Generalized polyspike train: An EEG biomarker of drug-resistant idiopathic generalized epilepsy

Seizure Cycles under Pharmacotherapy

OBJECTIVE

This study was undertaken to determine the effects of antiseizure medications (ASMs) on multidien (multiday) cycles of interictal epileptiform activity (IEA) and seizures and evaluate their potential clinical significance.

METHODS

We retrospectively analyzed up to 10 years of data from 88 of the 256 total adults with pharmacoresistant focal epilepsy who participated in the clinical trials of the RNS System, an intracranial device that keeps records of IEA counts. Following adjunctive ASM trials, we evaluated changes over months in (1) rates of self-reported disabling seizures and (2) multidien IEA cycle strength (spectral power for periodicity between 4 and 40 days). We used a survival analysis and the receiver operating characteristics to assess changes in IEA as a predictor of seizure control.

RESULTS

Among 56 (33.3%) of the 168 adjunctive ASM trials suitable for analysis, ASM introduction was followed by an average 50 to 70% decrease in multidien IEA cycle strength and a concomitant 50 to 70% decrease in relative seizure rate for up to 12 months. Individuals with a ≥50% decrease in IEA cycle strength in the first 3 months of an ASM trial had a higher probability of remaining seizure responders (≥50% seizure rate reduction, p < 10-7) or super-responders (≥90%, p < 10-8) over the next 12 months.

INTERPRETATION

In this large cohort, a decrease in multidien IEA cycle strength following initiation of an adjunctive ASM correlated with seizure control for up to 12 months, suggesting that fluctuations in IEA mirror "disease activity" in pharmacoresistant focal epilepsy and may have clinical utility as a biomarker to predict treatment response. ANN NEUROL 2024;95:743-753.

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.

The landscape of drug resistant absence seizures in adolescents and adults: Pathophysiology, electroclinical spectrum and treatment options

The persistence of typical absence seizures (AS) in adolescence and adulthood may reduce the quality of life of patients with genetic generalized epilepsies (GGEs). The prevalence of drug resistant AS is probably underestimated in this patient population, and treatment options are relatively scarce. Similarly, atypical absence seizures in developmental and epileptic encephalopathies (DEEs) may be unrecognized, and often persist into adulthood despite improvement of more severe seizures. These two seemingly distant conditions, represented by typical AS in GGE and atypical AS in DEE, share at least partially overlapping pathophysiological and genetic mechanisms, which may be the target of drug and neurostimulation therapies. In addition, some patients with drug-resistant typical AS may present electroclinical features that lie in between the two extremes represented by these generalized forms of epilepsy.

Idiopathic Generalized Epilepsy: Misunderstandings, Challenges, and Opportunities

The idiopathic generalized epilepsies (IGE) make up a fifth of all epilepsies, but <1% of epilepsy research. This skew reflects misperceptions: diagnosis is straightforward, pathophysiology is understood, seizures are easily controlled, epilepsy is outgrown, morbidity and mortality are low, and surgical interventions are impossible. Emerging evidence reveals that patients with IGE may go undiagnosed or misdiagnosed with focal epilepsy if EEG or semiology have asymmetric or focal features. Genetic, electrophysiologic, and neuroimaging studies provide insights into pathophysiology, including overlaps and differences from focal epilepsies. IGE can begin in adulthood and patients have chronic and drug-resistant seizures. Neuromodulatory interventions for drug-resistant IGE are emerging. Rates of psychiatric and other comorbidities, including sudden unexpected death in epilepsy, parallel those in focal epilepsy. IGE is an understudied spectrum for which our diagnostic sensitivity and specificity, scientific understanding, and therapies remain inadequate.

Epilepsy with generalized tonic-clonic seizures alone: Electroclinical features and prognostic patterns

OBJECTIVE

Epilepsy with generalized tonic-clonic seizures alone (GTCA) is a common but poorly characterized idiopathic generalized epilepsy (IGE) syndrome. Hence, we investigated electroclinical features, seizure outcome, and antiseizure medication (ASM) withdrawal in a large cohort of GTCA patients.

METHODS

In this multicenter retrospective study, GTCA patients defined according to the diagnostic criteria of the International League Against Epilepsy (2022) were included. We investigated prognostic patterns, drug resistance at the last visit, and ASM withdrawal, along with their prognostic factors.

RESULTS

We included 247 patients with a median (interquartile range [IQR]) age at onset of 17 years (13-22) and a median follow-up duration of 10 years (IQR = 5-20). Drug resistance at the last visit was observed in 40 (16.3%) patients, whereas the median latency to achieve 2-year remission was 24 months (IQR = 24-46.5) with a median number of 1 (IQR = 1-2) ASM. During the long-term follow-up (i.e., 202 patients followed ≥5-years after the first ASM trial), 69 (34.3%) patients displayed an early remission pattern and 36 (17.9%) patients displayed a late remission pattern, whereas 16 (8%) and 73 (36.3%) individuals had no-remission and relapsing-remitting patterns, respectively. Catamenial seizures and morning predominance of generalized tonic-clonic seizures (GTCS) independently predicted drug resistance at the last visit according to multivariable logistic regression. Treatment withdrawal was attempted in 63 (25.5%) patients, with 59 (93.7%) of them having at least a 12-month follow-up after ASM discontinuation. At the last visit, 49 (83%) of those patients had experienced GTCS recurrence. A longer duration of seizure freedom was the only factor predicting a higher chance of successful ASM withdrawal according to multivariable Cox regression.

SIGNIFICANCE

GTCA could be considered a relatively easily manageable IGE syndrome, with a low rate of drug resistance and a high prevalence of early response to treatment. Nevertheless, a considerable proportion of patients experience relapsing patterns of seizure control, highlighting the need for appropriate counseling and lifestyle recommendations.

Vagus nerve stimulation in refractory idiopathic generalised epilepsy: An Irish retrospective observational study

OBJECTIVE

Refractory idiopathic generalised epilepsy (IGE; also known as genetic generalised epilepsy) is a clinical challenge due to limited available therapeutic options. While vagus nerve stimulation (VNS) is approved as an adjunctive treatment for drug-resistant focal epilepsy, there is limited evidence supporting its efficacy for refractory IGE.

METHODS

We conducted a single-centre retrospective analysis of adult IGE patients treated with VNS between January 2003 and January 2022. We analysed the efficacy, safety, tolerability, stimulation parameters and potential clinical features of VNS response in this IGE cohort.

RESULTS

Twenty-three IGE patients were implanted with VNS between January 2003 and January 2022. Twenty-two patients (95.65%) were female. The median baseline seizure frequency was 30 per month (interquartile range [IQR]= 140), including generalised tonic-clonic seizures (GTCS), absences, myoclonus, and eyelid myoclonia with/without absences. The median number of baseline anti-seizure medications (ASM) was three (IQR= 2). Patients had previously failed a median of six ASM (IQR= 5). At the end of the study period, VNS therapy remained active in 17 patients (73.9%). amongst patients who continued VNS, thirteen (56.5% of the overall cohort) were considered responders (≥50% seizure frequency reduction). Amongst the clinical variables analysed, only psychiatric comorbidity correlated with poorer seizure outcomes, but was non-significant after applying the Bonferroni correction. Although 16 patients reported side-effects, none resulted in the discontinuation of VNS therapy.

SIGNIFICANCE

Over half of the patients with refractory IGE experienced a positive response to VNS therapy. VNS represents a viable treatment option for patients with refractory IGE, particularly for females, when other therapeutic options have been exhausted.

Drug-resistant idiopathic generalized epilepsy: A meta-analysis of prevalence and risk factors

BACKGROUND

Idiopathic generalized epilepsy (IGE) is a common epilepsy syndrome with early age onset and generally good seizure outcomes. This study aims to determine the incidence and predictive risk factors for drug-resistant IGE.

METHODS

We systematically searched three databases (PubMed, Embase, and Cochrane Library) in November 2022 and included 12 eligible studies which reported long-term outcomes (mean = 14.05) after antiseizure medications (ASMs) from 2001 to 2020. We defined drug resistance as the persistence of any seizure despite ASMs treatment (whether as monotherapies or in combination) given the criteria of drug resistance varied in original studies. A random-effects model was used to evaluate the prevalence of refractory IGE. Studies reporting potential poor prognostic factors were included for subsequent subgroup meta-analysis.

RESULTS

The pooled prevalence of drug resistance in IGE cohorts was 27% (95% CI: 0.19-0.36). Subgroup analysis of the risk factors revealed that the psychiatric comorbidities (odds ratio (OR): 4.87, 95% confidence interval (CI): 2.97-7.98), combined three seizure types (absences, myoclonic jerks, and generalized tonic-clonic seizures) (OR: 5.37, 95% CI: 3.16-9.13), the presence of absence seizure (OR: 4.38, 95% CI: 2.64-7.28), generalized polyspike trains (GPT) (OR: 4.83, 95% CI: 2.42-9.64), sex/catamenial epilepsy (OR: 3.25, 95% CI: 1.97-5.37), and status epilepticus (OR: 5.94, 95% CI: 2.23-15.85) increased the risk of poor prognosis. Other factors, including age onset, family history, and side effects of ASMs, were insignificantly associated with a higher incidence of refractory IGE.

CONCLUSION

Drug resistance is a severe complication of IGE. Further standardized research about clinical and electroencephalography factors is warranted.

Association of symptoms of psychiatric disease and electroencephalographic patterns in idiopathic generalized epilepsy

OBJECTIVE

Idiopathic generalized epilepsies (IGE) are genetic epilepsies with alterations of thalamo-frontocortical circuits that play a major role in seizure generation and propagation. Psychiatric diseases and drug resistance are strongly associated, but it remains unknown if they are symptoms of the same pathophysiological process. Hypothesizing that the same network alterations are associated with the frequency of epileptic discharges (ED) and psychiatric symptoms, we here tested the association of self-reported psychiatric symptoms and IGE severity estimated by electroencephalographic (EEG) biomarkers.

METHODS

Idiopathic generalized epilepsies patients were asked to fill out four validated psychiatric screening tools assessing symptoms of personality disorders (Standard Assessment of Personality- Abbreviated Scale), depression (Major Depression Inventory), impulsiveness (Barratt Impulsiveness Scale), and anxiety (brief Epilepsy Anxiety Survey Instrument). Blinded to results and clinical data on the patients, we analyzed the patients' EEGs, assessed, and quantified ED. The number and duration of ED divided by the duration of the EEG served as a proxy for the severity of IGE that was correlated with the results of the psychiatric screening.

RESULTS

Paired data from 64 patients were available for analysis. The duration of EDs per minute EEG was inversely associated with the time since the last seizure. The number of patients with generalized polyspike trains (n = 2), generalized paroxysmal fast activity (n = 3), and prolonged epileptiform discharges (n = 10) were too low for statistically meaningful analyses. Self-reported symptoms of depression, personality disorder, and impulsivity were not associated with EDs. In contrast, the duration of EDs per minute EEG was associated with self-reported symptoms of anxiety in univariate analyses, not significant, however, following adjustment for time since the last seizure in regression models.

SIGNIFICANCE

Self-reported symptoms of psychiatric diseases were not strongly associated with EDs as the best available quantifiable biomarker of IGE severity. As expected, the duration of EDs per minute and anxiety was inversely associated with time since the last seizure. Our data argue against a direct link between the frequency of EDs - as an objective proxy of IGE severity - and psychiatric symptoms.

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.

Neurophysiology of Juvenile and Progressive Myoclonic Epilepsy

SUMMARY

Myoclonus can be epileptic or nonepileptic. Epileptic myoclonus has been defined in clinical, neurophysiological, and neuroanatomical terms. Juvenile myoclonic epilepsy (JME) is typically considered to be an adolescent-onset idiopathic generalized epilepsy with a combination of myoclonic, generalized tonic-clonic, and absence seizures and normal cognitive status that responds well to anti-seizure medications but requires lifelong treatment. EEG shows generalized epileptiform discharges and photosensitivity. Recent observations indicate that the clinical picture of JME is heterogeneous and a number of neuropsychological and imaging studies have shown structural and functional abnormalities in the frontal lobes and thalamus. Advances in neurophysiology and imaging suggest that JME may not be a truly generalized epilepsy, in that restricted cortical and subcortical networks appear to be involved rather than the entire brain. Some patients with JME may be refractory to anti-seizure medications and attempts have been made to identify neurophysiological biomarkers predicting resistance. Progressive myoclonic epilepsy is a syndrome with multiple specific causes. It is distinct from JME because of the occurrence of progressive neurologic dysfunction in addition to myoclonus and generalized tonic-clonic seizures but may sometimes be difficult to distinguish from JME or misdiagnosed as drug-resistant JME. This article provides an overview of progressive myoclonic epilepsy and focuses on the clinical and neurophysiological findings in the two most commonly recognized forms of progressive myoclonic epilepsy-Unverricht-Lundborg disease (EPM1) and Lafora disease (EPM2). A variety of neurophysiological tests can be used to distinguish between JME and progressive myoclonic epilepsy and between EPM1 and EPM2.

Drug resistance in idiopathic generalized epilepsies: Evidence and concepts

Although approximately 10%-15% of patients with idiopathic generalized epilepsy (IGE)/genetic generalized epilepsy remain drug-resistant, there is no consensus or established concept regarding the underlying mechanisms and prevalence. This review summarizes the recent data and the current hypotheses on mechanisms that may contribute to drug-resistant IGE. A literature search was conducted in PubMed and Embase for studies on mechanisms of drug resistance published since 1980. The literature shows neither consensus on the definition nor a widely accepted model to explain drug resistance in IGE or one of its subsyndromes. Large-scale genetic studies have failed to identify distinct genetic causes or affected genes involved in pharmacokinetics. We found clinical and experimental evidence in support of four hypotheses: (1) "network hypothesis"-the degree of drug resistance in IGE reflects the severity of cortical network alterations, (2) "minor focal lesion in a predisposed brain hypothesis"-minor cortical lesions are important for drug resistance, (3) "interneuron hypothesis"-impaired functioning of γ-aminobutyric acidergic interneurons contributes to drug resistance, and (4) "changes in drug kinetics"-genetically impaired kinetics of antiseizure medication (ASM) reduce the effectiveness of available ASMs. In summary, the exact definition and cause of drug resistance in IGE is unknown. However, published evidence suggests four different mechanisms that may warrant further investigation.

Paroxysmal fast activity is a biomarker of treatment response in deep brain stimulation for Lennox-Gastaut syndrome

OBJECTIVE

Epilepsy treatment trials typically rely on seizure diaries to determine seizure frequency, but these are time-consuming and difficult to maintain accurately. Fast, reliable, and objective biomarkers of treatment response are needed, particularly in Lennox-Gastaut syndrome (LGS), where high seizure frequency and comorbid cognitive and behavioral issues are additional obstacles to accurate diary-keeping. Here, we measured generalized paroxysmal fast activity (GPFA), a key interictal electrographic feature of LGS, and correlated GPFA burden with seizure diaries during a thalamic deep brain stimulation (DBS) treatment trial (Electrical Stimulation of the Thalamus in Epilepsy of Lennox-Gastaut Phenotype [ESTEL]).

METHODS

GPFA and electrographic seizure counts from intermittent, 24-h electroencephalograms (EEGs) were compared to 3-month diary-recorded seizure counts in 17 young adults with LGS (mean age ± SD = 24.9 ± 6.6) in the ESTEL study, a randomized clinical trial of DBS lasting 12 months (comprising a 3-month baseline and 9 months of postimplantation follow-up).

RESULTS

Baseline median seizures measured by diaries numbered 2.6 (interquartile range [IQR] = 1.4-5) per day, compared to 284 (IQR = 120.5-360) electrographic seizures per day, confirming that diaries capture only a small fraction of seizure burden. Across all patient EEGs, the average number of GPFA discharges per hour of sleep was 138 (IQR =72-258). GPFA duration and frequency, quantified over 2-h windows of sleep EEG, were significantly associated with diary-recorded seizure counts over 3-month intervals (p < .001, η2 p  = .30-.48). For every GPFA discharge, there were 20-25 diary seizures witnessed over 3 months. There was high between-patient variability in the ratio between diary seizure burden and GPFA burden; however, within individual patients, the ratio was similar over time, such that the percentage change from pre-DBS baseline in seizure diaries strongly correlated with the percentage change in GPFA.

SIGNIFICANCE

When seeking to optimize treatment in patients with LGS, monitoring changes in GPFA may allow rapid titration of treatment parameters, rather than waiting for feedback from seizure diaries.

Individualised prediction of drug resistance and seizure recurrence after medication withdrawal in people with juvenile myoclonic epilepsy: A systematic review and individual participant data meta-analysis

BACKGROUND

A third of people with juvenile myoclonic epilepsy (JME) are drug-resistant. Three-quarters have a seizure relapse when attempting to withdraw anti-seizure medication (ASM) after achieving seizure-freedom. It is currently impossible to predict who is likely to become drug-resistant and safely withdraw treatment. We aimed to identify predictors of drug resistance and seizure recurrence to allow for individualised prediction of treatment outcomes in people with JME.

METHODS

We performed an individual participant data (IPD) meta-analysis based on a systematic search in EMBASE and PubMed - last updated on March 11, 2021 - including prospective and retrospective observational studies reporting on treatment outcomes of people diagnosed with JME and available seizure outcome data after a minimum one-year follow-up. We invited authors to share standardised IPD to identify predictors of drug resistance using multivariable logistic regression. We excluded pseudo-resistant individuals. A subset who attempted to withdraw ASM was included in a multivariable proportional hazards analysis on seizure recurrence after ASM withdrawal. The study was registered at the Open Science Framework (OSF; https://osf.io/b9zjc/).

FINDINGS

Our search yielded 1641 articles; 53 were eligible, of which the authors of 24 studies agreed to collaborate by sharing IPD. Using data from 2518 people with JME, we found nine independent predictors of drug resistance: three seizure types, psychiatric comorbidities, catamenial epilepsy, epileptiform focality, ethnicity, history of CAE, family history of epilepsy, status epilepticus, and febrile seizures. Internal-external cross-validation of our multivariable model showed an area under the receiver operating characteristic curve of 0·70 (95%CI 0·68-0·72). Recurrence of seizures after ASM withdrawal (n = 368) was predicted by an earlier age at the start of withdrawal, shorter seizure-free interval and more currently used ASMs, resulting in an average internal-external cross-validation concordance-statistic of 0·70 (95%CI 0·68-0·73).

INTERPRETATION

We were able to predict and validate clinically relevant personalised treatment outcomes for people with JME. Individualised predictions are accessible as nomograms and web-based tools.

FUNDING

MING fonds.

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.

Potential clinical and biochemical markers for the prediction of drug-resistant epilepsy: A literature review

Drug resistance is a major challenge in the treatment of epilepsy. Drug-resistant epilepsy (DRE) accounts for 30% of all cases of epilepsy and is a matter of great concern because of its uncontrollability and the high burden, mortality rate, and degree of damage. At present, considerable research has focused on the development of predictors to aid in the early identification of DRE in an effort to promote prompt initiation of individualized treatment. While multiple predictors and risk factors have been identified, there are currently no standard predictors that can be used to guide the clinical management of DRE. In this review, we discuss several potential predictors of DRE and related factors that may become predictors in the future and perform evidence rating analysis to identify reliable potential predictors.

Using Generalized Polyspike Train to Predict Drug-Resistant Idiopathic Generalized Epilepsy

INTRODUCTION

The authors tested the hypothesis that the EEG feature generalized polyspike train (GPT) is associated with drug-resistant idiopathic generalized epilepsy (IGE).

METHODS

The authors conducted a single-center case-control study of patients with IGE who had outpatient EEGs performed between 2016 and 2020. The authors classified patients as drug-resistant or drug-responsive based on clinical review and in a masked manner reviewed EEG data for the presence and timing of GPT (a burst of generalized rhythmic spikes lasting less than 1 second) and other EEG features. A relationship between GPT and drug resistance was tested before and after controlling for EEG duration. The EEG duration needed to observe GPT was also calculated.

RESULTS

One hundred three patients were included (70% drug-responsive and 30% drug-resistant patients). Generalized polyspike train was more prevalent in drug-resistant IGE (odds ratio, 3.8; 95% confidence interval, 1.3-11.4; P = 0.02). This finding persisted when controlling for EEG duration both with stratification and with survival analysis. A median of 6.5 hours (interquartile range, 0.5-12.7 hours) of EEG recording was required to capture the first occurrence of GPT.

CONCLUSIONS

The findings support the hypothesis that GPT is associated with drug-resistant IGE. Prolonged EEG recording is required to identify this feature. Thus, >24-hour EEG recording early in the evaluation of patients with IGE may facilitate prognostication.

Moving the field forward: detection of epileptiform abnormalities on scalp electroencephalography using deep learning—clinical application perspectives

The application of deep learning approaches for the detection of interictal epileptiform discharges is a nascent field, with most studies published in the past 5 years. Although many recent models have been published demonstrating promising results, deficiencies in descriptions of data sets, unstandardized methods, variation in performance evaluation and lack of demonstrable generalizability have made it difficult for these algorithms to be compared and progress to clinical validity. A few recent publications have provided a detailed breakdown of data sets and relevant performance metrics to exemplify the potential of deep learning in epileptiform discharge detection. This review provides an overview of the field and equips computer and data scientists with a synopsis of EEG data sets, background and epileptiform variation, model evaluation parameters and an awareness of the performance metrics of high impact and interest to the trained clinical and neuroscientist EEG end user. The gold standard and inter-rater disagreements in defining epileptiform abnormalities remain a challenge in the field, and a hierarchical proposal for epileptiform discharge labelling options is recommended. Standardized descriptions of data sets and reporting metrics are a priority. Source code-sharing and accessibility to public EEG data sets will increase the rigour, quality and progress in the field and allow validation and real-world clinical translation.

Drug-resistant epilepsy at the age extremes: Disentangling the underlying etiology

The incidence of epilepsy is highest at the extreme age ranges: childhood and elderly age. The most common syndromes in these demographics - self-limited epilepsies of childhood and idiopathic generalized epilepsies in pediatric age, focal epilepsy with structural etiology in older people - are expected to be drug responsive. In this work, we focus on such epilepsy types, overviewing the complex clinical background of unexpected drug-resistance. For self-limited epilepsies of childhood and idiopathic generalized epilepsies, we illustrate drug-resistance resulting from syndrome misinterpretation, reason on possible unexpected courses of epilepsy, and explicate the influence of inappropriate treatments. For elderly-onset epilepsy, we show the challenges in differential diagnosis possibly leading to pseudoresistance and analyze how drug-resistant epilepsy can arise in stroke, neurocognitive disorders, brain tumors, and autoimmune encephalitis. In children and senior people, drug-resistance can be regarded as a hint to review the diagnosis or explore alternative therapeutic strategies. Refractory seizures are not only a therapeutic challenge, but also a cardinal sign not to be overlooked in syndromes commonly deemed to be drug-responsive.

Correlations Between Structural Brain Abnormalities, Cognition and Electroclinical Characteristics in Patients With Juvenile Myoclonic Epilepsy

Objective

To explore the structural brain abnormality and its relationship with neuropsychological disorders and electroclinical characteristics in juvenile myoclonic epilepsy (JME) patients.

Methods

Sixty-seven patients diagnosed with JME and 56 healthy controls were enrolled. All subjects underwent MRI using T1-weighted 3D brain structural images with 1 mm thickness. Voxel-based morphometry (VBM) and surface-based morphometry (SBM) analyses were performed. They also underwent a series of neuropsychological tests to assess cognitive function. The correlation analyses were conducted between structural changes, neuropsychological outcomes, and electroclinical features.

Results

The gray matter concentration (GMC) was decreased in the bilateral pre-central and post-central gyrus, right anterior cingulate gyrus, left posterior orbital region, bilateral occipital regions, bilateral hippocampus and bilateral caudate nucleus in the JME groups (corrected P < 0.05). The evaluation of gray matter volume (GMV) showed significant decrease respectively in bilateral pre-central and post-central gyrus, left paracentral lobule, left orbital gyrus, left amygdala, left basal ganglia and left thalamus of JME patients (P < 0.05). The cortex thicknesses of the right inferior temporal gyrus, right insular gyrus, and right cingulate gyrus had negative correlations with the disease duration significantly. At the same time, the whole-brain white matter volume was positively associated with the course of the disease (P < 0.05). Patients with persistent abnormal EEG discharges had significantly less whole-brain gray matter volume than JME patients with normal EEG (P = 0.03). Correlation analyses and linear regression analyses showed that, in addition to the gray matter volumes of frontal and parietal lobe, the temporal lobe, as well as the basal ganglia and thalamus, were also significantly correlated with neuropsychological tests' results (P < 0.05).

Conclusion

The JME patients showed subtle structural abnormalities in multiple brain regions that were not only limited to the frontal lobe but also included the thalamus, basal ganglia, parietal lobe, temporal lobe and some occipital cortex, with significant involvement of the primary somatosensory cortex and primary motor cortex. And we significantly demonstrated a correlation between structural abnormalities and cognitive impairment. In addition, the course of disease and abnormal discharges had a specific negative correlation with the structural changes.

Responsive neurostimulation of the thalamus improves seizure control in idiopathic generalised epilepsy: initial case series

OBJECTIVES

Up to 40% of patients with idiopathic generalised epilepsy (IGE) are drug resistant and potentially could benefit from intracranial neuromodulation of the seizure circuit. We present outcomes following 2 years of thalamic-responsive neurostimulation for IGE.

METHODS

Four patients with pharmacoresistant epilepsy underwent RNS System implantation in the bilateral centromedian (CM) nucleus region. Electrophysiological data were extracted from the clinical patient data management system and analysed using a specialised platform (BRAINStim). Postoperative visualisation of electrode locations was performed using Lead-DBS. Seizure outcomes were reported using the Engel scale.

RESULTS

Patients experienced a 75%-99% reduction in seizure frequency with decreased seizure duration and severity (Engel class IB, IC, IIA and IIIA), as well as significant improvements in quality of life. Outcomes were durable through at least 2 years of therapy. Detection accuracy for all patients overall decreased over successive programming epochs from a mean of 96.5% to 88.3%. Most electrodes used to deliver stimulation were located in the CM (7/10) followed by the posterior dorsal ventral lateral (2/2), posterior ventral posterior lateral (3/4) and posterior ventral ventral lateral (2/3). In all patients, stimulation varied from 0.2 to 2.0 mA and amplitude only increased over successive epochs. The raw percentage of intracranial electroencephalography recordings with stimulations delivered to electrographic seizures was 24.8%, 1.2%, 7.6% and 8.8%.

CONCLUSION

Closed-loop stimulation of the CM region may provide significant improvement in seizure control and quality of life for patients with drug-resistant IGE. Optimal detection and stimulation locations and parameters remain an active area of investigation for accelerating and fine-tuning clinical responses.

Electroclinical Features and Long-term Seizure Outcome in Patients With Eyelid Myoclonia With Absences

BACKGROUND AND OBJECTIVES

Eyelid myoclonia with absences (EMA) is a generalized epilepsy syndrome whose prognosis and clinical characteristics are still partially undefined. We investigated electroclinical endophenotypes and long-term seizure outcome in a large cohort of EMA patients.

METHODS

In this multicenter retrospective study, EMA patients with ≥5 years of follow-up were included. We investigated prognostic patterns and sustained terminal remission (STR), along with their prognostic factors. Moreover, a two-step cluster analysis was used to investigate the presence of distinct EMA endophenotypes.

RESULTS

We included 172 patients, with a median age at onset of 7 years (interquartile range (IQR) 5-10) and a median follow-up duration of 14 years (IQR 8.25-23.75). Sixty-six patients (38.4%) displayed a non-remission pattern, whereas remission and relapse patterns were encountered in 56 (32.6%) and 50 (29.1%) subjects. Early epilepsy onset, history of febrile seizures (FS) and eyelid myoclonia (EM) status epilepticus significantly predicted a non-remission pattern according to multinomial logistic regression analysis. STR was achieved by 68 (39.5%) patients with a mean latency of 14.05 years (SD ± 12.47). Early epilepsy onset, psychiatric comorbidities, and a history of FS and generalized tonic-clonic seizures (GTCS) were associated with a lower probability of achieving STR according to a Cox regression proportional hazards model. Antiseizure medication (ASM) withdrawal was attempted in 62/172 patients, and seizures relapsed in 74.2%. Cluster analysis revealed two distinct clusters with 86 patients each. Cluster 2, which we defined as "EMA-plus", was characterized by an earlier age at epilepsy onset, higher rate of intellectual disability, EM status epilepticus, generalized paroxysmal fast activity, self-induced seizures, FS, and poor ASM response, whereas Cluster 1, the "EMA-only" cluster, was characterized by a higher rate of seizure remission and more favorable neuropsychiatric outcome.

DISCUSSION

Early epilepsy onset was the most relevant prognostic factor for poor treatment response. A long latency between epilepsy onset and ASM response was observed, suggesting the impact of age-related brain changes in EMA remission. Finally, our cluster analysis showed a clear-cut distinction of EMA patients into an EMA-plus insidious subphenotype and an EMA-only benign cluster that strongly differed in terms of remission rates and cognitive outcomes.

Generalized Fast Discharges Along the Genetic Generalized Epilepsy Spectrum: Clinical and Prognostic Significance

Objective

To investigate the electroclinical characteristics and the prognostic impact of generalized fast discharges in a large cohort of genetic generalized epilepsy (GGE) patients studied with 24-h prolonged ambulatory electroencephalography (paEEG).

Methods

This retrospective multicenter cohort study included 202 GGE patients. The occurrence of generalized paroxysmal fast activity (GPFA) and generalized polyspike train (GPT) was reviewed. GGE patients were classified as having idiopathic generalized epilepsy (IGE) or another GGE syndrome (namely perioral myoclonia with absences, eyelid myoclonia with absences, epilepsy with myoclonic absences, generalized epilepsy with febrile seizures plus, or GGE without a specific epilepsy syndrome) according to recent classification proposals.

Results

GPFA/GPT was found in overall 25 (12.4%) patients, though it was significantly less frequent in IGE compared with other GGE syndromes (9.3 vs. 25%, p = 0.007). GPFA/GPT was found independently of seizure type experienced during history, the presence of mild intellectual disability/borderline intellectual functioning, or EEG features. At multivariable analysis, GPFA/GPT was significantly associated with drug resistance (p = 0.04) and with a higher number of antiseizure medications (ASMs) at the time of paEEG (p < 0.001) and at the last medical observation (p < 0.001). Similarly, GPFA/GPT, frequent/abundant generalized spike-wave discharges during sleep, and a higher number of seizure types during history were the only factors independently associated with a lower chance of achieving 2-year seizure remission at the last medical observation. Additionally, a greater number of GPFA/GPT discharges significantly discriminated between patients who achieved 2-year seizure remission at the last medical observation and those who did not (area under the curve = 0.77, 95% confidence interval 0.57–0.97, p = 0.02)

Conclusion

We found that generalized fast discharges were more common than expected in GGE patients when considering the entire GGE spectrum. In addition, our study highlighted that GPFA/GPT could be found along the entire GGE continuum, though their occurrence was more common in less benign GGE syndromes. Finally, we confirmed that GPFA/GPT was associated with difficult-to-treat GGE, as evidenced by the multivariable analysis and the higher ASM load during history.

High rates of early remission pattern in adult-onset compared with earlier-onset idiopathic generalized epilepsy: A long-term follow-up study

OBJECTIVE

To investigate electroclinical characteristics and prognostic patterns of adult-onset vs. younger-onset idiopathic generalized epilepsy (IGE) patients during long-term follow-up.

METHODS

In this single-center retrospective cohort comparative study, adult-onset IGE was defined as onset after 20 years of age. Patients with a follow-up duration between 10 and 30 years from epilepsy diagnosis were enrolled. Maximum follow-up duration was limited to 30 years to ensure a better comparison of prognostic data between adult-onset and younger-onset patients. The Benjamini-Hochberg false discovery rate (FDR) method was applied to obtain FDR-adjusted p-values.

RESULTS

A total of 177 IGE patients were recruited and 27 adult-onset IGE patients were identified (15.3%). Follow-up duration was similar between younger- and adult-onset IGE patients and 74% of subjects performed at least one 24-hour EEG recording. Of adult-onset IGE patients, 8/27 were diagnosed with juvenile myoclonic epilepsy, while 19/27 were diagnosed with generalized tonic-clonic seizures (GTCS) only. EEG photosensitivity and absence seizures were significantly less frequent among adult-onset IGE patients as compared with younger subjects. When considering prognostic patterns, an early remission pattern was significantly higher among adult-onset IGE patients as compared with younger-onset IGE patients (55.6% vs. 24%, adjusted p value = 0.007). Antiseizure medication withdrawal was attempted in 3/27 adult-onset patients, and all had GTCS relapses.

CONCLUSION

Our study contributes to better defining the electroclinical characteristics and long-term follow-up of adult-onset IGE patients. A favorable long-term seizure outcome was found in adult-onset IGE patients, as evidenced by the high rates of early remission pattern when compared with younger onset patients.

Brainwaves beyond diagnosis: Wider applications of electroencephalography in idiopathic generalized epilepsy

Electroencephalography (EEG) has long been used as a versatile and noninvasive diagnostic tool in epilepsy. With the advent of digital EEG, more advanced applications of EEG have emerged. Compared with technologically advanced practice in focal epilepsies, the utilization of EEG in idiopathic generalized epilepsy (IGE) has been lagging, often restricted to a simple diagnostic tool. In this narrative review, we provide an overview of broader applications of EEG beyond this narrow scope, discussing how the current clinical and research applications of EEG may potentially be extended to IGE. The current literature, although limited, suggests that EEG can be used in syndromic classification, guiding antiseizure medication therapy, predicting prognosis, unraveling biorhythms, and investigating functional brain connectivity of IGE. We emphasize the need for longer recordings, particularly 24-h ambulatory EEG, to capture discharges reflecting circadian and sleep-wake cycle-associated variations for wider EEG applications in IGE. Finally, we highlight the challenges and limitations of the current body of literature and suggest future directions to encourage and enhance more extensive applications of this potent tool.

New advances in pharmacoresistant epilepsy towards precise management-from prognosis to treatments

Epilepsy, one of the most severe neurological diseases, is characterized by abrupt recurrent seizures. Despite great progress in the development of antiseizure drugs (ASDs) based on diverse molecular targets, more than one third of epilepsy patients still show resistance to ASDs, a condition termed pharmacoresistant epilepsy. The management of pharmacoresistant epilepsy involves serious challenges. In the past decade, promising advances have been made in the use of interdisciplinary techniques involving biophysics, bioinformatics, biomaterials and biochemistry, which allow more precise prognosis and development of drug target for pharmacoresistant epilepsy. Notably, novel experimental tools such as viral vector gene delivery, optogenetics and chemogenetics have provided a framework for promising approaches to the precise treatment of pharmacoresistant epilepsy. In this review, historical achievements especially recent advances of the past decade in the prognosis and treatment of pharmacoresistant epilepsy from both clinical and laboratory settings are presented and summarized. We propose that the further development of novel experimental tools at cellular or molecular levels with both temporal and spatial precision are necessary to make improve the management and drug development for pharmacoresistant epilepsy in the clinical arena.

Clinical and EEG factors associated with antiseizure medication resistance in idiopathic generalized epilepsy

OBJECTIVE

We sought to determine which combination of clinical and electroencephalography (EEG) characteristics differentiate between an antiseizure medication (ASM)-resistant vs ASM-responsive outcome for patients with idiopathic generalized epilepsy (IGE).

METHODS

This was a case-control study of ASM-resistant cases and ASM-responsive controls with IGE treated at five epilepsy centers in the United States and Australia between 2002 and 2018. We recorded clinical characteristics and findings from the first available EEG study for each patient. We then compared characteristics of cases vs controls using multivariable logistic regression to develop a predictive model of ASM-resistant IGE.

RESULTS

We identified 118 ASM-resistant cases and 114 ASM-responsive controls with IGE. First, we confirmed our recent finding that catamenial epilepsy is associated with ASM-resistant IGE (odds ratio [OR] 3.53, 95% confidence interval [CI] 1.32-10.41, for all study subjects) after covariate adjustment. Other independent factors seen with ASM resistance include certain seizure-type combinations (absence, myoclonic, and generalized tonic-clonic seizures [OR 7.06, 95% CI 2.55-20.96]; absence and generalized tonic-clonic seizures [OR 4.45, 95% CI 1.84-11.34]), as well as EEG markers of increased generalized spike-wave discharges (GSWs) in sleep (OR 3.43, 95% CI 1.12-11.36 for frequent and OR 7.21, 95% CI 1.50-54.07 for abundant discharges in sleep) and the presence of generalized polyspike trains (GPTs; OR 5.49, 95% CI 1.27-38.69). The discriminative ability of our final multivariable model, as measured by area under the receiver-operating characteristic curve, was 0.80.

SIGNIFICANCE

Multiple clinical and EEG characteristics independently predict ASM resistance in IGE. To improve understanding of a patient's prognosis, clinicians could consider asking about specific seizure-type combinations and track whether they experience catamenial epilepsy. Obtaining prolonged EEG studies to record the burden of GSWs in sleep and assessing for the presence of GPTs may provide additional predictive value.

Recent Developments in Diagnosis of Epilepsy: Scope of MicroRNA and Technological Advancements

Epilepsy is one of the most common neurological disorders, characterized by recurrent seizures, resulting from abnormally synchronized episodic neuronal discharges. Around 70 million people worldwide are suffering from epilepsy. The available antiepileptic medications are capable of controlling seizures in around 60-70% of patients, while the rest remain refractory. Poor seizure control is often associated with neuro-psychiatric comorbidities, mainly including memory impairment, depression, psychosis, neurodegeneration, motor impairment, neuroendocrine dysfunction, etc., resulting in poor prognosis. Effective treatment relies on early and correct detection of epileptic foci. Although there are currently a few well-established diagnostic techniques for epilepsy, they lack accuracy and cannot be applied to patients who are unsupportive or harbor metallic implants. Since a single test result from one of these techniques does not provide complete information about the epileptic foci, it is necessary to develop novel diagnostic tools. Herein, we provide a comprehensive overview of the current diagnostic tools of epilepsy, including electroencephalography (EEG) as well as structural and functional neuroimaging. We further discuss recent trends and advances in the diagnosis of epilepsy that will enable more effective diagnosis and clinical management of patients.

Treatment outcomes in drug resistant juvenile myoclonic epilepsy: Valproate resistance may not be the end of the road

OBJECTIVE

To determine treatment responses to various antiseizure medicines (ASMs) in patients with drug resistant juvenile myoclonic epilepsy (DRJME) METHODS: We reviewed records of all JME patients attending epilepsy clinics at 5 centers during a 5-year period. We used International Consensus Criteria to diagnose JME and International League Against Epilepsy Criteria to define drug resistance and sustained seizure freedom. We only used broad spectrum medicines which included valproate, lamotrigine, topiramate, levetiracetam, clobazam, phenobarbitone, clonazepam, and zonisamide. We considered an ASM successful if patient achieved seizure freedom within 3 months of attaining maintenance dose.

RESULTS

We studied 116 patients (61 males) with DRJME. At terminal followup, 82 (70.7%) patients had achieved sustained seizure freedom with a mean followup of 3.2 ± 1.3 years after last dose change. In patients where valproate failed as first- or second-line ASM (n=70; 60.3%), 49(70%) became seizure-free. In this group, 33(67%) patients became seizure-free after addition of lamotrigine. Success rate of lamotrigine and valproate combination was 69% as compared to 9% with all other combinations (p = 0.001). In patients who were not exposed to valproate as initial therapy (n=46), 33 (71.7%) became seizure-free, 30 (91%) after adding valproate. At last follow-up, 75 (90%) seizure-free patients were receiving valproate including 45 (55%) patients with a combination of valproate and lamotrigine. Only one of 24 patients became seizure-free after failing valproate and lamotrigine combination.

CONCLUSION

Seizure freedom can be achieved in two-thirds of patients with DRJME. A combination of valproate and lamotrigine is the most effective duotherapy.

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.

Under-sampling in epilepsy: Limitations of conventional EEG

The cyclical structure of epilepsy was recently (re)-discovered through years-long intracranial electroencephalography (EEG) obtained with implanted devices. In this review, we discuss how new revelations from chronic EEG relate to the practice and interpretation of conventional EEG. We argue for an electrographic definition of seizures and highlight the caveats of counting epileptiform discharges in EEG recordings of short duration. Limitations of conventional EEG have practical implications with regard to titrating anti-seizure medications and allowing patients to drive, and we propose that chronic monitoring of brain activity could greatly improve epilepsy care. An impending paradigm shift in epilepsy will involve using next-generation devices for chronic EEG to leverage known biomarkers of disease state.

Development and validation of a predictive model of drug-resistant genetic generalized epilepsy

OBJECTIVE

To develop and validate a clinical prediction model for antiepileptic drug (AED)-resistant genetic generalized epilepsy (GGE).

METHOD

We performed a case-control study of patients with and without drug-resistant GGE, nested within ongoing longitudinal observational studies of AED response at 2 tertiary epilepsy centers. Using a validation dataset, we tested the predictive performance of 3 candidate models, developed from a training dataset. We then tested the candidate models' predictive ability on an external testing dataset.

RESULTS

Of 5,189 patients in the ongoing longitudinal study, 121 met criteria for AED-resistant GGE and 468 met criteria for AED-responsive GGE. There were 66 patients with GGE in the external dataset, of whom 17 were cases. Catamenial epilepsy, history of a psychiatric condition, and seizure types were strongly related with drug-resistant GGE case status. Compared to women without catamenial epilepsy, women with catamenial epilepsy had about a fourfold increased risk for AED resistance. The calibration of 3 models, assessing the agreement between observed outcomes and predictions, was adequate. Discriminative ability, as measured with area under the receiver operating characteristic curve (AUC), ranged from 0.58 to 0.65.

CONCLUSION

Catamenial epilepsy, history of a psychiatric condition, and the seizure type combination of generalized tonic clonic, myoclonic, and absence seizures are negative prognostic factors of drug-resistant GGE. The AUC of 0.6 is not consistent with truly effective separation of the groups, suggesting other unmeasured variables may need to be considered in future studies to improve predictability.

Reflex epileptic features in patients with focal epilepsy of unknown cause

OBJECTIVES

There is a gap of knowledge regarding reflex seizures in patients with focal epilepsy of unknown cause (FEUC). We aimed to evaluate the prevalence, demographic and clinical characteristics of reflex seizures in patients with FEUC to provide an insight to the underlying ictogenic mechanisms and to draw attention to this important but under-investigated topic.

PATIENTS AND METHODS

After carefully questioning for reflex triggers, 186 patients diagnosed according to ILAE criteria and followed-up for a minimum of 5 years were included. The demographic and clinical properties as well as electrophysiological and neuroimaging data of these patients were reevaluated and compared to the patients without reflex seizures.

RESULTS

The reflex seizure rate was 6.5 % in patients with FEUC. Patients with reflex features had lower monotherapy rates (p = 0.005) and higher major depression rates (p = 0.001) than patients without reflex features. The distribution of the patients according to their reflex triggers were as follows: hot-water induced (n = 3, 25 %), photosensitive (n = 2, 16.7 %), eating- induced (n = 2, 16.7 %), musicogenic (n = 2, 16.7 %), startle induced (n = 2, 16.7 %) and both musicogenic and startle type (n = 1, 8.3 %) respectively. The drug resistance rate of patients with reflex seizures was 25 % (n = 3). One patient with drug resistant reflex seizures showed benefit from epilepsy surgery and became seizure-free during last 3 years of follow-up.

CONCLUSION

A careful and thoroughly history taking specifically questioning and focusing on seizure inducing factors in patients with FEUC is needed to confirm the presence of reflex seizures in patients with FEUC, who had higher rates of polytherapy and major depression. Elaborative evaluation of reflex features in FEUC might contribute to effective seizure control, ensure new therapeutic approaches, enlighten the obscurity and the resulting anxiety of having a diagnosis of FEUC in epilepsy patients.

Circulating microRNAs as potential biomarkers for genetic generalized epilepsies: a three microRNA panel

BACKGROUND AND PURPOSE

Genetic generalized epilepsies (GGEs) encompass a group of syndromes of mainly genetic causes, characterized by the involvement of both hemispheres. MicroRNAs (miRNAs) are small non-coding RNAs with a critical role in the regulation of neuronal biological processes through gene expression modulation. Dysregulated miRNA expression has been shown in epilepsy. Due to their stability in biological fluids like serum, miRNAs have assumed a prominent role in biomarker research. Our aim was to evaluate circulating levels of three miRNAs in GGE patients and assess their putative diagnostic value.

METHODS

MiR-146a, miR-155 and miR-132 were quantified by real-time polymerase chain reaction in the serum of 79 GGE patients (47 women, 32 men, 35.1 ± 12.4 years) and 67 healthy individuals (41 women, 26 men, 42.4 ± 10.1 years). Relative expression values were calculated using the 2^-ΔΔCt method. Receiver operating characteristic curve analysis was performed to assess diagnostic value. MiRNA expression was correlated with clinicopathological features.

RESULTS

Serum levels of miR-146a and miR-155 were significantly upregulated in GGE patients relative to controls (3.13 and 6.05, respectively). Combined miR-146a, miR-155 and miR-132 serum levels performed well as a diagnostic biomarker, discriminating GGE patients from controls with an area under the curve of 0.85, 80% specificity and 73% sensitivity.

CONCLUSIONS

Our results indicate that miR-146a, miR-155 and miR-132 may partake in GGE epileptogenesis. A panel of three circulating miRNAs with potential value as a GGE biomarker is reported for the first time. Novel biomarkers may help to identify new treatment targets and contribute to improved patients' quality of life through earlier diagnosis and a more precise prognosis.

Pharmacoresistance - Epidemiology, mechanisms, and impact on epilepsy treatment

Understanding the natural history of and factors associated with pharmacoresistant epilepsy provides the foundation for formulating mechanistic hypotheses that can be evaluated to drive the development of novel treatments. This article reviews the modern definition of drug-resistant epilepsy, its prevalence and incidence, risk factors, hypothesized mechanisms, and the implication of recognizing pharmacoresistance in therapeutic strategies. This article is part of the special issue entitled 'New Epilepsy Therapies for the 21st Century - From Antiseizure Drugs to Prevention, Modification and Cure of Epilepsy'.