Use of Recommended Neurodiagnostic Evaluation Among Patients With Drug-Resistant Epilepsy.

Importance: Interdisciplinary practice parameters recommend that patients with drug-resistant epilepsy (DRE) undergo comprehensive neurodiagnostic evaluation, including presurgical assessment. Reporting from specialized centers suggests long delays to referral and underuse of surgery; however, longitudinal data are limited to characterize neurodiagnostic evaluation among patients with DRE in more diverse US settings and populations. Objective: To examine the rate and factors associated with neurodiagnostic studies and comprehensive evaluation among patients with DRE within 3 US cohorts. Design, Setting, and Participants: A retrospective cross-sectional study was conducted using the Observational Medical Outcomes Partnership Common Data Model including US multistate Medicaid data, commercial claims data, and Columbia University Medical Center (CUMC) electronic health record data. Patients meeting a validated computable phenotype algorithm for DRE between January 1, 2015, and April 1, 2020, were included. No eligible participants were excluded. Exposure: Demographic and clinical variables were queried. Main Outcomes and Measures: The proportion of patients receiving a composite proxy for comprehensive neurodiagnostic evaluation, including (1) magnetic resonance or other advanced brain imaging, (2) video electroencephalography, and (3) neuropsychological evaluation within 2 years of meeting the inclusion criteria. Results: A total of 33 542 patients with DRE were included in the Medicaid cohort, 22 496 in the commercial insurance cohort, and 2741 in the CUMC database. A total of 31 516 patients (53.6%) were women. The proportion of patients meeting the comprehensive evaluation main outcome in the Medicaid cohort was 4.5% (n = 1520); in the commercial insurance cohort, 8.0% (n = 1796); and in the CUMC cohort, 14.3% (n = 393). Video electroencephalography (24.9% Medicaid, 28.4% commercial, 63.2% CUMC) and magnetic resonance imaging of the brain (35.6% Medicaid, 43.4% commercial, 52.6% CUMC) were performed more regularly than neuropsychological evaluation (13.0% Medicaid, 16.6% commercial, 19.2% CUMC) or advanced imaging (3.2% Medicaid, 5.4% commercial, 13.1% CUMC). Factors independently associated with greater odds of evaluation across all 3 data sets included the number of inpatient and outpatient nonemergency epilepsy visits and focal rather than generalized epilepsy. Conclusions and Relevance: The findings of this study suggest there is a gap in the use of diagnostic studies to evaluate patients with DRE. Care setting, insurance type, frequency of nonemergency visits, and epilepsy type are all associated with evaluation. A common data model can be used to measure adherence with best practices across a variety of observational data sources.

Delays in the diagnosis and surgical treatment of drug-resistant epilepsy: A cohort study.

OBJECTIVE: Delay in referral for epilepsy surgery of patients with drug-resistant epilepsy (DRE) is associated with decreased quality of life, worse surgical outcomes, and increased risk of sudden unexplained death in epilepsy (SUDEP). Understanding the potential causes of delays in referral and treatment is crucial for optimizing the referral and treatment process. We evaluated the treatment intervals, demographics, and clinical characteristics of patients referred for surgical evaluation at our level 4 epilepsy center in the U.S. Intermountain West. METHODS: We retrospectively reviewed the records of patients who underwent surgery for DRE between 2012 and 2022. Data collected included patient demographics, DRE diagnosis date, clinical characteristics, insurance status, distance from epilepsy center, date of surgical evaluation, surgical procedure, and intervals between different stages of evaluation. RESULTS: Within our cohort of 185 patients with epilepsy (99 female, 53.5%), the mean ± standard deviation (SD) age at surgery was 38.4 ± 11.9 years. In this cohort, 95.7% of patients had received definitive epilepsy surgery (most frequently neuromodulation procedures) and 4.3% had participated in phase 2 intracranial monitoring but had not yet received definitive surgery. The median (1st-3rd quartile) intervals observed were 10.1 (3.8-21.5) years from epilepsy diagnosis to DRE diagnosis, 16.7 (6.5-28.4) years from epilepsy diagnosis to surgery, and 1.4 (0.6-4.0) years from DRE diagnosis to surgery. We observed significantly shorter median times from epilepsy diagnosis to DRE diagnosis (p < .01) and epilepsy diagnosis to surgery (p < .05) in patients who traveled further for treatment. Patients with public health insurance had a significantly longer time from DRE diagnosis to surgery (p < .001). SIGNIFICANCE: Both shorter distance traveled to our epilepsy center and public health insurance were predictive of delays in diagnosis and treatment intervals. Timely referral of patients with DRE to specialized epilepsy centers for surgery evaluation is crucial, and identifying key factors that may delay referral is paramount to optimizing surgical outcomes.

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.

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

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

Multiscale neuro-inspired models for interpretation of EEG signals in patients with epilepsy.

OBJECTIVE: The aim is to gain insight into the pathophysiological mechanisms underlying interictal epileptiform discharges observed in electroencephalographic (EEG) and stereo-EEG (SEEG, depth electrodes) recordings performed during pre-surgical evaluation of patients with drug-resistant epilepsy. METHODS: We developed novel neuro-inspired computational models of the human cerebral cortex at three different levels of description: i) microscale (detailed neuron models), ii) mesoscale (neuronal mass models) and iii) macroscale (whole brain models). Although conceptually different, micro- and mesoscale models share some similar features, such as the typology of neurons (pyramidal cells and three types of interneurons), their spatial arrangement in cortical layers, and their synaptic connectivity (excitatory and inhibitory). The whole brain model consists of a large-scale network of interconnected neuronal masses, with connectivity based on the human connectome. RESULTS: For these three levels of description, the fine-tuning of free parameters and the quantitative comparison with real data allowed us to reproduce interictal epileptiform discharges with a high degree of fidelity and to formulate hypotheses about the cell- and network-related mechanisms underlying the generation of fast ripples and SEEG-recorded epileptic spikes and spike-waves. CONCLUSIONS: The proposed models provide valuable insights into the pathophysiological mechanisms underlying the generation of epileptic events. The knowledge gained from these models effectively complements the clinical analysis of SEEG data collected during the evaluation of patients with epilepsy. SIGNIFICANCE: These models are likely to play a key role in the mechanistic interpretation of epileptiform activity.

Predictors of medical intractability in children with epilepsy onset during the first two years of life, excluding infantile epileptic spasm syndrome.

PURPOSE: Early childhood epilepsy presents a significant challenge, with approximately 30 % of individuals experiencing treatment failure. This study aimed to identify predictors of medical intractability in children with epilepsy onset during the first two years of life, excluding infantile epileptic spasm syndrome. METHODS: A total of 323 children were retrospectively evaluated. The analyses included a review of medical records for demographic, laboratory, radiological, and electroencephalographic (EEG) findings. Children were diagnosed with drug-resistant epilepsy (DRE) according to the ILAE diagnostic criteria. Twenty-one potential prognostic predictors were examined in relation to medical intractability. RESULTS: Among the 323 children (56.7 % male), 119 (36.8 %) had unknown epilepsy, 131 (40.6 %) had structural epilepsy, 53 (16.4 %) had genetic epilepsy, and 20 (6.2 %) had metabolic epilepsy. Over a median follow-up of 68 months, 55.4 % of the children achieved ≥6 months of seizure freedom, 33.1 % developed DRE, and the remaining 11.5 % had rare ongoing seizures but did not meet the criteria for DRE because they were only treated with one antiseizure medication at the last follow-up. Univariate logistic regression analyses identified ten risk factors significantly associated with DRE. Multivariate logistic regression analyses revealed that the presence of developmental delay at epilepsy onset (p = 0.000; OR 7.890; 95 %CI 2.713 to 22.945), history of status epilepticus (p = 0.000; OR 8.247; 95 %CI 3.619 to 18.793), number of antiseizure medications (ASMs) at the sixth month of diagnosis (p = 0.000; OR 20.585; 95 %CI 8.993 to 47.117), and initial EEG findings (p = 0.046; OR 2.366; 95 %CI 1.015 to 5.518) were predictors of medical intractability. Nineteen (5.9 %) children died during follow-up for various reasons, including progressive neurogenetic or neurodegenerative disorders. CONCLUSION: Developmental delay at epilepsy onset, a history of status epilepticus, the use of two or more ASMs in the sixth month of diagnosis, and abnormal initial EEG findings were associated with medical intractability.

Epileptic tissue localization using graph-based networks in the high frequency oscillation range of intracranial electroencephalography.

PURPOSE: High frequency oscillations (HFOs) are an emerging biomarker of epilepsy. However, very few studies have investigated the functional connectivity of interictal iEEG signals in the frequency range of HFOs. Here, we study the corresponding functional networks using graph theory, and we assess their predictive value for automatic electrode classification in a cohort of 20 drug resistant patients. METHODS: Coherence-based connectivity analysis was performed on the iEEG recordings, and six different local graph measures were computed in both sub-bands of the HFO frequency range (80-250 Hz and 250-500 Hz). Correlation analysis was implemented between the local graph measures and the ripple and fast ripple rates. Finally, the WEKA software was employed for training and testing different predictive models on the aforementioned local graph measures. RESULTS: The ripple rate was significantly correlated with five out of six local graph measures in the functional network. For fast ripples, their rate was also significantly (but negatively) correlated with most of the local metrics. The results from WEKA showed that the Logistic Regression algorithm was able to classify highly HFO-contaminated electrodes with an accuracy of 82.5 % for ripples and 75.4 % for fast ripples. CONCLUSION: Functional connectivity networks in the HFO band could represent an alternative to the direct use of distinct HFO events, while also providing important insights about hub epileptic areas that can represent possible surgical targets. Automatic electrode classification through FC-based classifiers can help bypass the burden of manual HFO annotation, providing at the same time similar amount of information about the epileptic tissue.

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.

Impaired post-sleep apnea autonomic arousals in patients with drug-resistant epilepsy.

OBJECTIVE: Sudden and unexpected deaths in epilepsy (SUDEP) pathophysiology may involve an interaction between respiratory dysfunction and sleep/wake state regulation. We investigated whether patients with epilepsy exhibit impaired sleep apnea-related arousals. METHODS: Patients with drug-resistant (N = 20) or drug-sensitive (N = 20) epilepsy and obstructive sleep apnea, as well as patients with sleep apnea but without epilepsy (controls, N = 20) were included. We explored (1) the respiratory arousal threshold based on nadir oxygen saturation, apnea-hypopnea index, and fraction of hypopnea among respiratory events; (2) the cardiac autonomic response to apnea/hypopnea quantified as percentages of changes from the baseline in RR intervals (RRI), high (HF) and low (LF) frequency powers, and LF/HF. RESULTS: The respiratory arousal threshold did not differ between groups. At arousal onset, RRI decreased (-9.42%) and LF power (179%) and LF/HF ratio (190%) increased. This was followed by an increase in HF power (118%), p < 0.05. The RRI decrease was lower in drug-resistant (-7.40%) than in drug-sensitive patients (-9.94%) and controls (-10.91%), p < 0.05. LF and HF power increases were higher in drug-resistant (188%/126%) than in drug-sensitive patients (172%/126%) and controls (177%/115%), p < 0.05. CONCLUSIONS: Cardiac reactivity following sleep apnea is impaired in drug-resistant epilepsy. SIGNIFICANCE: This autonomic dysfunction might contribute to SUDEP pathophysiology.

Vagus nerve stimulation and heart rate variability: A scoping review of a somatic oscillatory signal.

The goal of this review is to synthesize the literature on vagus nerve stimulator (VNS)-related changes in heart rate variability (HRV) in patients with drug-resistant epilepsy (DRE) and assess the role of these changes in seizure relief. A scoping literature review was performed with the following inclusion criteria: primary articles written in English, involved implantable VNS in humans, and had HRV as a primary outcome. Twenty-nine studies were retrieved, however with considerable heterogeneity in study methods. The overall depression in HRV seen in DRE patients compared to healthy controls persisted even after VNS implant, indicating that achieving "healthy" HRV is not necessary for VNS therapeutic success. Within DRE patients, changes in frequency domain parameters six months after VNS implant returned to baseline after a year. The mechanism of how VNS reduces seizure burden does not appear to be significantly related to alterations in baseline HRV. However, the subtlety of sympathetic/parasympathetic signaling likely requires a more structured approach to experimental and analytic techniques than currently found in the literature.

Ictal Central Apnea Is Predictive of Mesial Temporal Seizure Onset: An Intracranial Investigation.

OBJECTIVE: Ictal central apnea (ICA) is a semiological sign of focal epilepsy, associated with temporal and frontal lobe seizures. In this study, using qualitative and quantitative approaches, we aimed to assess the localizational value of ICA. We also aimed to compare ICA clinical utility in relation to other seizure semiological features of focal epilepsy. METHODS: We analyzed seizures in patients with medically refractory focal epilepsy undergoing intracranial stereotactic electroencephalographic (SEEG) evaluations with simultaneous multimodal cardiorespiratory monitoring. A total of 179 seizures in 72 patients with reliable artifact-free respiratory signal were analyzed. RESULTS: ICA was seen in 55 of 179 (30.7%) seizures. Presence of ICA predicted a mesial temporal seizure onset compared to those without ICA (odds ratio = 3.8, 95% confidence interval = 1.3-11.6, p = 0.01). ICA specificity was 0.82. ICA onset was correlated with increased high-frequency broadband gamma (60-150Hz) activity in specific mesial or basal temporal regions, including amygdala, hippocampus, and fusiform and lingual gyri. Based on our results, ICA has an almost 4-fold greater association with mesial temporal seizure onset zones compared to those without ICA and is highly specific for mesial temporal seizure onset zones. As evidence of symptomatogenic areas, onset-synchronous increase in high gamma activity in mesial or basal temporal structures was seen in early onset ICA, likely representing anatomical substrates for ICA generation. INTERPRETATION: ICA recognition may help anatomoelectroclinical localization of clinical seizure onset to specific mesial and basal temporal brain regions, and the inclusion of these regions in SEEG evaluations may help accurately pinpoint seizure onset zones for resection. ANN NEUROL 2024;95:998-1008.

Frame-based versus robot-assisted stereo-electro-encephalography for drug-resistant epilepsy.

BACKGROUND: Stereoelectroencephalography (SEEG) is an effective presurgical invasive evaluation for drug-resistant epilepsies. The introduction of robotic devices provides a simplified, accurate, and safe alternative to the conventional SEEG technique. We report our institutional experience with robot-assisted SEEG and compare its in vivo accuracy, operation efficiency, and safety with the more traditional SEEG workflow. METHODS: All patients with medically refractory focal epilepsy who underwent SEEG depth electrode implantation between 2014 and 2022 were included in this study. Technical advancements of the robot-assisted technique are described. Analyses of patient demographics, electrode implantation accuracy, operation time, and procedure-related complications were performed. RESULTS: One hundred and sixty-six patients underwent 167 SEEG procedures. The first 141 procedures were performed using a conventional approach involving a Leksell stereotactic system, and the last 26 procedures were robot-assisted. Among the 1726 depth electrodes that were inserted, the median entry point localization error was as follows: conventional (1.0 mm; range, 0.1-33.5 mm) and robot-assisted (1.1 mm; range, 0-4.8 mm) (P = 0.17). The median target point localization error was as follows: conventional (2.8 mm; range, 0.1-49 mm) and robot-assisted (1.8 mm; range, 0-30.3 mm) (P < 0.001). The median operation time was significantly reduced with the robot-assisted workflow (90 min vs. 77.5 min; P < 0.01). Total complication rates were as follows: conventional (17.7%) and robot-assisted (11.5%) (P = 0.57). Major complication rates were 3.5% and 7.7% (P = 0.77), respectively. CONCLUSIONS: SEEG is a safe and highly accurate method that provides essential guidance for epilepsy surgery. Implementing SEEG in conjunction with multimodal planning systems and robotic devices can further increase safety margin, surgical efficiency, and accuracy.

Identifying epilepsy surgery referral candidates with natural language processing in an Australian context.

OBJECTIVE: Epilepsy surgery is known to be underutilized. Machine learning-natural language processing (ML-NLP) may be able to assist with identifying patients suitable for referral for epilepsy surgery evaluation. METHODS: Data were collected from two tertiary hospitals for patients seen in neurology outpatients for whom the diagnosis of "epilepsy" was mentioned. Individual case note review was undertaken to characterize the nature of the diagnoses discussed in these notes, and whether those with epilepsy fulfilled prespecified criteria for epilepsy surgery workup (namely focal drug refractory epilepsy without contraindications). ML-NLP algorithms were then developed using fivefold cross-validation on the first free-text clinic note for each patient to identify these criteria. RESULTS: There were 457 notes included in the study, of which 250 patients had epilepsy. There were 37 (14.8%) individuals who fulfilled the prespecified criteria for epilepsy surgery referral without described contraindications, 32 (12.8%) of whom were not referred for epilepsy surgical evaluation in the given clinic visit. In the prediction of suitability for epilepsy surgery workup using the prespecified criteria, the tested models performed similarly. For example, the random forest model returned an area under the receiver operator characteristic curve of 0.97 (95% confidence interval 0.93-1.0) for this task, sensitivity of 1.0, and specificity of 0.93. SIGNIFICANCE: This study has shown that there are patients in tertiary hospitals in South Australia who fulfill prespecified criteria for epilepsy surgery evaluation who may not have been referred for such evaluation. ML-NLP may assist with the identification of patients suitable for such referral. PLAIN LANGUAGE SUMMARY: Epilepsy surgery is a beneficial treatment for selected individuals with drug-resistant epilepsy. However, it is vastly underutilized. One reason for this underutilization is a lack of prompt referral of possible epilepsy surgery candidates to comprehensive epilepsy centers. Natural language processing, coupled with machine learning, may be able to identify possible epilepsy surgery candidates through the analysis of unstructured clinic notes. This study, conducted in two tertiary hospitals in South Australia, demonstrated that there are individuals who fulfill criteria for epilepsy surgery evaluation referral but have not yet been referred. Machine learning-natural language processing demonstrates promising results in assisting with the identification of such suitable candidates in Australia.

The value of additional electrodes when stereo-electroencephalography is inconclusive.

OBJECTIVE: Stereo-electroencephalography (SEEG) is the preferred method for intracranial localization of the seizure-onset zone (SOZ) in drug-resistant focal epilepsy. Occasionally SEEG evaluation fails to confirm the pre-implantation hypothesis. This leads to a decision tree regarding whether the addition of SEEG electrodes (two-step SEEG - 2sSEEG) or placement of subdural electrodes (SDEs) after SEEG (SEEG2SDE) would help. There is a dearth of literature encompassing this scenario, and here we aimed to characterize outcomes following unplanned two-step intracranial EEG (iEEG). METHODS: All 225 adult SEEG cases over 8 years at our institution were reviewed to extract patient data and outcomes following a two-step evaluation. Three raters independently quantified benefits of additional intracranial electrodes. The relationship between two-step iEEG benefit and clinical outcome was then analyzed. RESULTS: Fourteen patients underwent 2sSEEG and nine underwent SEEG2SDE. In the former cohort, the second SEEG procedure was performed for these reasons-precise localization of the SOZ (36%); defining margins of eloquent cortex (21%); and broadening coverage in the setting of non-localizable seizure onsets (43% of cases). Sixty-four percent of 2sSEEG cases were consistently deemed beneficial (Light's κ = 0.80). 2sSEEG performed for the first two indications was much more beneficial than when onsets were not localizable (100% vs 17%, p = .02). In the SEEG2SDE cohort, SDEs identified the SOZ and enabled delineation of margins relative to eloquent cortex in all cases. SIGNIFICANCE: The two-step iEEG is useful if the initial evaluation is broadly concordant with the original electroclinical hypothesis, where it can clarify onset zones or delineate safe surgical margins; however, it provides minimal benefit when the implantation hypothesis is erroneous, and we recommend that 2sSEEG not be generally utilized in such cases. SDE implantation after SEEG minimizes the need for SDEs and is helpful in delineating surgical boundaries relative to ictal-onset zones and eloquent cortex.

Stereoelectroencephalography: a review of complications and outcomes in a new Australian centre.

BACKGROUND: Surgical management of refractory focal epilepsy requires preoperative localisation of the epileptogenic zone (EZ). To augment noninvasive studies, stereoelectroencephalography (SEEG) is being increasingly adopted as a form of intracranial monitoring. AIMS: This study aimed to determine the rate of complications for patients undergoing SEEG and to report the success of SEEG with regard to EZ detection and seizure outcome following definitive surgery. METHODS: A retrospective cohort design investigated all cases of SEEG at our institution. Surgical, anaesthetic and medical complications with subsequent epilepsy surgery and seizure outcome data were extracted from medical records. Multivariate logistic regression was used to investigate the relationship between both the number of electrodes per patient and the duration of SEEG recording with the rate of complications. RESULTS: Sixty-four patients with 66 implantations were included. Headache was the most common complication (n = 54, 82%). There were no major surgical or medical complications. Two anaesthetic complications occurred. EZ localisation was successful in 63 cases (95%). Curative intent surgery was performed in 39 patients (59%) and 23 patients achieved an Engel class I outcome (59% of those undergoing surgery). The number of electrodes and duration of recording were not associated with complications. CONCLUSIONS: No patients in our series experienced major surgical or medical complications and we have highlighted the challenges associated with neuroanaesthesia in SEEG. Our complication rates and seizure outcomes are equivalent to published literature indicating that this technique can be successfully established in newer centres using careful case selection. Standardised reporting of SEEG complications should be adopted.

NLP-based tools for localization of the epileptogenic zone in patients with drug-resistant focal epilepsy.

Epilepsy surgery is an option for people with focal onset drug-resistant (DR) seizures but a delayed or incorrect diagnosis of epileptogenic zone (EZ) location limits its efficacy. Seizure semiological manifestations and their chronological appearance contain valuable information on the putative EZ location but their interpretation relies on extensive experience. The aim of our work is to support the localization of EZ in DR patients automatically analyzing the semiological description of seizures contained in video-EEG reports. Our sample is composed of 536 descriptions of seizures extracted from Electronic Medical Records of 122 patients. We devised numerical representations of anamnestic records and seizures descriptions, exploiting Natural Language Processing (NLP) techniques, and used them to feed Machine Learning (ML) models. We performed three binary classification tasks: localizing the EZ in the right or left hemisphere, temporal or extra-temporal, and frontal or posterior regions. Our computational pipeline reached performances above 70% in all tasks. These results show that NLP-based numerical representation combined with ML-based classification models may help in localizing the origin of the seizures relying only on seizures-related semiological text data alone. Accurate early recognition of EZ could enable a more appropriate patient management and a faster access to epilepsy surgery to potential candidates.

Expanding eligibility for intracranial electroencephalography using Dexmedetomidine Hydrochloride in children with behavioral dyscontrol.

INTRODUCTION: Invasive intracranial electroencephalography (IEEG) is advantageous for identifying epileptogenic foci in pediatric patients with medically intractable epilepsy. Patients with behavioral challenges due to autism, intellectual disabilities, and hyperactivity have greater difficulty tolerating prolonged IEEG recording and risk injuring themselves or others. There is a need for therapies that increase the safety of IEEG but do not interfere with IEEG recording or prolong hospitalization. Dexmedetomidine Hydrochloride's (DH) use has been reported to improve safety in patients with behavioral challenges during routine surface EEG recording but has not been characterized during IEEG. Here we evaluated DH administration in pediatric patients undergoing IEEG to assess its safety and impact on the IEEG recordings. METHODS: A retrospective review identified all pediatric patients undergoing IEEG between January 2016 and September 2022. Patient demographics, DH administration, DH dose, hospital duration, and IEEG seizure data were analyzed. The number of seizures recorded for each patient was divided by the days each patient was monitored with IEEG. The total number of seizures, as well as seizures per day, were compared between DH and non-DH patients via summary statistics, multivariable linear regression, and univariate analysis. Other data were compared across groups with univariate statistics. RESULTS: Eighty-four pediatric patients met the inclusion criteria. Eighteen (21.4 %) received DH treatment during their IEEG recording. There were no statistical differences between the DH and non-DH groups' demographic data, length of hospital stays, or seizure burden. Non-DH patients had a median age of 12.0 years (interquartile range: 7.25-15.00), while DH-receiving patients had a median age of 8.0 years old (interquartile range: 3.00-13.50) (p = 0.07). The non-DH cohort was 57.6 % male, and the DH cohort was 50.0 % male (p = 0.76). The median length of IEEG recordings was 5.0 days (interquartile range: 4.00-6.25) for DH patients versus 6.0 days (interquartile range: 4.00-8.00) for non-DH patients (p = 0.25). Median total seizures recorded in the non-DH group was 8.0 (interquartile range: 5.00-13.25) versus 15.0 in the DH group (interquartile range: 5.00-22.25) (p = 0.33). Median total seizures per day of IEEG monitoring were comparable across groups: 1.50 (interquartile range: 0.65-3.17) for non-DH patients compared to 2.83 (interquartile range: 0.89-4.35) (p = 0.25) for those who received DH. Lastly, non-DH patients were hospitalized for a median of 8.0 days (interquartile range: 6.00-11.25), while DH patients had a median length of stay of 7.00 days (interquartile range: 5.00-8.25) (p = 0.27). No adverse events were reported because of DH administration. CONCLUSIONS: Administration of DH was not associated with adverse events. Additionally, the frequency of seizures captured on the IEEG, as well as the duration of hospitalization, were not significantly different between patients receiving and not receiving DH during IEEG. Incorporating DH into the management of patients with behavioral dyscontrol and intractable epilepsy may expand the use of IEEG to patients who previously could not tolerate it, improve safety, and preserve epileptic activity during the recording period.

Real-Life Experience With Purified Cannabidiol Treatment for Refractory Epilepsy: A Multicenter Retrospective Study.

BACKGROUND: Drug-resistant epilepsy (DRE) affects the development and quality of life of children and young adults. We analyzed the effectiveness and safety of purified CBD in this population. METHODS: A retrospective analysis of medical records of 139 children and young adults (54.7% female, median age 12.0 years) with DRE treated with purified CBD from 2018 to 2022 at five medical centers in Israel. RESULTS: The most common diagnosis was Lennox-Gastaut syndrome (37.4%) followed by Dravet syndrome (16.5%) and tuberous sclerosis complex (16.5%). Median purified CBD dose was 12.5 mg/kg (range 2.5 to 20.0), and median treatment duration was 9.0 months (range 0.5 to 48.0). Most patients (92.2%) had a reduced seizure frequency following treatment initiation; 41.1% had >50% reduction. Fifty-three patients (38.1%) had positive effects: improved alertness (31.7%), improved speech (10.1%), and achievement of new developmental milestones (2.2%). A multivariate linear model assessing predictive factors for seizure reduction demonstrated that patients previously treated with CBD oils, especially those with >50% seizure reduction on prior treatment, were also more likely to have a reduced seizure frequency while they were treated with purified CBD (P = 0.01, P < 0.0001). Development, diagnosis, age, purified CBD dose (0 to 10 mg/kg/day vs 10 to 20 mg/kg/day), and concomitant treatment with clobazam, valproic acid, or everolimus did not affect seizure reduction by purified CBD. The most common adverse events were irritability (20.9%) and drowsiness (12.9%). CONCLUSION: Purified CBD is well-tolerated and effective in reducing seizure frequency in children and young adults with DRE.

Effectiveness and safety of mono- and add-on perampanel in pediatric patients with epilepsy: Experience from a single-center retrospective study.

OBJECTIVE: To evaluate the effectiveness and safety of perampanel (PER) monotherapy (MT) or add-on therapy (AT) in Chinese children with epilepsy, as well as to evaluate the data from routine therapeutic drug monitoring (TDM) of PER for these pediatric patients. METHODS: This retrospective and observational study was carried out on children with epilepsy (n = 340) from 2020 to 2022 at the Children's Hospital of Nanjing Medical University. Outcome measures were the responder rate (50% or greater seizure reduction), long-term efficacy, and tolerability (number and types of adverse events) in MT and AT groups. Concentrations of plasma PER obtained from these patients, if available, were analyzed too. RESULTS: A total of 279 patients achieved at least 3 months of therapy, and 58.1% responded to PER therapy. 53 of the responders were seizure-free (32.7%). The retention rate dropped from 88.0% at 3 months to 40.6% at 12 months after treatment. Patients with MT achieved better seizure control than those with AT (P < 0.001). Intriguingly, PER exerted a very weak effect on patients who took more than 2 ASMs or were diagnosed with drug-resistant epilepsy. There were no significant differences in tolerability between the two groups. In addition, 179 patients were routinely monitored for PER, and the trough concentrations (C0 ) for these patients ranged from 30.0 to 992.0 ng/mL. However, no significant difference in C0 was observed between responders and nonresponders (333 ng/mL vs 325.5 ng/mL, P = 0.264). SIGNIFICANCE: This study provides effectiveness and safety data on Chinese children with epilepsy treated with PER either as MT or as AT. The efficacy of patients receiving MT was much better than cases administered with more than 2 ASMs or diagnosed with drug-resistant epilepsy. In addition, no association was found between the plasma PER concentration and efficacy or safety. PLAIN LANGUAGE SUMMARY: The study reports the effects of perampanel on seizures and adverse effects in Chinese patients with epilepsy younger than 18 years. Seizures decreased in 58.1% of patients (responders); in a third of these responders, seizures stopped. After treatment was started, 88% of patients were still on perampanel at 3 months and 40.6% at 12 months. People who were treated with perampanel only were more likely to respond than those who received perampanel and other antiseizure treatments, although perampanel was tolerated equally well in these groups. Plasma perampanel concentration did not predict seizure response or adverse effects.

Dancing epilepsy: A stereo encephalography case report.

Ictal semiology is essential to identify the epileptogenic zone (EZ), especially in drug-resistant focal epilepsy (DRE), as its accurate identification determines the surgical prognosis. Dancing is highly unusual ictal semiology, and its underlying neural networks remain somehow unclear since both temporal and frontal lobe (FL) have been implicated in its generation. We present a 21-year-old male with DRE characterized by dancing seizures. Homemade videos were obtained. Through a non-invasive pre-surgical evaluation, the epileptogenic zone was localized within a gross lesion in the left FL. Using stereo electroencephalography (SEEG), we successfully identified the ictal-onset zone in the mesial middle, inferior, and orbito-frontal cortex, with rapid propagation of ictal activity extending backward and laterally to the precentral regions. Subsequently, a left frontal middle and inferior gyrectomy was performed, resulting in seizure freedom for the patient. Pathology results revealed a mild malformation of cortical development with oligodendroglial hyperplasia (MOGHE). Atypical seizure semiology, such as dancing, provides an interesting starting point for the analysis of the areas involved in the EZ. Further intracranial recordings are required to fully comprehend the underlying networks and interactions of cerebral areas during dancing seizures.