Measuring the effects of sleep on epileptogenicity with multifrequency entropy.

OBJECTIVE: We demonstrate that multifrequency entropy gives insight into the relationship between epileptogenicity and sleep, and forms the basis for an improved measure of medical assessment of sleep impairment in epilepsy patients. METHODS: Multifrequency entropy was computed from electroencephalography measurements taken from 31 children with Benign Epilepsy with Centrotemporal Spikes and 31 non-epileptic controls while awake and during sleep. Values were compared in the epileptic zone and away from the epileptic zone in various sleep stages. RESULTS: We find that (I) in lower frequencies, multifrequency entropy decreases during non-rapid eye movement sleep stages when compared with wakefulness in a general population of pediatric patients, (II) patients with Benign Epilepsy with Centrotemporal Spikes had lower multifrequency entropy across stages of sleep and wakefulness, and (III) the epileptic regions of the brain exhibit lower multifrequency entropy patterns than the rest of the brain in epilepsy patients. CONCLUSIONS: Our results show that multifrequency entropy decreases during sleep, particularly sleep stage 2, confirming, in a pediatric population, an association between sleep, lower multifrequency entropy, and increased likelihood of seizure. SIGNIFICANCE: We observed a correlation between lowered multifrequency entropy and increased epileptogenicity that lays preliminary groundwork for the detection of a digital biomarker for epileptogenicity.

Nonlinear Analysis of Visually Normal EEGs to Differentiate Benign Childhood Epilepsy with Centrotemporal Spikes (BECTS).

Childhood epilepsy with centrotemporal spikes, previously known as Benign Epilepsy with Centro-temporal Spikes (BECTS) or Rolandic Epilepsy, is one of the most common forms of focal childhood epilepsy. Despite its prevalence, BECTS is often misdiagnosed or missed entirely. This is in part due to the nocturnal and brief nature of the seizures, making it difficult to identify during a routine electroencephalogram (EEG). Detecting brain activity that is highly associated with BECTS on a brief, awake EEG has the potential to improve diagnostic screening for BECTS and predict clinical outcomes. For this study, 31 patients with BECTS were retrospectively selected from the BCH Epilepsy Center database along with a contrast group of 31 patients in the database who had no form of epilepsy and a normal EEG based on a clinical chart review. Nonlinear features, including multiscale entropy and recurrence quantitative analysis, were computed from 30-second segments of awake EEG signals. Differences were found between these multiscale nonlinear measures in the two groups at all sensor locations, while visual EEG inspection by a board-certified child neurologist did not reveal any distinguishing features. Moreover, a quantitative difference in the nonlinear measures (sample entropy, trapping time and the Lyapunov exponents) was found in the centrotemporal region of the brain, the area associated with a greater tendency to have unprovoked seizures, versus the rest of the brain in the BECTS patients. This difference was not present in the contrast group. As a result, the epileptic zone in the BECTS patients appears to exhibit lower complexity, and these nonlinear measures may potentially serve as a clinical screening tool for BECTS, if replicated in a larger study population.

Ictal onset patterns of subdural intracranial electroencephalogram in children: How helpful for predicting epilepsy surgery outcome?

AIMS: We aimed to classify ictal onset patterns (IOPs) in pediatric patients undergoing intracranial electroencephalography (IEEG) to guide surgery for refractory epilepsy. We aimed to determine if morphology of IOPs can predict surgical outcome. MATERIALS AND METHODS: We performed a retrospective review of pediatric patients who underwent epilepsy surgery guided by subdural IEEG from 2007 to 2016. IEEG seizures were reviewed by a blinded epileptologist. Data was collected on outcomes. RESULTS: Twenty-three patients with 784 seizures were included. Age at seizure onset was 0.2-11 (mean 4.3, standard deviation 3.2) years. Age at time of IEEG was 4-20 (mean 13.5, standard deviation 4.4) years. Five distinct IOPs were seen at seizure onset: A) Low voltage fast activity (LVFA) with spread to adjacent electrodes (n = 7 patients, 30%), B) Burst of LVFA followed by electrodecrement (n = 12 patients, 52%), C) Burst of rhythmic spike waves (RSW) followed by electrodecrement (n = 9 patients, 39%), D) RSW followed by LVFA (n = 7 patients, 30%), E) Rhythmic spikes alone (n = 10 patients, 43%). Twelve patients (52%) had the same IOP type with all seizures. When the area of the IOP was resected, 14 patients (61%) had Engel I outcomes. Patients who had LVFA seen within their predominant IOP type were more likely to have good surgical outcomes (odds ratio 7.50, 95% confidence interval 1.02-55.0, p = 0.05). Patients who had only one IOP type were more likely to have good outcomes than patients who had multiple IOP types (odds ratio 12.6, 95% confidence interval 1.19-134, p = 0.04). Patients who had LVFA in their predominant IOP type were older than patients who did not have LVFA (mean age 15.0 vs. 9.9 years, p = 0.02). CONCLUSIONS: LVFA at ictal onset and all seizures having the same IOP morphology are associated with increased likelihood of surgical success in children, but LVFA is less common in children who are younger at the time of IEEG.

Long-term clinical course of Glut1 deficiency syndrome.

Our objective is to characterize the long-term course of Glut1 deficiency syndrome. Longitudinal outcome measures, including Columbia Neurological Scores, neuropsychological tests, and adaptive behavior reports, were collected for 13 participants with Glut1 deficiency syndrome who had been followed for an average of 14.2 (range = 8.9-23.6) years. A parent questionnaire assessed manifestations throughout development. The 6-Minute Walk Test captured gait disturbances and triggered paroxysmal exertional dyskinesia. All longitudinal outcomes remained stable over time. Epilepsy dominated infancy and improved during childhood. Dystonia emerged during childhood or adolescence. Earlier introduction of the ketogenic diet correlated with better long-term outcomes on some measures. Percent-predicted 6-Minute Walk Test distance correlated significantly with Columbia Neurological Scores. We conclude that Glut1 deficiency syndrome is a chronic condition, dominated by epilepsy in infancy and by movement disorders thereafter. Dietary treatment in the first postnatal months may effect improved outcomes, emphasizing the importance of early diagnosis and treatment.

Weakness and fatigue in diverse neuromuscular diseases.

Weakness and fatigue are captured by the 6-minute walk test, but the relationship between these symptoms is uncertain. Comparison across neuromuscular diseases has not been examined. A cohort study of 114 patients with spinal muscular atrophy, Duchenne/Becker muscular dystrophy, myasthenia gravis, and energy failure syndromes were included. Percent-predicted distance on the 6-minute walk test was computed from normative values to determine weakness. Fatigue was determined by the decrement in distance from the first to sixth minute. Weakness was seen across all groups (61.9%) but significant fatigue was seen only in spinal muscular atrophy (21.0%). Other groups showed little fatigue. Correlation between weakness and fatigue was significant only in spinal muscular atrophy (R = -0.71; P < .001). Longitudinally, distance walked declined only in Duchenne/Becker muscular dystrophy. In spinal muscular atrophy, weakness did not change, but fatigue increased significantly. These findings suggest independent mechanisms underlying weakness and fatigue in diverse neuromuscular conditions.