Treatment of electrical status epilepticus in sleep: A pooled analysis of 575 cases.

OBJECTIVE: Epileptic encephalopathy with electrical status epilepticus in sleep (ESES) is a pediatric epilepsy syndrome with sleep-induced epileptic discharges and acquired impairment of cognition or behavior. Treatment of ESES is assumed to improve cognitive outcome. The aim of this study is to create an overview of the current evidence for different treatment regimens in children with ESES syndrome. METHODS: A literature search using PubMed and Embase was performed. Articles were selected that contain original treatment data of patients with ESES syndrome. Authors were contacted for additional information. Individual patient data were collected, coded, and analyzed using logistic regression analysis. The three predefined main outcome measures were improvement in cognitive function, electroencephalography (EEG) pattern, and any improvement (cognition or EEG). RESULTS: The literature search yielded 1,766 articles. After applying inclusion and exclusion criteria, 112 articles and 950 treatments in 575 patients could be analyzed. Antiepileptic drugs (AEDs, n = 495) were associated with improvement (i.e., cognition or EEG) in 49% of patients, benzodiazepines (n = 171) in 68%, and steroids (n = 166) in 81%. Surgery (n = 62) resulted in improvement in 90% of patients. In a subgroup analysis of patients who were consecutively reported (585 treatments in 282 patients), we found improvement in a smaller proportion treated with AEDs (34%), benzodiazepines (59%), and steroids (75%), whereas the improvement percentage after surgery was preserved (93%). Possible predictors of improved outcome were treatment category, normal development before ESES onset, and the absence of structural abnormalities. SIGNIFICANCE: Although most included studies were small and retrospective and their heterogeneity allowed analysis of only qualitative outcome data, this pooled analysis suggests superior efficacy of steroids and surgery in encephalopathy with ESES.

Corticosteroids as treatment of epileptic syndromes with continuous spike-waves during slow-wave sleep.

To assess the efficacy and tolerability of steroids in epileptic syndromes with continuous spike-waves during slow-wave sleep (CSWS), charts of 44 children (25 boys) who received corticosteroids for cognitive and/or behavioral deterioration associated with CSWS were retrospectively reviewed. Awake and sleep electroencephalography (EEG) records, clinical and neuropsychological assessments were available before, during, and after corticosteroid therapy. Evaluation focused on effects on EEG, behavior, and cognition. All but two patients received hydrocortisone (initial dose of 5 mg/kg/day). The treatment was slowly tapered with a total duration of 21 months. There were 18 symptomatic and 26 cryptogenic cases. Mean age was 7 years and mean intelligence quotient/developmental quotient (IQ/DQ) was 65. Mean CSWS duration before corticosteroid treatment was 1.7 years. Twenty patients had tried more than two antiepileptic drugs (AEDs) before steroids. Positive response to steroids was found during the first 3 months of treatment in 34 of 44 patients (77.2%), with normalization of the EEG in 21 patients. Relapse occurred in 14 of them. Hence, 20 patients (45.4%) were long-term responders after a single but prolonged trial of steroids, including all four cases of Landau-Kleffner syndrome. Positive response to steroids was highly significantly associated with higher IQ/DQ. Shorter CSWS duration, but not age, etiology, or previous AED trials, was associated with positive response to steroids. Early discontinuation of the treatment for side effects was encountered in seven patients. We conclude that corticosteroids are safe and efficient for treatment of epilepsy with CSWS. Poor responders are patients with very low IQ and long duration of CSWS.

Expanding the phenotypic spectrum associated with OPHN1 mutations: Report of 17 individuals with intellectual disability but no cerebellar hypoplasia.

Mutations in the oligophrenin 1 gene (OPHN1) have been identified in patients with X-linked intellectual disability (XLID) associated with cerebellar hypoplasia and ventriculomegaly, suggesting it could be a recognizable syndromic intellectual disability (ID). Affected individuals share additional clinical features including speech delay, seizures, strabismus, behavioral difficulties, and slight facial dysmorphism. OPHN1 is located in Xq12 and encodes a Rho-GTPase-activating protein involved in the regulation of the G-protein cycle. Rho protein members play an important role in dendritic growth and in plasticity of excitatory synapses. Here we report on 17 individuals from four unrelated families affected by mild to severe intellectual disability due to OPHN1 mutations without cerebellar anomaly on brain MRI. We describe clinical, genetic and neuroimaging data of affected patients. Among the identified OPHN1 mutations, we report for the first time a missense mutation occurring in a mosaic state. We discuss the intrafamilial clinical variability of the disease and compare our patients with those previously reported. We emphasize the power of next generation techniques (X-exome sequencing, whole-exome sequencing and targeted multi-gene panel) to expand the phenotypic and mutational spectrum of OPHN1-related ID.

Cluster-based spike detection algorithm adapts to interpatient and intrapatient variation in spike morphology.

Visual quantification of interictal epileptiform activity is time consuming and requires a high level of expert's vigilance. This is especially true for overnight recordings of patient suffering from epileptic encephalopathy with continuous spike and waves during slow-wave sleep (CSWS) as they can show tens of thousands of spikes. Automatic spike detection would be attractive for this condition, but available algorithms have methodological limitations related to variation in spike morphology both between patients and within a single recording. We propose a fully automated method of interictal spike detection that adapts to interpatient and intrapatient variation in spike morphology. The algorithm works in five steps. (1) Spikes are detected using parameters suitable for highly sensitive detection. (2) Detected spikes are separated into clusters. (3) The number of clusters is automatically adjusted. (4) Centroids are used as templates for more specific spike detections, therefore adapting to the types of spike morphology. (5) Detected spikes are summed. The algorithm was evaluated on EEG samples from 20 children suffering from epilepsy with CSWS. When compared to the manual scoring of 3 EEG experts (3 records), the algorithm demonstrated similar performance since sensitivity and selectivity were 0.3% higher and 0.4% lower, respectively. The algorithm showed little difference compared to the manual scoring of another expert for the spike-and-wave index evaluation in 17 additional records (the mean absolute difference was 3.8%). This algorithm is therefore efficient for the count of interictal spikes and determination of a spike-and-wave index.