass model of epileptic seizure termination and postictal recovery was developed. The model provided three predictions that were validated in EEG recordings of 48 convulsive seizures from 48 subjects with refractory focal epilepsy (20 females, age range 15-61 years). The duration of ictal and postictal generalized EEG suppression periods in human EEG followed a gamma probability distribution indicative of a deterministic process (shape parameter 2.6 and 1.5, respectively) as predicted by the model. In the model and in humans, the time between two clonic bursts increased exponentially from the start of the clonic phase of the seizure. The terminal interclonic interval, calculated using the projected terminal value of the log-linear fit of the clonic frequency decrease was correlated with the presence and duration of postictal suppression. The projected terminal interclonic interval explained 41% of the variation in postictal generalized EEG suppression duration (P < 0.02). Conversely, postictal generalized EEG suppression duration explained 34% of the variation in the last interclonic interval duration. Our findings suggest that postictal generalized EEG suppression is a separate brain state and that seizure termination is a plastic and autonomous process, reflected in increased duration of interclonic intervals that determine the duration of postictal generalized EEG suppression., (© The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Automated monitoring and alerting for adverse events in people with epilepsy can provide higher security and quality of life for those who suffer from this debilitating condition. Recently, we found a relation between clonic slowing at the end of a convulsive seizure (CS) and the occurrence and duration of a subsequent period of postictal generalized EEG suppression (PGES). Prolonged periods of PGES can be predicted by the amount of progressive increase of interclonic intervals (ICIs) during the seizure. The purpose of the present study is to develop an automated, remote video sensing-based algorithm for real-time detection of significant clonic slowing that can be used to alert for PGES. This may help preventing sudden unexpected death in epilepsy (SUDEP). The technique is based on our previously published optical flow video sequence processing paradigm that was applied for automated detection of major motor seizures. Here, we introduce an integral Radon-like transformation on the time-frequency wavelet spectrum to detect log-linear frequency changes during the seizure. We validate the automated detection and quantification of the ICI increase by comparison to the results from manually processed electroencephalography (EEG) traces as "gold standard". We studied 48 cases of convulsive seizures for which synchronized EEG-video recordings were available. In most cases, the spectral ridges obtained from Gabor-wavelet transformations of the optical flow group velocities were in close proximity to the ICI traces detected manually from EEG data during the seizure. The quantification of the slowing-down effect measured by the dominant angle in the Radon transformed spectrum was significantly correlated with the exponential ICI increase factors obtained from manual detection. If this effect is validated as a reliable precursor of PGES periods that lead to or increase the probability of SUDEP, the proposed method would provide an efficient alerting device.