Neonatal seizures—diagnostic options and treatment recommendations

Seizures in neonates should prompt rapid evaluation to verify the diagnosis, determine etiology, and initiate appropriate treatment. Neonatal seizure diagnosis requires EEG confirmation and clinical observation alone is insufficient. Although most neonatal seizures are related to acute brain injury, some neonates present early-onset structural or metabolic/genetic epilepsy. Video-EEG monitoring, the gold standard for neonatal seizure detection and quantification, is resource-intensive and often unavailable, with amplitude-integrated EEG offering a reasonable alternative in guiding treatment. Whereas new-generation antiseizure medication (ASM), such as levetiracetam, appear promising, particularly in terms of tolerability, older-generation ASM, such as phenobarbital and phenytoin, are yet to be replaced. Acute treatment should aim at stopping both electroclinical and electrographic-only seizures. In neonates with acute provoked seizures, ASM should be discontinued without tapering after 72 h of seizure freedom and before hospital discharge

Ketogene Ernährungstherapien: mehr als nur Lifestyle-Diät

Ketogene Ernährungsformen werden heutzutage gerne eingesetzt zum Abnehmen oder für den Muskelaufbau. Im medizinischen Bereich stellen sie jedoch eine evidenzbasierte, etablierte Behandlungsoption bei pädiatrischen Epilepsien und ausgewählten Stoffwechselerkrankungen dar

Epilepsy Phenotypes of Vitamin B6-Dependent Diseases: An Updated Systematic Review

Background: Vitamin B6-dependent epilepsies include treatable diseases responding to pyridoxine or pyridoxal-5Iphosphate (ALDH7A1 deficiency, PNPO deficiency, PLP binding protein deficiency, hyperprolinemia type II and hypophosphatasia and glycosylphosphatidylinositol anchor synthesis defects). Patients and methods: We conducted a systematic review of published pediatric cases with a confirmed molecular genetic diagnosis of vitamin B6-dependent epilepsy according to PRISMA guidelines. Data on demographic features, seizure semiology, EEG patterns, neuroimaging, treatment, and developmental outcomes were collected. Results: 497 published patients fulfilled the inclusion criteria. Seizure onset manifested at 59.8 ± 291.6 days (67.8% of cases in the first month of life). Clonic, tonic-clonic, and myoclonic seizures accounted for two-thirds of the cases, while epileptic spasms were observed in 7.6%. Burst-suppression/suppression-burst represented the most frequently reported specific EEG pattern (14.4%), mainly in PLPB, ALDH7A1, and PNPO deficiency. Pyridoxine was administered to 312 patients (18.5% intravenously, 76.9% orally, 4.6% not specified), and 180 also received antiseizure medications. Pyridoxine dosage ranged between 1 and 55 mg/kg/die. Complete seizure freedom was achieved in 160 patients, while a significant seizure reduction occurred in 38. PLP, lysine-restricted diet, and arginine supplementation were used in a small proportion of patients with variable efficacy. Global developmental delay was established in 30.5% of a few patients in whom neurocognitive tests were performed. Conclusions: Despite the wide variability, the most frequent hallmarks of the epilepsy phenotype in patients with vitamin B6-dependent seizures include generalized or focal motor seizure semiology and a burst suppression/suppression burst pattern in EEG

A Spiking Neural Network (SNN) for detecting High Frequency Oscillations (HFOs) in the intraoperative ECoG

To achieve seizure freedom, epilepsy surgery requires the complete resection of the epileptogenic brain tissue. In intraoperative ECoG recordings, high frequency oscillations (HFOs) generated by epileptogenic tissue can be used to tailor the resection margin. However, automatic detection of HFOs in real-time remains an open challenge. Here we present a spiking neural network (SNN) for automatic HFO detection that is optimally suited for neuromorphic hardware implementation. We trained the SNN to detect HFO signals measured from intraoperative ECoG on-line, using an independently labeled dataset. We targeted the detection of HFOs in the fast ripple frequency range (250-500 Hz) and compared the network results with the labeled HFO data. We endowed the SNN with a novel artifact rejection mechanism to suppress sharp transients and demonstrate its effectiveness on the ECoG dataset. The HFO rates (median 6.6 HFO/min in pre-resection recordings) detected by this SNN are comparable to those published in the dataset (58 min, 16 recordings). The postsurgical seizure outcome was "predicted" with 100% accuracy for all 8 patients. These results provide a further step towards the construction of a real-time portable battery-operated HFO detection system that can be used during epilepsy surgery to guide the resection of the epileptogenic zone.Comment: 11 pages, 3 figures, 2 tables. The results of this publication were obtained by simulating our hardware platform, built for online processing of biological signals. This hardware combines neural recording headstages with a multi-core neuromorphic processor arxiv.org/abs/2009.1124

Levetiracetam versus Phenobarbital for Neonatal Seizures: A Retrospective Cohort Study

BACKGROUND Although phenobarbital (PB) is commonly used as a first-line antiseizure medication (ASM) for neonatal seizures, in 2015 we chose to replace it with levetiracetam (LEV), a third-generation ASM. Here, we compared the safety and efficacy of LEV and PB as first-line ASM, considering the years before and after modifying our treatment protocol. METHODS We conducted a retrospective cohort study of 108 neonates with electroencephalography (EEG)-confirmed seizures treated with first-line LEV or PB in 2012 to 2020. RESULTS First-line ASM was LEV in 33 (31%) and PB in 75 (69%) neonates. The etiology included acute symptomatic seizures in 69% of cases (30% hypoxic-ischemic encephalopathy, 32% structural vascular, 6% infectious, otherwise metabolic) and neonatal epilepsy in 22% (5% structural due to brain malformation, 17% genetic). Forty-two of 108 (39%) neonates reached seizure freedom following first-line therapy. Treatment response did not vary by first-line ASM among all neonates, those with acute symptomatic seizures, or those with neonatal-onset epilepsy. Treatment response was lowest for neonates with a higher seizure frequency, particularly for those with status epilepticus versus rare seizures (P < 0.001), irrespective of gestational age, etiology, or EEG findings. Adverse events were noted in 22 neonates treated with PB and in only one treated with LEV (P < 0.001). CONCLUSIONS Our study suggests a potential noninferiority and a more acceptable safety profile for LEV, which may thus be a reasonable option as first-line ASM for neonatal seizures in place of PB. Treatment should be initiated as early as possible since higher seizure frequencies predispose to less favorable responses

Scalp high-frequency oscillations differentiate neonates with seizures from healthy neonates

OBJECTIVE We aimed to investigate (1) whether an automated detector can capture scalp high-frequency oscillations (HFO) in neonates and (2) whether scalp HFO rates can differentiate neonates with seizures from healthy neonates. METHODS We considered 20 neonates with EEG-confirmed seizures and four healthy neonates. We applied a previously validated automated HFO detector to determine scalp HFO rates in quiet sleep. RESULTS Etiology in neonates with seizures included hypoxic-ischemic encephalopathy in 11 cases, structural vascular lesions in 6, and genetic causes in 3. The HFO rates were significantly higher in neonates with seizures (0.098 ± 0.091 HFO/min) than in healthy neonates (0.038 ± 0.025 HFO/min; P = 0.02) with a Hedge's g value of 0.68 indicating a medium effect size. The HFO rate of 0.1 HFO/min/ch yielded the highest Youden index in discriminating neonates with seizures from healthy neonates. In neonates with seizures, etiology, status epilepticus, EEG background activity, and seizure patterns did not significantly impact HFO rates. SIGNIFICANCE Neonatal scalp HFO can be detected automatically and differentiate neonates with seizures from healthy neonates. Our observations have significant implications for neuromonitoring in neonates. This is the first step in establishing neonatal HFO as a biomarker for neonatal seizures

Scalp HFO rates are higher for larger lesions

High frequency oscillations (HFO) in scalp EEG are a new and promising non-invasive epilepsy biomarker, providing added prognostic value, particularly in pediatric lesional epilepsy. However, it is unclear if lesion characteristics, such as lesion volume, depth, type, and localization, impact scalp HFO rates. We analyzed scalp EEG from 13 children and adolescents with focal epilepsy associated with focal cortical dysplasia (FCD), low-grade tumors, or hippocampal sclerosis. We applied a validated automated detector to determine HFO rates in bipolar channels. We identified the lesion characteristics in MRI. Larger lesions defined by MRI volumetric analysis corresponded to higher cumulative scalp HFO rates (p=0.01) that were detectable in a higher number of channels (p=0.05). Both superficial and deep lesions generated HFO detectable in the scalp EEG. Lesion type (FCD vs. tumor) and lobar localization (temporal vs. extratemporal) did not affect scalp HFO rates in our study. Our observations support that all lesions may generate HFO detectable in scalp EEG, irrespective of their characteristics, whereas larger epileptogenic lesions generate higher scalp HFO rates over larger areas that are thus more accessible to detection. Our study provides crucial insight into scalp HFO detectability in pediatric lesional epilepsy, facilitating their implementation as an epilepsy biomarker in a clinical setting

Lesion Extent Negatively Impacts Intellectual Skills in Pediatric Focal Epilepsy

BACKGROUND Cognitive development in children and adolescents with focal lesional epilepsy is determined by the underlying epileptogenic lesion, in addition to epilepsy itself. However, the impact of lesion-related variables on intelligence quotient (IQ) and developmental quotient (DQ) remains largely unexplored. Here, we aimed to determine the effect of lesion-related predictors and their relation with epilepsy-related predictors of intellectual functioning. METHODS We retrospectively analyzed data from children with focal lesional epilepsy who underwent standardized cognitive evaluation yielding IQ/DQ in our institution. RESULTS We included 50 consecutive patients aged 0.5 to 17.5 years (mean, 9.3; S.D., 4.9) at cognitive assessment. Epilepsy duration was 0 to 15.5 years (mean, 3.8; S.D., 4.1). Of the total cohort, 30 (60%) patients had unilobar lesions, seven (14%) multilobar, 10 (20%) hemispheric, and three (6%) bilateral. Etiology was congenital in 32 (64%) cases, acquired in 14 (28%), and progressive in four (8%). For patients with unilobar lesions, the mean IQ/DQ was 97.1 ± 15.7, for multilobar 98.9 ± 20.2, for hemispheric 76.1 ± 20.5, and for bilateral 76.3 ± 4.5. Larger lesion extent, earlier epilepsy onset, and longer epilepsy duration correlated with lower IQ/DQ in the univariate analysis, whereas only lesion extent and epilepsy duration contributed significantly to the explanatory model in the multivariable analysis. CONCLUSIONS The present study demonstrates that lesion extent and epilepsy duration are important risk factors for intellectual impairment in pediatric patients with focal lesional epilepsy. These findings are useful for family counseling and the early consideration of interventions that may limit the duration of epilepsy

Closed-Loop Acoustic Stimulation During Sleep in Children With Epilepsy: A Hypothesis-Driven Novel Approach to Interact With Spike-Wave Activity and Pilot Data Assessing Feasibility

Slow waves, the electroencephalographic (EEG) hallmark of deep sleep, can be systematically manipulated by acoustic stimulation: stimulation time-locked to the down phase of slow waves reduces, whereas stimulation time-locked to the up phase increases slow waves. Spike-waves during sleep seem to be related to slow waves, raising the question of whether spike-waves can be systematically influenced by such acoustic stimulation. In five pediatric patients, all-night EEG was recorded, combined with real-time slow wave detection. Throughout the night, acoustic stimulation was performed in a 3 × 5-min-block design (no stimulation—stimulation—no stimulation). Tones were applied time-locked either to the up or to the down phase of the detected slow waves in an alternating pattern. All patients tolerated the acoustic stimulation during sleep well. They showed high sleep quality and no signs of clinical or non-convulsive electrographic seizures. Our preliminary analysis shows no systematic effect of acoustic stimulation on spike-wave activity. Moreover, with our stimulation approach tones were distributed over a rather broad phase-range during the DOWN or UP stimulation and showed inter-individual differences in their distribution. In this study, we applied for the first time an acoustic closed-loop slow wave stimulation tool for a non-invasive manipulation of spike-wave activity. Thus, our pilot data show that closed-loop acoustic stimulation is feasible and well tolerated in children with spike wave activity during sleep. Improved precision in phase targeting and personalized stimulation parameters in a larger sample of subjects might be needed to show systematic effects