No abstract

Limited-channel bedside electroencephalography combining amplitude-integrated electroencephalography with 2-channel electroencephalography, interpreted by experienced neonatal readers, detected the majority of electrical seizures in at-risk newborn infants.

Electrographic seizure burden is associated with severity of brain injury on MRI in newborns with HIE undergoing TH, independent of degree of abnormality on aEEG background. Seizures are common during cooling, particularly on day 1, with a significant rebound on day 4.

A substantial number of prematurely born infants will experience later neurodevelopmental challenges. Abnormal development of the cerebellum may be related to some of the impairments exhibited by preterm children. To test the hypothesis that cerebellar development is structurally impaired in preterm infants and associated with adverse outcomes, we studied 83 preterm infants and 13 term controls using volumetric magnetic resonance imaging techniques to obtain cerebellar volumes (CV) at term corrected and subsequent neurodevelopmental assessment at 2 y of age. The preterm group had smaller mean CV at term compared with the term control infants [mean (SD) CV, 22.0 (5.0) versus 23.5 (5.0) cc; mean difference (95% confidence interval), 1.5 (-1.5, 4.4)] although this did not reach statistical significance. Within the preterm group, there was evidence of a reduction in CV related to the presence of white matter injury (WMI) after adjusting for intracranial volume (ICV) [WMI grade 1 versus grade 2: mean (SD) CV, 23.6 (5.0) versus 21.6 (4.5); p ϭ 0.01; WMI grade 1 versus grade 3 and 4: 23.6 (5.0) versus 20.8 (5.6); p ϭ 0.07]. Within the preterm infants, there was no apparent relationship between CV at term and gestational age at birth after adjusting for ICV. At 2 y of age, CV showed a weak correlation with cognitive and motor development, although this was principally mediated by WMI. In conclusion, we found no evidence for a primary impairment in cerebellar development in relation to prematurity, although there was evidence for a secondary effect of cerebral WMI on cerebellar development independent of immaturity.

Background Despite the availability of continuous conventional electroencephalography (cEEG), accurate diagnosis of neonatal seizures is challenging in clinical practice. Algorithms for decision support in the recognition of neonatal seizures could improve detection. We aimed to assess the diagnostic accuracy of an automated seizure detection algorithm called Algorithm for Neonatal Seizure Recognition (ANSeR). Methods This multicentre, randomised, two-arm, parallel, controlled trial was done in eight neonatal centres across Ireland, the Netherlands, Sweden, and the UK. Neonates with a corrected gestational age between 36 and 44 weeks with, or at significant risk of, seizures requiring EEG monitoring, received cEEG plus ANSeR linked to the EEG monitor displaying a seizure probability trend in real time (algorithm group) or cEEG monitoring alone (nonalgorithm group). The primary outcome was diagnostic accuracy (sensitivity, specificity, and false detection rate) of health-care professionals to identify neonates with electrographic seizures and seizure hours with and without the support of the ANSeR algorithm. Neonates with data on the outcome of interest were included in the analysis. This study is registered with ClinicalTrials.gov, NCT02431780. Findings Between Feb 13, 2015, and Feb 7, 2017, 132 neonates were randomly assigned to the algorithm group and 132 to the non-algorithm group. Six neonates were excluded (four from the algorithm group and two from the non-algorithm group). Electrographic seizures were present in 32 (25•0%) of 128 neonates in the algorithm group and 38 (29•2%) of 130 neonates in the non-algorithm group. For recognition of neonates with electrographic seizures, sensitivity was 81•3% (95% CI 66•7-93•3) in the algorithm group and 89•5% (78•4-97•5) in the non-algorithm group; specificity was 84•4% (95% CI 76•9-91•0) in the algorithm group and 89•1% (82•5-94•7) in the non-algorithm group; and the false detection rate was 36•6% (95% CI 22•7-52•1) in the algorithm group and 22•7% (11•6-35•9) in the non-algorithm group. We identified 659 h in which seizures occurred (seizure hours): 268 h in the algorithm versus 391 h in the nonalgorithm group. The percentage of seizure hours correctly identified was higher in the algorithm group than in the non-algorithm group (177 [66•0%; 95% CI 53•8-77•3] of 268 h vs 177 [45•3%; 34•5-58•3] of 391 h; difference 20•8% [3•6-37•1]). No significant differences were seen in the percentage of neonates with seizures given at least one inappropriate antiseizure medication (37•5% [95% CI 25•0 to 56•3] vs 31•6% [21•1 to 47•4]; difference 5•9% [-14•0 to 26•3]). Interpretation ANSeR, a machine-learning algorithm, is safe and able to accurately detect neonatal seizures. Although the algorithm did not enhance identification of individual neonates with seizures beyond conventional EEG, recognition of seizure hours was improved with use of ANSeR. The benefit might be greater in less experienced centres, but further study is required.

ABSTRACT:The aim of the study was to determine the incidence of electrographic seizure activity in a prospective cohort of preterm infants and relate it to the presence of cerebral injury. Infants born Ͻ30-wk gestation received a median 74 h of continuous 2-channel EEG with amplitude-integrated EEG monitoring in the first week of life. Infants were classified in the abnormal outcome group if they died in the neonatal period and/or had grades 3-4 intraventricular hemorrhage and/or moderate or severe abnormalities on cerebral MRI. Seizures were defined as rhythmic spike and/or wave activity lasting at least 10 s on the raw EEG trace. Eleven of 51 infants monitored had electrographic seizures. These infants were more premature had lower birth weights and a greater proportion had abnormal outcomes. In four infants, seizures preceded ultrasound findings of grades 3-4 intraventricular hemorrhage. Three of the four infants with seizures and concurrent physiologic recordings displayed concurrent rises in heart rate and one showed a fall in respiratory rate. In conclusion, electrographic seizures were more likely to occur in the sicker and more premature infants with abnormal outcomes. Seizures detected on continuous amplitude-integrated EEG monitoring with the raw EEG were associated with poor outcome. (Pediatr Res 67: 102-106, 2010)

ObjectiveThe aim of this multicentre study was to describe detailed characteristics of electrographic seizures in a cohort of neonates monitored with multichannel continuous electroencephalography (cEEG) in 6 European centres.MethodsNeonates of at least 36 weeks of gestation who required cEEG monitoring for clinical concerns were eligible, and were enrolled prospectively over 2 years from June 2013. Additional retrospective data were available from two centres for January 2011 to February 2014. Clinical data and EEGs were reviewed by expert neurophysiologists through a central server.ResultsOf 214 neonates who had recordings suitable for analysis, EEG seizures were confirmed in 75 (35%). The most common cause was hypoxic-ischaemic encephalopathy (44/75, 59%), followed by metabolic/genetic disorders (16/75, 21%) and stroke (10/75, 13%). The median number of seizures was 24 (IQR 9–51), and the median maximum hourly seizure burden in minutes per hour (MSB) was 21 min (IQR 11–32), with 21 (28%) having status epilepticus defined as MSB>30 min/hour. MSB developed later in neonates with a metabolic/genetic disorder. Over half (112/214, 52%) of the neonates were given at least one antiepileptic drug (AED) and both overtreatment and undertreatment was evident. When EEG monitoring was ongoing, 27 neonates (19%) with no electrographic seizures received AEDs. Fourteen neonates (19%) who did have electrographic seizures during cEEG monitoring did not receive an AED.ConclusionsOur results show that even with access to cEEG monitoring, neonatal seizures are frequent, difficult to recognise and difficult to treat.Oberservation study numberNCT02160171

This review aims to highlight a possible relationship between hypoxic-ischaemic encephalopathy (HIE) and the disruption of the blood-brain barrier (BBB). Inflammatory reactions perpetuate a large proportion of cerebral injury. The extent of injury noted in HIE is not only determined by the biochemical cascades that trigger the apoptosis-necrosis continuum of cell death in the brain parenchyma, but also by the breaching of the BBB by pro-inflammatory factors. We examine the changes that contribute to the breakdown of the BBB that occur during HIE at a macroscopic, cellular, and molecular level. The BBB is a permeability barrier which separates a large majority of brain areas from the systemic circulation. The concept of a physiological BBB is based at the anatomical level on the neurovascular unit (NVU). The NVU consists of various cellular components that jointly regulate the exchanges that occur at the interface between the systemic circulation and the brain parenchyma. There is increased understanding of the contribution of the components of the NVU, e.g., astrocytes and pericytes, to the maintenance of this physiological barrier. We also explore the development of therapeutic options in HIE, such as harnessing the transport systems in the BBB, to enable the delivery of large molecules with molecular Trojan horse technology, and the reinforcement of the physical barrier with cell-based therapy which utilizes endothelial progenitor cells and stem cells.