Prognostic value of EEG asymmetries for development of drug-resistance in drug-naïve patients with genetic generalized epilepsies

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.

Electroclinical Presentations of Fixation-off Sensitivity in Adults With Symptomatic Epilepsy

PURPOSE

Fixation-off sensitivity (FOS) is a discharge pattern on EEG that occurs owing to the loss of central vision or fixation. Knowledge regarding the relationship between FOS and symptomatic epilepsy is limited. Therefore, we aimed to evaluate the electroclinical features of FOS in adult patients with symptomatic epilepsy.

METHODS

Outpatient video-EEG records of the Hacettepe University Faculty of Medicine were reviewed from 2009 to 2019. Patients aged >18 years with symptomatic epilepsy with a FOS pattern were included. Demographic, clinical, EEG, and neuroimaging data were retrospectively evaluated from an electronic database and patient files.

RESULTS

Eight patients (50% female) were included in this study; seven (87%) had refractory epilepsy. Prominent risk factors were family history of epilepsy in five patients and prenatal/natal insult in four patients. Notable MRI signs included cortical developmental malformation, posterior gliosis, and frontoparietal porencephalic cyst. The FOS pattern was generalized with posterior emphasis in two patients and lateralized or localized in six patients: frontocentroparietal ( n = 1) and temporoparietooccipital ( n = 5). Fixation-off sensitivity discharges were found to be increased by hyperventilation and decreased by drowsiness and sleep in 50% of patients. Fixation-off sensitivity disappeared in one patient with good seizure control.

CONCLUSIONS

In this study, the disappearance of FOS in an epileptic patient with a structural lesion and detection of FOS activity related to a frontoparietal porencephalic cyst were remarkable. Family history of epilepsy was also substantially high. Our results indicate that the underlying mechanism of FOS is much more complicated than previously thought.

Responsive Neurostimulation of the Anterior Thalamic Nuclei in Refractory Genetic Generalized Epilepsy: A Case Series

Genetic generalized epilepsies (GGEs) are thought to represent disorders of thalamocortical networks. There are currently no well-established non-pharmacologic treatment options for patients with drug-resistant GGE. NeuroPace's Responsive Neurostimulation (RNS) System was approved by the United States Food and Drug Administration to treat focal seizures with up to two ictal foci. We report on three adults with drug-resistant GGE who were treated with thalamic RNS. Given the severity of their epilepsies and the potential ictogenic role of the thalamus in the pathophysiology of GGE, the RNS System was palliatively implanted with leads in the bilateral anterior thalamic nuclei (ANT) of these patients. The ANT was selected because it was demonstrated to be a safe target. We retrospectively evaluated metrics including seizure frequency over 18-32 months. One patient required explantation due to infection. The other two patients were clinical responders. By the end of the observation period reported here, one patient was seizure-free for over 9 months. All three self-reported an improved quality of life. The clinical response observed in these patients provides 'proof-of-principle' that GGE may be treatable with responsive thalamic stimulation. Our results support proceeding to a larger study investigating the efficacy and safety of thalamic RNS in drug-resistant GGE.

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.

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.

Quantitative EEG biomarkers for epilepsy and their relation to chemical biomarkers

The electroencephalogram (EEG) is the most important method to diagnose epilepsy. In clinical settings, it is evaluated by experts who identify patterns visually. Quantitative EEG is the application of digital signal processing to clinical recordings in order to automatize diagnostic procedures, and to make patterns visible that are hidden to the human eye. The EEG is related to chemical biomarkers, as electrical activity is based on chemical signals. The most well-known chemical biomarkers are blood laboratory tests to identify seizures after they have happened. However, research on chemical biomarkers is much less extensive than research on quantitative EEG, and combined studies are rarely published, but highly warranted. Quantitative EEG is as old as the EEG itself, but still, the methods are not yet standard in clinical practice. The most evident application is an automation of manual work, but also a quantitative description and localization of interictal epileptiform events as well as seizures can reveal important hints for diagnosis and contribute to presurgical evaluation. In addition, the assessment of network characteristics and entropy measures were found to reveal important insights into epileptic brain activity. Application scenarios of quantitative EEG in epilepsy include seizure prediction, pharmaco-EEG, treatment monitoring, evaluation of cognition, and neurofeedback. The main challenges to quantitative EEG are poor reliability and poor generalizability of measures, as well as the need for individualization of procedures. A main hindrance for quantitative EEG to enter clinical routine is also that training is not yet part of standard curricula for clinical neurophysiologists.

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

OBJECTIVE

To identify clinical and EEG biomarkers of drug resistance in adults with idiopathic generalized epilepsy.

METHODS

We conducted a case-control study consisting of a discovery cohort and a replication cohort independently assessed at 2 different centers. In each center, patients with the idiopathic generalized epilepsy phenotype and generalized spike-wave discharges on EEG were classified as drug-resistant or drug-responsive. EEG changes were classified into predefined patterns and compared between the 2 groups in the discovery cohort. Factors associated with drug resistance in multivariable analysis were tested in the replication cohort.

RESULTS

The discovery cohort included 85 patients (29% drug-resistant and 71% drug-responsive). Their median age at assessment was 32 years and 50.6% were female. Multivariable analysis showed that higher number of seizure types ever experienced (3 vs 1: odds ratio [OR] = 31.1, 95% confidence interval [CI]: 4.5-214, p < 0.001; 3 vs 2: OR = 14.6, 95% CI: 2.3-93.1, p = 0.004) and generalized polyspike train (burst of generalized rhythmic spikes lasting less than 1 second) during sleep were associated with drug resistance (OR = 10.8, 95% CI: 2.4-49.4, p = 0.002). When these factors were tested in the replication cohort of 80 patients (27.5% drug-resistant and 72.5% drug-responsive; 71.3% female; median age 27.5 years), the proportion of patients with generalized polyspike train during sleep was also higher in the drug-resistant group (OR = 4.0, 95% CI: 1.35-11.8, p = 0.012).

CONCLUSION

Generalized polyspike train during sleep may be an EEG biomarker for drug resistance in adults with idiopathic generalized epilepsy.

White Matter Abnormalities in Patients with Treatment-Resistant Genetic Generalized Epilepsies

Background

Genetic generalized epilepsies (GGEs) are associated with microstructural brain abnormalities that can be evaluated with diffusion tensor imaging (DTI). Available studies on GGEs have conflicting results. Our primary goal was to compare the white matter structure in a cohort of patients with video/EEG-confirmed GGEs to healthy controls (HCs). Our secondary goal was to assess the potential effect of age at GGE onset on the white matter structure.

Material/Methods

A convenience sample of 23 patients with well-characterized treatment-resistant GGEs (13 female) was compared to 23 HCs. All participants received MRI at 3T. DTI indices, including fractional anisotropy (FA) and mean diffusivity (MD), were compared between groups using Tract-Based Spatial Statistics (TBSS).

Results

After controlling for differences between groups, abnormalities in DTI parameters were observed in patients with GGEs, including decreases in functional anisotropy (FA) in the hemispheric (left>right) and brain stem white matter. The examination of the effect of age at GGE onset on the white matter integrity revealed a significant negative correlation in the left parietal white matter region FA (R=−0.504; p=0.017); similar trends were observed in the white matter underlying left motor cortex (R=−0.357; p=0.103) and left posterior limb of the internal capsule (R=−0.319; p=0.148).

Conclusions

Our study confirms the presence of widespread white matter abnormalities in patients with GGEs and provides evidence that the age at GGE onset may have an important effect on white matter integrity.