The use of conventional EEG for the assessment of hypoxic ischaemic encephalopathy in the newborn: a review

Advances in Electroencephalographic Biomarkers of Neonatal Hypoxic Ischemic Encephalopathy

Electroencephalography (EEG) is a key objective biomarker of newborn brain function, delivering critical, cotside insights to aid the management of encephalopathy. Access to continuous EEG is limited, forcing reliance on subjective clinical assessments. In hypoxia ischaemia, the primary cause of encephalopathy, alterations in EEG patterns correlate with. injury severity and evolution. As HIE evolves, causing secondary neuronal death, EEG can track injury progression, informing neuroprotective strategies, seizure management and prognosis. Despite its value, challenges with interpretation and lack of on site expertise has limited its broader adoption. Technological advances, particularly in digital EEG and machine learning, are enhancing real-time analysis. This will allow EEG to expand its role in HIE diagnosis, management and outcome prediction.

How do we reach the goal of personalized medicine for neuroprotection in neonatal hypoxic-ischemic encephalopathy?

Therapeutic hypothermia is now standard of care for neonates with hypoxic-ischemic encephalopathy (HIE) in high income countries (HIC). Conversely, compelling trial evidence suggests that hypothermia is ineffective, and may be deleterious, in low- and middle-income countries (LMIC), likely reflecting the lower proportion of infants who had sentinel events at birth, suggesting that injury had advanced to a stage when hypothermia is no longer effective. Although hypothermia significantly reduced the risk of death and disability in HICs, many infants survived with disability and in principle may benefit from targeted add-on neuroprotective or neurorestorative therapies. The present review will assess biomarkers that could be used to personalize treatment for babies with HIE - to determine first whether an individual infant is likely to respond to hypothermia, and second, whether additional treatments may be beneficial.

Clinical outcome prediction with an automated EEG trend, Brain State of the Newborn, after perinatal asphyxia

OBJECTIVE

To evaluate the utility of a fully automated deep learning -based quantitative measure of EEG background, Brain State of the Newborn (BSN), for early prediction of clinical outcome at four years of age.

METHODS

The EEG monitoring data from eighty consecutive newborns was analyzed using the automatically computed BSN trend. BSN levels during the first days of life (a of total 5427 hours) were compared to four clinical outcome categories: favorable, cerebral palsy (CP), CP with epilepsy, and death. The time dependent changes in BSN-based prediction for different outcomes were assessed by positive/negative predictive value (PPV/NPV) and by estimating the area under the receiver operating characteristic curve (AUC).

RESULTS

The BSN values were closely aligned with four visually determined EEG categories (p < 0·001), as well as with respect to clinical milestones of EEG recovery in perinatal Hypoxic Ischemic Encephalopathy (HIE; p < 0·003). Favorable outcome was related to a rapid recovery of the BSN trend, while worse outcomes related to a slow BSN recovery. Outcome predictions with BSN were accurate from 6 to 48 hours of age: For the favorable outcome, the AUC ranged from 95 to 99% (peak at 12 hours), and for the poor outcome the AUC ranged from 96 to 99% (peak at 12 hours). The optimal BSN levels for each PPV/NPV estimate changed substantially during the first 48 hours, ranging from 20 to 80.

CONCLUSIONS

We show that the BSN provides an automated, objective, and continuous measure of brain activity in newborns.

SIGNIFICANCE

The BSN trend discloses the dynamic nature that exists in both cerebral recovery and outcome prediction, supports individualized patient care, rapid stratification and early prognosis.

Quantitative EEG features during the first day correlate to clinical outcome in perinatal asphyxia

OBJECTIVE

To assess whether computational electroencephalogram (EEG) measures during the first day of life correlate to clinical outcomes in infants with perinatal asphyxia with or without hypoxic-ischemic encephalopathy (HIE).

METHODS

We analyzed four-channel EEG monitoring data from 91 newborn infants after perinatal asphyxia. Altogether 42 automatically computed amplitude- and synchrony-related EEG features were extracted as 2-hourly average at very early (6 h) and early (24 h) postnatal age; they were correlated to the severity of HIE in all infants, and to four clinical outcomes available in a subcohort of 40 newborns: time to full oral feeding (nasogastric tube NGT), neonatal brain MRI, Hammersmith Infant Neurological Examination (HINE) at three months, and Griffiths Scales at two years.

RESULTS

At 6 h, altogether 14 (33%) EEG features correlated significantly to the HIE grade ([r]= 0.39-0.61, p < 0.05), and one feature correlated to NGT ([r]= 0.50). At 24 h, altogether 13 (31%) EEG features correlated significantly to the HIE grade ([r]= 0.39-0.56), six features correlated to NGT ([r]= 0.36-0.49) and HINE ([r]= 0.39-0.61), while no features correlated to MRI or Griffiths Scales.

CONCLUSIONS

Our results show that the automatically computed measures of early cortical activity may provide outcome biomarkers for clinical and research purposes.

IMPACT

The early EEG background and its recovery after perinatal asphyxia reflect initial severity of encephalopathy and its clinical recovery, respectively. Computational EEG features from the early hours of life show robust correlations to HIE grades and to early clinical outcomes. Computational EEG features may have potential to be used as cortical activity biomarkers in early hours after perinatal asphyxia.

Electroencephalography Prediction of Neurological Outcomes After Hypoxic-Ischemic Brain Injury: A Systematic Review and Meta-Analysis

Background. Predicting neurological outcomes after hypoxic-ischemic brain injury (HIBI) is difficult. Objective. Electroencephalography (EEG) can identify acute and subacute brain abnormalities after hypoxic brain injury and predict HIBI recovery. We examined EEG's ability to predict neurologic outcomes following HIBI. Method. A PRISMA-compliant search was conducted in the Medline, Embase, Cochrane, and Central databases until January 2023. EEG-predicted neurological outcomes in HIBI patients were selected from relevant perspective and retrospective cohort studies. RevMan did meta-analysis, while QDAS2 assessed research quality. Results. Eleven studies with 3761 HIBI patients met the inclusion and exclusion criteria. We aggregated study-level estimates of sensitivity and specificity for EEG patterns determined a priori using random effect bivariate and univariate meta-analysis when appropriate. Positive indicators and anatomical area heterogeneity impacted prognosis accuracy. Funnel plots analyzed publication bias. Significant heterogeneity of greater than 80% was among the included studies with P < 0.001. The area under the curve was 0.94, the threshold effect was P < 0.001, and the sensitivity and specificity, with 95% confidence intervals, were 0.91 (0.84-0.99) and 0.86 (0.75-0.97). EEG detects status epilepticus and burst suppression with good sensitivity, specificity, and little probability of false-negative impairment result attribution. Study quality varied by domain, but patient flow and timing were well conducted in all. Conclusion. EEG can predict the outcome of HIBI with good prognostic accuracy, but more standardized cross-study protocols and descriptions of EEG patterns are needed to better evaluate its prognostic use for patients with HIBI.

Technical feasibility of multimodal imaging in neonatal hypoxic-ischemic encephalopathy from an ovine model to a human case series

Hypoxic-ischemic encephalopathy (HIE) secondary to perinatal asphyxia occurs when the brain does not receive enough oxygen and blood. A surrogate marker for "intact survival" is necessary for the successful management of HIE. The severity of HIE can be classified based on clinical presentation, including the presence of seizures, using a clinical classification scale called Sarnat staging; however, Sarnat staging is subjective, and the score changes over time. Furthermore, seizures are difficult to detect clinically and are associated with a poor prognosis. Therefore, a tool for continuous monitoring on the cot side is necessary, for example, an electroencephalogram (EEG) that noninvasively measures the electrical activity of the brain from the scalp. Then, multimodal brain imaging, when combined with functional near-infrared spectroscopy (fNIRS), can capture the neurovascular coupling (NVC) status. In this study, we first tested the feasibility of a low-cost EEG-fNIRS imaging system to differentiate between normal, hypoxic, and ictal states in a perinatal ovine hypoxia model. Here, the objective was to evaluate a portable cot-side device and perform autoregressive with extra input (ARX) modeling to capture the perinatal ovine brain states during a simulated HIE injury. So, ARX parameters were tested with a linear classifier using a single differential channel EEG, with varying states of tissue oxygenation detected using fNIRS, to label simulated HIE states in the ovine model. Then, we showed the technical feasibility of the low-cost EEG-fNIRS device and ARX modeling with support vector machine classification for a human HIE case series with and without sepsis. The classifier trained with the ovine hypoxia data labeled ten severe HIE human cases (with and without sepsis) as the "hypoxia" group and the four moderate HIE human cases as the "control" group. Furthermore, we showed the feasibility of experimental modal analysis (EMA) based on the ARX model to investigate the NVC dynamics using EEG-fNIRS joint-imaging data that differentiated six severe HIE human cases without sepsis from four severe HIE human cases with sepsis. In conclusion, our study showed the technical feasibility of EEG-fNIRS imaging, ARX modeling of NVC for HIE classification, and EMA that may provide a biomarker of sepsis effects on the NVC in HIE.

Neonatal EEG graded for severity of background abnormalities in hypoxic-ischaemic encephalopathy

This report describes a set of neonatal electroencephalogram (EEG) recordings graded according to the severity of abnormalities in the background pattern. The dataset consists of 169 hours of multichannel EEG from 53 neonates recorded in a neonatal intensive care unit. All neonates received a diagnosis of hypoxic-ischaemic encephalopathy (HIE), the most common cause of brain injury in full term infants. For each neonate, multiple 1-hour epochs of good quality EEG were selected and then graded for background abnormalities. The grading system assesses EEG attributes such as amplitude, continuity, sleep-wake cycling, symmetry and synchrony, and abnormal waveforms. Background severity was then categorised into 4 grades: normal or mildly abnormal EEG, moderately abnormal EEG, majorly abnormal EEG, and inactive EEG. The data can be used as a reference set of multi-channel EEG for neonates with HIE, for EEG training purposes, or for developing and evaluating automated grading algorithms.

Partial wavelet coherence as a robust method for assessment of neurovascular coupling in neonates with hypoxic ischemic encephalopathy

In neonates with hypoxic ischemic encephalopathy, the computation of wavelet coherence between electroencephalogram (EEG) power and regional cerebral oxygen saturation (rSO2) is a promising method for the assessment of neurovascular coupling (NVC), which in turn is a promising marker for brain injury. However, instabilities in arterial oxygen saturation (SpO2) limit the robustness of previously proposed methods. Therefore, we propose the use of partial wavelet coherence, which can eliminate the influence of SpO2. Furthermore, we study the added value of the novel NVC biomarkers for identification of brain injury compared to traditional EEG and NIRS biomarkers. 18 neonates with HIE were monitored for 72 h and classified into three groups based on short-term MRI outcome. Partial wavelet coherence was used to quantify the coupling between C3-C4 EEG bandpower (2-16 Hz) and rSO2, eliminating confounding effects of SpO2. NVC was defined as the amount of significant coherence in a frequency range of 0.25-1 mHz. Partial wavelet coherence successfully removed confounding influences of SpO2 when studying the coupling between EEG and rSO2. Decreased NVC was related to worse MRI outcome. Furthermore, the combination of NVC and EEG spectral edge frequency (SEF) improved the identification of neonates with mild vs moderate and severe MRI outcome compared to using EEG SEF alone. Partial wavelet coherence is an effective method for removing confounding effects of SpO2, improving the robustness of automated assessment of NVC in long-term EEG-NIRS recordings. The obtained NVC biomarkers are more sensitive to MRI outcome than traditional rSO2 biomarkers and provide complementary information to EEG biomarkers.

An automated bedside measure for monitoring neonatal cortical activity: a supervised deep learning-based electroencephalogram classifier with external cohort validation

BACKGROUND

Electroencephalogram (EEG) monitoring is recommended as routine in newborn neurocritical care to facilitate early therapeutic decisions and outcome predictions. EEG's larger-scale implementation is, however, hindered by the shortage of expertise needed for the interpretation of spontaneous cortical activity, the EEG background. We developed an automated algorithm that transforms EEG recordings to quantified interpretations of EEG background and provides simple intuitive visualisations in patient monitors.

METHODS

In this method-development and proof-of-concept study, we collected visually classified EEGs from infants recovering from birth asphyxia or stroke. We used unsupervised learning methods to explore latent EEG characteristics, which guided the supervised training of a deep learning-based classifier. We assessed the classifier performance using cross-validation and an external validation dataset. We constructed a novel measure of cortical function, brain state of the newborn (BSN), from the novel EEG background classifier and a previously published sleep-state classifier. We estimated clinical utility of the BSN by identification of two key items in newborn brain monitoring, the onset of continuous cortical activity and sleep-wake cycling, compared with the visual interpretation of the raw EEG signal and the amplitude-integrated (aEEG) trend.

FINDINGS

We collected 2561 h of EEG from 39 infants (gestational age 35·0-42·1 weeks; postnatal age 0-7 days). The external validation dataset included 105 h of EEG from 31 full-term infants. The overall accuracy of the EEG background classifier was 92% in the whole cohort (95% CI 91-96; range 85-100 for individual infants). BSN trend values were closely related to the onset of continuous EEG activity or sleep-wake cycling, and BSN levels showed robust difference between aEEG categories. The temporal evolution of the BSN trends showed early diverging trajectories in infants with severely abnormal outcomes.

INTERPRETATION

The BSN trend can be implemented in bedside patient monitors as an EEG interpretation that is intuitive, transparent, and clinically explainable. A quantitative trend measure of brain function might harmonise practices across medical centres, enable wider use of brain monitoring in neurocritical care, and might facilitate clinical intervention trials.

FUNDING

European Training Networks Funding Scheme, the Academy of Finland, Finnish Pediatric Foundation (Lastentautiensäätiö), Aivosäätiö, Sigrid Juselius Foundation, HUS Children's Hospital, HUS Diagnostic Center, National Health and Medical Research Council of Australia.

Cortical networks show characteristic recruitment patterns after somatosensory stimulation by pneumatically evoked repetitive hand movements in newborn infants

Controlled assessment of functional cortical networks is an unmet need in the clinical research of noncooperative subjects, such as infants. We developed an automated, pneumatic stimulation method to actuate naturalistic movements of an infant’s hand, as well as an analysis pipeline for assessing the elicited electroencephalography (EEG) responses and related cortical networks. Twenty newborn infants with perinatal asphyxia were recruited, including 7 with mild-to-moderate hypoxic–ischemic encephalopathy (HIE). Statistically significant corticokinematic coherence (CKC) was observed between repetitive hand movements and EEG in all infants, peaking near the contralateral sensorimotor cortex. CKC was robust to common sources of recording artifacts and to changes in vigilance state. A wide recruitment of cortical networks was observed with directed phase transfer entropy, also including areas ipsilateral to the stimulation. The extent of such recruited cortical networks was quantified using a novel metric, Spreading Index, which showed a decrease in 4 (57%) of the infants with HIE. CKC measurement is noninvasive and easy to perform, even in noncooperative subjects. The stimulation and analysis pipeline can be fully automated, including the statistical evaluation of the cortical responses. Therefore, the CKC paradigm holds great promise as a scientific and clinical tool for controlled assessment of functional cortical networks.

Preconditioning in hypoxic-ischemic neonate mice triggers Na+-Ca2+ exchanger-dependent neurogenesis

To identify alternative interventions in neonatal hypoxic-ischemic encephalopathy, researchers’ attention has been focused to the study of endogenous neuroprotective strategies. Based on the preconditioning concept that a subthreshold insult may protect from a subsequent harmful event, we aimed at identifying a new preconditioning protocol able to enhance Ca²⁺-dependent neurogenesis in a mouse model of neonatal hypoxia ischemia (HI). To this purpose, we also investigated the role of the preconditioning-linked protein controlling ionic homeostasis, Na⁺/Ca²⁺ exchanger (NCX). Hypoxic Preconditioning (HPC) was reproduced by exposing P7 mice to 20’ hypoxia. HI was induced by isolating and cutting the right common carotid artery. A significant reduction in ischemic damage was observed in mice subjected to 20’ hypoxia followed,3 days later, by 60’ HI, thus suggesting that 20’ hypoxia functions as preconditioning stimulus. HPC promoted neuroblasts proliferation in the dentate gyrus mirrored by an increase of NCX1 and NCX3-positive cells and an improvement of behavioral motor performances in HI mice. An attenuation of HPC neuroprotection as well as a reduction in the expression of neurogenesis markers, including p57 and NeuroD1, was observed in preconditioned mice lacking NCX1 or NCX3. In summary, PC in neonatal mice triggers a neurogenic process linked to ionic homeostasis maintenance, regulated by NCX1 and NCX3.

An Introduction to Neonatal EEG

Newborn care has witnessed significant improvements in survival, but ongoing concerns persist about neurodevelopmental outcome. Protecting the newborn brain is the focus of neurocritical care in the intensive care unit. Brain-focused care places emphasis on clinical practices supporting neurodevelopment in conjunction with early detection, diagnosis, and treatment of brain injury. Technology now facilitates continuous cot-side monitoring of brain function. Neuromonitoring techniques in neonatal intensive care units include the use of electroencephalography (EEG) or amplitude-integrated EEG (aEEG) and near-infrared spectroscopy. This article aims to provide an introduction to EEG, which is appropriate for neonatal healthcare professionals.

Consensus protocol for EEG and amplitude-integrated EEG assessment and monitoring in neonates

The aim of this work is to establish inclusive guidelines on electroencephalography (EEG) applicable to all neonatal intensive care units (NICUs). Guidelines on ideal EEG monitoring for neonates are available, but there are significant barriers to their implementation in many centres around the world. These include barriers due to limited resources regarding the availability of equipment and technical and interpretive round-the-clock personnel. On the other hand, despite its limitations, amplitude-integrated EEG (aEEG) (previously called Cerebral Function Monitor [CFM]) is a common alternative used in NICUs. The Italian Neonatal Seizure Collaborative Network (INNESCO), working with all national scientific societies interested in the field of neonatal clinical neurophysiology, performed a systematic literature review and promoted interdisciplinary discussions among experts (neonatologists, paediatric neurologists, neurophysiologists, technicians) between 2017 and 2020 with the aim of elaborating shared recommendations. A consensus statement on videoEEG (vEEG) and aEEG for the principal neonatal indications was established. The authors propose a flexible frame of recommendations based on the complementary use of vEEG and aEEG applicable to the various neonatal units with different levels of complexity according to local resources and specific patient features. Suggestions for promoting cooperation between neonatologists, paediatric neurologists, and neurophysiologists, organisational restructuring, and teleneurophysiology implementation are provided.

Quantitative approach to early neonatal EEG visual analysis in hypoxic-ischemic encephalopathy severity: Bridging the gap between eyes and machine

OBJECTIVES

To identify relevant quantitative parameters for early classification of neonatal hypoxic-ischemic encephalopathy (HIE) severity from conventional EEGs.

METHODS

Ninety EEGs, recorded in full-term infants within 6 h of life after perinatal hypoxia, were visually classified according to the French EEG classification into three groups of increasing HIE severity. Physiologically significant EEG features (signal amplitude, continuity and frequency content) were automatically quantified using different parameters. The EEG parameters selection was based on their ability to reproduce the visual EEG classification. Post hoc analysis based on clinical outcome was performed.

RESULTS

Six EEG parameters were selected, with overall EEG classification performances between 61% and 70%. All parameters differed significantly between group 3 (severe) and groups 1 (normal-mildly abnormal) and 2 (moderate) EEGs (p < 0.001). Amplitude and discontinuity parameters were different between the 3 groups (p < 0.01) and were also the best predictors of clinical outcome. Conversely, pH and lactate did not differ between groups.

DISCUSSION

This study provides quantitative EEG parameters that are complementary to visual analysis as early markers of neonatal HIE severity. These parameters could be combined in a multiparametric algorithm to improve their classification performance. The absence of relationship between pH lactate and HIE severity reinforces the central role of early neonatal EEG.

Grading the severity of hypoxic-ischemic encephalopathy in newborn EEG using a convolutional neural network

Electroencephalography (EEG) is a valuable clinical tool for grading injury caused by lack of blood and oxygen to the brain during birth. This study presents a novel end-to-end architecture, using a deep convolutional neural network, that learns hierarchical representations within raw EEG data. The system classifies 4 grades of hypoxic-ischemic encephalopathy and is evaluated on a multi-channel EEG dataset of 63 hours from 54 newborns. The proposed method achieves a testing accuracy of 79.6% with one-step voting and 81.5% with two-step voting. These results show how a feature-free approach can be used to classify different grades of injury in newborn EEG with comparable accuracy to existing feature-based systems. Automated grading of newborn background EEG could help with the early identification of those infants in need of interventional therapies such as hypothermia.

Comparison of conventional, amplitude-integrated and geodesic sensor net EEG used in premature neonates: a systematic review

INTRODUCTION

The use of methods to evaluate cortical activity in neonates has great importance in modern medicine, as it allows the observation and evaluation of several clinical aspects, which guarantees that the health team has knowledge about possible intervention measures that may be necessary in the treatment of newborns.

OBJECTIVE

This systematic review aimed to compare the main technologies available for the evaluation of brain functions in neonates, among them: the conventional electroencephalogram (EEG), the amplitude-integrated electroencephalogram (aEEG) and the geodesic sensor net EEG.

METHODS

A search was conducted forarticles from national and international periodicals included in the Web of Science, LILACS, SciELO and Medline electronic databases.

RESULTS

The search found 39 among 155 articles of interest and the analyses indicated that, in the clinical environment, the use of both conventional EEG and aEEG is highly recommended, as the combination of their functions allows, for example, a greater number of subclinical seizures to be detected. Conversely, the use of a geodesic sensor net EEG could be of great value, as it allows a large amount of data to be analyzed.

CONCLUSION

This analysis may be useful in studies and research related to diseases and symptoms, such as seizures, a current challenge for neonatal neuromonitoring, as well as aspects of neurological development and functional studies. However, despite many advances in technology, electroencephalography in preterm neonates remains a challenge worldwide and still requires more robust research and efforts towards the best clinical assistance in this extremely early stage of life.

Caveats of Cooling: Available Evidence and Ongoing Investigations of Therapeutic Hypothermia

Therapeutic hypothermia (TH) mitigates the long-term effects of neuronal excitotoxicity and cell death seen in hypoxic-ischemic encephalopathy (HIE). It remains the most evidence-based therapy for HIE, but it is not without clinical controversy. The literature abounds with questions, such as "When should we start cooling-as early as the delivery room?" "Given the efficacy of TH for moderate to severe HIE when started within 6 hours of birth, can we expand the therapy to infants with mild HIE?" "What should the target temperature be?" "What is the optimal duration of treatment?" "Is early discontinuation acceptable if the examination findings normalize?" These questions about TH, its incomplete neurologic rescue, and variations in the delivery of this therapy have prompted this review. This article summarizes changing procedural considerations for TH, the level of neuromonitoring available, the use of sedation, and considerations for neuroimaging during and after TH.

Suitability of an inter-burst detection method for grading hypoxic-ischemic encephalopathy in newborn EEG

Electroencephalography (EEG) is an important clinical tool for grading injury caused by lack of oxygen or blood to the brain during birth. Characteristics of low-voltage waveforms, known as inter-bursts, are related to different grades of injury. This study assesses the suitability of an existing inter-burst detection method, developed from preterm infants born <; 30 weeks of gestational age, to detect inter-bursts in term infants. Different features from the temporal organisation of the inter-bursts are combined using a multi-layer perceptron (MLP) machine learning algorithm to classify four grades of injury in the EEG. We find that the best performing feature, percentage of inter-bursts, has an accuracy of 59.3%. Combining this with the maximum duration of inter-bursts in the MLP produces a testing accuracy of 77.8%, with similar performance to existing multi-feature methods. These results validate the use of the preterm detection method in term EEG and show how simple measures of the inter-burst interval can be used to classify different grades of injury.

Untargeted metabolomic analysis and pathway discovery in perinatal asphyxia and hypoxic-ischaemic encephalopathy

Elucidating metabolic effects of hypoxic-ischaemic encephalopathy (HIE) may reveal early biomarkers of injury and new treatment targets. This study uses untargeted metabolomics to examine early metabolic alterations in a carefully defined neonatal population. Infants with perinatal asphyxia who were resuscitated at birth and recovered (PA group), those who developed HIE (HIE group) and healthy controls were all recruited at birth. Metabolomic analysis of cord blood was performed using direct infusion FT-ICR mass spectrometry. For each reproducibly detected metabolic feature, mean fold differences were calculated HIE vs. controls (ΔHIE) and PA vs. controls (ΔPA). Putative metabolite annotations were assigned and pathway analysis was performed. Twenty-nine putatively annotated metabolic features were significantly different in ΔPA after false discovery correction ( q < 0.05), with eight of these also significantly altered in ΔHIE. Altered putative metabolites included; melatonin, leucine, kynurenine and 3-hydroxydodecanoic acid which differentiated between infant groups (ΔPA and ΔHIE); and D-erythrose-phosphate, acetone, 3-oxotetradecanoic acid and methylglutarylcarnitine which differentiated across severity grades of HIE. Pathway analysis revealed ΔHIE was associated with a 50% and 75% perturbation of tryptophan and pyrimidine metabolism, respectively. We have identified perturbed metabolic pathways and potential biomarkers specific to PA and HIE, which measured at birth, may help direct treatment.

Diagnosis of seizures and encephalopathy using conventional EEG and amplitude integrated EEG

Seizures are more common in the neonatal period than at any other time of life, partly due to the relative hyperexcitability of the neonatal brain. Brain monitoring of sick neonates in the NICU using either conventional electroencephalography or amplitude integrated EEG is essential to accurately detect seizures. Treatment of seizures is important, as evidence increasingly indicates that seizures damage the brain in addition to that caused by the underlying etiology. Prompt treatment has been shown to reduce seizure burden with the potential to ameliorate seizure-mediated damage. Neonatal encephalopathy most commonly caused by a hypoxia-ischemia results in an alteration of mental status and problems such as seizures, hypotonia, apnea, and feeding difficulties. Confirmation of encephalopathy with EEG monitoring can act as an important adjunct to other investigations and the clinical examination, particularly when considering treatment strategies such as therapeutic hypothermia. Brain monitoring also provides useful early prognostic indicators to clinicians. Recent use of machine learning in algorithms to continuously monitor the neonatal EEG, detect seizures, and grade encephalopathy offers the exciting prospect of real-time decision support in the NICU in the very near future.

Biomarkers in neonatal hypoxic-ischemic encephalopathy-Review of the literature to date and future directions for research

The widespread introduction of therapeutic hypothermia as a standard of care in hypoxic-ischemic encephalopathy (HIE) has brought increasing pressure on clinicians to make an early and accurate assessment of the degree of hypoxic injury (HI) that has occurred and the severity of the encephalopathy that will ensue. No single blood-based marker is currently robust enough to detect significant HI or predict outcome. However, research in the field has been active in the last 10 years and we know that HIE is associated with predictable alterations in the expression of a number of inflammatory proteins, neuron-specific proteins, metabolite pathways, and microRNA. These alterations evolve quickly over the first hours and days of life. Predictive power varies depending on the timing of measurement of the biomarker, the sample type, and the case mix of the cohort examined. Combining clinical data with biochemical measurements is currently the most likely path toward improved detection and prediction of outcome in neonatal HIE.

Predictive value of early EEG for seizures in neonates with hypoxic-ischemic encephalopathy undergoing therapeutic hypothermia

OBJECTIVES

To assess the prognostic significance of an early normal/mildly abnormal conventional EEG (cEEG) on seizure risk in neonates undergoing therapeutic hypothermia.

METHODS

We reviewed the video-EEG recordings from a large cohort of neonates treated with therapeutic hypothermia for hypoxic-ischemic encephalopathy from 2008 to 2017 in a single tertiary center. Continuous video-EEG was started as soon as possible (median 8.2 h) and continued throughout hypothermia and rewarming. We studied those neonates with a normal/mildly abnormal EEG during the first 24 h of monitoring.

RESULTS

A total of 331 neonates were treated with hypothermia and 323 had cEEG recordings available for review; 99 were excluded because of a moderately/severely abnormal cEEG background and/or seizure during the first 24 h of recording, and an additional eight because of early rewarming. The remaining 216 had a normal/mildly abnormal cEEG in the first 24 h. None of these patients subsequently developed seizures.

CONCLUSION

A normal/mildly abnormal cEEG during the first 24 h indicates a very low risk of subsequent seizures. This suggests that cEEG monitoring can be safely discontinued after 24 h if it has remained normal or excessively discontinuous and no seizures are detected, limiting the need for this resource-intensive and expensive tool.

Visual and Quantitative Electroencephalographic Analysis in Healthy Term Neonates Within the First Six Hours and the Third Day of Life

BACKGROUND

What constitutes a "normal" background electroencephalography (EEG) rhythm immediately after birth is not well understood. We performed video-electroencephalography recordings in the first six hours (first measure) and the third day of life (second measure) for evidence of transient changes in brain function.

METHODS

We performed a cohort study of an incidental sample of healthy term neonates in a single-center nursery. Main outcome measures were as follows: (1) EEG visual analysis, which included sleep-wake cycles, proportions of discontinuity and bursts with delta brushes, and number per hour of alpha/theta rolandic activity, encoches frontales, and transients; and (2) the electroencephalographic spectral analysis, which included power spectrum in the following frequency bands: delta, 0.5 to 4 Hz; theta, 4 to 8 Hz; alpha, 8 to 13 Hz; and beta, 13 to 30 Hz. Theta/delta and alpha/delta ratios were also calculated.

RESULTS

Twenty-two babies were enrolled. Significant findings (P < 0.05) in the first six hours with respect to 48 to 72 hours of life were (1) increased discontinuity, indeterminate sleep, and bursts with delta brushes; (2) higher number of transients, and lower number of alpha/theta rolandic activity and encoches frontales. Minimal changes were found in power spectrum data. However, using receiver operating characteristic curve analysis, theta/delta ratio ≤0.484 was the best cutoff to discriminate between the two measures (positive predictive value, 100.0; 95% confidence interval 71.0 to 100).

CONCLUSIONS

In healthy term neonates, immature electroencephalographic patterns, lack of clearly defined sleep-wake cycles, and frequent transients can be considered normal electroencephalographic findings in the first six hours of life. Normative power spectrum data are provided. These findings suggest that neonatal adaptation immediately after birth leads to transient changes in brain function.

Neonatal Hypoxia Ischaemia: Mechanisms, Models, and Therapeutic Challenges

Neonatal hypoxia-ischaemia (HI) is the most common cause of death and disability in human neonates, and is often associated with persistent motor, sensory, and cognitive impairment. Improved intensive care technology has increased survival without preventing neurological disorder, increasing morbidity throughout the adult population. Early preventative or neuroprotective interventions have the potential to rescue brain development in neonates, yet only one therapeutic intervention is currently licensed for use in developed countries. Recent investigations of the transient cortical layer known as subplate, especially regarding subplate's secretory role, opens up a novel set of potential molecular modulators of neonatal HI injury. This review examines the biological mechanisms of human neonatal HI, discusses evidence for the relevance of subplate-secreted molecules to this condition, and evaluates available animal models. Neuroserpin, a neuronally released neuroprotective factor, is discussed as a case study for developing new potential pharmacological interventions for use post-ischaemic injury.

Treatment Effects on Neonatal EEG

Conventional EEG and amplitude-integrated electroencephalography are used in neonates to assess prognosis and significant changes in brain activity. Neuroactive medications and hypothermia can influence brain activity and therefore alter EEG interpretation. There are limited studies on the effect of these therapies on neonatal EEG background activity. Medication effects on the EEG or amplitude-integrated electroencephalography include increased interburst interval duration, voltage suppression, and sleep disruption. The effect is transient in term newborns but can be persistent in premature newborns. Although therapeutic hypothermia does not produce significant changes in EEG activity, it does change the time point at which EEG can accurately predict neurodevelopmental outcome. It is important to account for these effects on the EEG to avoid inaccurate interpretation that may affect prognostication.

Electroencephalographic discontinuity during sevoflurane anesthesia in infants and children

BACKGROUND

Deep anesthesia in adults may be associated with electroencephalographic (EEG) suppression and higher rates of postoperative complications. Little is known about the impact of anesthetic depth on short- or long-term outcomes in pediatrics. Brain activity monitoring may complement clinical signs of anesthetic depth. This prospective observational study aimed to assess the frequency and degree of profound EEG suppression using multichannel EEG in children during sevoflurane general anesthesia.

METHODS

Children aged 0-40 months who required general anesthesia for elective surgery were included. Continuous EEG recordings were performed starting from when anesthesia began and until recovery. Discontinuity was defined as EEG amplitude <25 uV, lasting ≥2 s, and observed in all electrodes across the scalp. Frequency, duration, and inter-event interval of discontinuity events were measured. Relationships between discontinuity events and postnatal age, endtidal sevoflurane concentration (etSEVO), and multiple clinical parameters were analyzed.

RESULTS

Discontinuity events were observed in 35/68 children, with a median duration of 10 s (95%CI: 8-12) and a median of 4 events per patient (95%CI: 2-7). Children who had discontinuity events were younger (5.5 months, 95%CI: 3.6-6.5) compared to children who did not have discontinuity events (10.2 months, 95%CI: 6.1-14); (difference between medians, 4.7 months, 95%CI: 2.3-8, P = 0.0002). Younger infants exhibited a higher number of discontinuity events, and the incidence decreased with postnatal age (r₆₈ = -0.53, P < 0.0001). The majority of discontinuity events were observed during the first 30 min of anesthesia (66.4% total events), where etSEVO was >3%. Few discontinuity events were observed during maintenance and none during emergence. Blood pressure, heart rate, tissue oxygen saturation, and endtidal CO₂ partial pressure did not change during these events.

CONCLUSIONS

Electroencephalographic monitoring may complement clinical signs in providing information about brain homeostasis during general anesthesia. The impact of discontinuity events on immediate and long-term outcomes merits further study.

The Correlation Between a Short-term Conventional Electroencephalography in the First Day of Life and Brain Magnetic Resonance Imaging in Newborns Undergoing Hypothermia for Hypoxic-Ischemic Encephalopathy

OBJECTIVE

Electroencephalograph recorded in the first day of life in newborns treated with hypothermia for hypoxic-ischemic encephalopathy could be utilized as a predictive tool for the severity of brain injury on magnetic resonance imaging and mortality.

STUDY DESIGN

We analyzed newborns who were admitted for therapeutic hypothermia due to hypoxic-ischemic encephalopathy. All enrolled infants underwent encephalography within the first 24 hours of life and underwent brain magnetic resonance imaging after rewarming. All encephalographs were independently reviewed for background amplitude, continuity, and variability. Brain injury determined by magnetic resonance imaging was scored using methods described by Bonifacio et al.

RESULTS

Forty-one newborns were included in the study. Each encephalograph variable correlated significantly with the severity of injury on brain magnetic resonance imaging (P < 0.001 for each). The overall encephalograph severity estimated as mild, moderate, and severe also correlated with injury (P < 0.001). Each encephalograph variable correlated with mortality (P < 0.001 for each) and also the overall encephalograph severity (P < 0.001).

CONCLUSION

Severity of electrographic findings on encephalograph in the first day of life during therapeutic hypothermia for hypoxic-ischemic encephalopathy correlated with the extent of injury on brain magnetic resonance imaging. This information may be useful for families and aid guide clinical decision making.

Abnormal Interhemispheric Synchrony in Neonatal Hypoxic-Ischemic Encephalopathy: A Retrospective Pilot Study

BACKGROUND

Abnormal interhemispheric synchrony has been described in many clinical compromises in brain function, but its prognostic value in neonatal hypoxic-ischemic encephalopathy (HIE) is unknown.

OBJECTIVES

The study aimed at describing the frequency of abnormal interhemispheric synchrony in infants with HIE and to explore its prognostic value. The main outcome was survival without major disabilities.

METHODS

We performed a single-center retrospective cohort study and enrolled 40 neonates with HIE who underwent hypothermia.

RESULTS

Abnormal interhemispheric synchrony was observed in 23% of the patients with HIE. Sensitivity and specificity values for predicting survival without major disabilities were 90 and 67% for seizures, 50 and 97% for status epilepticus, 60 and 97% for highly abnormal EEG in the first 48 h, and 80 and 97% for EEG asynchrony, respectively. The prognostic value of asynchrony improved to 100% sensitivity, whereas specificity remained unchanged, when associated with highly abnormal EEG within the first 48 h of life.

CONCLUSIONS

Abnormal interhemispheric synchrony was observed in a quarter of the patients with HIE. This pilot study suggests that the prognostic value of asynchrony is excellent, especially when combined with EEG background analysis.

Short and long term prognosis in perinatal asphyxia: An update

Interruption of blood flow and gas exchange to the fetus in the perinatal period, known as perinatal asphyxia, can, if significant, trigger a cascade of neuronal injury, leading on to neonatal encephalopathy (NE) and resultant long-term damage. While the majority of infants who are exposed to perinatal hypoxia-ischaemia will recover quickly and go on to have a completely normal survival, a proportion will suffer from an evolving clinical encephalopathy termed hypoxic-ischaemic encephalopathy (HIE) or NE if the diagnosis is unclear. Resultant complications of HIE/NE are wide-ranging and may affect the motor, sensory, cognitive and behavioural outcome of the child. The advent of therapeutic hypothermia as a neuroprotective treatment for those with moderate and severe encephalopathy has improved prognosis. Outcome prediction in these infants has changed, but is more important than ever, as hypothermia is a time sensitive intervention, with a very narrow therapeutic window. To identify those who will benefit from current and emerging neuroprotective therapies we must be able to establish the severity of their injury soon after birth. Currently available indicators such as blood biochemistry, clinical examination and electrophysiology are limited. Emerging biological and physiological markers have the potential to improve our ability to select those infants who will benefit most from intervention. Biomarkers identified from work in proteomics, metabolomics and transcriptomics as well as physiological markers such as heart rate variability, EEG analysis and radiological imaging when combined with neuroprotective measures have the potential to improve outcome in HIE/NE. The aim of this review is to give an overview of the literature in regards to short and long-term outcome following perinatal asphyxia, and to discuss the prediction of this outcome in the early hours after birth when intervention is most crucial; looking at both currently available tools and introducing novel markers.

Preterm Hypoxic-Ischemic Encephalopathy

Hypoxic-ischemic encephalopathy (HIE) is a recognizable and defined clinical syndrome in term infants that results from a severe or prolonged hypoxic-ischemic episode before or during birth. However, in the preterm infant, defining hypoxic-ischemic injury (HII), its clinical course, monitoring, and outcomes remains complex. Few studies examine preterm HIE, and these are heterogeneous, with variable inclusion criteria and outcomes reported. We examine the available evidence that implies that the incidence of hypoxic-ischemic insult in preterm infants is probably higher than recognized and follows a more complex clinical course, with higher rates of adverse neurological outcomes, compared to term infants. This review aims to elucidate the causes and consequences of preterm hypoxia-ischemia, the subsequent clinical encephalopathy syndrome, diagnostic tools, and outcomes. Finally, we suggest a uniform definition for preterm HIE that may help in identifying infants most at risk of adverse outcomes and amenable to neuroprotective therapies.

Early Cord Metabolite Index and Outcome in Perinatal Asphyxia and Hypoxic-Ischaemic Encephalopathy

BACKGROUND

A 1H-NMR-derived metabolomic index based on early umbilical cord blood alterations of succinate, glycerol, 3-hydroxybutyrate and O-phosphocholine has shown potential for the prediction of hypoxic-ischaemic encephalopathy (HIE) severity.

OBJECTIVE

To evaluate whether this metabolite score can predict 3-year neurodevelopmental outcome in infants with perinatal asphyxia and HIE, compared with current standard biochemical and clinical markers.

METHODS

From September 2009 to June 2011, infants at risk of perinatal asphyxia were recruited from a single maternity hospital. Cord blood was drawn and biobanked at delivery. Neonates were monitored for development of encephalopathy both clinically and electrographically. Neurodevelopmental outcome was assessed at 36-42 months using the Bayley Scales of Infant and Toddler Development, ed. III (BSID-III). Death and cerebral palsy were also considered as abnormal end points.

RESULTS

Thirty-one infants had both metabolomic analysis and neurodevelopmental outcome at 36-42 months. No child had a severely abnormal BSID-III result. The metabolite index significantly correlated with outcome (ρ2 = 0.30, p < 0.01), which is robust to predict both severe outcome (area under the receiver operating characteristic curve: 0.92, p < 0.01) and intact survival (0.80, p = 0.01). There was no correlation between the index score and performance in the individual BSID-III subscales (cognitive, language, motor).

CONCLUSIONS

The metabolite index outperformed other standard biochemical markers at birth for prediction of outcome at 3 years, but was not superior to EEG or the Sarnat score.

Improving Reliability of Monitoring Background EEG Dynamics in Asphyxiated Infants

The goal of this study is to develop an automated algorithm to quantify background electroencephalography (EEG) dynamics in term neonates with hypoxic ischemic encephalopathy. The recorded EEG signal is adaptively segmented and the segments with low amplitudes are detected. Next, depending on the spatial distribution of the low-amplitude segments, the first part of the algorithm detects (dynamic) interburst intervals (dIBIs) and performs well on the relatively artifact-free EEG periods and well-defined burst-suppression EEG periods. However, on testing the algorithm on EEG recordings of more than 48 h per neonate, a significant number of misclassified and dubious detections were encountered. Therefore, as the next step, we applied machine learning classifiers to differentiate between definite dIBI detections and misclassified ones. The developed algorithm achieved a true positive detection rate of 98%, 97%, 88%, and 95% for four duration-related dIBI groups that we subsequently defined. We benchmarked our algorithm with an expert diagnostic interpretation of EEG periods (1 h long) and demonstrated its effectiveness in clinical practice. We show that the detection algorithm effectively discriminates challenging cases encountered within mild and moderate background abnormalities. The dIBI detection algorithm improves identification of neonates with good clinical outcome as compared to the classification based on the classical burst-suppression interburst interval.

Objective differentiation of neonatal EEG background grades using detrended fluctuation analysis

A quantitative and objective assessment of background electroencephalograph (EEG) in sick neonates remains an everyday clinical challenge. We studied whether long range temporal correlations quantified by detrended fluctuation analysis (DFA) could be used in the neonatal EEG to distinguish different grades of abnormality in the background EEG activity. Long-term EEG records of 34 neonates were collected after perinatal asphyxia, and their background was scored in 1 h epochs (8 h in each neonate) as mild, moderate or severe. We applied DFA on 15 min long, non-overlapping EEG epochs (n = 1088) filtered from 3 to 8 Hz. Our formal feasibility study suggested that DFA exponent can be reliably assessed in only part of the EEG epochs, and in only relatively short time scales (10-60 s), while it becomes ambiguous if longer time scales are considered. This prompted further exploration whether paradigm used for quantifying multifractal DFA (MF-DFA) could be applied in a more efficient way, and whether metrics from MF-DFA paradigm could yield useful benchmark with existing clinical EEG gradings. Comparison of MF-DFA metrics showed a significant difference between three visually assessed background EEG grades. MF-DFA parameters were also significantly correlated to interburst intervals quantified with our previously developed automated detector. Finally, we piloted a monitoring application of MF-DFA metrics and showed their evolution during patient recovery from asphyxia. Our exploratory study showed that neonatal EEG can be quantified using multifractal metrics, which might offer a suitable parameter to quantify the grade of EEG background, or to monitor changes in brain state that take place during long-term brain monitoring.

Metabolomic profiling in perinatal asphyxia: a promising new field

Metabolomics, the latest “omic” technology, is defined as the comprehensive study of all low molecular weight biochemicals, “metabolites” present in an organism. As a systems biology approach, metabolomics has huge potential to progress our understanding of perinatal asphyxia and neonatal hypoxic-ischaemic encephalopathy, by uniquely detecting rapid biochemical pathway alterations in response to the hypoxic environment. The study of metabolomic biomarkers in the immediate neonatal period is not a trivial task and requires a number of specific considerations, unique to this disease and population. Recruiting a clearly defined cohort requires standardised multicentre recruitment with broad inclusion criteria and the participation of a range of multidisciplinary staff. Minimally invasive biospecimen collection is a priority for biomarker discovery. Umbilical cord blood presents an ideal medium as large volumes can be easily extracted and stored and the sample is not confounded by postnatal disease progression. Pristine biobanking and phenotyping are essential to ensure the validity of metabolomic findings. This paper provides an overview of the current state of the art in the field of metabolomics in perinatal asphyxia and neonatal hypoxic-ischaemic encephalopathy. We detail the considerations required to ensure high quality sampling and analysis, to support scientific progression in this important field.

Electroencephalogram and magnetic resonance imaging comparison as a predicting factor for neurodevelopmental outcome in hypoxic ischemic encephalopathy infant treated with hypothermia

Hypoxic-ischemic encephalopathy (HIE) is an important cause of acute neurological damage in newborns at (or near) term. Several trials in recent years have shown that moderate hypothermia by total body cooling or selective head is an effective intervention to reduce mortality and major disability in infants survived a perinatal hypoxic-ischemic attack. Follow-up in these patients is very important to establish neurodevelopmental outcome, and specific markers can lead us to detect predicting sign for good or poor outcome. We reported a few cases of newborn with HIE treated with hypothermia, in whom the comparison between electroencephalogram (EEG) and magnetic resonance imaging (MRI) represents the first marker for neurodevelopment outcome prediction. The continuous EEG monitoring showed a depressed EEG activity with diffuse burst depression in 7 patients. No epileptic abnormalities were registered. In 10 out of 20 patients no abnormalities of the background activity and no epileptic abnormalities were observed. We found that a depressed EEG activity during the first 72 h of life and a diffused alteration of basal ganglia at MRI were correlated with a poor neurodevelopmental outcome at 18 months of follow-up.

Novel features of early burst suppression predict outcome after birth asphyxia

Burst suppression patterns in the electroencephalogram are a reliable marker of recent severe brain insult. Here we analyze statistical properties of bursts occurring in 20 electroencephalographic recordings acquired from hypothermic asphyxic newborns in the hours immediately following birth. We show that the distributions of burst area and duration in these acute data predict later clinical outcome in both structural neuroimaging and neurodevelopment. Our findings indicate the first early electroencephalographic metrics that offer outcome prediction in asphyxic neonates undergoing hypothermia treatment.

Automated EEG inter-burst interval detection in neonates with mild to moderate postasphyxial encephalopathy

EEG inter-burst interval (IBI) and its evolution is a robust parameter for grading hypoxic encephalopathy and prognostication in newborns with perinatal asphyxia. We present a reliable algorithm for the automatic detection of IBIs. This automated approach is based on adaptive segmentation of EEG, classification of segments and use of temporal profiles to describe the global distribution of EEG activity. A pediatric neurologist has blindly scored data from 8 newborns with perinatal postasphyxial encephalopathy varying from mild to severe. 15 minutes of EEG have been scored per patient, thus totaling 2 hours of EEG that was used for validation. The algorithm shows good detection accuracy and provides insight into challenging cases that are difficult to detect.

Feasibility of adjunct therapeutic hypothermia treatment for hyperammonemia and encephalopathy due to urea cycle disorders and organic acidemias

BACKGROUND

Children with urea cycle disorders (UCDs) or organic acidemias (OAs) and acute hyperammonemia and encephalopathy are at great risk for neurological injury, developmental delay, intellectual disability, and death. Nutritional support, intravenous alternative pathway therapy, and dialysis are used to treat severe hyperammonemia associated with UCDs and nutritional support and dialysis are used to treat severe hyperammonemia in OAs. Brain protective treatment while therapy is initiated may improve neurological and cognitive function for the lifetime of the child. Animal experiments and small clinical trials in hepatic encephalopathy caused by acute liver failure suggest that therapeutic hypothermia provides neuroprotection in hyperammonemia associated encephalopathy. We report results of an ongoing pilot study that assesses if whole body cooling during rescue treatment of neonates with acute hyperammonemia and encephalopathy is feasible and can be conducted safely.

METHODS

Adjunct whole body therapeutic hypothermia was conducted in addition to standard treatment in acutely encephalopathic, hyperammonemic neonates with UCDs and OAs requiring dialysis. Therapeutic hypothermia was initiated using cooling blankets as preparations for dialysis were underway. Similar to standard therapeutic hypothermia treatment for neonatal hypoxic ischemic encephalopathy, patients were maintained at 33.5°C±1°C for 72h, they were then slowly rewarmed by 0.5°C every 3h over 18h. In addition data of age-matched historic controls were collected for comparison.

RESULTS

Seven patients were cooled using the pilot study protocol and data of seven historic controls were reviewed. All seven patients survived the initial rescue and cooling treatment, 6 patients were discharged home 2-4weeks after hospitalization, five of them feeding orally. The main complication observed in a majority of patients was hypotension.

CONCLUSION

Adjunct therapeutic hypothermia for neonates with UCDs and OAs receiving standard treatment was feasible and could be conducted safely in pediatric and neonatal intensive care units experienced in the application of therapeutic hypothermia in critically ill neonates. However, including adjunct therapeutic hypothermia in the already involved treatment regimen of critically ill patients with hyperammonemia and encephalopathy adds to the complexity of care and should not be done unless it is proven efficacious in a randomized clinical trial.

Outcome following neonatal seizures

Neonatal seizures are the most common manifestation of neurological disorders in the newborn period and an important determinant of outcome. Overall, for babies born at full term, mortality following seizures has improved in the last decade, typical current mortality rates being 10% (range: 7-16%), down from 33% in reports from the 1990s. By contrast, the prevalence of adverse neurodevelopmental sequelae remains relatively stable, typically 46% (range: 27-55%). The strongest predictors of outcome are the underlying cause, together with the background electroencephalographic activity. In preterm babies, for whom the outlook tends to be worse as background mortality and disability are high, seizures are frequently associated with serious underlying brain injury and therefore subsequent impairments. When attempting to define the prognosis for a baby with neonatal seizures, we propose a pathway involving history, examination, and careful consideration of all available results (ideally including brain magnetic resonance imaging) and the response to treatment before synthesizing the best estimate of risk to be conveyed to the family.

EEG findings in cooled asphyxiated newborns and correlation with site and severity of brain damage

OBJECTIVE

EEG and MRI are useful tools to evaluate the severity of brain damage and to provide prognostic indications in asphyxiated neonates. Aim of our study is to analyze the relationship between serial neonatal EEGs and severity and sites of brain lesions on MRI in neonates undergoing hypothermia, following a hypoxic-ischemic injury.

PATIENTS AND METHODS

Forty-eight term newborns underwent hypothermia. Serial videoEEG recordings were taken at 6, 24, 48 and 72 h and during 2nd week of life. Brain MRI was performed at the end of 2nd postnatal week and correlated with EEG.

RESULTS

EEGs improved during the first days. At the first recording 25 infants showed a severe or very low amplitude EEG pattern while at the 2nd week only 7 showed such patterns. As regards MRI, 21 infants showed a predominant Basal Ganglia and Thalami damage, 4 infants showed a predominant focal Thalami lesion and 23 showed normal imaging or just mild White Matter abnormalities. Severity of EEG pattern was associated with the odds of having MRI lesions at Basal Ganglia, Thalami, White Matter, Internal Capsule, but not at Cortex. Infants who showed only mild EEG abnormalities in the first 2 days had no Basal Ganglia and Thalami MRI lesion. The persistence of a discontinuous EEG at the 2nd week recording is always associated with Basal Ganglia and Thalami damage.

CONCLUSION

The severity of EEG background is associated with severity and site of MRI lesion pattern in neonates treated with hypothermia because of hypoxic-ischemic encephalopathy.

Early neurophysiology and MRI in predicting neurological outcome at 9-10 years after birth asphyxia

OBJECTIVE

To assess whether early somatosensory evoked potentials (SEP) predict long-term neurodevelopmental outcome in normothermic, full-term infants with mild to moderate neonatal encephalopathy (NE), and to compare their predictive value to already available amplitude integrated EEG (aEEG) and magnetic resonance imaging (MRI).

METHODS

Fifty-six infants with post-asphyxia NE were prospectively recruited, and their SEP, aEEG and MRI data were acquired during the first five days. Follow-up continued to 9-10 years for assessment of neuromotor and neurocognitive development. We analysed SEP latency (N1 component), normality of aEEG background pattern, as well as patterns of injury on the neonatal MRI. Neurological outcome measures at 9-10 years included conventional MRI, Movement-ABC and the WISC-III NL.

RESULTS

A SEP latency <50 ms during the first five days was associated with a normal neuromotor outcome (p < 0.03), and a prolonged day 3 latency was associated with lower childhood IQ (p = 0.02). The presence of multiple seizures in aEEG, as well as a moderate or severe injury on the neonatal MRI was associated with a poor neuromotor score (p = 0.03 and p < 0.01, respectively). Combination of multiple techniques improved prediction of long-term outcome compared to single modality.

CONCLUSION

Early SEPs provide information that is comparable to the already available aEEG and MRI paradigms in the prediction of long-term outcome of full-term infants with mild to moderate neonatal encephalopathy.

SIGNIFICANCE

The present results call for further studies using early SEP to aid early assessment of infants treated with hypothermia.

An automated system for grading EEG abnormality in term neonates with hypoxic-ischaemic encephalopathy

Automated analysis of the neonatal EEG has the potential to assist clinical decision making for neonates with hypoxic-ischaemic encephalopathy. This paper proposes a method of automatically grading the degree of abnormality in an hour long epoch of neonatal EEG. The automated grading system (AGS) was based on a multi-class linear classifier grading of short-term epochs of EEG which were converted into a long-term grading of EEG using a majority vote operation. The features used in the AGS were summary measurements of two sub-signals extracted from a quadratic time-frequency distribution: the amplitude modulation and instantaneous frequency. These sub-signals were based on a model of EEG as a multiplication of a coloured random process with a slowly varying pseudo-periodic waveform and may be related to macroscopic neurophysiological function. The 4 grade AGS had a classification accuracy of 83% compared to human annotation of the EEG (level of agreement, κ = 0.76). Features estimated on the developed sub-signals proved more effective at grading the EEG than measures based solely on the EEG and the incorporation of additional sub-grades based on EEG states into the AGS also improved performance.