Electroencephalographic Abnormalities are Common in COVID-19 and are Associated with Outcomes.

OBJECTIVE: The aim was to determine the prevalence and risk factors for electrographic seizures and other electroencephalographic (EEG) patterns in patients with Coronavirus disease 2019 (COVID-19) undergoing clinically indicated continuous electroencephalogram (cEEG) monitoring and to assess whether EEG findings are associated with outcomes. METHODS: We identified 197 patients with COVID-19 referred for cEEG at 9 participating centers. Medical records and EEG reports were reviewed retrospectively to determine the incidence of and clinical risk factors for seizures and other epileptiform patterns. Multivariate Cox proportional hazards analysis assessed the relationship between EEG patterns and clinical outcomes. RESULTS: Electrographic seizures were detected in 19 (9.6%) patients, including nonconvulsive status epilepticus (NCSE) in 11 (5.6%). Epileptiform abnormalities (either ictal or interictal) were present in 96 (48.7%). Preceding clinical seizures during hospitalization were associated with both electrographic seizures (36.4% in those with vs 8.1% in those without prior clinical seizures, odds ratio [OR] 6.51, p = 0.01) and NCSE (27.3% vs 4.3%, OR 8.34, p = 0.01). A pre-existing intracranial lesion on neuroimaging was associated with NCSE (14.3% vs 3.7%; OR 4.33, p = 0.02). In multivariate analysis of outcomes, electrographic seizures were an independent predictor of in-hospital mortality (hazard ratio [HR] 4.07 [1.44-11.51], p < 0.01). In competing risks analysis, hospital length of stay increased in the presence of NCSE (30 day proportion discharged with vs without NCSE: HR 0.21 [0.03-0.33] vs 0.43 [0.36-0.49]). INTERPRETATION: This multicenter retrospective cohort study demonstrates that seizures and other epileptiform abnormalities are common in patients with COVID-19 undergoing clinically indicated cEEG and are associated with adverse clinical outcomes. ANN NEUROL 2021;89:872-883.

Human Brain Ages With Hierarchy-Selective Attenuation of Prediction Errors.

From the perspective of predictive coding, our brain embodies a hierarchical generative model to realize perception, which proactively predicts the statistical structure of sensory inputs. How are these predictive processes modified as we age? Recent research suggested that aging leads to decreased weighting of sensory inputs and increased reliance on predictions. Here we investigated whether this age-related shift from sensorium to predictions occurs at all levels of hierarchical message passing. We recorded the electroencephalography responses with an auditory local-global paradigm in a cohort of 108 healthy participants from 3 groups: seniors, adults, and adolescents. The detection of local deviancy seems largely preserved in older individuals at earlier latency (including the mismatch negativity followed by the P3a but not the reorienting negativity). In contrast, the detection of global deviancy is clearly compromised in older individuals, as they showed worse task performance and attenuated P3b. Our findings demonstrate that older brains show little decline in sensory (i.e., first-order) prediction errors but significant diminution in contextual (i.e., second-order) prediction errors. Age-related deficient maintenance of auditory information in working memory might affect whether and how lower-level prediction errors propagate to the higher level.

Age-dependent cross frequency coupling features from children to adults during general anesthesia.

BACKGROUND: The frequency coupling characteristics in electroencephalogram (EEG) induced by anesthetics have been well studied in adults, but the investigation of the age-dependent cross frequency coupling features from children to adults is still lacking. METHODS: We analyzed EEG signals recorded from pediatric to adult patients (n = 131), separated into six age groups: <1 year (n = 15), 1-3 years (n = 23), 3-6 years (n = 19), 6-12 years (n = 18), 12-18 years (n = 16), and 18-45 years (n = 40). Age related EEG power and cross frequency coupling analysis (phase amplitude coupling (PAC) and quadratic phase coupling) of data from maintenance of a surgical state of anesthesia (MOSSA) was conducted. Also, for patients of ages less than 6 years, we analyzed the performance of cross frequency coupling derived indices in distinguishing the states of wakefulness, MOSSA, and recovery of consciousness (ROC). RESULTS: (1) During MOSSA, EEG power substantially increased with age from infancy to 3-6 years then decreased with age in the theta-gamma frequency bands. The infant group (<1 year) had the highest slow oscillation (SO) power among all age groups. (2) The distinct PAC pattern is absent in patients less than 1 year of age both in SO-alpha and delta-alpha frequency band coupling during propofol induced unconsciousness. The modulation index between delta and alpha oscillations in MOSSA increased with age. (3) Wavelet bicoherence derived indices reach their peaks in the 3-6 years group and then decrease with age growth. (4) The Diag_En index (normalized entropy of the diagonal bicoherence entries of the bicoherence matrix) performed the best at distinguishing different states for ages less than 6 years (p<0.05). CONCLUSIONS: The combination of propofol induction and sevoflurane maintenance exhibited age-dependent EEG power spectra, PAC, and bicoherence, likely related to brain development. These observations suggest new rules for infant and child brain state monitoring during general anesthesia are needed.

Neurodevelopmental effects of childhood malnutrition: A neuroimaging perspective.

Approximately one in five children worldwide suffers from childhood malnutrition and its complications, including increased susceptibility to inflammation and infectious diseases. Due to improved early interventions, most of these children now survive early malnutrition, even in low-resource settings (LRS). However, many continue to exhibit neurodevelopmental deficits, including low IQ, poor school performance, and behavioral problems over their lifetimes. Most studies have relied on neuropsychological tests, school performance, and mental health and behavioral measures. Few studies, in contrast, have assessed brain structure and function, and to date, these have mainly relied on low-cost techniques, including electroencephalography (EEG) and evoked potentials (ERP). The use of more advanced methods of neuroimaging, including magnetic resonance imaging (MRI) and functional near-infrared spectroscopy (fNIRS), has been limited by cost factors and lack of availability of these technologies in developing countries, where malnutrition is nearly ubiquitous. This report summarizes the current state of knowledge and evidence gaps regarding childhood malnutrition and the study of its impact on neurodevelopment. It may help to inform the development of new strategies to improve the identification, classification, and treatment of neurodevelopmental disabilities in underserved populations at the highest risk for childhood malnutrition.

Long-term seizure dynamics are determined by the nature of seizures and the mutual interactions between them.

The seemingly random and unpredictable nature of seizures is a major debilitating factor for people with epilepsy. An increasing body of evidence demonstrates that the epileptic brain exhibits long-term fluctuations in seizure susceptibility, and seizure emergence seems to be a consequence of processes operating over multiple temporal scales. A deeper insight into the mechanisms responsible for long-term seizure fluctuations may provide important information for understanding the complex nature of seizure genesis. In this study, we explored the long-term dynamics of seizures in the tetanus toxin model of temporal lobe epilepsy. The results demonstrate the existence of long-term fluctuations in seizure probability, where seizures form clusters in time and are then followed by seizure-free periods. Within each cluster, seizure distribution is non-Poissonian, as demonstrated by the progressively increasing inter-seizure interval (ISI), which marks the approaching cluster termination. The lengthening of ISIs is paralleled by: increasing behavioral seizure severity, the occurrence of convulsive seizures, recruitment of extra-hippocampal structures and the spread of electrographic epileptiform activity outside of the limbic system. The results suggest that repeated non-convulsive seizures obey the 'seizures-beget-seizures' principle, leading to the occurrence of convulsive seizures, which decrease the probability of a subsequent seizure and, thus, increase the following ISI. The cumulative effect of repeated convulsive seizures leads to cluster termination, followed by a long inter-cluster period. We propose that seizures themselves are an endogenous factor that contributes to long-term fluctuations in seizure susceptibility and their mutual interaction determines the future evolution of disease activity.

Alterations of brain activity and functional connectivity in transition from acute to chronic tinnitus.

The objective of this study was to investigate alterations to brain activity and functional connectivity in patients with tinnitus, exploring neural features in the transition from acute to chronic phantom perception. Twenty-four patients with acute tinnitus, 23 patients with chronic tinnitus, and 32 healthy controls were recruited. High-density electroencephalography (EEG) was used to explore changes in brain areas and functional connectivity in different groups. When compared with healthy subjects, acute tinnitus patients had a significant reduction in superior frontal cortex activity across all frequency bands, whereas chronic tinnitus patients had a significant reduction in the superior frontal cortex at beta 3 and gamma frequency bands as well as a significant increase in the inferior frontal cortex at delta-band and superior temporal cortex at alpha 1 frequency band. When compared to the chronic tinnitus group, the acute tinnitus group activity was significantly increased in the middle frontal and parietal gyrus at the gamma-band. Functional connectivity analysis showed that the chronic tinnitus group had increased connections between the parahippocampus gyrus, posterior cingulate cortex, and precuneus when compared with the healthy group. Alterations of local brain activity and connections between the parahippocampus gyrus and other nonauditory areas appeared in the transition from acute to chronic tinnitus. This indicates that the appearance and development of tinnitus is a dynamic process involving aberrant local neural activity and abnormal connectivity in multifunctional brain networks.

Machine learning and wearable devices of the future.

Machine learning (ML) is increasingly recognized as a useful tool in healthcare applications, including epilepsy. One of the most important applications of ML in epilepsy is seizure detection and prediction, using wearable devices (WDs). However, not all currently available algorithms implemented in WDs are using ML. In this review, we summarize the state of the art of using WDs and ML in epilepsy, and we outline future development in these domains. There is published evidence for reliable detection of epileptic seizures using implanted electroencephalography (EEG) electrodes and wearable, non-EEG devices. Application of ML using the data recorded with WDs from a large number of patients could change radically the way we diagnose and manage patients with epilepsy.

Twenty-four-hour patterns in electrodermal activity recordings of patients with and without epileptic seizures.

OBJECTIVE: Daytime and nighttime patterns affect the dynamic modulation of brain and body functions and influence the autonomic nervous system response to seizures. Therefore, we aimed to evaluate 24-hour patterns of electrodermal activity (EDA) in patients with and without seizures. METHODS: We included pediatric patients with (a) seizures (SZ), including focal impaired awareness seizures (FIAS) or generalized tonic-clonic seizures (GTCS), (b) no seizures and normal electroencephalography (NEEG), or (c) no seizures but epileptiform activity in the EEG (EA) during vEEG monitoring. Patients wore a device that continuously recorded EDA and temperature (TEMP). EDA levels, EDA spectral power, and TEMP levels were analyzed. To investigate 24-hour patterns, we performed a nonlinear mixed-effects model analysis. Relative mean pre-ictal (-30 min to seizure onset) and post-ictal (I: 30 min after seizure offset; II: 30 to 60 min after seizure offset) values were compared for SZ subgroups. RESULTS: We included 119 patients (40 SZ, 17 NEEG, 62 EA). EDA level and power group-specific models (SZ, NEEG, EA) (h = 1; P < .01) were superior to the all-patient cohort model. Fifty-nine seizures were analyzed. Pre-ictal EDA values were lower than respective 24-hour modulated SZ group values. Post hoc comparisons following the period-by-seizure type interaction (EDA level: χ2  = 18.50; P < .001, and power: χ2  = 6.73; P = .035) revealed that EDA levels were higher in the post-ictal period I for FIAS and GTCS and in post-ictal period II for GTCS only compared to the pre-ictal period. SIGNIFICANCE: Continuously monitored EDA shows a pattern of change over 24 hours. Curve amplitudes in patients with recorded seizures were lower as compared to patients who did not exhibit seizures during the recording period. Sympathetic skin responses were greater and more prolonged in GTCS compared to FIAS. EDA recordings from wearable devices offer a noninvasive tool to continuously monitor sympathetic activity with potential applications for seizure detection, prediction, and potentially sudden unexpected death in epilepsy (SUDEP) risk estimation.

Seizure forecasting and cyclic control of seizures.

Epilepsy is a unique neurologic condition characterized by recurrent seizures, where causes, underlying biomarkers, triggers, and patterns differ across individuals. The unpredictability of seizures can heighten fear and anxiety in people with epilepsy, making it difficult to take part in day-to-day activities. Epilepsy researchers have prioritized developing seizure prediction algorithms to combat episodic seizures for decades, but the utility and effectiveness of prediction algorithms has not been investigated thoroughly in clinical settings. In contrast, seizure forecasts, which theoretically provide the probability of a seizure at any time (as opposed to predicting the next seizure occurrence), may be more feasible. Many advances have been made over the past decade in the field of seizure forecasting, including improvements in algorithms as a result of machine learning and exploration of non-EEG-based measures of seizure susceptibility, such as physiological biomarkers, behavioral changes, environmental drivers, and cyclic seizure patterns. For example, recent work investigating periodicities in individual seizure patterns has determined that more than 90% of people have circadian rhythms in their seizures, and many also experience multiday, weekly, or longer cycles. Other potential indicators of seizure susceptibility include stress levels, heart rate, and sleep quality, all of which have the potential to be captured noninvasively over long time scales. There are many possible applications of a seizure-forecasting device, including improving quality of life for people with epilepsy, guiding treatment plans and medication titration, optimizing presurgical monitoring, and focusing scientific research. To realize this potential, it is vital to better understand the user requirements of a seizure-forecasting device, continue to advance forecasting algorithms, and design clear guidelines for prospective clinical trials of seizure forecasting.

Epidemiology of status epilepticus in a non-urban area in Switzerland.

OBJECTIVE: The aim of this study is to provide a precise population-based data on incidence, types, and causes of SE according to the 2015 ILAE definition and classification using a prospectively cohort in an adult population of a non-urban area. MATERIALS & METHODS: Prospective observational SE cohort in a single large community hospital. The center is the only one in the region (French-speaking Valais canton), with all available resources to treat SE (including neurologist available 24/7, EEG monitoring and ICU). Every adult patient with SE is included (except post-anoxic SE). All variables are collected prospectively using the 2015 ILAE status epilepticus classification. RESULTS: We identified 103 patients with SE in the study period between 1st of May 2015 and 30th of June 2019 for a population of 260,855 people. The incidence is 8.6 per 100,000 adults per year with an overall case-fatality rate of 7.8%. SE was generalized convulsive in 52% of cases and nonconvulsive SE in coma in 34%. CONCLUSIONS: Using a prospective reliable data collection with strict inclusion criteria, we found an incidence of 8.6 per 100,000 persons per year, in line with previous report using similar methods. The most severe forms-generalized convulsive and nonconvulsive SE in coma-represent the majority of cases. These data might be important for resources allocation in non-urban area with non-university healthcare system.

Diagnosing and managing childhood absence epilepsy by telemedicine.

The diagnosis of childhood absence epilepsy (CAE) is typically based on history and description of spells, supported by an office-based positive hyperventilation test and confirmed by routine electroencephalography (EEG). In the current coronavirus disease 2019 (COVID-19) pandemic, many pediatric neurologists have switched to telemedicine visits for nonemergent outpatient evaluations. We present a series of children diagnosed as having CAE on the basis of a positive hyperventilation test performed during remote televisits. Several of these children were begun on treatment for CAE prior to obtaining an EEG, with significant seizure reduction. Our series documents the feasibility of CAE diagnosis and management by telemedicine.

Variation in perioperative cerebral and hemodynamic monitoring during carotid endarterectomy.

BACKGROUND: Hemodynamic disturbances cause half of the perioperative strokes following carotid endarterectomy (CEA). Guidelines strongly recommend strict pre- and postoperative blood pressure (BP) monitoring in CEA patients, but do not provide firm practical recommendations. Although in the Netherlands 50 centres perform CEA, no national protocol on perioperative hemodynamic, and cerebral monitoring exists. To assess current monitoring policies of all Dutch CEA-centres, a national survey was conducted. METHODS: Between May and July 2017 all 50 Dutch CEA-centres were invited to complete a 42-question survey addressing perioperative hemodynamic and cerebral monitoring during CEA. Nonresponders received a reminder after 1 and 2 months. By November 2017 the survey was completed by all centres. RESULTS: Preoperative baseline BP was based on a single bilateral BP-measurement at the outpatient-clinic in the majority of centres (n = 28). In 43 centres (86%) pre-operative monitoring (transcranial Doppler (TCD, n = 6), electroencephalography (EEG, n = 11), or TCD + EEG (n = 26)) was performed as a baseline reference. Intraoperatively, large diversity for type of anaesthesia (general: 45 vs. local [LA]:5) and target systolic BP (>100 mm hg - 160 mm hg [n = 12], based on preoperative outpatient-clinic or admission BP [n = 18], other [n = 20]) was reported. Intraoperative cerebral monitoring included EEG + TCD (n = 28), EEG alone (n = 13), clinical neurological examination with LA (n = 5), near-infrared spectroscopy with stump pressure (n = 1), and none due to standard shunting (n = 3). Postoperatively, significant variation was reported in standard duration of admission at a recovery or high-care unit (range 3-48 hr, mean:12 hr), maximum accepted systolic BP (range >100 mm hg - 180 mm Hg [n = 32]), postoperative cerebral monitoring (standard TCD [n = 16], TCD on indication [n = 5] or none [n = 24]) and in timing of postoperative cerebral monitoring (range directly postoperative - 24 hr postoperative; median 3 hr). CONCLUSIONS: In Dutch centres performing CEA the perioperative hemodynamic and cerebral monitoring policies are widely diverse. Diverse policies may theoretically lead to over- or under treatment. The results of this national audit may serve as the baseline dataset for development of a standardized and detailed (inter)national protocol on perioperative hemodynamic and cerebral monitoring during CEA.

Gamma oscillations weaken with age in healthy elderly in human EEG.

Gamma rhythms (~20-70 â€‹Hz) are abnormal in mental disorders such as autism and schizophrenia in humans, and Alzheimer's disease (AD) models in rodents. However, the effect of normal aging on these oscillations is unknown, especially for elderly subjects in whom AD is most prevalent. In a first large-scale (236 subjects; 104 females) electroencephalogram (EEG) study on gamma oscillations in elderly subjects (aged 50-88 years), we presented full-screen visual Cartesian gratings that induced two distinct gamma oscillations (slow: 20-34 â€‹Hz and fast: 36-66 â€‹Hz). Power decreased with age for gamma, but not alpha (8-12 â€‹Hz). Reduction was more salient for fast gamma than slow. Center frequency also decreased with age for both gamma rhythms. The results were independent of microsaccades, pupillary reactivity to stimulus, and variations in power spectral density with age. Steady-state visual evoked potentials (SSVEPs) at 32 â€‹Hz also reduced with age. These results are crucial for developing gamma/SSVEP-based biomarkers of cognitive decline in elderly.

High-Frequency Oscillation Networks and Surgical Outcome in Adult Focal Epilepsy.

OBJECTIVE: To investigate whether high-frequency oscillations (HFOs) show spatiotemporal propagation and assess the relevance of the earliest oscillations in relation to the seizure onset zone (SOZ) and postsurgical outcome. METHODS: We retrospectively investigated the intracerebral electroencephalography (EEG) of patients who became seizure free after subsequent surgery. We marked HFOs during 1 hour of recordings. We calculated the time delay between pairs of channels as the median delay between their HFOs and constructed a time line of the delay of each channel with respect to the earliest channel (first source channel). A network was defined when a temporal order could be established among the channels based on the existence of statistically significant delays. RESULTS: Fifteen patients with good surgical outcome were included. We found ripple networks in all patients, and fast ripple networks in 9. For ripples, first source channels were found in a higher proportion in the SOZ than the rest of the network channels (15 of 27 [56%] versus 93 of 262 [35%]; p = 0.04). For both ripples and fast ripples, first source channels were resected more often that the rest of the network channels (ripples: 13 of 27 [48%] versus 65 of 262 [25%]; p = 0.01; fast ripples: 8 of 9 [89%] versus 17 of 40 [43%]; p = 0.002); channels with the highest rates of ripples and fast ripples were resected in a similar proportion. INTERPRETATION: These results demonstrate that interictal HFOs are organized in networks and indicate a possible need for the resection of first source channels. However, resecting them is not superior to resecting channels with highest rates of HFOs. Ann Neurol 2019;85:485-494.

Low-Frequency Brain Oscillations Track Motor Recovery in Human Stroke.

OBJECTIVE: The majority of patients with stroke survive the acute episode and live with enduring disability. Effective therapies to support recovery of motor function after stroke are yet to be developed. Key to this development is the identification of neurophysiologic signals that mark recovery and are suitable and susceptible to interventional therapies. Movement preparatory low-frequency oscillations (LFOs) play a key role in cortical control of movement. Recent animal data point to a mechanistic role of motor cortical LFOs in stroke motor deficits and demonstrate neuromodulation intervention with therapeutic benefit. Their relevance in human stroke pathophysiology is unknown. METHODS: We studied the relationship between movement-preparatory LFOs during the performance of a visuomotor grip task and motor function in a longitudinal (<5 days, 1 and 3 months) cohort study of 33 patients with motor stroke and in 19 healthy volunteers. RESULTS: Acute stroke-lesioned brains fail to generate the LFO signal. Whereas in healthy humans, a transient occurrence of LFOs preceded movement onset at predominantly contralateral frontoparietal motor regions, recordings in patients revealed that movement-preparatory LFOs were substantially diminished to a level of 38% after acute stroke. LFOs progressively increased at 1 and 3 months. This re-emergence closely tracked the recovery of motor function across several movement qualities including grip strength, fine motor skills, and synergies and was frequency band specific. INTERPRETATION: Our results provide the first human evidence for a link between movement-preparatory LFOs and functional recovery after stroke, promoting their relevance for movement control. These results suggest that it may be interesting to explore targeted, LFOs-restorative brain stimulation therapy in human stroke patients. ANN NEUROL 2019;86:853-865.

Trends in the use of automated algorithms for the detection of high-frequency oscillations associated with human epilepsy.

High-frequency oscillations (HFOs) in intracranial electroencephalography (EEG) are a promising biomarker of the epileptogenic zone and tool for surgical planning. Many studies have shown that a high rate of HFOs (number per minute) is correlated with the seizure-onset zone, and complete removal of HFO-generating brain regions has been associated with seizure-free outcome after surgery. In order to use HFOs as a biomarker, these transient events must first be detected in electrophysiological data. Because visual detection of HFOs is time-consuming and subject to low interrater reliability, many automated algorithms have been developed, and they are being used increasingly for such studies. However, there is little guidance on how to select an algorithm, implement it in a clinical setting, and validate the performance. Therefore, we aim to review automated HFO detection algorithms, focusing on conceptual similarities and differences between them. We summarize the standard steps for data pre-processing, as well as post-processing strategies for rejection of false-positive detections. We also detail four methods for algorithm testing and validation, and we describe the specific goal achieved by each one. We briefly review direct comparisons of automated algorithms applied to the same data set, emphasizing the importance of optimizing detection parameters. Then, to assess trends in the use of automated algorithms and their potential for use in clinical studies, we review evidence for the relationship between automatically detected HFOs and surgical outcome. We conclude with practical recommendations and propose standards for the selection, implementation, and validation of automated HFO-detection algorithms.

Past, Present and Future of Home video-electroencephalographic telemetry: A review of the development of in-home video-electroencephalographic recordings.

Video-electroencephalographic (EEG) monitoring is an essential tool in epileptology, conventionally carried out in a hospital epilepsy monitoring unit. Due to high costs and long waiting times for hospital admission, coupled with technological advances, several centers have developed and implemented video-EEG monitoring in the patient's home (home video-EEG telemetry [HVET]). Here, we review the history and current status of three general approaches to HVET: (1) supervised HVET, which entails setting up video-EEG in the patient's home with daily visiting technologist support; (2) mobile HVET (also termed ambulatory video-EEG), which entails attaching electrodes in a health care facility, supplying the patient and carers with the hardware and instructions, and then asking the patient and carer to set up recording at home without technologist support; and (3) cloud-based HVET, which adds to either of the previous models continuous streaming of video-EEG from the home to the health care provider, with the option to review data in near real time, troubleshoot hardware remotely, and interact remotely with the patient. Our experience shows that HVET can be highly cost-effective and is well received by patients. We note limitations related to long-term electrode attachment and correct camera placing while the patient is unsupervised at home, and concerns related to regulations regarding data privacy for cloud services. We believe that HVET opens significant new opportunities for research, especially in the field of understanding the many influences in seizure occurrence. We speculate that in the future HVET may merge into innovative new multisensor approaches to continuously monitoring people with epilepsy.

Neonatal developmental and epileptic encephalopathy due to autosomal recessive variants in SLC13A5 gene.

OBJECTIVE: Autosomal recessive pathogenic variants of the SLC13A5 gene are associated with severe neonatal epilepsy, developmental delay, and tooth hypoplasia/hypodontia. We report on 14 additional patients and compare their phenotypic features to previously published patients to identify the clinical hallmarks of this disorder. METHODS: We collected clinical features of 14 patients carrying biallelic variants in SLC13A5 and performed a PubMed search to identify previously published patients. RESULTS: All patients presented clonic or tonic seizures in the first days of life, evolving into status epilepticus in 57%. Analysis of seizure frequency and developmental milestones divided into five epochs showed an evolutionary trajectory of both items. In the first 3 years of life, 72% of patients had weekly/monthly seizures, often triggered by fever; 14% were seizure-free. Between the ages of 3 and 12 years, 60% become seizure-free; in the following years, up to age 18 years, 57% were seizure-free. After the age of 18 years, all three patients reaching this age were seizure-free. Similarly, 86% of patients at onset presented mild to moderate developmental impairment and diffuse hypotonia. In late childhood, all had developmental delay that was severe in most. Benzodiazepines, phenobarbital, phenytoin, and carbamazepine were the most effective drugs. Eight probands carried heterozygous compound variants, and homozygous pathogenic variants occurred in six. Literature review identified 45 patients carrying SLC13A5 gene pathogenic variants whose clinical features overlapped with our cohort. A peculiar and distinguishing sign is the presence of tooth hypoplasia and/or hypodontia in most patients. SIGNIFICANCE: Autosomal recessive pathogenic variants in SLC13A5 are associated with a distinct neonatal epileptic encephalopathy evolving into severe cognitive and motor impairment, yet with seizures that settle down in late childhood. Tooth hypoplasia or hypodontia remains the peculiar feature. The SLC13A5 gene should be screened in neonatal epileptic encephalopathies; its recessive inheritance has relevance for genetic counseling.

Developmental and epilepsy spectrum of KCNB1 encephalopathy with long-term outcome.

OBJECTIVE: We aimed to delineate the phenotypic spectrum and long-term outcome of individuals with KCNB1 encephalopathy. METHODS: We collected genetic, clinical, electroencephalographic, and imaging data of individuals with KCNB1 pathogenic variants recruited through an international collaboration, with the support of the family association "KCNB1 France." Patients were classified as having developmental and epileptic encephalopathy (DEE) or developmental encephalopathy (DE). In addition, we reviewed published cases and provided the long-term outcome in patients older than 12 years from our series and from literature. RESULTS: Our series included 36 patients (21 males, median age = 10 years, range = 1.6 months-34 years). Twenty patients (56%) had DEE with infantile onset seizures (seizure onset = 10 months, range = 10 days-3.5 years), whereas 16 (33%) had DE with late onset epilepsy in 10 (seizure onset = 5 years, range = 18 months-25 years) and without epilepsy in six. Cognitive impairment was more severe in individuals with DEE compared to those with DE. Analysis of 73 individuals with KCNB1 pathogenic variants (36 from our series and 37 published individuals in nine reports) showed developmental delay in all with severe to profound intellectual disability in 67% (n = 41/61) and autistic features in 56% (n = 32/57). Long-term outcome in 22 individuals older than 12 years (14 in our series and eight published individuals) showed poor cognitive, psychiatric, and behavioral outcome. Epilepsy course was variable. Missense variants were associated with more frequent and more severe epilepsy compared to truncating variants. SIGNIFICANCE: Our study describes the phenotypic spectrum of KCNB1 encephalopathy, which varies from severe DEE to DE with or without epilepsy. Although cognitive impairment is worse in patients with DEE, long-term outcome is poor for most and missense variants are associated with more severe epilepsy outcome. Further understanding of disease mechanisms should facilitate the development of targeted therapies, much needed to improve the neurodevelopmental prognosis.

Who seizes longest? Impact of clinical and demographic factors.

OBJECTIVE: To investigate the impact of clinical and demographic parameters on the duration of focal onset seizures with and without secondary generalization using precise duration measurements from intracranial electroencephalographic (iEEG) recordings. METHODS: Patients with unifocal epilepsy syndromes and iEEG recording were retrospectively identified from the database of the local epilepsy center (2006-2016). Seizure duration was defined as time difference of iEEG seizure pattern onset and cessation. The seizure semiology was classified based on video recordings. Clinical and demographic data were extracted from patient reports. RESULTS: In total, 69 adults were included, and 654 focal onset seizures were analyzed. Focal to bilateral tonic-clonic seizures (FBTCSs; 98/654) were significantly longer than focal seizures (FSs) without generalization (FS-BTCs; 556/654, P < .001), and most FSs (545/654, 83.3%) terminated within 2 minutes. The duration of FSs was prolonged with increasing age of the patients (P = .003) and was significantly shortened (P < .001) by evolution into an FBTCS. FBTCSs with lateralizing semiologies like version (P = .015) and sign of four (P = .043) were associated with longer bilateral tonic-clonic manifestations. Furthermore, FBTCSs with preceding aura, frontal origin, or onset during sleep were by trend shorter. Age (P < .001) and disease duration (P = .028) were essential for prediction of FS-BTC duration, whereas the vigilance state (P = .085) was the main prediction factor for the duration of FBTCSs. SIGNIFICANCE: The identified modifiers of seizure duration are of great relevance for clinical risk evaluation, especially in the aging epilepsy patient suffering from temporal lobe epilepsy with secondary generalized seizures.