Efficacy and safety of VNS therapy or continued medication management for treatment of adults with drug-resistant epilepsy: systematic review and meta-analysis

Vagus nerve stimulation (VNS) Therapy® is an adjunctive neurostimulation treatment for people with drug-resistant epilepsy (DRE) who are unwilling to undergo resective surgery, have had unsuccessful surgery or are unsuitable for surgery. A systematic review and meta-analysis were conducted to determine the treatment effects of VNS Therapy as an adjunct to anti-seizure medications (ASMs) for the management of adults with DRE. A literature search was performed in August 2020 of the Medline®, Medline® Epub Ahead of Print, Embase, and the Cochrane library databases. Outcomes examined included reduction in seizure frequency, seizure freedom, ASM load, discontinuations, and serious adverse events (SAEs). Comparators included best medical practice, ASMs, low-stimulation or sham VNS Therapy. Four RCTs and six comparative observational studies were identified for inclusion. Against comparators, individuals treated with VNS had a significantly better odds of experiencing a ≥ 50% reduction in seizure frequency (OR: 2.27 [95% CI 1.47, 3.51]; p = 0.0002), a ≥ 75% reduction in seizure frequency (OR: 3.56 [95% CI 1.59, 7.98]; p = 0.002) and a reduced risk for increased ASM load (risk ratio: 0.36 [95% CI 0.21, 0.62]; p = 0.0002). There was no difference in the odds of discontinuation or the rate of SAEs between VNS versus comparators. This meta-analysis demonstrated the benefits of VNS Therapy in people with DRE, which included improvement in seizure frequency without an increase in the rate of SAEs or discontinuations, thereby supporting the consideration of VNS Therapy for people who are not responding to ASMs and those unsuitable or unwilling to undergo surgery.

SUDEP in adults and children

Sudden unexpected death in epilepsy (SUDEP) represents an important cause of death in patients with epilepsy and it exceeds the expected rate of sudden death in the general population by nearly 24 times. We searched the electronic databases (Cochrane, EMBASE, Scopus, Medline, Pubmed) for studies related to etiology and risk stratification of SUDEP including data on Takotsubo cardiomyopathy (TKC) following seizures resulting in death or near death.: SUDEP is more common among males in the fourth decade of life. Risk for SUDEP is increased by early onset of seizures, low IQ, generalised tonic clonic seizures, nocturnal seizures and seizure frequency. Nonadherance to antiepileptic medications, absence of therapeutic drug level monitoring, presence of neuropathological lesions on imaging and certain subgroups like Dravet syndrome increase its risk. The risk for premature death in patients undergoing temporal lobe resection for drug resistant epilepsy decreased over time but remained above the standard population. Prolonged postictal electroencephalographic suppression was a risk factor for SUDEP in patients with generalised seizures which may indicate a cerebral electrical shutdown. Documented ictal/postictal hypoventilation, laryngeal spasm and cardiac rhythm abnormalities prior to SUDEP may suggest central apnea, neurogenic pulmonary edema, cardiac arrhythmia, or a combination of the above as a cause. Seizure triggered TKC does not seem to play a major role in the pathogenesis of SUDEP.

Anxiety and Depression in School-going children with Epilepsy

Background: This study was designed to find the prevalence of anxiety and depression in school-going children with epilepsy.Methods:All the patients with epilepsy presenting during the study period underwent detailed clinical and EEG evaluation. Hospital Anxiety and Depression score (HADS) was used to screen for anxiety and depression.Results:We identified 190 patients with epilepsy during the study period. Out of these 30 (15.8%) were diagnosed as having treatment resistance epilepsy. Anxiety was diagnosed in 114 (60%) and depression in 62 (32.6%). Patients with drug resistant epilepsy were found to have statistically significant markers in the form of higher scores for depression and anxiety, and lower IQ scores. Frequency of GTCS (Generaized Tonic Clonic Seizures) showed inverse correlation with IQ scores and direct correlation to the anxiety/depression scores.Conclusion:We conclude that anxiety and depression in school-going children with epilepsy is common and that it has a correlation with treatment resistance.

Development of a clinical model to predict vagus nerve stimulation response in pediatric patients with drug-resistant epilepsy

Introduction Epilepsy impacts 470,000 children in the United States, and children with epilepsy are estimated to expend 6 times more on healthcare than those without epilepsy. For patients with antiseizure medication (ASM)-resistant epilepsy and unresectable seizure foci, vagus nerve stimulation (VNS) is a treatment option. Predicting response to VNS has been historically challenging. We aimed to create a clinical prediction score which could be utilized in a routine outpatient clinical setting. Methods We performed an 11-year, single-center retrospective analysis of patients <21 years old with ASM-resistant epilepsy who underwent VNS. The primary outcome was >50% seizure frequency reduction after one year. Univariate and multivariate logistic regressions were performed to assess clinical factors associated with VNS response; 70% and 30% of the sample were used to train and validate the multivariate model, respectively. A prediction score was developed based on the multivariate regression. Sensitivity, specificity, and area under the receiver operating curve (AUC) were calculated. Results This analysis included 365 patients. Multivariate logistic regression revealed that variables associated with VNS response were: <4 years of epilepsy duration before VNS (p=0.008) and focal motor seizures (p=0.037). The variables included in the clinical prediction score were: epilepsy duration before VNS, age at seizure onset, number of pre-VNS ASMs, if VNS was the patient's first therapeutic epilepsy surgery, and predominant seizure semiology. The final AUC was 0.7013 for the "fitted" sample and 0.6159 for the "validation" sample. Conclusions We developed a clinical model to predict VNS response in one of the largest samples of pediatric VNS patients to date. While the presented clinical prediction model demonstrated an acceptable AUC in the training cohort, clinical variables alone likely do not accurately predict VNS response. This score may be useful upon further validation, though its predictive ability underscores the need for more robust biomarkers of treatment response.

Localization of irritative zones in epilepsy with thermochromic silicone

Background: During epilepsy surgery, the gold standard to identify irritative zones (IZ) is electrocorticography (ECoG); however, new techniques are being developed to detect IZ in epilepsy surgery and in neurosurgery in general, such as infrared thermography mapping (ITM), and the use of thermosensitive/thermochromic materials. Methods: In a cohort study of consecutive patients with focal drug-resistant epilepsy of the temporal lobe treated with surgery, we evaluated possible adverse effects to the transient placement of a thermochromic/thermosensitive silicone (TTS) on the cerebral cortex and their postoperative evolution. Furthermore, we compared the precision of TTS for detecting cortical IZ against the gold standard ECoG and with ITM, as proof of concept. Results: We included 10 consecutive patients, 6 women (60%) and 4 men (40%). Age ranges from 15 to 56 years, mean 33.2 years. All were treated with unilateral temporal functional lobectomy. The mean hospital stay was 4 days. There were no immediate or late complications associated with the use of any of the modalities described. In the 10 patients, we obtained consistency in locating the IZ with ECoG, ITM, and the TTS. Conclusion: The TTS demonstrated biosecurity in this series. The accuracy of the TTS to locate IZ was similar to that of ECoG and ITM in this study. More extensive studies are required to determine its sensitivity and specificity.

BICS01 Mediates Reversible Anti-seizure Effects in Brain Slice Models of Epilepsy

Drug-resistant epilepsy remains a significant clinical and societal burden, with one third of people with epilepsy continuing to experience seizures despite the availability of around 30 anti-seizure drugs (ASDs). Further, ASDs often have substantial adverse effects, including impacts on learning and memory. Therefore, it is important to develop new ASDs, which may be more potent or better tolerated. Here, we report the preliminary preclinical evaluation of BICS01, a synthetic product based on a natural compound, as a potential ASD. To model seizure-like activity in vitro, we prepared hippocampal slices from adult male Sprague Dawley rats, and elicited epileptiform bursting using high extracellular potassium. BICS01 (200 μM) rapidly and reversibly reduced the frequency of epileptiform bursting but did not change broad measures of network excitability or affect short-term synaptic facilitation. BICS01 was well tolerated following systemic injection at up to 1,000 mg/kg. However, we did not observe any protective effect of systemic BICS01 injection against acute seizures evoked by pentylenetetrazol. These results indicate that BICS01 is able to acutely reduce epileptiform activity in hippocampal networks. Further preclinical development studies to enhance pharmacokinetics and accumulation in the brain, as well as studies to understand the mechanism of action, are now required.

Efficacy and Safety of VNS Therapy or Continued Medication Management for Treatment of Adults with Drug-Resistant Epilepsy: Systematic Review and Meta-Analysis

Vagus nerve stimulation (VNS) Therapy® is an adjunctive neurostimulation treatment for people withdrug-resistant epilepsy (DRE) who are unwilling to undergo resective surgery, have had unsuccessfulsurgery or are unsuitable for surgery. A systematic review and meta-analysis were conducted todetermine the treatment effects of VNS Therapy as an adjunct to anti-seizure medications (ASMs) forthe management of adults with DRE.A literature search was performed in August 2020 of the Medline®, Medline® Epub Ahead of Print,Embase, and the Cochrane library databases. Outcomes examined included reduction in seizurefrequency, seizure freedom, ASM load, discontinuations, and serious adverse events (SAEs).Comparators included best medical practice, ASMs, low-stimulation or sham VNS Therapy.Four RCTs and six comparative observational studies were identified for inclusion. Against comparators,individuals treated with VNS had a significantly better odds of experiencing a ≥50% reduction in seizurefrequency (OR: 2.27 [95% CI: 1.47, 3.51]; p=0.0002), a ≥75% reduction in seizure frequency (OR: 3.56[95% CI: 1.59, 7.98]; p=0.002) and a reduced risk for increased ASM load (risk ratio: 0.36 [95% CI: 0.21,0.62]; p=0.0002). There was no difference in the odds of discontinuation or the rate of SAEs betweenVNS versus comparators.This meta-analysis demonstrated the benefits of VNS Therapy in people with DRE, which includedimprovement in seizure frequency without an increase in the rate of SAEs or discontinuations, therebysupporting the consideration of VNS Therapy for people who are not responding to ASMs and thoseunsuitable or unwilling to undergo surgery.

Seizure Prediction With HIVE-CODAs: The Hierarchical Vote Collective of Domain Adaptation Methods

Epileptic seizure prediction is one of the most used therapeutic adjuvant strategies for drug-resistant epilepsy. Conventional methods are usually trained and tested on the same patient due to the interindividual variability. However, the challenging problem of the domain shift between different subjects remains unsolved, resulting in low prevalence of clinical application. In this study, a generic model based on the domain adaptation (DA) technique is proposed to alleviate such problems. Ensemble learning is employed by developing a hierarchical vote collective of seven DA modules over multi-modality data, such that the predictive performance is improved by training multiple models. Moreover, to increase the feasibility of its implementation, this study mimics the data distribution of clinical sampling and tests the model under this simulated realistic condition. Based on the performance of seven subnetworks, the applicability of each DA algorithm for seizure prediction is evaluated, which is the first study that provides the assessment. Experimental results on both intracranial and scalp EEG databases demonstrate that this method can reduce the domain gap effectively compared with previous studies.

Interictal SEEG resting-state connectivity localizes seizure onset zone and predicts seizure outcome

Stereotactic-electroencephalography (SEEG) is a common neurosurgical method to localize epileptogenic zone in drug resistant epilepsy patients and inform treatment recommendations. In the current clinical practice, localization of epileptogenic zone typically requires prolonged recordings to capture seizure, which may take days to weeks. Although epilepsy surgery has been proven to be effective in general, the percentage of unsatisfactory seizure outcomes is still concerning. We developed a method to identify the seizure onset zone (SOZ) and predict seizure outcome using short-time resting-state SEEG data. In a cohort of 43 drug resistant epilepsy patients, we estimated the information flow via directional connectivity and inferred the excitation-inhibition ratio from the 1/f power slope. We hypothesized that the antagonism of information flow at multiple frequencies between SOZ and non-SOZ underlying the relatively stable epilepsy resting state could be related to the disrupted excitation-inhibition balance. We found higher excitability in non-SOZ regions compared to the SOZ, with dominant information flow from non-SOZ to SOZ regions, probably reflecting inhibitory input from non-SOZ to prevent seizure initiation. Greater differences in information flow between SOZ and non-SOZ regions were associated with favorable seizure outcome. By integrating a balanced random forest model with resting-state connectivity, our method localized the SOZ with an accuracy of 85% and predicted the seizure outcome with an accuracy of 77% using clinically determined SOZ. Overall, our study suggests that brief resting-state SEEG data can significantly facilitate the identification of SOZ and may eventually predict seizure outcomes without requiring long-term ictal recordings.