Neonatal Seizure Management: Is the Timing of Treatment Critical?

OBJECTIVE: To assess the impact of the time to treatment of the first electrographic seizure on subsequent seizure burden and describe overall seizure management in a large neonatal cohort. STUDY DESIGN: Newborns (36-44 weeks of gestation) requiring electroencephalographic (EEG) monitoring recruited to 2 multicenter European studies were included. Infants who received antiseizure medication exclusively after electrographic seizure onset were grouped based on the time to treatment of the first seizure: antiseizure medication within 1 hour, between 1 and 2 hours, and after 2 hours. Outcomes measured were seizure burden, maximum seizure burden, status epilepticus, number of seizures, and antiseizure medication dose over the first 24 hours after seizure onset. RESULTS: Out of 472 newborns recruited, 154 (32.6%) had confirmed electrographic seizures. Sixty-nine infants received antiseizure medication exclusively after the onset of electrographic seizure, including 21 infants within 1 hour of seizure onset, 15 between 1 and 2 hours after seizure onset, and 33 at >2 hours after seizure onset. Significantly lower seizure burden and fewer seizures were noted in the infants treated with antiseizure medication within 1 hour of seizure onset (P = .029 and .035, respectively). Overall, 258 of 472 infants (54.7%) received antiseizure medication during the study period, of whom 40 without electrographic seizures received treatment exclusively during EEG monitoring and 11 with electrographic seizures received no treatment. CONCLUSIONS: Treatment of neonatal seizures may be time-critical, but more research is needed to confirm this. Improvements in neonatal seizure diagnosis and treatment are also needed.

Deep Learning for EEG Seizure Detection in Preterm Infants.

EEG is the gold standard for seizure detection in the newborn infant, but EEG interpretation in the preterm group is particularly challenging; trained experts are scarce and the task of interpreting EEG in real-time is arduous. Preterm infants are reported to have a higher incidence of seizures compared to term infants. Preterm EEG morphology differs from that of term infants, which implies that seizure detection algorithms trained on term EEG may not be appropriate. The task of developing preterm specific algorithms becomes extra-challenging given the limited amount of annotated preterm EEG data available. This paper explores novel deep learning (DL) architectures for the task of neonatal seizure detection in preterm infants. The study tests and compares several approaches to address the problem: training on data from full-term infants; training on data from preterm infants; training on age-specific preterm data and transfer learning. The system performance is assessed on a large database of continuous EEG recordings of 575[Formula: see text]h in duration. It is shown that the accuracy of a validated term-trained EEG seizure detection algorithm, based on a support vector machine classifier, when tested on preterm infants falls well short of the performance achieved for full-term infants. An AUC of 88.3% was obtained when tested on preterm EEG as compared to 96.6% obtained when tested on term EEG. When re-trained on preterm EEG, the performance marginally increases to 89.7%. An alternative DL approach shows a more stable trend when tested on the preterm cohort, starting with an AUC of 93.3% for the term-trained algorithm and reaching 95.0% by transfer learning from the term model using available preterm data. The proposed DL approach avoids time-consuming explicit feature engineering and leverages the existence of the term seizure detection model, resulting in accurate predictions with a minimum amount of annotated preterm data.

A machine-learning algorithm for neonatal seizure recognition: a multicentre, randomised, controlled trial.

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 (non-algorithm 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 non-algorithm 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. FUNDING: Wellcome Trust, Science Foundation Ireland, and Nihon Kohden.

Reliability and accuracy of EEG interpretation for estimating age in preterm infants.

OBJECTIVES: To determine the accuracy of, and agreement among, EEG and aEEG readers' estimation of maturity and a novel computational measure of functional brain age (FBA) in preterm infants. METHODS: Seven experts estimated the postmenstrual ages (PMA) in a cohort of recordings from preterm infants using cloud-based review software. The FBA was calculated using a machine learning-based algorithm. Error analysis was used to determine the accuracy of PMA assessments and intraclass correlation (ICC) was used to assess agreement between experts. RESULTS: EEG recordings from a PMA range 25 to 38 weeks were successfully interpreted. In 179 recordings from 62 infants interpreted by all human readers, there was moderate agreement between experts (aEEG ICC = 0.724; 95%CI:0.658-0.781 and EEG ICC = 0.517; 95%CI:0.311-0.664). In 149 recordings from 61 infants interpreted by all human readers and the FBA algorithm, random and systematic errors in visual interpretation of PMA were significantly higher than the computational FBA estimate. Tracking of maturation in individual infants showed stable FBA trajectories, but the trajectories of the experts' PMA estimate were more likely to be obscured by random errors. The accuracy of visual interpretation of PMA estimation was compromised by neurodevelopmental outcome for both aEEG and EEG review. INTERPRETATION: Visual assessment of infant maturity is possible from the EEG or aEEG, with an average of human experts providing the highest accuracy. Tracking PMA of individual infants was hampered by errors in experts' estimates. FBA provided the most accurate maturity assessment and has potential as a biomarker of early outcome.

No effect of a musical intervention on stress response to venepuncture in a neonatal population.

AIM: To investigate the effect of a musical intervention on neonatal stress response to venepuncture as measured by salivary cortisol levels and pain profile scores. METHODS: In a randomised control crossover trial, participants were randomised to both a control arm (sucrose) and intervention arm (sucrose and music) for routine venepuncture procedures. Salivary swabs were collected at baseline, 20 minutes post-venepuncture and 4 hours post-venepuncture. Pain levels were assessed using the Premature Infant Pain Profile (PIPP). A total of 16 preterm neonates participated in both arms to complete the study. RESULTS: Cortisol values were elevated at all timepoints in the intervention arm (baseline, 20 minutes, and 4 hours post-procedure) but not significantly so (P = .056, P = .3, and P = .575, respectively). Median change in cortisol values from baseline was +128.48 pg/mL (-47.66 to 517.02) at 20 minutes and +393.52 pg/mL (47.88-1221.34) at 4 hours post-procedure in the control arm compared to -69.564 pg/mL (-860.96 to 397.289) and +100.48 pg/mL (-560.46 to 842.99) at 20 minutes and 4 hours post-procedure in the intervention arm. There was no statistically significant difference observed between groups (P = .311 at 20 minutes, and P = .203 at 4 hours post-procedure). PIPP scores were not significantly different between study arms. CONCLUSION: Our findings did not support the additional benefit of music intervention on neonatal stress response to venepuncture in preterm infants.

A standardised assessment scheme for conventional EEG in preterm infants.

OBJECTIVE: To develop a standardised scheme for assessing normal and abnormal electroencephalography (EEG) features of preterm infants. To assess the interobserver agreement of this assessment scheme. METHODS: We created a standardised EEG assessment scheme for 6 different post-menstrual age (PMA) groups using 4 EEG categories. Two experts, not involved in the development of the scheme, evaluated this on 24 infants <32 weeks gestational age (GA) using random 2 hour EEG epochs. Where disagreements were found, the features were checked and modified. Finally, the two experts independently evaluated 2 hour EEG epochs from an additional 12 infants <37 weeks GA. The percentage of agreement was calculated as the ratio of agreements to the sum of agreements plus disagreements. RESULTS: Good agreement in all patients and EEG feature category was obtained, with a median agreement between 80% and 100% over the 4 EEG assessment categories. No difference was found in agreement rates between the normal and abnormal features (p = 0.959). CONCLUSIONS: We developed a standard EEG assessment scheme for preterm infants that shows good interobserver agreement. SIGNIFICANCE: This will provide information to Neonatal Intensive Care Unit (NICU) staff about brain activity and maturation. We hope this will prove useful for many centres seeking to use neuromonitoring during critical care for preterm infants.

Encephalopathy with continuous spike-waves during slow-wave sleep: evolution and prognosis.

Encephalopathy with continuous spike-waves during slow-wave sleep (CSWS) evolves over time, and three stages can be recognized: before the onset of CSWS, during CSWS, and after the CSWS period. Clinical seizures tend to remit spontaneously around puberty. This pattern is independent of the etiological lesion. The CSWS also disappears in all cases. Focal abnormalities instead, may persist for some time after the disappearance of CSWS. The disappearance of the clinical seizures and CSWS may be simultaneous or seizures may disappear before or after disappearance of the CSWS pattern on the EEG. Electroclinical parameters in the pre-CSWS period that have been proposed to predict a poor outcome are early-onset seizures, appearance of new seizures, and a significant increase in seizure frequency. From the electrical point of view, an increase in the frequency of the interictal EEG paroxysms while awake and during sleep and bilateral spike-and-wave paroxysms may also be predictive of a poor evolution in CSWS. When CSWS disappears, neurocognitive and behavioral status improve, but in most patients, residual moderate to severe neurocognitive impairments remain. In non-lesional epilepsy, cognitive recovery after cessation of the CSWS depends on the severity and duration of the initial regression. The duration of the CSWS seems to be the most important predictor of cognitive outcome. Early recognition and effective therapy to reduce the seizures and resolve the CSWS may be crucial to improve long-term prognosis. Cognitive recovery is observed in patients who respond well to AED treatment and outcome depends on the etiology.

Idiopathic encephalopathy related to status epilepticus during slow sleep (ESES) as a "pure" model of epileptic encephalopathy. An electroclinical, genetic, and follow-up study.

OBJECTIVE: The objective of the study was to investigate electroclinical and neuropsychological features, genetic background, and evolution of children with idiopathic encephalopathy with status epilepticus during slow sleep (ESES), including Landau-Kleffner syndrome (LKS). MATERIAL AND METHODS: All children diagnosed with idiopathic ESES at the Danish Epilepsy Centre between March 2003 and December 2014 were retrospectively reviewed. Repeated 24-hour electroencephalography (24-h EEG) recordings, neuropsychological assessments, and clinical-neurological evaluation were performed throughout the follow-up in all patients. In 13 children, genetic investigations were performed. RESULTS: We collected 24 children (14 males and 10 females). Mean age at ESES diagnosis was 6 years, and mean ESES duration was 2 years and 7 months. Twenty-one children had epileptic seizures. Three children had LKS. Topography of sleep-related EEG epileptic abnormalities was diffuse in 3 subjects, hemispheric in 6, multifocal in 9, and focal in 6. During the active phase of ESES, all children presented with a heterogeneous combination of behavioral and cognitive disturbances. In 14 children, a parallel between severity of the clinical picture and spike-wave index (SWI) was observed. We could not find a strict correlation between the type and severity of neurobehavioral impairment and the side/topography of sleep-related EEG discharges during the active phase of ESES. At the last follow-up, 21 children were in remission from ESES. Complete recovery from neurobehavioral disorders was observed in 5 children. Genetic assessment, performed in 13 children, showed GRIN2A variant in two (15.4%). SIGNIFICANCE: Our patients with idiopathic ESES showed a heterogeneous pattern of epileptic seizures, neurobehavioral disorders, and sleep EEG features. Only one-fourth of children completely recovered from the neuropsychological disturbances after ESES remission. Lack of correlation between severity/type of cognitive derangement and SWI and/or topography of sleep EEG epileptic abnormalities may suggest the contribution of additional factors (including impaired sleep homeostasis due to epileptic activity) in the neurobehavioral derangement that characterize ESES.

Quantitative EEG analysis in Encephalopathy related to Status Epilepticus during slow Sleep.

Since its first description, quantifying the burden of epileptiform abnormalities in sleep EEG has played a fundamental role in the diagnosis of Encephalopathy related to Status Epilepticus during slow Sleep (ESES). In fact, in the 1971 seminal paper by Tassinari's group and in the following studies on this syndrome, the amount of epileptiform discharges (EDs) was calculated as the percentage of slow sleep occupied by spike-and-waves and referred to as "spike and wave index" (SWI). However, nowadays it is becoming increasingly clear that the SWI alone does not explain the whole clinical course of patients affected by ESES. In this paper, we aim to provide a state-of-the-art summary of the quantitative EEG methods currently used in the ESES/CSWS literature, highlighting the possible pitfalls and discrepancies explaining the unsatisfactory correlation between SWI and clinical course. Furthermore; we illustrate a number of methodological refinements - taking into account inter-individual, intra-individual, and temporal variability of EDs - alongside "new" quantitative variables -including ED-related and sleep-related features - potentially useful to reach a reliable electro-clinical correlation in patients with ESES.

Temporal evolution of quantitative EEG within 3 days of birth in early preterm infants.

For the premature newborn, little is known about changes in brain activity during transition to extra-uterine life. We aim to quantify these changes in relation to the longer-term maturation of the developing brain. We analysed EEG for up to 72 hours after birth from 28 infants born <32 weeks of gestation. These infants had favourable neurodevelopment at 2 years of age and were without significant neurological compromise at time of EEG monitoring. Quantitative EEG was generated using features representing EEG power, discontinuity, spectral distribution, and inter-hemispheric connectivity. We found rapid changes in cortical activity over the 3 days distinct from slower changes associated with gestational age: for many features, evolution over 1 day after birth is equivalent to approximately 1 to 2.5 weeks of maturation. Considerable changes in the EEG immediately after birth implies that postnatal adaption significantly influences cerebral activity for early preterm infants. Postnatal age, in addition to gestational age, should be considered when analysing preterm EEG within the first few days after birth.

Charcot-Marie-Tooth disease with pyramidal features due to a new mutation of EGR2 gene.

BACKGROUND AND AIM OF THE WORK: Childhood-onset peripheral neuropathies are often of genetic origin. Charcot-Marie-Tooth (CMT), is considered the commonest neuromuscular disorder. Due to its high clinical heterogeneity, especially in the pediatric age, the co-existence of central and peripheral symptoms and signs does not necessarily rule out a diagnosis of hereditary peripheral neuropathy. METHODS: We describe the clinical, neurophysiological and genetic findings in a teen-age patient evaluated for acquired toe-walking and progressive difficulties in walking since the age of 5. Genetic testing was carried out with a targeted NGS panel. Identified variants are analyzed using Variant Studio program (Illumina). Rare variants and variants considered as pathogenic were analyzed by Sanger direct sequencing. RESULTS: The coexistence of peripheral and pyramidal signs in the lower limbs, the absence of a significant pre/perinatal history, the unremarkable brain and spine MRI, together with the presence of a sensory-motor polyneuropathy in all four limbs, prompted the execution of genetic investigations with an NGS panel covering hereditary spastic paraplegias, motor neuron disease and Charcot-Marie-Tooth. We identified a previously undescribed variant (c.1142G>T, p.Arg381Leu) in the EGR2 gene. CONCLUSIONS: ERG2 gene has been described as a cause of various phenotypes, including a rare autosomal dominant form of CMT (CMT type 1D) representing approximately 1% of all CMT subgroups. We describe a novel pathogenic variant in EGR2 gene leading to the development of a complex association of peripheral and central neurological signs, underscoring the genetic and clinical heterogeneity of hereditary neuropathies of pediatric onset.

Characterisation of neonatal seizures and their treatment using continuous EEG monitoring: a multicentre experience.

OBJECTIVE: The 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. METHODS: Neonates 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. RESULTS: Of 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. CONCLUSIONS: Our results show that even with access to cEEG monitoring, neonatal seizures are frequent, difficult to recognise and difficult to treat. OBERSERVATION STUDY NUMBER: NCT02160171.

What is new: Talk about status epilepticus in the neonatal period.

Nowadays, no general consensus was achieved regarding neonatal status epilepticus and its definition. Indeed, different criteria (mainly based on seizure duration) were used. Whereas a recent proposal has been developed to define status epilepticus in older ages, it seems that the peculiar characteristics of neonatal seizures and of the immature brain make difficult to find a tailored definition for this period of life. Achieving a consensus on this entity would mean to make the first step toward a targeted therapeutic strategy of intervention.

The role of electroencephalogram in neonatal seizure detection.

INTRODUCTION: The role of EEG in neonatal seizure detection is well-established, being the multichannel video-EEG the gold standard. However, in the clinical practice often amplitude integrated EEG (aEEG) is used, in order to overcome the difficulties related to EEG use. Areas covered: An overview regarding neonatal seizures, current tools used to detect these (multichannel EEG versus aEEG) with respective strenghts and limitations, and some tools that can implement the use of multichannel EEG in the NICU. Expert commentary: Multichannel video-EEG is still a gold standard for seizure detection. Indeed, this tool allows to avoid both underestimation of neonatal seizure incidence and overtreatment with anticonvulsant drugs. Furthermore, it has to be acknowledged that multichannel video-EEG monitoring is not limited to the only seizure detection, providing also the information needed for a more accurate assessment of the background activity and some specific waves/pattern and features indicative of the brain development.

Hereditary neuropathy with liability to pressure palsy (HNPP): report of a family with a new point mutation in PMP22 gene.

BACKGROUND: Hereditary neuropathy with liability to pressure palsy (HNPP) is an autosomal dominant disorder most commonly presenting with acute-onset, non-painful focal sensory and motor mononeuropathy. Approximately 80% of patients carry a 1.5 Mb deletion of chromosome 17p11.2 involving the peripheral myelin protein 22 gene (PMP22), the same duplicated in Charcot-Marie-Tooth 1A patients. In a small proportion of patients the disease is caused by PMP22 point mutations. CASE PRESENTATION: We report on a familial case harbouring a new point mutation in the PMP22 gene. The proband is a 4-years-old girl with acute onset of focal numbness and weakness in her right hand. Electroneurography demonstrated transient sensory and motor radial nerves involvement. In her father, reporting chronic symptoms (cramps and exercise-induced myalgia), we uncovered mild atrophy and areflexia on clinical examination and a mixed (predominantly demyelinating) polyneuropathy with sensory-motor involvement on electrophysiological study. Both carried a nucleotidic substitution c.178 + 2 T > C on intron 3 of the PMP22 gene, involving the splicing donor site, not reported on databases but predicted to be likely pathogenic. CONCLUSIONS: We described a previously unreported point mutation in PMP22 gene, which led to the development of a HNPP phenotype in a child and her father. In children evaluated for a sensory and motor transient episode, HNPP disorder due to PMP22 mutations should be suspected. Clinical and electrophysiological studies should be extended to all family members even in the absence of previous episodes suggestive for HNPP.

Remission of encephalopathy with status epilepticus (ESES) during sleep renormalizes regulation of slow wave sleep.

OBJECTIVE: In previous studies, we showed an altered overnight decrease of non-rapid-eye-movement (NREM) sleep slow waves in children with encephalopathy related to status epilepticus during sleep (ESES). Here, we test the hypothesis that these alterations renormalize after remission of ESES. Because overnight decrease of slow waves has been linked to brain recovery and cognition, we investigate whether cognitive outcome is related to overnight changes of slow waves. METHODS: We performed a retrospective analysis of longitudinal overnight electroencephalography (EEG) in 10 patients with idiopathic ESES. Automated slow wave detection and calculation of slope of slow waves during the first and last hour of NREM sleep were employed. Intraindividual comparisons were undertaken of the slope during active phase and after remission of ESES, and between patients after remission of ESES and healthy controls. Explorative analysis of the relationship between slow wave slope and cognitive outcome was performed. RESULTS: The slope of slow waves did not decrease significantly across the night during active ESES, particularly at the spike focus. After remission of ESES, the slope decreased significantly overnight. Compared to controls, there was no difference in overnight slope decrease. Association between slope and neuropsychological outcome showed best cognitive outcome after remission in those children (n = 3) who showed some degree of slope decline during active ESES. SIGNIFICANCE: This study provides evidence that alterations of overnight changes of NREM-sleep slow waves during active ESES are reversible when ESES resolves, and that the severity of neuropsychological compromise might be related to the extent of slow wave impairment during ESES. Our findings suggest that analysis of slow waves might serve as a prognostic factor regarding cognitive outcome. ESES may serve as disease model of pathologic slow wave sleep and our results might be expanded to epilepsies with spike wave activation in slow wave sleep not only in children but also in adults.

Alternating hemiplegia of childhood and a pathogenic variant of ATP1A3: a case report and pathophysiological considerations.

We describe a case of a child suffering from alternating hemiplegia with a heterozygous p. E815K pathogenic variant of ATP1A3. The patient started to present abnormal eye movements in the first days of life, followed by the appearance at 2 months of dystonic episodes, and later on, by recurrent episodes of alternating hemiplegia more often on the right side. A severe epilepsy started at the age of 2 years with episodes of status epilepticus since the onset which frequently recurred, requiring admission to the intensive care unit. MRI showed bilateral mesial temporal sclerosis and a left-sided ischaemic lesion. Interictal EEG showed bilateral abnormalities, whereas postictal EEG after status epilepticus showed overt slowing on the left side, suggesting a predominant involvement of ictal activity of the left hemisphere. We hypothesize that in our patient, the left hemisphere might have been more prominently affected by the pathogenetic abnormalities underlying alternating hemiplegia of childhood, rendering it more prone to early ischaemic lesions and recurrent unilateral status epilepticus. We speculate whether alternating hemiplegia of childhood shares some common pathophysiological mechanisms with familial hemiplegic migraine that may be associated with a pathogenic variant of ATP1A2.

A review of important electroencephalogram features for the assessment of brain maturation in premature infants.

This review describes the maturational features of the baseline electroencephalogram (EEG) in the neurologically healthy preterm infant. Features such as continuity, sleep state, synchrony and transient waveforms are described, even from extremely preterm infants and includes abundant illustrated examples. The physiological significance of these EEG features and their relationship to neurodevelopment are highlighted where known. This review also demonstrates the importance of multichannel conventional EEG monitoring for preterm infants as many of the features described are not apparent if limited channel EEG monitors are used. CONCLUSION: This review aims to provide healthcare professionals in the neonatal intensive care unit with guidance on the more common normal maturational features seen in the EEG of preterm infants.

EEG - A Valuable Biomarker of Brain Injury in Preterm Infants.

This review focuses on the role of electroencephalography (EEG) in monitoring abnormalities of preterm brain function. EEG features of the most common developmental brain injuries in preterm infants, including intraventricular haemorrhage, periventricular leukomalacia, and perinatal asphyxia, are described. We outline the most common EEG biomarkers associated with these injuries, namely seizures, positive rolandic sharp waves, EEG suppression/increased interburst intervals, mechanical delta brush activity, and other deformed EEG waveforms, asymmetries, and asynchronies. The increasing survival rate of preterm infants, in particular those that are very and extremely preterm, has led to a growing demand for a specific and shared characterization of the patterns related to adverse outcome in this unique population. This review includes abundant high-quality images of the EEG patterns seen in premature infants and will provide a valuable resource for everyone working in developmental neuroscience.