Focal EEG features and therapeutic response in patients with juvenile absence and myoclonic epilepsy

Drug-resistant juvenile myoclonic epilepsy: A literature review

The ILAE's Task Force on Nosology and Definitions revised in 2022 its definition of juvenile myoclonic epilepsy (JME), the most common idiopathic generalized epilepsy disorder, but this definition may well change again in the future. Although good drug response could almost be a diagnostic criterion for JME, drug resistance (DR) is observed in up to a third of patients. It is important to distinguish this from pseudoresistance, which is often linked to psychosocial problems or psychiatric comorbidities. After summarizing these aspects and the various definitions applied to JME, the present review lists the risk factors for DR-JME that have been identified in numerous studies and meta-analyses. The factors most often cited are absence seizures, young age at onset, and catamenial seizures. By contrast, photosensitivity seems to favor good treatment response, at least in female patients. Current hypotheses on DR mechanisms in JME are based on studies of either simple (e.g., cortical excitability) or more complex (e.g., anatomical and functional connectivity) neurophysiological markers, bearing in mind that JME is regarded as a neural network disease. This research has revealed correlations between the intensity of some markers and DR, and above all shed light on the role of these markers in associated neurocognitive and neuropsychiatric disorders in both patients and their siblings. Studies of neurotransmission have mainly pointed to impaired GABAergic inhibition. Genetic studies have generally been inconclusive. Increasing restrictions have been placed on the use of valproate, the standard antiseizure medication for this syndrome, owing to its teratogenic and developmental risks. Levetiracetam and lamotrigine are prescribed as alternatives, as is vagal nerve stimulation, and there are several other promising antiseizure drugs and neuromodulation methods. The development of better alternative treatments is continuing to take place alongside advances in our knowledge of JME, as we still have much to learn and understand.

Focal electroclinical features in generalized tonic-clonic seizures: Decision flowchart for a diagnostic challenge

OBJECTIVE

Bilateral tonic-clonic seizures with focal semiology or focal interictal electroencephalography (EEG) can occur in both focal and generalized epilepsy types, leading to diagnostic errors and inappropriate therapy. We investigated the prevalence and prognostic values of focal features in patients with idiopathic generalized epilepsy (IGE), and we propose a decision flowchart to distinguish between focal and generalized epilepsy in patients with bilateral tonic-clonic seizures and focal EEG or semiology.

METHODS

We retrospectively analyzed video-EEG recordings of 101 bilateral tonic-clonic seizures from 60 patients (18 with IGE, 42 with focal epilepsy). Diagnosis and therapeutic response were extracted after ≥1-year follow-up. The decision flowchart was based on previous observations and assessed concordance between interictal and ictal EEG.

RESULTS

Focal semiology in IGE was observed in 75% of seizures and 77.8% of patients, most often corresponding to forced head version (66.7%). In patients with multiple seizures, direction of head version was consistent across seizures. Focal interictal epileptiform discharges (IEDs) were observed in 61.1% of patients with IGE, whereas focal ictal EEG onset only occurred in 13% of seizures and 16.7% of patients. However, later during the seizures, a reproducible pattern of 7-Hz lateralized ictal rhythm was observed in 56% of seizures, associated with contralateral head version. We did not find correlation between presence of focal features and therapeutic response in IGE patients. Our decision flowchart distinguished between focal and generalized epilepsy in patients with bilateral tonic-clonic seizures and focal features with an accuracy of 96.6%.

SIGNIFICANCE

Focal semiology associated with bilateral tonic-clonic seizures and focal IEDs are common features in patients with IGE, but focal ictal EEG onset is rare. None of these focal findings appears to influence therapeutic response. By assessing the concordance between interictal and ictal EEG findings, one can accurately distinguish between focal and generalized epilepsies.

Changes in awake and sleep electroencephalography characteristics after 1-year treatment for childhood and juvenile absence epilepsy

PURPOSE

To compare electroencephalography (EEG) features of newly diagnosed drug-naive childhood absence epilepsy (CAE) and juvenile absence epilepsy (JAE) patients and analyze their response to anti-seizure medications (ASMs).

METHOD

EEG characteristics between CAE and JAE patients and responders and non-responders to ASM at baseline and 12 months were compared, and the changes from baseline were analysed.

RESULTS

A total of 62 patients (32 CAE and 30 JAE) were included. Discharges in baseline awake and sleep EEGs and interictal and polyspike discharges in baseline sleep EEGs were more frequent in JAE patients. Although the median discharge densities (discharge containing seconds per minute) were similar in baseline awake and sleep EEGs between the groups, the median was higher in the JAE group at 12 months and decreased significantly in both groups at 12 months compared to the baseline values. Responses to initial ASMs were 94% and 77% in the CAE and JAE groups, respectively. In initial sleep EEGs of non-responders with JAE, focal onset generalized spike and slow wave discharges (GSWDs) were more frequent, and the median ictal and interictal discharge densities were higher.

CONCLUSION

JAE patients had more frequent disorganized discharges at baseline in both awake and sleep EEGs and interictal and polyspike discharges in sleep EEGs than those of CAE patients. Improvement in EEG was more pronounced in CAE patients than in JAE patients. Focal-onset GSWDs and higher ictal and interictal discharge densities on baseline EEG were associated with a poor response to initial ASMs in JAE patients.

Variation in prognosis and treatment outcome in juvenile myoclonic epilepsy: a Biology of Juvenile Myoclonic Epilepsy Consortium proposal for a practical definition and stratified medicine classifications

Reliable definitions, classifications and prognostic models are the cornerstones of stratified medicine, but none of the current classifications systems in epilepsy address prognostic or outcome issues. Although heterogeneity is widely acknowledged within epilepsy syndromes, the significance of variation in electroclinical features, comorbidities and treatment response, as they relate to diagnostic and prognostic purposes, has not been explored. In this paper, we aim to provide an evidence-based definition of juvenile myoclonic epilepsy showing that with a predefined and limited set of mandatory features, variation in juvenile myoclonic epilepsy phenotype can be exploited for prognostic purposes. Our study is based on clinical data collected by the Biology of Juvenile Myoclonic Epilepsy Consortium augmented by literature data. We review prognosis research on mortality and seizure remission, predictors of antiseizure medication resistance and selected adverse drug events to valproate, levetiracetam and lamotrigine. Based on our analysis, a simplified set of diagnostic criteria for juvenile myoclonic epilepsy includes the following: (i) myoclonic jerks as mandatory seizure type; (ii) a circadian timing for myoclonia not mandatory for the diagnosis of juvenile myoclonic epilepsy; (iii) age of onset ranging from 6 to 40 years; (iv) generalized EEG abnormalities; and (v) intelligence conforming to population distribution. We find sufficient evidence to propose a predictive model of antiseizure medication resistance that emphasises (i) absence seizures as the strongest stratifying factor with regard to antiseizure medication resistance or seizure freedom for both sexes and (ii) sex as a major stratifying factor, revealing elevated odds of antiseizure medication resistance that correlates to self-report of catamenial and stress-related factors including sleep deprivation. In women, there are reduced odds of antiseizure medication resistance associated with EEG-measured or self-reported photosensitivity. In conclusion, by applying a simplified set of criteria to define phenotypic variations of juvenile myoclonic epilepsy, our paper proposes an evidence-based definition and prognostic stratification of juvenile myoclonic epilepsy. Further studies in existing data sets of individual patient data would be helpful to replicate our findings, and prospective studies in inception cohorts will contribute to validate them in real-world practice for juvenile myoclonic epilepsy management.

Juvenile Myoclonic Epilepsy: Seizure and Social Outcomes in Taiwan

Patients with juvenile myoclonic epilepsy (JME) may not achieve seizure freedom despite optimal treatment with antiseizure medications (ASMs). The aim of this study was to investigate the clinical and social features of patients with JME, and to determine the factors associated with outcomes. We retrospectively identified 49 patients with JME (25 females, mean age 27.6 ± 8.9 years) who were assessed at the Epilepsy Centre of Linkou Chang Gung Memorial Hospital in Taiwan. The patients were divided into two groups, those who were seizure-free and those with ongoing seizures according to their seizure outcome at the last follow-up for one year. Clinical features and social status were compared between these two groups. Twenty-four (49%) of the JME patients were seizure-free for at least one year, while 51% continued to experience seizures despite being treated with multiple ASMs. The presence of epileptiform discharges in the last electroencephalogram and seizures during sleep were significantly associated with worse seizure outcomes (p < 0.05). The patients who were seizure-free had a higher employment rate compared to those who continued to experience seizures (75% vs. 32%, p = 0.004). Despite receiving ASM treatment, a considerable proportion of the patients with JME continued to have seizures. Moreover, poor seizure control was associated with a lower employment rate, which may lead to negative socioeconomic consequences related to JME.

Dynamic flexibility and controllability of network communities in juvenile myoclonic epilepsy

Juvenile myoclonic epilepsy (JME) is the most common syndrome within the idiopathic generalized epilepsy spectrum, manifested by myoclonic and generalized tonic-clonic seizures and spike-and-wave discharges (SWDs) on electroencephalography (EEG). Currently, the pathophysiological concepts addressing SWD generation in JME are still incomplete. In this work, we characterize the temporal and spatial organization of functional networks and their dynamic properties as derived from high-density EEG (hdEEG) recordings and MRI in 40 JME patients (25.4 ± 7.6 years, 25 females). The adopted approach allows for the construction of a precise dynamic model of ictal transformation in JME at the cortical and deep brain nuclei source levels. We implement Louvain algorithm to attribute brain regions with similar topological properties to modules during separate time windows before and during SWD generation. Afterwards, we quantify how modular assignments evolve and steer through different states towards the ictal state by measuring characteristics of flexibility and controllability. We find antagonistic dynamics of flexibility and controllability within network modules as they evolve towards and undergo ictal transformation. Prior to SWD generation, we observe concomitantly increasing flexibility (F(1,39) = 25.3, corrected p < 0.001) and decreasing controllability (F(1,39) = 55.3, p < 0.001) within the fronto-parietal module in γ-band. On a step further, during interictal SWDs as compared to preceding time windows, we notice decreasing flexibility (F(1,39) = 11.9, p < 0.001) and increasing controllability (F(1,39) = 10.1, p < 0.001) within the fronto-temporal module in γ-band. During ictal SWDs as compared to prior time windows, we demonstrate significantly decreasing flexibility (F(1,14) = 31.6; p < 0.001) and increasing controllability (F(1,14) = 44.7, p < 0.001) within the basal ganglia module. Furthermore, we show that flexibility and controllability within the fronto-temporal module of the interictal SWDs relate to seizure frequency and cognitive performance in JME patients. Our results demonstrate that detection of network modules and quantification of their dynamic properties is relevant to track the generation of SWDs. The observed flexibility and controllability dynamics reflect the reorganization of de-/synchronized connections and the ability of evolving network modules to reach a seizure-free state, respectively. These findings may advance the elaboration of network-based biomarkers and more targeted therapeutic neuromodulatory approaches in JME.

EEG Markers of Treatment Resistance in Idiopathic Generalized Epilepsy: From Standard EEG Findings to Advanced Signal Analysis

Idiopathic generalized epilepsy (IGE) represents a common form of epilepsy in both adult and pediatric epilepsy units. Although IGE has been long considered a relatively benign epilepsy syndrome, a remarkable proportion of patients could be refractory to treatment. While some clinical prognostic factors have been largely validated among IGE patients, the impact of routine electroencephalography (EEG) findings in predicting drug resistance is still controversial and a growing number of authors highlighted the potential importance of capturing the sleep state in this setting. In addition, the development of advanced computational techniques to analyze EEG data has opened new opportunities in the identification of reliable and reproducible biomarkers of drug resistance in IGE patients. In this manuscript, we summarize the EEG findings associated with treatment resistance in IGE by reviewing the results of studies considering standard EEGs, 24-h EEG recordings, and resting-state protocols. We discuss the role of 24-h EEG recordings in assessing seizure recurrence in light of the potential prognostic relevance of generalized fast discharges occurring during sleep. In addition, we highlight new and promising biomarkers as identified by advanced EEG analysis, including hypothesis-driven functional connectivity measures of background activity and data-driven quantitative findings revealed by machine learning approaches. Finally, we thoroughly discuss the methodological limitations observed in existing studies and briefly outline future directions to identify reliable and replicable EEG biomarkers in IGE patients.

Triphasic Waves Are Generated by Widespread Bilateral Cortical Networks

PURPOSE

Triphasic waves (TWs) have been observed in the EEG recorded in patients with various types of encephalopathy, yet their genesis and significance is still debated. The aim of this study was to elucidate the localization of the cortical generators of TWs using EEG source imaging.

METHODS

In 20 consecutive patients who had encephalopathy with TWs, EEG source imaging of the first negative and the positive phases of the TW was performed. Three different approaches were used: equivalent current dipoles, a distributed source model, and a recently described spatial filtration method for visualizing EEG in source space.

RESULTS

Equivalent current dipole models failed to provide valid solutions. The distributed source model and the spatial filtration method suggested that TWs were generated by large, bilateral cortical networks, invariably involving the anterior frontal and the temporo-polar areas.

CONCLUSIONS

Source imaging localized TWs to anterior frontal and temporo-frontal structures. Involvement of these regions is consistent with the typical pathophysiological changes of altered consciousness and cognitive changes observed in patients with TW encephalopathy.

Identifying juvenile myoclonic epilepsy via diffusion tensor imaging using machine learning analysis

The aim of this study was to evaluate the feasibility of using a machine learning approach based on diffusion tensor imaging (DTI) to identify patients with juvenile myoclonic epilepsy. We analyzed the usefulness of combining conventional DTI measures and structural connectomic profiles. This retrospective study was conducted at a tertiary hospital. We enrolled 55 patients with juvenile myoclonic epilepsy. All of the subjects underwent DTI from January 2017 to March 2020. We also enrolled 58 healthy subjects as a normal control group. We extracted conventional DTI measures and structural connectomic DTI profiles. We employed the support vector machines (SVM) algorithm to classify patients with juvenile myoclonic epilepsy and healthy subjects based on the conventional DTI measures and structural connectomic profiles. The SVM classifier based on conventional DTI measures had an accuracy of 68.1% and an area under the curve (AUC) of 0.682. Another SVM classifier based on the structural connectomic profiles demonstrated an accuracy of 72.7% and an AUC of 0.727. The SVM classifier based on combining the conventional DTI measures and structural connectomic profiles had an accuracy of 81.8% and an AUC of 0.818. DTI using machine learning is useful for classifying patients with juvenile myoclonic epilepsy and healthy subjects. Combining both the conventional DTI measures and structural connectomic profiles results in a better classification performance than using conventional DTI measures or the structural connectomic profiles alone to identify juvenile myoclonic epilepsy.

Diagnostic and therapeutic approach to drug-resistant juvenile myoclonic epilepsy

INTRODUCTION

Juvenile myoclonic epilepsy (JME), also known as Janz syndrome, is a common form of generalized epilepsy of presumed genetic origin representing up to 10% of all epilepsy cases. Despite adequate anti-seizure medication (ASM) treatment, seizures persist in one-third of JME patients.

AREAS COVERED

A literature search was conducted using Pubmed search on the topics of drug-resistant JME.

EXPERT OPINION

About 30% of JME patients are drug-resistant. Valproate (VPA) is considered the first-choice drug. In women of childbearing potential, levetiracetam (LEV) should represent the first-choice treatment. Alternative monotherapy or add-on therapy should be considered in subjects with resistant seizures after the exclusion of pseudo-drug resistance. The choice of the add-on ASM depends on the predominant seizure type. In subjects with persistent bilateral tonic-clonic seizures, LEV or lamotrigine should be firstly considered. In patients with difficult-to-treat myoclonic seizures, clonazepam or LEV are recommended. In case of persistent absences, ethosuximide should be considered. With appropriate selection and safeguards in place, VPA should remain available as an option in women of childbearing potential whose seizures are resistant to other treatments.

Prognostic Value of Generalized Polyspike Trains and Prolonged Epileptiform EEG Runs

INTRODUCTION

A considerable proportion of patients with genetic/idiopathic generalized epilepsy (IGE) suffer from persistent seizures. In this study, it was questioned if generalized polyspike trains (GPT) or prolonged epileptiform EEG runs allow identification of difficult-to-treat patients in a first seizure clinic setting or after recurrent seizures.

METHODS

The first routine outpatient EEGs from untreated patients (later diagnosed with IGE) and routine EEGs from IGE patients with persistent seizures despite medical treatment were analyzed. Seizure outcome and clinical characteristics were retrospectively assessed based on the patients' records.

RESULTS

In routine EEGs recorded after first seizure in untreated patients (n = 79), the prevalence of GPT (n = 1; 1.3%) and prolonged epileptiform EEG runs (n = 13; 16.5%) was low. At follow-up, 24 patients (30.4%) were not seizure free, and 3 (3.8%) of them developed drug-resistant IGE. None of the interictal discharges studied was associated with long-term seizure outcome. Treated IGE patients with recurrent seizures (n = 69) had a similar prevalence of GPT (n = 3; 4.3%) and prolonged epileptiform EEG runs (n = 7; 10.1%). At follow-up, 42 patients (60.8%) suffered persistent seizures, and 18 (26%) were drug resistant. Generalized polyspike train and prolonged epileptiform EEG runs had a higher prevalence in patients with drug-resistant epilepsy (GPT: 11.1% vs. 2%; P = 0.1; prolonged epileptiform EEG runs: 27.8% vs. 3.9%; P = 0.004) and persistent seizures (GPT: 7.1% vs. 0%; P = 0.16; prolonged epileptiform EEG runs: 16.7% vs. 0%; P = 0.03) as compared with nonresistant patients.

CONCLUSIONS

Generalized polyspike train and prolonged epileptiform EEG runs were associated with persistent seizures and drug-resistant IGE, but the overall prevalence was low. In a first seizure clinic setting, the diagnostic value of these biomarkers was limited.

Do interictal EEG findings reflect cognitive function in juvenile myoclonic epilepsy?

PURPOSE

This study investigated the relationship between frontal lobe cognitive function and frontal focal electroencephalography (EEG) findings in patients with juvenile myoclonic epilepsy (JME).

METHODS

The study enrolled 60 patients diagnosed with JME and followed at the Epilepsy Outpatient Clinic of the University of Health Sciences, Bakırkoy Psychiatric Hospital, and 30 healthy volunteers. Demographic and clinical features were recorded. Frontal lobe cognitive functions were tested in both groups. Video-EEG recordings of patients with JME were evaluated. The presence and duration of generalized discharges, the presence and lateralization of focal findings, and the presence of generalized discharges during hyperventilation and photic stimulation were recorded during EEG. Cognitive function test results were compared between the two groups, and the relationship between the EEG findings and cognitive function was investigated.

RESULTS

The study included 35 (58.3%) female and 25 (41.6%) male patients and 17 (56.7%) female and 13 (43.3%) male healthy controls. The mean ages of the group with JME and controls were 28.3 ± 8.6 (16-50) and 31.3 ± 7.9 (17-45) years, respectively. Patients with JME performed more poorly on the frontal lobe cognitive tests than controls (p < 0.05). Patients whose generalized discharges were longer than 1 s performed more poorly on tests evaluating attention and made more perseverative errors (p < 0.05). There was no significant correlation between the presence of focal EEG findings and the scores on frontal lobe cognitive functions tests in the group with JME (p > 0.05).

CONCLUSION

Frontal lobe cognitive functions are affected in patients with JME. The cognitive effects were more pronounced in patients with prolonged generalized discharges on EEG.

Polygenic burden in focal and generalized epilepsies

Rare genetic variants can cause epilepsy, and genetic testing has been widely adopted for severe, paediatric-onset epilepsies. The phenotypic consequences of common genetic risk burden for epilepsies and their potential future clinical applications have not yet been determined. Using polygenic risk scores (PRS) from a European-ancestry genome-wide association study in generalized and focal epilepsy, we quantified common genetic burden in patients with generalized epilepsy (GE-PRS) or focal epilepsy (FE-PRS) from two independent non-Finnish European cohorts (Epi25 Consortium, n = 5705; Cleveland Clinic Epilepsy Center, n = 620; both compared to 20 435 controls). One Finnish-ancestry population isolate (Finnish-ancestry Epi25, n = 449; compared to 1559 controls), two European-ancestry biobanks (UK Biobank, n = 383 656; Vanderbilt biorepository, n = 49 494), and one Japanese-ancestry biobank (BioBank Japan, n = 168 680) were used for additional replications. Across 8386 patients with epilepsy and 622 212 population controls, we found and replicated significantly higher GE-PRS in patients with generalized epilepsy of European-ancestry compared to patients with focal epilepsy (Epi25: P = 1.64×10-15; Cleveland: P = 2.85×10-4; Finnish-ancestry Epi25: P = 1.80×10-4) or population controls (Epi25: P = 2.35×10-70; Cleveland: P = 1.43×10-7; Finnish-ancestry Epi25: P = 3.11×10-4; UK Biobank and Vanderbilt biorepository meta-analysis: P = 7.99×10-4). FE-PRS were significantly higher in patients with focal epilepsy compared to controls in the non-Finnish, non-biobank cohorts (Epi25: P = 5.74×10-19; Cleveland: P = 1.69×10-6). European ancestry-derived PRS did not predict generalized epilepsy or focal epilepsy in Japanese-ancestry individuals. Finally, we observed a significant 4.6-fold and a 4.5-fold enrichment of patients with generalized epilepsy compared to controls in the top 0.5% highest GE-PRS of the two non-Finnish European cohorts (Epi25: P = 2.60×10-15; Cleveland: P = 1.39×10-2). We conclude that common variant risk associated with epilepsy is significantly enriched in multiple cohorts of patients with epilepsy compared to controls-in particular for generalized epilepsy. As sample sizes and PRS accuracy continue to increase with further common variant discovery, PRS could complement established clinical biomarkers and augment genetic testing for patient classification, comorbidity research, and potentially targeted treatment.

Genome-wide mega-analysis identifies 16 loci and highlights diverse biological mechanisms in the common epilepsies

The epilepsies affect around 65 million people worldwide and have a substantial missing heritability component. We report a genome-wide mega-analysis involving 15,212 individuals with epilepsy and 29,677 controls, which reveals 16 genome-wide significant loci, of which 11 are novel. Using various prioritization criteria, we pinpoint the 21 most likely epilepsy genes at these loci, with the majority in genetic generalized epilepsies. These genes have diverse biological functions, including coding for ion-channel subunits, transcription factors and a vitamin-B6 metabolism enzyme. Converging evidence shows that the common variants associated with epilepsy play a role in epigenetic regulation of gene expression in the brain. The results show an enrichment for monogenic epilepsy genes as well as known targets of antiepileptic drugs. Using SNP-based heritability analyses we disentangle both the unique and overlapping genetic basis to seven different epilepsy subtypes. Together, these findings provide leads for epilepsy therapies based on underlying pathophysiology.

Epilepsies are common brain disorders and are classified based on clinical phenotyping, imaging and genetics. Here, the authors perform genome-wide association studies for 3 broad and 7 subtypes of epilepsy and identify 16 loci - 11 novel - that are further annotated by eQTL and partitioned heritability analyses.

Clinical and genetic study of Tunisian families with genetic generalized epilepsy: contribution of CACNA1H and MAST4 genes

Genetic generalized epilepsies (GGE) (childhood absence epilepsy (CAE), juvenile myoclonic epilepsy (JME) and epilepsy with generalized tonic-clonic seizures (GTCS)) are mainly determined by genetic factors. Since few mutations were identified in rare families with autosomal dominant GGE, a polygenic inheritance was suspected in most patients. Recent studies on large American or European cohorts of sporadic cases showed that susceptibility genes were numerous although their variants were rare, making their identification difficult. Here, we reported clinical and genetic characteristics of 30 Tunisian GGE families, including 71 GGE patients. The phenotype was close to that in sporadic cases. Nineteen pedigrees had a homogeneous type of GGE (JME-CAE-CGTS), and 11 combined these epileptic syndromes. Rare non-synonymous variants were selected in probands using a targeted panel of 30 candidate genes and their segregation was determined in families. Molecular studies incriminated different genes, mainly CACNA1H and MAST4. The segregation of at least two variants in different genes in some pedigrees was compatible with the hypothesis of an oligogenic inheritance, which was in accordance with the relatively low frequency of consanguineous probands. Since at least 2 susceptibility genes were likely shared by different populations, genetic factors involved in the majority of Tunisian GGE families remain to be discovered. Their identification should be easier in families with a homogeneous type of GGE, in which an intra-familial genetic homogeneity could be suspected.

Predictive factors of higher drug load for seizure freedom in idiopathic generalized epilepsy: Comparison between juvenile myoclonic epilepsy and other types

PURPOSE

Predictive factors of higher drug load for seizure freedom were investigated in idiopathic generalized epilepsy (IGE), focusing on the difference between juvenile myoclonic epilepsy (JME) and other types of IGE (non-JME IGE).

METHODS

Twelve patients with JME and 12 patients with non-JME IGE, who achieved seizure freedom for 1 year or longer with appropriate antiepileptic drugs (AEDs) after video electroencephalography monitoring, were reviewed retrospectively. The sum of prescribed daily dose/defined daily dose ratio of all prescribed AEDs at the final visit was defined as total AED load. Patients requiring total AED load >1 were classified into the higher AED load group. Clinical background and the presence of interictal focal epileptiform abnormalities (FEAs) were compared between the higher and lower AED load groups.

RESULTS

Higher AED load group of patients with JME had interictal FEAs and family history of epilepsy more frequently than the lower AED load group (p = 0.03 and p = 0.03). Similar comparison of patients with non-JME IGE showed no significant differences.

CONCLUSIONS

The presence of interictal FEAs and a family history of epilepsy are significantly associated variables for higher AED load for seizure freedom in patients with JME, but not in patients with non-JME IGE.

Generalized nonmotor (absence) seizures-What do absence, generalized, and nonmotor mean?

OBJECTIVE

Clinical absences are now classified as "generalized nonmotor (absence) seizures" by the International League Against Epilepsy (ILAE). The aim of this paper is to critically review the concept of absences and to put the accompanying focal and motor symptoms into the context of the emerging pathophysiological knowledge.

METHODS

For this narrative review we performed an extensive literature search on the term "absence," and analyzed the plethora of symptoms observed in clinical absences.

RESULTS

Arising from the localization and the involved cortical networks, motor symptoms may include bilateral mild eyelid fluttering and mild myoclonic jerks of extremities. These motor symptoms may also occur unilaterally, analogous to a focal motor seizure with Jacksonian march. Furthermore, electroencephalography (EEG) abnormalities may exhibit initial frontal focal spikes and consistent asymmetries. Electroclinical characteristics support the cortical focus theory of absence seizures. Simultaneous EEG/functional magnetic resonance imaging (fMRI) measurements document cortical deactivation and thalamic activation. Cortical deactivation is related to slow waves and disturbances of consciousness of varying degrees. Motor symptoms correspond to the spike component of the 3/s spike-and-wave-discharges. Thalamic activation can be interpreted as a response to overcome cortical deactivation. Furthermore, arousal reaction during drowsiness or sleep triggers spikes in an abnormally excitable cortex. An initial disturbance in arousal mechanisms ("dyshormia") might be responsible for the start of this abnormal sequence.

SIGNIFICANCE

The classification as "generalized nonfocal and nonmotor (absence) seizure" does not covey the complex semiology of a patient's clinical events.

Prolonged epileptiform EEG runs are associated with persistent seizures in juvenile myoclonic epilepsy

OBJECTIVE

In juvenile myoclonic epilepsy (JME), various EEG characteristics have been suggested as poor prognostic signs, but their significance is unclear. The aim of this study was to assess the influence of EEG variables on seizure and psychosocial outcome after a follow-up exceeding 20 years.

METHODS

396 EEG recordings were available for assessment in 40 patients (42 complete digital, 330 paper segments and 24 written reports only). Mean follow-up was 31 years (range 20-68). The number of EEGs per patient ranged from 2 to 23 (mean 9). Twenty-one patients were in remission for >5 years, whereas 19 had persistent seizures. Favorable psychosocial outcome was found in 14 of 37. EEGs were retrospectively categorized into four main groups; normal, slowing, epileptiform discharges or both slowing and epileptiform discharges, with further sub-classification. Hyperventilation and photoparoxysmal responses were also evaluated. Scoring of EEG findings was blinded to seizure and psychosocial outcome.

RESULTS

Significant associations were found between poor seizure control and prolonged ≥3s epileptiform runs, p=0.03 (8/19 vs 2/21), long ≥3s photoparoxysmal runs, p=0.04 (6/19 vs 1/21) and long ≥3s hyperventilation-induced epileptiform runs, p=0.02 (5/19 vs 0/21). The strongest association between persistent seizures and EEG was found when all epileptiform runs ≥3s were combined (p=0.007), with a positive predictive value equal to 79% and a negative predictive value equal to 69%. Fast (4-5c/s) spike-wave runs were also more frequent in patients with persistent seizures compared to the remission group, p=0.04 (9/19 vs 3/21). Other epileptiform elements occurred equally in the two prognostic groups. Psychosocial outcome was not influenced by EEG findings. Prolonged runs within 6 months from first recording did also predict clinical outcome, p=0.03; (8/19 vs 2/21), with a positive predictive value equal to 80% and a negative predictive value equal to 63%.

SIGNIFICANCE

Fast spike-wave runs and prolonged (≥3s) epileptiform runs, including photoparoxysmal and hyperventilation-induced runs were associated with persistent seizures in JME. Focal EEG abnormalities were not associated with clinical outcome. Conceivably, the duration of epileptiform bursts reflects the degree of deficient intracortical inhibition. Prolonged runs may represent an essential predictive feature for poor seizure control in JME.

Source localization of epileptiform discharges in juvenile myoclonic epilepsy (JME) using magnetoencephalography (MEG)

OBJECTIVE

The purpose of this study is to localize the sources of epileptiform discharges (EDs), in juvenile myoclonic epilepsy (JME) using Magnetoencephalography (MEG), at three different time instances and analyze the propagation of EDs, from onset to offset, for inferring the cortical and subcortical region of involvement.

METHODS

Twenty patients (age 23.5±6.3years old) with JME were recruited in this prospective study. MEG source analysis was performed on the independently collected EDs of each patient. The distributed source model was employed for source localization using low resolution electromagnetic brain tomography (LORETA). In each EDs, the onset (leading edge of the spike from baseline), peak and offset (trailing edge of the spike), with time window of 8ms, were subjected for source localization in order to study the propagation of the EDs. The obtained source location coordinates, from each individual MRI, were transformed in Talairach space and the distribution of region of source involvement was analysed.

RESULTS

The frequency pattern of lobar distribution at onset, peak and offset respectively suggest that discharges most commonly localized at onset from sublobar region, at peak from frontal lobe and at offset from the sublobar region. It was observed that the maximum involvement of sources from the sublobar, limbic and frontal lobes at different time instances. It indicates that the restricted cortical-subcortical involvement during the generation and propagation of EDs in JME.

SIGNIFICANCE

This MEG study supported the cortical-subcortical region of involvement and provided further insights in our understanding the network involvement in generation and propagation of EDs in JME.