EEG in focal and generalized epilepsies: Pearls and perils.

Correctly diagnosing and classifying seizures and epilepsies is vital to ensure a tailored approach to patients with epilepsy. The ILAE seizure classification consists of two main groups: focal and generalized. Establishing if a seizure is focal or generalized is essential to classify the epilepsy type and the epilepsy syndrome, providing more personalized treatment and counseling about prognosis. EEG is one of the most essential tools for this classification process and further localization of the epileptogenic focus. However, some EEG findings are misleading and may postpone the correct diagnosis and proper treatment. Knowing the most common EEG pitfalls in focal and generalized epilepsies is valuable for clinical practice, avoiding misinterpretations. Some atypical features can be challenging in focal epilepsies, such as secondary bilateral synchrony, focal epileptiform activity induced by hyperventilation and photic stimulation, and non-focal slowing. On the other hand, more than 60 % of persons with idiopathic generalized epilepsies have at least one type of atypical abnormality. In this manuscript, we describe and illustrate some of the most common EEG findings that can make even experienced epileptologists question not only where the epileptogenic focus is but also if the patient has focal or generalized epilepsy. This review summarizes the perils and provide some pearls to assist EEG readers.

Incidence and Types of Cardiac Arrhythmias in the Peri-Ictal Period in Patients Having a Generalized Convulsive Seizure.

BACKGROUND AND OBJECTIVES: Generalized convulsive seizures (GCSs) are the main risk factor of sudden unexpected death in epilepsy (SUDEP), which is likely due to peri-ictal cardiorespiratory dysfunction. The incidence of GCS-induced cardiac arrhythmias, their relationship to seizure severity markers, and their role in SUDEP physiopathology are unknown. The aim of this study was to analyze the incidence of seizure-induced cardiac arrhythmias, their association with electroclinical features and seizure severity biomarkers, as well as their specific occurrences in SUDEP cases. METHODS: This is an observational, prospective, multicenter study of patients with epilepsy aged 18 years and older with recorded GCS during inpatient video-EEG monitoring for epilepsy evaluation. Exclusion criteria were status epilepticus and an obscured video recording. We analyzed semiologic and cardiorespiratory features through video-EEG (VEEG), electrocardiogram, thoracoabdominal bands, and pulse oximetry. We investigated the presence of bradycardia, asystole, supraventricular tachyarrhythmias (SVTs), premature atrial beats, premature ventricular beats, nonsustained ventricular tachycardia (NSVT), atrial fibrillation (Afib), ventricular fibrillation (VF), atrioventricular block (AVB), exaggerated sinus arrhythmia (ESA), and exaggerated sinus arrhythmia with bradycardia (ESAWB). A board-certified cardiac electrophysiologist diagnosed and classified the arrhythmia types. Bradycardia, asystole, SVT, NSVT, Afib, VF, AVB, and ESAWB were classified as arrhythmias of interest because these were of SUDEP pathophysiology value. The main outcome was the occurrence of seizure-induced arrhythmias of interest during inpatient VEEG monitoring. Moreover, yearly follow-up was conducted to identify SUDEP cases. Binary logistic generalized estimating equations were used to determine clinical-demographic and peri-ictal variables that were predictive of the presence of seizure-induced arrhythmias of interest. The z-score test for 2 population proportions was used to test whether the proportion of seizures and patients with postconvulsive ESAWB or bradycardia differed between SUDEP cases and survivors. RESULTS: This study includes data from 249 patients (mean age 37.2 ± 23.5 years, 55% female) who had 455 seizures. The most common arrhythmia was ESA, with an incidence of 137 of 382 seizures (35.9%) (106/224 patients [47.3%]). There were 50 of 352 seizure-induced arrhythmias of interest (14.2%) in 41 of 204 patients (20.1%). ESAWB was the commonest in 22 of 394 seizures (5.6%) (18/225 patients [8%]), followed by SVT in 18 of 397 seizures (4.5%) (17/228 patients [7.5%]). During follow-up (48.36 ± 31.34 months), 8 SUDEPs occurred. Seizure-induced bradycardia (3.8% vs 12.5%, z = -16.66, p < 0.01) and ESAWB (6.6% vs 25%; z = -3.03, p < 0.01) were over-represented in patients who later died of SUDEP. There was no association between arrhythmias of interest and seizure severity biomarkers (p > 0.05). DISCUSSION: Markers of seizure severity are not related to seizure-induced arrhythmias of interest, suggesting that other factors such as occult cardiac abnormalities may be relevant for their occurrence. Seizure-induced ESAWB and bradycardia were more frequent in SUDEP cases, although this observation was based on a very limited number of SUDEP patients. Further case-control studies are needed to evaluate the yield of arrhythmias of interest along with respiratory changes as potential SUDEP biomarkers.

Social cognition in Idiopathic generalised epilepsies.

Social cognition is a set of mental skills necessary to create satisfactory interpersonal relationships and feel a sense of belonging to a social group. Its deficits significantly reduce the quality of life in people with epilepsy. Studies on social cognition and its impairments focus predominantly on people with focal epilepsies. Idiopathic generalised epilepsies are a group of diseases that share similar clinical, prognostic and electrographic characteristics. Despite their typically normal intelligence, people with Idiopathic generalised epilepsies can suffer from learning disabilities and executive dysfunctions. Current studies also suggest social cognition impairments, but their results are inconsistent. This review offers the latest knowledge of social cognition in adults with Idiopathic generalised epilepsies. In addition, we provide an overview of the most frequently used assessment methods. We explain possible reasons for different outcomes and discuss future research perspectives.

Déjà vu in idiopathic generalized epilepsy: A systematic review.

INTRODUCTION: Déjà vu (DV), a French term meaning "already seen," refers to inappropriate sensation of familiarity in the present moment, as if it had been experienced before without a specific recollection of when or where. Traditionally, DV has been closely associated with focal seizures originating from the medial temporal lobe. However, there are occasional reports of DV occurring in idiopathic generalized epilepsies (IGEs). The objective of our study was to assess the presence and frequency of DV in individuals with IGE. METHODS: We used the Preferred Reporting Items for Systematic Review and Meta-Analysis for protocols (PRISMA-P) and searched PubMed and Embase from January 2000 to July 2022. RESULTS: 5 studies were included with a total of 1177 IGE and 1026 with temporal lobe epilepsy (TLE) patients. The frequency of DV in IGE ranged from 0 to 11 %, and the average was 3 %, compared to 19.6 % in TLE. Broadly, 40 % of patients with IGE reported some type of aura. EEG correlation of DV in IGE was not appropriately evaluated in the studies. CONCLUSION: Clinicians should be aware that individuals with IGE may experience DV and other types of auras. Recognizing these auras is crucial in order to avoid misdiagnosing IGE as focal epilepsy. This is important to prevent unnecessary investigations and incorrect treatment decisions.

Predictors of Seizure Recurrence in Women With Idiopathic Generalized Epilepsy Who Switch From Valproate to Another Medication.

BACKGROUND AND OBJECTIVES: To investigate the predictors of seizure recurrence in women of childbearing age with idiopathic generalized epilepsy (IGE) who switched from valproate (VPA) to alternative antiseizure medications (ASMs) and compare the effectiveness of levetiracetam (LEV) and lamotrigine (LTG) as VPA alternatives after switch. METHODS: This multicenter retrospective study included women of childbearing age diagnosed with IGE from 16 epilepsy centers. Study outcomes included worsening or recurrence of generalized tonic-clonic seizure (GTCS) at 12 months and 24 months after the switch from VPA to an alternative ASM. The comparative effectiveness of LEV and LTG as alternative ASM following VPA discontinuation was assessed through inverse probability treatment-weighted (IPTW) Cox regression analysis. RESULTS: We included 426 women with IGE, with a median (interquartile range) age at VPA switch of 24 (19-30) years and a median VPA dosage of 750 (500-1,000) mg/d. The most common reason for VPA switch was teratogenicity concern in 249 women (58.6%), and the most common ASM used in place of VPA was LEV in 197 (46.2%) cases, followed by LTG in 140 (32.9%). GTCS worsening/recurrence occurred in 105 (24.6%) and 139 (32.6%) women at 12 and 24 months, respectively. Catamenial worsening of seizures, higher VPA dosage during switch, multiple seizure types, and shorter duration of GTCS freedom before switch were independent predictors of GTCS recurrence or worsening at 12 months according to mixed multivariable logistic regression analysis. After internal-external validation through 16 independent cohorts, the model showed an area under the curve of 0.71 (95% CI 0.64-0.77). In the subgroup of 337 women who switched to LEV or LTG, IPTW Cox regression analysis showed that LEV was associated with a reduced risk of GTCS worsening or recurrence compared with LTG (adjusted hazard ratio 0.59, 95% CI 0.40-0.87, p = 0.008) during the 24-month follow-up. DISCUSSION: Our findings can have practical implications for optimizing counselling and treatment choices in women of childbearing age with IGE and may help clinicians in making informed treatment decisions in this special population of patients. CLASSIFICATION OF EVIDENCE: This study provides Class III evidence that for women with IGE switching from VPA, LEV was associated with a reduced risk of GTCS worsening or recurrence compared with LTG.

Clustered de novo start-loss variants in GLUL result in a developmental and epileptic encephalopathy via stabilization of glutamine synthetase.

Glutamine synthetase (GS), encoded by GLUL, catalyzes the conversion of glutamate to glutamine. GS is pivotal for the generation of the neurotransmitters glutamate and gamma-aminobutyric acid and is the primary mechanism of ammonia detoxification in the brain. GS levels are regulated post-translationally by an N-terminal degron that enables the ubiquitin-mediated degradation of GS in a glutamine-induced manner. GS deficiency in humans is known to lead to neurological defects and death in infancy, yet how dysregulation of the degron-mediated control of GS levels might affect neurodevelopment is unknown. We ascertained nine individuals with severe developmental delay, seizures, and white matter abnormalities but normal plasma and cerebrospinal fluid biochemistry with de novo variants in GLUL. Seven out of nine were start-loss variants and two out of nine disrupted 5' UTR splicing resulting in splice exclusion of the initiation codon. Using transfection-based expression systems and mass spectrometry, these variants were shown to lead to translation initiation of GS from methionine 18, downstream of the N-terminal degron motif, resulting in a protein that is stable and enzymatically competent but insensitive to negative feedback by glutamine. Analysis of human single-cell transcriptomes demonstrated that GLUL is widely expressed in neuro- and glial-progenitor cells and mature astrocytes but not in post-mitotic neurons. One individual with a start-loss GLUL variant demonstrated periventricular nodular heterotopia, a neuronal migration disorder, yet overexpression of stabilized GS in mice using in utero electroporation demonstrated no migratory deficits. These findings underline the importance of tight regulation of glutamine metabolism during neurodevelopment in humans.

Oligoepilepsy and lifelong seizure susceptibility in epilepsy with generalized tonic-clonic seizures alone: Experience at an adult tertiary center.

OBJECTIVE: Epilepsy with generalized tonic-clonic seizures alone (GTCA) is the least studied syndrome within the idiopathic generalized epilepsy (IGE) spectrum. We characterize a large cohort of adult patients with GTCA to understand natural history and drug responsiveness. METHODS: In this retrospective single-center study using our epilepsy electronic record, we evaluated clinical characteristics, seizure outcomes, anti-seizure medication (ASM) response including seizure recurrence after ASM withdrawal, and sex differences in a cohort of GTCA patients aged ≥17 years. RESULTS: Within a cohort of 434 IGE patients, 87 patients (20 %) with GTCA were included. The mean age was 34.9 years (range 17-73 years). Forty-six patients (52.8 %) were females. Seventy-two patients (82.8 %) were seizure-free and 15 (17.2 %) had active epilepsy over the previous 12 months. Thirty-four patients (39.1 %) had ≤5 lifetime seizures, aligning with a prior definition of 'oligoepilepsy'. Sixty-five patients (74.7 %) were treated with monotherapy, 19 (21.8 %) were treated with polytherapy, and three were not taking any ASM. Levetiracetam (37.9 %) was the most commonly prescribed ASM, followed by lamotrigine (32.1 %) and valproate (31 %). Seventeen patients (19.5 %) attempted to withdraw their ASM. The rate of seizure recurrence after ASM withdrawal was 88.2 % (15/17), including two patients who relapsed more than 20 years after ASM discontinuation. Females had more seizures in their lifetime and had trialed more ASM compared to males. SIGNIFICANCE: GTCA has a relatively good prognosis, with most patients becoming seizure-free on monotherapy. The high rate of seizure recurrence after ASM withdrawal supports lifetime seizure susceptibility. We found potential sex differences in seizure outcomes and ASM response, although further research is needed to validate this finding.

Idiopathic generalized epilepsies in the epilepsy monitoring unit: Systematic quantification of focal EEG and semiological signs.

OBJECTIVE: Focal seizure symptoms (FSS) and focal interictal epileptiform discharges (IEDs) are common in patients with idiopathic generalized epilepsies (IGEs), but dedicated studies systematically quantifying them both are lacking. We used automatic IED detection and localization algorithms and correlated these EEG findings with clinical FSS for the first time in IGE patients. METHODS: 32 patients with IGEs undergoing long-term video EEG monitoring were systematically analyzed regarding focal vs. generalized IEDs using automatic IED detection and localization algorithms. Quantitative EEG findings were correlated with FSS. RESULTS: We observed FSS in 75% of patients, without significant differences between IGE subgroups. Mostly varying/shifting lateralizations of FSS across successive recorded seizures were seen. We detected a total of 81,949 IEDs, whereof 19,513 IEDs were focal (23.8%). Focal IEDs occurred in all patients (median 13% focal IEDs per patient, range 1.1 - 51.1%). Focal IED lateralization and localization predominance had no significant effect on FSS. CONCLUSIONS: All included patients with IGE showed focal IEDs and three-quarter had focal seizure symptoms irrespective of the specific IGE subgroup. Focal IED localization had no significant effect on lateralization and localization of FSS. SIGNIFICANCE: Our findings may facilitate diagnostic and treatment decisions in patients with suspected IGE and focal signs.

Attention-based deep convolutional neural network for classification of generalized and focal epileptic seizures.

Epilepsy affects over 50 million people globally. Electroencephalography is critical for epilepsy diagnosis, but manual seizure classification is time-consuming and requires extensive expertise. This paper presents an automated multi-class seizure classification model using EEG signals from the Temple University Hospital Seizure Corpus ver. 1.5.2. 11 features including time-based correlation, time-based eigenvalues, power spectral density, frequency-based correlation, frequency-based eigenvalues, sample entropy, spectral entropy, logarithmic sum, standard deviation, absolute mean, and ratio of Daubechies D4 wavelet transformed coefficients were extracted from 10-second sliding windows across channels. The model combines multi-head self-attention mechanism with a deep convolutional neural network (CNN) to classify seven subtypes of generalized and focal epileptic seizures. The model achieved 0.921 weighted accuracy and 0.902 weighted F1 score in classifying focal onset non-motor, generalized onset non-motor, simple partial, complex partial, absence, tonic, and tonic-clonic seizures. In comparison, a CNN model without multi-head attention achieved 0.767 weighted accuracy. Ablation studies were conducted to validate the importance of transformer encoders and attention. The promising classification results demonstrate the potential of deep learning for handling EEG complexity and improving epilepsy diagnosis. This seizure classification model could enable timely interventions when translated into clinical practice.

Construction and validation of an algorithm to separate focal and generalised epilepsy using clinical variables: A comparison of machine learning approaches.

PURPOSE: Epilepsy type, whether focal or generalised, is important in deciding anti-seizure medication (ASM). In resource-limited settings, investigations are usually not available, so a clinical separation is required. We used a naïve Bayes approach to devise an algorithm to do this, and compared its accuracy with algorithms devised by five other machine learning methods. METHODS: We used data on 28 clinical variables from 503 patients attending an epilepsy clinic in India with defined epilepsy type, as determined by an epileptologist with access to clinical, imaging, and EEG data. We adopted a machine learning approach to select the most relevant variables based on mutual information, to train the model on part of the data, and then to evaluate it on the remaining data (testing set). We used a naïve Bayes approach and compared the results in the testing set with those obtained by several other machine learning algorithms by measuring sensitivity, specificity, accuracy, area under the curve, and Cohen's kappa. RESULTS: The six machine learning methods produced broadly similar results. The best naïve Bayes algorithm contained eleven variables, and its accuracy was 92.2% in determining epilepsy type (sensitivity 92.0%, specificity 92.7%). An algorithm incorporating the best eight of these variables was only slightly less accurate - 91.0% (sensitivity 89.6%, and specificity 95.1%) - and easier for clinicians to use. CONCLUSION: A clinical algorithm with eight variables is effective and accurate at separating focal from generalised epilepsy. It should be useful in resource-limited settings, by epilepsy-inexperienced doctors, to help determine epilepsy type and therefore optimal ASMs for individual patients, without the need for EEG or neuroimaging.

Idiopathic generalized epilepsy in a family with SCN4A-related myotonia.

OBJECTIVES: Myotonia is a clinical sign typical of a group of skeletal muscle channelopathies, the non-dystrophic myotonias. These disorders are electrophysiologically characterized by altered membrane excitability, due to specific genetic variants in known causative genes (CLCN1 and SCN4A). Juvenile Myoclonic Epilepsy (JME) is an epileptic syndrome identified as idiopathic generalized epilepsy, its genetics is complex and still unclarified. The co-occurrence of these two phenotypes is rare and the causes likely have a genetic background. In this study, we have genetically investigated an Italian family in which co-segregates myotonia, JME, or abnormal EEG without seizures was observed. METHODS: All six individuals of the family, 4 affected and 2 unaffected, were clinically evaluated; EMG and EEG examinations were performed. For genetic testing, Exome Sequencing was performed for the six family members and Sanger sequencing was used to confirm the candidate variant. RESULTS: Four family members, the mother and three siblings, were affected by myotonia. Moreover, EEG recordings revealed interictal generalized sharp-wave discharges in all affected individuals, and two siblings were affected by JME. All four affected members share the same identified variant, c.644 T > C, p.Ile215Thr, in SCN4A gene. Variants that could account for the epileptic phenotype alone, separately from the myotonic one, were not identified. SIGNIFICANCE: These results provide supporting evidence that both myotonic and epileptic phenotypes could share a common genetic background, due to variants in SCN4A gene. SCN4A pathogenic variants, already known to be causative of myotonia, likely increase the susceptibility to epilepsy in our family. PLAIN LANGUAGE SUMMARY: This study analyzed all members of an Italian family, in which the mother and three siblings had myotonia and epilepsy. Genetic analysis allowed to identify a variant in the SCN4A gene, which appears to be the cause of both clinical signs in this family.

Gene-gene interaction network analysis indicates CNTN2 is a candidate gene for idiopathic generalized epilepsy.

Twin and family studies have established the genetic contribution to idiopathic generalized epilepsy (IGE). The genetic architecture of IGE is generally complex and heterogeneous, and the majority of the genetic burden in IGE remains unsolved. We hypothesize that gene-gene interactions contribute to the complex inheritance of IGE. CNTN2 (OMIM* 615,400) variants have been identified in cases with familial adult myoclonic epilepsy and other epilepsies. To explore the gene-gene interaction network in IGE, we took the CNTN2 gene as an example and investigated its co-occurrent genetic variants in IGE cases. We performed whole-exome sequencing in 114 unrelated IGE cases and 296 healthy controls. Variants were qualified with sequencing quality, minor allele frequency, in silico prediction, genetic phenotype, and recurrent case numbers. The STRING_TOP25 gene interaction network analysis was introduced with the bait gene CNTN2 (denoted as A). The gene-gene interaction pair mode was presumed to be A + c, A + d, A + e, with a leading gene A, or A + B + f, A + B + g, A + B + h, with a double-gene A + B, or other combinations. We compared the number of gene interaction pairs between the case and control groups. We identified three pairs in the case group, CNTN2 + PTPN18, CNTN2 + CNTN1 + ANK2 + ANK3 + SNTG2, and CNTN2 + PTPRZ1, while we did not discover any pairs in the control group. The number of gene interaction pairs in the case group was much more than in the control group (p = 0.021). Taking together the genetic bioinformatics, reported epilepsy cases, and statistical evidence in the study, we supposed CNTN2 as a candidate pathogenic gene for IGE. The gene interaction network analysis might help screen candidate genes for IGE or other complex genetic disorders.

Feasibility study of microburst VNS therapy in drug-resistant focal and generalized epilepsy.

BACKGROUND: Vagus nerve stimulation (VNS) at low frequencies (≤30 Hz) has been an established treatment for drug-resistant epilepsy (DRE) for over 25 years. OBJECTIVE: To examine the initial safety and efficacy performance of an investigational, high-frequency (≥250 Hz) VNS paradigm herein called "Microburst VNS" (µVNS). µVNS consists of short, high-frequency bursts of electrical pulses believed to preferentially modulate certain brain regions. METHODS: Thirty-three (33) participants were enrolled into an exploratory feasibility study, 21 with focal-onset seizures and 12 with generalized-onset seizures. Participants were titrated to a personalized target dose of µVNS using an investigational fMRI protocol. Participants were then followed for up to 12 months, with visits every 3 months, and monitored for side-effects at all time points. This study was registered as NCT03446664 on February 27th, 2018. RESULTS: The device was well-tolerated. Reported adverse events were consistent with typical low frequency VNS outcomes and tended to diminish in severity over time, including dysphonia, cough, dyspnea, and implant site pain. After 12 months of µVNS, the mean seizure frequency reduction for all seizures was 61.3% (median reduction: 70.4%; 90% CI of median: 48.9%-83.3%). The 12-month responder rate (≥50% reduction) was 63.3% (90% CI: 46.7%-77.9%) and the super-responder rate (≥80% reduction) was 40% (90% CI: 25.0%-56.6%). Participants with focal-onset seizures appeared to benefit similarly to participants with generalized-onset seizures (mean reduction in seizures at 12 months: 62.6% focal [n = 19], versus 59.0% generalized [n = 11]). CONCLUSION: Overall, µVNS appears to be safe and potentially a promising therapeutic alternative to traditional VNS. It merits further investigation in randomized controlled trials which will help determine the impact of investigational variables and which patients are most suitable for this novel therapy.

Clearance for Driving in Genetic Generalized Epilepsy.

A key aspect of management of genetic generalized epilepsy involves assessing seizure control and deciding suitability for driving motor vehicles. We surveyed child neurologists and pediatric epileptologists on key questions that practitioners should ask prior to providing clearance for driving. The results showed a wide variability of practice among responders. We propose a likely appropriate process necessary to determine seizure control.

Drug-resistant generalized epilepsies: Revisiting the frontiers of idiopathic generalized epilepsies.

The 2017 International League Against Epilepsy (ILAE) classification suggested that the term "genetic generalized epilepsies" (GGEs) should be used for the broad group of epilepsies with so-called "generalized" seizure types and "generalized" spike-wave activity on EEG, based on a presumed genetic etiology. Within this framework, idiopathic generalized epilepsies (IGEs) are described as a subset of GGEs and include only four epileptic syndromes: childhood absence epilepsy, juvenile absence epilepsy, juvenile myoclonic epilepsy, and epilepsy with generalized tonic-clonic seizures alone. The recent 2022 ILAE definition of IGEs is based on the current state of knowledge and reflects a community consensus and is designed to evolve as knowledge advances. The term "frontiers of IGEs" refers to the actual limits of our understanding of these four syndromes. Indeed, among patients presenting with a syndrome compatible with the 2022 definition of IGEs, we still observe a significant proportion of patients presenting with specific clinical features, refractory seizures, or drug-resistant epilepsies. This leads to the discussion of the boundaries of IGEs and GGEs, or what is accepted within a clinical spectrum of a definite IGE. Here, we discuss several entities that have been described in the literature for many years and that may either constitute rare features of IGEs or a distinct differential diagnosis. Their recognition by clinicians may allow a more individualized approach and improve the management of patients presenting with such entities.

Outcomes and predictors of seizure recurrence in post-stroke epilepsy, a retrospective hospital-based study.

BACKGROUND: The occurrence of seizures following a stroke is a well-recognized complication associated with a significant increase in morbidity and mortality. Despite the numerous studies examining outcomes and risk factors related to post-stroke seizures (PSS), there remains a lack of clarity regarding the clinical characteristics, treatment, and PSS recurrence (PSSR) rates in patients experiencing their initial episode of PSS. PURPOSE: This study aimed to determine the risk factors for developing recurrent seizures after first PSS and their effects on functional outcomes and mortality. METHODS: All patients underwent an electroencephalography (EEG) and were monitored for a minimum of 24 months following the first PSS. The primary endpoint was the recurrence of seizures. Predictive factors for PSSR were determined by using the Cox-proportional hazards model, and the cumulative latency of recurrence at 90, 180, 360, and 720 days was estimated using Kaplan-Meier analysis. RESULTS: Seizure recurred in 36.8% (39/106). Significant association of PSSR was noted with female gender, use of older anti-seizure medications (ASMs) (p<0.001), EEG findings as focal slow wave activity (p<0.001), Ictal epileptiform abnormalities (p=0.015), status epilepticus (p=0.015), and with severe disability (p=0.008). However, multivariate cox-proportional hazards model showed significant association of female gender (HR=3.28; 95% CI: 1.42-7.58; p=0.006). Hazard ratio (HR) was increased with older ASMs use, focal aware seizure types, Ictal EAs, and periodic discharges on EEG; though, statistically significant. CONCLUSION: Factors such as the type of ASMs, EEG findings, and seizure type were significantly linked to PSSR. Female gender was the only independent predictor established. Additionally, significant functional decline was reported with recurrence.

Perampanel for the treatment of epilepsy with genetic aetiology: Real-world evidence from the PERMIT Extension study.

Genetic factors contribute to the aetiology of epilepsy in >50% of cases, and information on the use of antiseizure medications in people with specific aetiologies will help guide treatment decisions. The PERMIT Extension study pooled data from two real-world studies (PERMIT and PROVE) to investigate the effectiveness and safety/tolerability of perampanel (PER) when used to treat people with focal and generalised epilepsy in everyday clinical practice. This post-hoc analysis of PERMIT Extension explored the use of PER when used to treat individuals presumed to have epilepsy with a genetic aetiology. Assessments included retention rate (evaluated at 3, 6 and 12 months), effectiveness (responder and seizure freedom rates; evaluated at 3, 6, 12 months and the last visit [last observation carried forward) and tolerability (adverse events [AEs]). Of the 6822 people with epilepsy included in PERMIT Extension, 1012 were presumed to have a genetic aetiology. The most common genetic aetiologies were idiopathic generalised epilepsy (IGE; 58.2%), tuberous sclerosis (1.1%), Dravet syndrome (0.8%) and genetic epilepsy with febrile seizures plus (GEFS+; 0.5%). Retention rates at 3, 6 and 12 months in the total genetic aetiology population were 89.3%, 79.7% and 65.9%, respectively. In the total genetic aetiology population, responder rates at 12 months and the last visit were 74.8% and 68.3%, respectively, and corresponding seizure freedom rates were 48.9% and 46.5%, respectively. For the specific aetiology subgroups, responder rates at 12 months and the last visit were, respectively: 90.4% and 84.4% (IGE), 100% and 57.1% (tuberous sclerosis), 100% and 71.4% (Dravet syndrome), and 33.3% and 20.0% (GEFS+). Corresponding seizure freedom rates were, respectively: 73.1% and 64.6% (IGE), 33.3% and 22.2% (tuberous sclerosis), 20.0% and 28.6% (Dravet syndrome), and 0% and 0% (GEFS+). The incidence of AEs was 46.5% for the total genetic aetiology population, 48.8% for IGE, 27.3% for tuberous sclerosis, 62.5% for Dravet syndrome, and 20% for GEFS+. Tolerability findings were consistent with PER's known safety profile. PER was effective and generally well tolerated when used in individuals with a presumed genetic epilepsy aetiology in clinical practice. PER was effective across a wide range of genetic aetiologies.

Long-term prognosis of patients with photosensitive idiopathic generalized epilepsy.

OBJECTIVE: The long-term prognosis of photosensitive idiopathic generalized epilepsy (p-IGE) is generally considered favorable; however, its specific characteristics remain unclear. Our objective was to investigate the extended prognosis of p-IGE. METHODS: We analyzed the demographics, clinical, and electroencephalographic (EEG) data of consecutive patients who were diagnosed as having p-IGE, who were under follow-up for a minimum of 10 years and exhibited a photoparoxysmal response (PPR) in their EEGs. Prognostic data, epilepsy course types, and electroclinical variables were compared using appropriate statistical methods. RESULTS: The mean follow-up duration for 108 consecutive patients with p-IGE (74.1 % female) was 16.8 ± 6.5 years. The main syndromes within this cohort included juvenile myoclonic epilepsy (37 %), juvenile absence epilepsy (15.7 %), and epilepsy with eyelid myoclonia (EEM) (14.8 %). In terms of epilepsy course types, 27.8 % were in the relapse-remission group, and 13.9 % had never experienced remission. A low early remission rate (5.6 %) was evident, with the remaining half of the cohort categorized as the late remission group. Several significant poor prognostic factors were identified including self-induction, clinical symptoms accompanying PPR, asynchrony and focal findings in EEG discharges, a wide frequency range of PPR, the coexistence of three seizure types, the presence of accompanying focal seizure features, and a history of convulsive status epilepticus. CONCLUSIONS: Our long-term follow-up study, conducted within a substantial p-IGE group, unveiled newly proposed course types within this epilepsy category and highlighted significant poor prognostic factors related to photosensitivity. These findings furnish valuable insights for precise prognosis counselling and effective management strategies for patients with p-IGE.

Genetic causal association between physical activities and epilepsy: A Mendelian randomization study.

BACKGROUND: Despite numerous investigations into the relationship between physical activities (PA) and epilepsy, the causal effects remain contentious. Thus, we conducted a two-sample Mendelian randomization (MR) study to assess the potential causality. METHODS: Single-nucleotide polymorphisms (SNPs) predisposed to self-reported moderate and vigorous physical activities (MPA and VPA) and overall acceleration average (OAA) calculated through wrist-worn accelerometers were selected as exposure instrumental variables. Five subtypes of epilepsy, including all epilepsy, focal epilepsy and generalized epilepsy (with or without each other), focal epilepsy-strict definition and generalized epilepsy-strict definition (without overlap), were chosen as the outcomes. The MR study utilized the inverse-variance weighted (IVW) method as the primary analytical tool, supplemented by MR-Egger, simple mode, weighted mode, and weighted median methods. Cochran's Q and MR-Egger intercept tests were employed to assess heterogeneity and pleiotropy, while MR pleiotropy residual sum and outlier and leave-one-out analyses were conducted to identify potential SNP outliers. RESULTS: The study indicated that OAA was genetically linked to a decreased risk of both focal epilepsy (OR = 0.812, 95% CI: 0.687-0.960, p = .015, IVW) and focal epilepsy-strict definition (OR = 0.732, 95% CI: 0.596-0.900, p = .003, IVW; OR = 0.749, 95% CI: 0.573-0.979, p = .035, Weighted median). Genetically predicted MPA and VPA did not exhibit a causal association with all epilepsy or its subtypes (p>.05). No evidence of heterogeneity, pleiotropy, or SNP outlier was observed. CONCLUSIONS: Our findings suggested that PA with accelerometer monitoring may potentially reduce the risk of focal epilepsy, while there is no evidence supporting causal association between self-reported MPA or VPA and either focal or generalized epilepsy.