Circadian distribution of epileptiform discharges in epilepsy: Candidate mechanisms of variability.

Epilepsy is a serious neurological disorder characterised by a tendency to have recurrent, spontaneous, seizures. Classically, seizures are assumed to occur at random. However, recent research has uncovered underlying rhythms both in seizures and in key signatures of epilepsy-so-called interictal epileptiform activity-with timescales that vary from hours and days through to months. Understanding the physiological mechanisms that determine these rhythmic patterns of epileptiform discharges remains an open question. Many people with epilepsy identify precipitants of their seizures, the most common of which include stress, sleep deprivation and fatigue. To quantify the impact of these physiological factors, we analysed 24-hour EEG recordings from a cohort of 107 people with idiopathic generalized epilepsy. We found two subgroups with distinct distributions of epileptiform discharges: one with highest incidence during sleep and the other during day-time. We interrogated these data using a mathematical model that describes the transitions between background and epileptiform activity in large-scale brain networks. This model was extended to include a time-dependent forcing term, where the excitability of nodes within the network could be modulated by other factors. We calibrated this forcing term using independently-collected human cortisol (the primary stress-responsive hormone characterised by circadian and ultradian patterns of secretion) data and sleep-staged EEG from healthy human participants. We found that either the dynamics of cortisol or sleep stage transition, or a combination of both, could explain most of the observed distributions of epileptiform discharges. Our findings provide conceptual evidence for the existence of underlying physiological drivers of rhythms of epileptiform discharges. These findings should motivate future research to explore these mechanisms in carefully designed experiments using animal models or people with epilepsy.

Diagnostic utility of prolonged ambulatory video-electroencephalography monitoring.

OBJECTIVES: Ambulatory video-electroencephalography (video-EEG) represents a low-cost, convenient and accessible alternative to inpatient video-EEG monitoring, however few studies have examined their diagnostic yield. In this large-scale retrospective study conducted in Australia, we evaluated the efficacy of prolonged ambulatory video-EEG recordings in capturing diagnostic events and resolving the referring question. METHODS: Sequential adult and paediatric ambulatory video-EEG reports from April 2020 to June 2021 were reviewed retrospectively. Data collection included patient demographics, clinical information, and details of events and EEG abnormalities. Clinical utility was assessed by examining i) time to first diagnostic event, and ii) ability to resolve the referring questions - seizure localisation, quantification, classification, and differentiation (differentiating seizures from non-epileptic events). RESULTS: Of the 600 reports analysed, 49 % captured at least one event, and 45 % captured interictal abnormalities (epileptiform or non-epileptiform). Seizures, probable psychogenic events (mostly non-convulsive), and other non-epileptic events occurred in 13 %, 23 % and 21 % of recordings respectively, with overlap. Unreported events were captured in 53 (9 %) recordings, and unreported seizures represented more than half of all seizures captured (51 %, 392/773). Nine percent of events were missing clinical, video or electrographic data. A diagnostic event occurred in 244 (41 %) recordings, of which 14 % were captured between the fifth and eighth day of recording. Reported event frequency ≥ 1/week was the only significant predictor of diagnostic event capture. In recordings with both seizures and psychogenic events, unrecognized seizures were frequent, and seizures may be missed if recording is terminated early. The referring question was resolved in 85 % of reports with at least one event, and 53 % of all reports. Specifically, this represented 46 % of reports (235/512) for differentiation of events, and 75 % of reports (27/36) for classification of seizures. CONCLUSION: Ambulatory video-EEG recordings are of high diagnostic value in capturing clinically relevant events and resolving the referring clinical questions.

Language impairments in seropositive and seronegative autoimmune encephalitis.

BACKGROUND AND OBJECTIVE: Autoimmune encephalitis (AE) is a rare neuroinflammatory disease affecting the central nervous system. To examine language functions in patients with different subsets of AE consisting of seropositive and seronegative groups. METHODS: Fifty-two patients were recruited from neurology departments in Melbourne, Australia, who met clinical criteria for possible AE. Language tests include the Naming Test from the Sydney Language Battery (SydBat), the semantic fluency trial from the Controlled Oral Word Association Test (COWAT), and the Vocabulary and Similarities subtests of the Weschler Abbreviated Scale of Intelligence-Second Edition. The results were standardised with normative data. RESULTS: The mean age of our cohort was 52.5 years old, with the average time from hospital admission to recruitment being 38.41 months. At an aggregate level, none of the mean language test z-scores were below normative data. At the patient level, impairment rates were 18.37% for COWAT (animals), 28.57% for SydBat (naming), 4.65% for Similarities, and 4.55% for Vocabulary. Chi-squared goodness of fit tests indicated that observed performances were significantly below expected performances for the SydBat (naming) test (p < 0.0001) and COWAT (animals) (p = 0.004). DISCUSSION: While, on average, language functions were within normal limits in patients with AE, but a subgroup exhibited lower performance in semantic fluency and visual confrontation naming, with impairment rates below expected norms. To advance understanding of language in chronic AE patients, exploring the impact of seizure burden, antiseizure medication use, and the relationship of language functions with other cognitive functions is crucial.

Peripheral monocytes and soluble biomarkers in autoimmune encephalitis.

BACKGROUND AND OBJECTIVES: Autoimmune encephalitis (AE) is an inflammatory disease of the central nervous system which can result in long-term seizures and cognitive dysfunction despite treatment with immunotherapy. The role of the innate immune system in AE is not well established. To investigate the contribution of innate immunity to AE and its long-term outcomes we evaluated peripheral monocytes and serum cytokines in the periphery of patients with AE. METHODS AND RESULTS: We recruited 40 patients with previously diagnosed AE and 28 healthy volunteers to our cross-sectional observation study and evaluated their peripheral blood monocytes via flow cytometry and serum cytokines (CCL-2, CCL-17, G-CSF, GM-CSF, IFNγ, IL-1α, IL-1ß, IL-2, IL-4, IL-5, IL-6, IL-10, IL-17, TNFα) via ELISA.Compared with controls the AE cohort had expansion of the 'pro-inflammatory' CD14+CD16+ monocyte sub-population (7.13% vs 5.46%, p < 0.01) with higher levels of serum IL-6 (2.34 pg/mL vs 0.54 pg/mL, p < 0.001). These changes were most significant in anti-LGI-1 antibody mediated AE, an AE subtype with poor long-term cognitive outcomes. CONCLUSION: Expansion of the peripheral CD14+CD16+ monocyte population and increased serum IL-6 in AE is reflective of changes seen in other systemic inflammatory and neurodegenerative conditions. These changes may indicate a persistent pro-inflammatory state in AE and may contribute to poor long-term outcomes.

A cross-sectional investigation of cognition and epileptiform discharges in juvenile absence epilepsy.

OBJECTIVES: Despite the prevalence of cognitive symptoms in the idiopathic generalized epilepsies (IGEs), cognitive dysfunction in juvenile absence epilepsy (JAE), a common yet understudied IGE subtype, remains poorly understood. This descriptive study provides a novel, comprehensive characterization of cognitive functioning in a JAE sample and examines the relationship between cognition and 24-h epileptiform discharge load. METHOD: Forty-four individuals diagnosed with JAE underwent cognitive assessment using Woodcock Johnson III Test of Cognitive Abilities with concurrent 24-h ambulatory EEG monitoring. Generalized epileptiform discharges of any length, and prolonged generalized discharges ≥3 s were quantified across wakefulness and sleep. The relationship between standardized cognitive scores and epileptiform discharges was assessed through regression models. RESULTS: Cognitive performances in overall intellectual ability, acquired comprehension-knowledge, processing speed, long-term memory storage and retrieval, and executive processes were 0.63-1.07 standard deviation (SD) units lower in the JAE group compared to the population reference mean, adjusted for educational attainment. Prolonged discharges (≥3 s) were recorded in 20 patients (47.6%) from 42 available electroencephalography (EEG) studies and were largely unreported. Duration and number of prolonged discharges were associated with reduced processing speed and long-term memory storage and retrieval. SIGNIFICANCE: Cognitive dysfunction is seen in patients with JAE across various cognitive abilities, including those representing more stable processes like general intellect. During 24-h EEG, prolonged epileptiform discharges are common yet underreported in JAE despite treatment, and they show moderate effects on cognitive abilities. If epileptiform burden is a modifiable predictor of cognitive dysfunction, therapeutic interventions should consider quantitative 24-h EEG with routine neuropsychological screening. The growing recognition of the spectrum of neuropsychological comorbidities of IGE highlights the value of multidisciplinary approaches to explore the causes and consequences of cognitive deficits in epilepsy.

Seizure-induced reversible magnetic resonance imaging abnormalities: A retrospective cohort study.

PURPOSE: Seizure-induced reversible magnetic resonance imaging (MRI) abnormalities (SRMA) present challenges in seizure management. We sought to investigate the frequency, risk factors, evolution and prognostic value of SRMA. METHODS: A retrospective observational cohort study of consecutive seizure patients investigated with an MRI of the brain was conducted. Clinical and MRI data were reviewed to determine the clinical characteristics and imaging findings of SRMA. Outcomes (seizure freedom versus uncontrolled seizures and deaths) were assessed upon the last clinic follow-up. Mann-Whitney U test and chi-square test for independence with Bonferroni correction were used to explore the statistical significance of predictive factors. RESULTS: The study included 483 consecutive seizure patients with 7.6% developing SRMA. Patients with SRMA were older (median age 57 years, interquartile range-IQR 52-66, p < 0.001) and experienced longer seizures (median 5 minutes, IQR 2-15, p = 0.002) compared with seizure patients with normal MRI. Seizure type (provoked versus unprovoked), recurrence (first versus recurrent) and epileptiform EEG changes did not demonstrate a significant association. Diffusion restriction and ADC reduction observed in SRMA resolved earlier, while T2, FLAIR hyperintensities and temporal lobes changes persisted longer on follow-up scans. The median time interval from seizure to complete resolution of SRMA was 87 days (IQR 45-225). No statistical difference in outcomes was seen between patients with SRMA and normal MRIs (p = 0.19). CONCLUSIONS: SRMA is an uncommon finding following seizures. It is not associated with poor seizure control or mortality. Risk factors associated with SRMA include older age and longer seizure duration including status epilepticus.

The efficacy and tolerability of adjunctive brivaracetam for the treatment of adult epilepsy: An Australian multi-center retrospective real-world observational cohort study.

OBJECTIVE: Assess the efficacy and tolerability of add-on therapy brivaracetam (BRV) in adult patients with epilepsy in a real-world setting. METHODS: This multi-center retrospective observational cohort study examined all adult patients who commenced on BRV at 11 Australian epilepsy centers between 2017 and 2020. Primary outcomes were seizure response (≥50% reduction in frequency) and seizure freedom 12 months post BRV commencement, and tolerability. We report three approaches to missing data (complete case analysis, CCA; last observation carried forward, LOCF; and intention to treat, ITT). Secondary outcomes included the durability of early BRV response and continuous seizure freedom from BRV initiation. Subgroup analysis examined patients with focal and generalized epilepsy and patients with refractory (≥4 prior ASMs) and highly refractory (≥7 prior ASMs) epilepsy. Outcomes were also assessed at 'personalized' seizure outcome time points based on baseline seizure frequency. RESULTS: Baseline and follow-up data were available for 228 patients. The mean age was 41.5 years (IQR 30, 50). Most had focal epilepsy (188/228, 82.5%). Median number of previous ASMs was 4 (2, 7), and concomitant ASMs 2 (2, 3). Twelve-month responder rate was: 46.3% using CCA (95% CI 34.0, 58.9); 39.5% using LOCF (33.1, 46.1); and 15.4% using ITT (10.9, 20.7). Twelve-month seizure freedom was: 23.9% using CCA (14.3, 35.9); 24.6% using LOCF (19.1, 30.7); and 7.9% using ITT (4.7, 12.1). The most frequent adverse effects were sedation or cognitive slowing (33/228, 14.5%), irritability or aggression (16/228, 7.0%), and low mood (14/228, 6.1%). Outcomes were similar using continuous outcome definitions and 'personalized' outcome assessment time points. Early responses were highly durable, with 3-month response maintained at all subsequent time points at 83%, and seizure freedom maintained at 85%. Outcomes were similar in focal (n = 187) and generalizsed (n = 25) subgroups. Outcomes were similar in refractory patients (n = 129), but lower in the highly refractory group (n = 62), however improvement with BRV was still observed with 12-month seizure freedom of 8.3% using CCA (1.0, 27), 6.5% using LOCF (1.8, 15.7); and 3.2% using ITT (0.4, 11.2). CONCLUSIONS: Meaningful real-world responder and seizure freedom rates can be still observed in a refractory epilepsy population. Brivaracetam response can occur early and appears to be maintained with minimal later relapse. The results should be interpreted with caution given the retrospective nature of the study and the quantities of missing data at later time points.

Neuroimaging characteristics may aid in diagnosis, subtyping, and prognosis in autoimmune encephalitis.

OBJECTIVE: To examine the utility of neuroimaging characteristics as biomarkers of prognosis in seropositive autoimmune encephalitis (AE). METHODS: In this multi-center study, we retrospectively analyzed 66 cases of seropositive AE. The MRI and PET imaging was assessed by independent visual inspection. Whole brain and regional volumes were imputed by IcoMetrix, an automated volumetric assessment package. The modified Rankin Scale (mRS) was utilized to assess the patients' follow-up disability. Other outcomes were mortality, first line treatment failure, medial temporal lobe (MTL) atrophy, and clinical relapse. Univariate and multivariable regression analysis was performed. RESULTS: Abnormalities on MRI were detected in 35.1% of patients, while PET was abnormal in 46.4%. Initial median whole brain and hippocampal volumes were below the 5th and 20th percentile respectively compared to an age-matched healthy database. After a median follow-up of 715 days, 85.2% had good functional outcome (mRS ≤ 2). Nine patients developed MTL atrophy during follow-up. On multivariable analysis, inflammatory MTL changes were associated with development of MTL atrophy (HR 19.6, p = 0.007) and initial hippocampal volume had an inverse relationship with mortality (HR 0.04, p = 0.011). Patients who developed MTL atrophy had a reduced chance of good final mRS (HR 0.16, p = 0.015). CONCLUSIONS: Neuroimaging on initial hospital admission may be provide important diagnostic and prognostic information. This study demonstrates that structural and inflammatory changes of the MTL may have importance in clinical and radiological prognosis in seropositive AE.

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.

Psychometric deficits in autoimmune encephalitis: A retrospective study from the Australian Autoimmune Encephalitis Consortium.

BACKGROUND AND PURPOSE: Despite the rapid increase in research examining outcomes in autoimmune encephalitis (AE) patients, there are few cohort studies examining cognitive outcomes in this population. The current study aimed to characterise psychometric outcomes in this population, and explore variables that may predict psychometric outcomes. METHODS: This retrospective observational study collected psychometric data from 59 patients across six secondary and tertiary referral centres in metropolitan hospitals in Victoria, Australia between January 2008 and July 2019. Frequency and pattern analysis were employed to define and characterize psychometric outcomes. Univariable logistic regression was performed to examine predictors of intact and pathological psychometric outcomes. RESULTS: Deficits in psychometric markers of executive dysfunction were the most common finding in this cohort, followed by deficits on tasks sensitive to memory. A total of 54.2% of patients were classified as having psychometric impairments across at least two cognitive domains. Twenty-nine patterns were observed, suggesting outcomes in AE are complex. None of the demographic data, clinical features or auxiliary examination variables were predictors of psychometric outcome. CONCLUSIONS: Cognitive outcomes in AE are complex. Further detailed and standardized cognitive testing, in combination with magnetic resonance imaging volumetrics and serum/cerebrospinal fluid biomarkers, is required to provide rigorous assessments of disease outcomes.

Semiologic differences between bilateral tonic-clonic seizures of focal onset and generalized onset.

BACKGROUND: Focal semiologies have been described in idiopathic generalized epilepsies (IGE) and generalized-onset bilateral tonic-clonic seizures (GBTCS). These focal signs may lead to wrong diagnosis and inappropriate choice of antiseizure medications. We sought to investigate the differences in focal semiologic features between GBTCS and focal-onset bilateral tonic-clonic seizures (FBTCS). METHODS: We retrospectively reviewed video-EEG data of captured GBTCS and FBTCS over a period of five years. The presence or absence of 12 focal signs as well seizure duration and time to head version was tabulated for each seizure. We used the chi-square test for independence and Fisher's exact test to investigate the occurrence of each focal sign in FBTCS compared with GBTCS. Additionally, we used receiver operating characteristic (ROC) curves to explore if the seizure duration and time to head version from the ictal onset can reliably differentiate between FBTCS and GBTCS. Finally, we employed hierarchical cluster analysis to visualize how these focal signs appear in combination. RESULTS: Head version (p <.001), preceding automatisms (p <.001), eye version (p <.001), unilateral facial clonic activity (p <.001), and mouth deviation (p =.004) were found to be significantly more frequent in FBTCS. Longer seizures were highly in favor of FBTCS whereas shorter time to head version from the ictal onset indicated GBTCS in the ROC curve analysis. CONCLUSIONS: Though focal signs occur in GBTCS, careful evaluation of semiology can help the clinician distinguish FBTCS from GBTCS.

Prevalence, risk factors, and prognosis of drug-resistant epilepsy in autoimmune encephalitis.

OBJECTIVE: To evaluate the prevalence and biomarkers of drug-resistant epilepsy (DRE) in patients with autoimmune encephalitis (AIE). METHODS: Sixty-nine patients with AIE were recruited retrospectively and electroencephalographies (EEGs) were reviewed using a standard reporting proforma. Associations between EEG biomarkers and DRE development at 12 months were examined using logistic regression modeling and were utilized to create a DRE risk score. RESULTS: Sixteen percent of patients with AIE developed DRE at 12-month follow-up. The presence of status epilepticus (SE) (OR 11.50, 95% CI [2.81, 51.86], p-value <0.001), temporal lobe focality (OR 9.90, 95% CI [2.60, 50.71], p-value 0.001) and periodic discharges (OR 19.12, 95% CI [3.79, 191.10], p-value 0.001) on the admission EEG were associated with the development of DRE at 12 months. These variables were utilized to create a clinically applicable risk score for the prediction of DRE development. CONCLUSIONS: Drug-resistant epilepsy is an infrequent complication of AIE. Electroencephalography changes during the acute illness can predict the risk of DRE at 12 months post-acute AIE. SIGNIFICANCE: The identified EEG biomarkers provide the basis to generate a clinically applicable prediction tool which could be used to inform treatment, prognosis, and select patients for acute treatment trials.

Electroclinical biomarkers of autoimmune encephalitis.

OBJECTIVE: To evaluate the utility of electroencephalography (EEG) changes as diagnostic and prognostic biomarkers in acute autoimmune encephalitis (AIE). METHODS: One hundred and thirty-one patients with AIE were recruited retrospectively across 7 hospitals. Clinical data were collected during admission and at 12 months. EEGs were reviewed using a standard reporting proforma. Associations between EEG biomarkers, AIE subtypes, and clinical outcomes were assessed using logistic regression modeling. RESULTS: Presence of superimposed fast activity (OR 34.33; 95% CI 3.90, 4527.27; p < 0.001), fluctuating EEG abnormality (OR 6.60; 95% CI 1.60, 37.59; p = 0.008), and hemispheric focality (OR 28.48; 95% CI 3.14, 3773.14; p < 0.001) were significantly more common in N-methyl-d-aspartate receptor (NMDAR) antibody-associated patients with AIE compared to other AIE subtypes. Abnormal background rhythm was associated with a poor mRS (modified Rankin score) at discharge (OR 0.29; 95% CI 0.10, 0.75; p = 0.01) and improvement in mRS at 12 months compared with admission mRS (3.72; 95% CI 1.14, 15.23; p = 0.04). SIGNIFICANCE: We have identified EEG biomarkers that differentiate NMDAR AIE from other subtypes. We have also demonstrated EEG biomarkers that are associated with poor functional outcomes.

Revisiting an ancient legend: influence of the lunar cycle on occurrence of first-ever unprovoked seizures.

BACKGROUND: The mythical effect of the lunar cycle on seizures has been debated over time. Previously healthy individuals presenting with first-ever seizures in whom investigations are negative often invoke questions about potential reasons including a full moon. AIMS: To determine whether there is a temporal relationship between the occurrence of the first-ever unprovoked seizure and the lunar cycle. METHODS: We studied adults who presented with a first-ever unprovoked seizure to two tertiary centres in Australia. Seizure onset time was obtained from the emergency department and ambulance documentations. We used Poisson regression modelling and incidence rate ratios (IRR) to determine whether seizures have a preponderance for a particular lunar phase. We performed further analysis on 'first seizure epilepsy' and 'first seizure not epilepsy' subgroups based on the International League Against Epilepsy criteria for a diagnosis of epilepsy after a single unprovoked seizure. RESULTS: We analysed 1710 patients (38% females; median age 39 years), of whom 18% had epileptiform abnormalities on electroencephalogram (EEG) and potentially epileptogenic lesions were detected on neuroimaging in 28%. Based on the EEG and imaging findings, 684 (40%) patients were categorised as 'first seizure epilepsy' and 1026 (60%) 'first seizure not epilepsy'. The whole cohort and subgroup analysis demonstrated no significant difference in the seizure occurrence among the four lunar quarters. CONCLUSIONS: First unprovoked seizures are not influenced by the lunar cycle. Patients pondering the cause of their first-ever unprovoked seizure can be reassured that the full moon was not responsible.

Domino-like transient dynamics at seizure onset in epilepsy.

The International League Against Epilepsy (ILAE) groups seizures into "focal", "generalized" and "unknown" based on whether the seizure onset is confined to a brain region in one hemisphere, arises in several brain region simultaneously, or is not known, respectively. This separation fails to account for the rich diversity of clinically and experimentally observed spatiotemporal patterns of seizure onset and even less so for the properties of the brain networks generating them. We consider three different patterns of domino-like seizure onset in Idiopathic Generalized Epilepsy (IGE) and present a novel approach to classification of seizures. To understand how these patterns are generated on networks requires understanding of the relationship between intrinsic node dynamics and coupling between nodes in the presence of noise, which currently is unknown. We investigate this interplay here in the framework of domino-like recruitment across a network. In particular, we use a phenomenological model of seizure onset with heterogeneous coupling and node properties, and show that in combination they generate a range of domino-like onset patterns observed in the IGE seizures. We further explore the individual contribution of heterogeneous node dynamics and coupling by interpreting in-vitro experimental data in which the speed of onset can be chemically modulated. This work contributes to a better understanding of possible drivers for the spatiotemporal patterns observed at seizure onset and may ultimately contribute to a more personalized approach to classification of seizure types in clinical practice.

Temporal patterns in the first unprovoked seizure.

OBJECTIVE: Cyclic phenomena in epilepsy are well recognized. We investigated a multicenter cohort of unprovoked first seizure presentations to determine whether seizures have a preponderance to occur in: a particular time of the day, a particular day of the week, a particular month of the year, day time versus night time, and wakefulness versus sleep. METHODS: We retrospectively studied adults who presented with a first-ever unprovoked seizure to the First Seizure Clinic at two tertiary centers in Australia. Seizure onset time was obtained from the emergency department and ambulance documentations. Electro-clinical and neuroimaging findings were reviewed. We used histograms and Poisson regression modeling to determine whether seizures have a preponderance to occur at a particular time and calculated incidence rate ratios (IRR). We performed further analysis on patients with "first seizure epilepsy" and "first seizure not epilepsy" based on the ILAE criteria for a diagnosis of epilepsy after a single unprovoked seizure, as well as comparing patients that could be categorized as having a generalized-onset seizure versus those with focal-onset seizures. RESULTS: We analyzed 1724 patients (38% females; age range 14-97 yr, median 39 yr), of whom 18% had epileptiform abnormalities on EEG and potentially epileptogenic lesions were detected on neuroimaging in 28%. Whole cohort analysis shows the incidence rate ratios (IRR) of seizures varied significantly across the 24-hour clock-time of the day (p < 0.001), peaking at hour 12 (IRR 3.18). The first unprovoked seizure was significantly less likely to be reported during the night (IRR 0.61, p < 0.001) and during sleep (IRR 0.29, p < 0.001). Both the "first seizure epilepsy" and "first seizure not epilepsy" subgroups' analysis demonstrated similar patterns. An infraradian pattern was also noted with seizures most likely to occur in May (IRR 1.29, p = 0.02). Both "first seizure epilepsy - generalized" and "first seizure epilepsy - focal" groups had a preponderance for seizures to occur during the day versus night and wakefulness as opposed to sleep, but the association was more robust for generalized seizures. CONCLUSIONS: Our results suggest that temporal patterns are seen in patients with first-ever unprovoked seizures, including those that meet contemporary criteria for epilepsy. These results raise the possibility that first unprovoked seizures have intrinsic rhythmicity similar to epileptic seizures.

Can semiology differentiate between bilateral tonic-clonic seizures of focal-onset and generalized-onset? A systematic review.

OBJECTIVE: Bilateral tonic-clonic seizures are encountered in both focal and generalized epilepsies. We reviewed the literature regarding the presence of focal signs in generalized-onset tonic-clonic seizures (GOTCS) and the utility of semiology in differentiating those from focal to bilateral tonic-clonic seizures (FBTCS). METHODS: We conducted a comprehensive literature search using four electronic databases (Medline, Embase, Web of Science, and Psychinfo) and constructed a systematic review in keeping with the Preferred Items for Systematic Reviews and Meta-analyses guidelines. RESULTS: We included 13 studies on focal semiological features of GOTCS. These studies included a total of 952 participants. The key focal signs described in GOTCS included: early head version, figure of four sign, asymmetric seizure termination, and a multitude of auras as well as automatisms. Additionally, we reviewed five studies that investigated the use of semiology to differentiate GOTCS from FBTCS; these studies had a total of 289 participants. Asymmetry in clonic phase, side-to-side axial movements, asymmetrical seizure termination, figure of four sign, index finger pointing, and fanning posture of the hand were found to be significantly more frequent in FBTCS compared with GOTCS. Furthermore, combinations of focal semiological features occurring in a single seizure were found to be suggestive of FBTCS rather than GOTCS. CONCLUSION: Focal signs are often evident in GOTCS. Though the observation of multiple focal signs within a given seizure may be in favor of an FBTCS, our findings caution against differentiating between the two seizure types based on semiology alone due to considerable overlap in focal features.

Long-term mood, quality of life, and seizure freedom in intracranial EEG epilepsy surgery.

OBJECTIVES: To determine the long-term outcomes in patients undergoing intracranial EEG (iEEG) evaluation for epilepsy surgery in terms of seizure freedom, mood, and quality of life at St. Vincent's Hospital, Melbourne. METHODS: Patients who underwent iEEG between 1999 and 2016 were identified. Patients were retrospectively assessed between 2014 and 2017 by specialist clinic record review and telephone survey with standardized validated questionnaires for: 1) seizure freedom using the Engel classification; 2) Mood using the Neurological Disorders Depression Inventory for Epilepsy (NDDI-E); 3) Quality-of-life outcomes using the QOLIE-10 questionnaire. Summary statistics and univariate analysis were performed to investigate variables for significance. RESULTS: Seventy one patients underwent iEEG surgery: 49 Subdural, 14 Depths, 8 Combination with 62/68 (91.9%) of those still alive, available at last follow-up by telephone survey or medical record review (median of 8.2 years). The estimated epileptogenic zone was 62% temporal and 38% extra-temporal. At last follow-up, 69.4% (43/62) were Engel Class I and 30.6% (19/62) were Engel Class II-IV. Further, a depressive episode (NDDI-E > 15)was observed in 34% (16/47), while a 'better quality of life' (QOLIE-10 score < 25) was noted in 74% (31/42). Quality of life (p < 0.001) but not mood (p = 0.24) was associated with seizure freedom. SIGNIFICANCE: Long-term seizure freedom can be observed in patients undergoing complex epilepsy surgery with iEEG evaluation and is associated with good quality of life.

Efficacy and tolerability of adjuvant perampanel: an Australian multicenter real-world observational study in refractory focal and generalized epilepsy syndromes.

PURPOSE: To explore the efficacy and tolerability of adjuvant perampanel (PER) and their associated risk factors in late add-on drug-resistant epilepsy. METHOD: Retrospective multicenter 'real-world' observational study. Consecutively identified patients commenced on PER, with mixed epilepsy syndromes, from nine Australian epilepsy centers. Primary efficacy endpoints were at least 50% reduction in seizure frequency (responders), seizure freedom, and retention at 6 and 12 months, following a 3-month titration period. Tolerability endpoints were cessation of PER for any reason, cessation of PER due to treatment-emergent adverse events (TEAE), or cessation due to inefficacy. Outcomes were assessed for a-priori risk factors associated with efficacy and tolerability. RESULTS: Three-hundred and eighty seven adults were identified and followed up for a median of 12.1 months (IQR 7.0-25.2). Focal epilepsy accounted for 79.6% (FE), idiopathic generalized epilepsy (IGE), 10.3% and developmental epileptic encephalopathy (DEE) 10.1%, of the cohort. All patients had drug-resistant epilepsy, 71.6% had never experienced six months of seizure freedom, and the mean number of antiepileptic medications (AEDs) prior to starting PER was six. At 12 months, with missing cases classified as treatment failure, retention was 40.0%, responder 21.7%, and seizure freedom 9.0%, whereas, using last outcome carried forward (LOCF), responder and seizure freedom rates were 41.3% and 14.7%, respectively. Older age of epilepsy onset was associated with a marginal increase in the likelihood of seizure freedom at 12-month maintenance (OR 1.04, 95% CI 1.02, 1.06). Male sex (adjusted OR [aOR] 2.06 95% CI 1.33, 3.19), lower number of prior AEDs (aOR 0.84, 95% CI 0.74, 0.96) and no previous seizure-free period of at least 6-month duration (aOR 2.04 95% CI 1.21, 3.47) were associated with retention. Perampanel combined with a GABA receptor AED was associated with a lower responder rate at 12 months but reduced cessation of PER. The most common TEAEs were neuropsychiatric (18.86%), followed by dizziness (13.70%), and sleepiness (5.68%). CONCLUSIONS: Adjuvant PER treatment, even in late-add on drug-resistant epilepsy is an effective and well-tolerated treatment for drug-resistant epilepsy.

Computer-assisted EEG diagnostic review for idiopathic generalized epilepsy.

Epilepsy diagnosis can be costly, time-consuming, and not uncommonly inaccurate. The reference standard diagnostic monitoring is continuous video-electroencephalography (EEG) monitoring, ideally capturing all events or concordant interictal discharges. Automating EEG data review would save time and resources, thus enabling more people to receive reference standard monitoring and also potentially heralding a more quantitative approach to therapeutic outcomes. There is substantial research into the automated detection of seizures and epileptic activity from EEG. However, automated detection software is not widely used in the clinic, and despite numerous published algorithms, few methods have regulatory approval for detecting epileptic activity from EEG. This study reports on a deep learning algorithm for computer-assisted EEG review. Deep convolutional neural networks were trained to detect epileptic discharges using a preexisting dataset of over 6000 labelled events in a cohort of 103 patients with idiopathic generalized epilepsy (IGE). Patients underwent 24-hour ambulatory outpatient EEG, and all data were curated and confirmed independently by two epilepsy specialists (Seneviratne et al., 2016). The resulting automated detection algorithm was then used to review diagnostic scalp EEG for seven patients (four with IGE and three with events mimicking seizures) to validate performance in a clinical setting. The automated detection algorithm showed state-of-the-art performance for detecting epileptic activity from clinical EEG, with mean sensitivity of >95% and corresponding mean false positive rate of 1 detection per minute. Importantly, diagnostic case studies showed that the automated detection algorithm reduced human review time by 80%-99%, without compromising event detection or diagnostic accuracy. The presented results demonstrate that computer-assisted review can increase the speed and accuracy of EEG assessment and has the potential to greatly improve therapeutic outcomes. This article is part of the Special Issue "NEWroscience 2018".