Prediction of Neonatal Seizures in Hypoxic-Ischemic Encephalopathy Using Electroencephalograph Power Analyses

A Comparison of Automatically Extracted Quantitative EEG Features for Seizure Risk Stratification in Neonatal Encephalopathy

PURPOSE

Seizures occur in up to 40% of neonates with neonatal encephalopathy. Earlier identification of seizures leads to more successful seizure treatment, but is often delayed because of limited availability of continuous EEG monitoring. Clinical variables poorly stratify seizure risk, and EEG use to stratify seizure risk has previously been limited by need for manual review and artifact exclusion. The goal of this study is to compare the utility of automatically extracted quantitative EEG (qEEG) features for seizure risk stratification.

METHODS

We conducted a retrospective analysis of neonates with moderate-to-severe neonatal encephalopathy who underwent therapeutic hypothermia at a single center. The first 24 hours of EEG underwent automated artifact removal and qEEG analysis, comparing qEEG features for seizure risk stratification.

RESULTS

The study included 150 neonates and compared the 36 (23%) with seizures with those without. Absolute spectral power best stratified seizure risk with area under the curve ranging from 63% to 71%, followed by range EEG lower and upper margin, median and SD of the range EEG lower margin. No features were significantly more predictive in the hour before seizure onset. Clinical examination was not associated with seizure risk.

CONCLUSIONS

Automatically extracted qEEG features were more predictive than clinical examination in stratifying neonatal seizure risk during therapeutic hypothermia. qEEG represents a potential practical bedside tool to individualize intensity and duration of EEG monitoring and decrease time to seizure recognition. Future work is needed to refine and combine qEEG features to improve risk stratification.

Prediction of outcome of hypoxic-ischemic encephalopathy in newborns undergoing therapeutic hypothermia using heart rate variability

OBJECTIVE

To assess the use of continuous heart rate variability (HRV) as a predictor of brain injury severity in newborns with moderate to severe HIE that undergo therapeutic hypothermia.

STUDY DESIGN

Two cohorts of newborns (n1 = 55, n2 = 41) with moderate to severe hypoxic-ischemic encephalopathy previously treated with therapeutic hypothermia. HRV was characterized by root mean square in the short time scales (RMSS) during therapeutic hypothermia and through completion of rewarming. A logistic regression and Naïve Bayes models were developed to predict the MRI outcome of the infants using RMSS. The encephalopathy grade and gender were used as control variables.

RESULTS

For both cohorts, the predicted outcomes were compared with the observed outcomes. Our algorithms were able to predict the outcomes with an area under the receiver operating characteristic curve of about 0.8.

CONCLUSIONS

HRV assessed by RMSS can predict severity of brain injury in newborns with HIE.

Quantitative EEG and prediction of outcome in neonatal encephalopathy: a review

Electroencephalogram (EEG) is an important biomarker for neonatal encephalopathy (NE) and has significant predictive value for brain injury and neurodevelopmental outcomes. Quantitative analysis of EEG involves the representation of complex EEG data in an objective, reproducible and scalable manner. Quantitative EEG (qEEG) can be derived from both a limited channel EEG (as available during amplitude integrated EEG) and multi-channel conventional EEG. It has the potential to enable bedside clinicians to monitor and evaluate details of cortical function without the necessity of continuous expert input. This is particularly useful in NE, a dynamic and evolving condition. In these infants, continuous, detailed evaluation of cortical function at the bedside is a valuable aide to management especially in the current era of therapeutic hypothermia and possible upcoming neuroprotective therapies. This review discusses the role of qEEG in newborns with NE and its use in informing monitoring and therapy, along with its ability to predict imaging changes and short and long-term neurodevelopmental outcomes. IMPACT: Quantitative representation of EEG data brings the evaluation of continuous brain function, from the neurophysiology lab to the NICU bedside and has a potential role as a biomarker for neonatal encephalopathy. Clinical and research applications of quantitative EEG in the newborn are rapidly evolving and a wider understanding of its utility is valuable. This overview summarizes the role of quantitative EEG at different timepoints, its relevance to management and its predictive value for short- and long-term outcomes in neonatal encephalopathy.

Evaluating Injury Severity in Neonatal Encephalopathy Using Automated Quantitative Electroencephalography Analysis: A Pilot Study

Quantitative analysis of electroencephalography (qEEG) is a potential source of biomarkers for neonatal encephalopathy (NE). However, prior studies using qEEG in NE were limited in their generalizability due to individualized techniques for calculating qEEG features or labor-intensive pre-selection of EEG data. We piloted a fully automated method using commercially available software to calculate the suppression ratio (SR), absolute delta power, and relative delta, theta, alpha, and beta power from EEG of neonates undergoing 72 h of therapeutic hypothermia (TH) for NE between April 20, 2018, and November 4, 2019. We investigated the association of qEEG with degree of encephalopathy (modified Sarnat score), severity of neuroimaging abnormalities following TH (National Institutes of Child Health and Development Neonatal Research Network [NICHD-NRN] score), and presence of seizures. Thirty out of 38 patients met inclusion criteria. A more severe modified Sarnat score was associated with higher SR during all phases of TH, lower absolute delta power during all phases except rewarming, and lower relative delta power during the last 24 h of TH. In 21 patients with neuroimaging data, a worse NICHD-NRN score was associated with higher SR, lower absolute delta power, and higher relative beta power during all phases. QEEG features were not significantly associated with the presence of seizures after correction for multiple comparisons. Our results are consistent with those of prior studies using qEEG in NE and support automated qEEG analysis as an accessible, generalizable method for generating biomarkers of NE and response to TH. Additionally, we found evidence of an immature relative frequency composition in neonates with more severe brain injury, suggesting that automated qEEG analysis may have a use in the assessment of brain maturity.

Leveraging electronic medical record-embedded standardised electroencephalogram reporting to develop neonatal seizure prediction models: a retrospective cohort study

BACKGROUND

Accurate prediction of seizures can help to direct resource-intense continuous electroencephalogram (CEEG) monitoring to neonates at high risk of seizures. We aimed to use data from standardised EEG reports to generate seizure prediction models for vulnerable neonates.

METHODS

In this retrospective cohort study, we included neonates who underwent CEEG during the first 30 days of life at the Children's Hospital of Philadelphia (Philadelphia, PA, USA). The hypoxic ischaemic encephalopathy subgroup included only patients with CEEG data during the first 5 days of life, International Classification of Diseases, revision 10, codes for hypoxic ischaemic encephalopathy, and documented therapeutic hypothermia. In January, 2018, we implemented a novel CEEG reporting system within the electronic medical record (EMR) using common data elements that incorporated standardised terminology. All neonatal CEEG data from Jan 10, 2018, to Feb 15, 2022, were extracted from the EMR using age at the time of CEEG. We developed logistic regression, decision tree, and random forest models of neonatal seizure prediction using EEG features on day 1 to predict seizures on future days.

FINDINGS

We evaluated 1117 neonates, including 150 neonates with hypoxic ischaemic encephalopathy, with CEEG data reported using standardised templates between Jan 10, 2018, and Feb 15, 2022. Implementation of a consistent EEG reporting system that documents discrete and standardised EEG variables resulted in more than 95% reporting of key EEG features. Several EEG features were highly correlated, and patients could be clustered on the basis of specific features. However, no simple combination of features adequately predicted seizure risk. We therefore applied computational models to complement clinical identification of neonates at high risk of seizures. Random forest models incorporating background features performed with classification accuracies of up to 90% (95% CI 83-94) for all neonates and 97% (88-99) for neonates with hypoxic ischaemic encephalopathy; recall (sensitivity) of up to 97% (91-100) for all neonates and 100% (100-100) for neonates with hypoxic ischaemic encephalopathy; and precision (positive predictive value) of up to 92% (84-96) in the overall cohort and 97% (80-99) in neonates with hypoxic ischaemic encephalopathy.

INTERPRETATION

Using data extracted from the standardised EEG report on the first day of CEEG, we predict the presence or absence of neonatal seizures on subsequent days with classification performances of more than 90%. This information, incorporated into routine care, could guide decisions about the necessity of continuing EEG monitoring beyond the first day, thereby improving the allocation of limited CEEG resources. Additionally, this analysis shows the benefits of standardised clinical data collection, which can drive learning health system approaches to personalised CEEG use.

FUNDING

Children's Hospital of Philadelphia, the Hartwell Foundation, the National Institute of Neurological Disorders and Stroke, and the Wolfson Foundation.

Machine learning for the early prediction of infants with electrographic seizures in neonatal hypoxic-ischemic encephalopathy

OBJECTIVE

To assess if early clinical and electroencephalography (EEG) features predict later seizure development in infants with hypoxic-ischemic encephalopathy (HIE).

METHODS

Clinical and EEG parameters <12 h of birth from infants with HIE across eight European Neonatal Units were used to develop seizure-prediction models. Clinical parameters included intrapartum complications, fetal distress, gestational age, delivery mode, gender, birth weight, Apgar scores, assisted ventilation, cord pH, and blood gases. The earliest EEG hour provided a qualitative analysis (discontinuity, amplitude, asymmetry/asynchrony, sleep-wake cycle [SWC]) and a quantitative analysis (power, discontinuity, spectral distribution, inter-hemispheric connectivity) from full montage and two-channel amplitude-integrated EEG (aEEG). Subgroup analysis, only including infants without anti-seizure medication (ASM) prior to EEG was also performed. Machine-learning (ML) models (random forest and gradient boosting algorithms) were developed to predict infants who would later develop seizures and assessed using Matthews correlation coefficient (MCC) and area under the receiver-operating characteristic curve (AUC).

RESULTS

The study included 162 infants with HIE (53 had seizures). Low Apgar, need for ventilation, high lactate, low base excess, absent SWC, low EEG power, and increased EEG discontinuity were associated with seizures. The following predictive models were developed: clinical (MCC 0.368, AUC 0.681), qualitative EEG (MCC 0.467, AUC 0.729), quantitative EEG (MCC 0.473, AUC 0.730), clinical and qualitative EEG (MCC 0.470, AUC 0.721), and clinical and quantitative EEG (MCC 0.513, AUC 0.746). The clinical and qualitative-EEG model significantly outperformed the clinical model alone (MCC 0.470 vs 0.368, p-value .037). The clinical and quantitative-EEG model significantly outperformed the clinical model (MCC 0.513 vs 0.368, p-value .012). The clinical and quantitative-EEG model for infants without ASM (n = 131) had MCC 0.588, AUC 0.832. Performance for quantitative aEEG (n = 159) was MCC 0.381, AUC 0.696 and clinical and quantitative aEEG was MCC 0.384, AUC 0.720.

SIGNIFICANCE

Early EEG background analysis combined with readily available clinical data helped predict infants who were at highest risk of seizures, hours before they occur. Automated quantitative-EEG analysis was as good as expert analysis for predicting seizures, supporting the use of automated assessment tools for early evaluation of HIE.

Developmental characteristics of early electroencephalography in preterm neonates: Differences between twins and singletons

BACKGROUND

To analyze the early electroencephalography (EEG) development of twins and singleton preterm neonates using 5 measurement indicators.

METHODS

On the 1st and 7th days after birth, EEG monitoring was performed on 102 preterm neonates (62 males, median gestational age 33.15 weeks, IQR 31.00-35.75). The minimum amplitude, maximum amplitude, maximum interburst intervals (IBI), total duration of trace discontinue (TD), maximum duration of single TD, and the Burdjalov score of amplitude-integrated electroencephalography (aEEG) were used to evaluate EEG recordings.

RESULTS

The minimum amplitude of EEG increases with gestational age (GA), while the maximum amplitude decreases, the maximum IBI decreases, and the total duration of TD and the maximum duration of single TD decrease (all p < 0.05). Burdjalov score did not differ significantly between the 1st and 7th days (p = 0.075). There is no significant difference between twins and singleton preterm infants in the five EEG measurement indicators (p > 0.05 for all).

CONCLUSION

The five EEG measurement indicators can better reflect preterm infants' brain maturation than the Burdjalov score in aEEG. There were no statistical differences in brain maturation between twin and singleton preterm infants.

Risk Factors for Clinical Seizures in Neonates with Hypoxic-ischemic Encephalopathy Treated with Therapeutic Hypothermia

BACKGROUND

This study aimed to assess the risk factors for clinical seizures in newborns treated with whole body cooling (WBC) for hypoxic ischemic encephalopathy (HIE).

METHODS

Infants with gestational age≥36 weeks and birth weight≥2.000 g who were treated with WBC due to HIE were retrospectively enrolled in this study. Patients were assigned to two groups: infants without clinical seizures (Group 1) and infants with clinical seizures (Group 2). The two groups were compared to determine the risk factors for the occurrence of clinical seizures.

RESULTS

A total of 25 patients (Group 1=10 and Group 2=15) were included in the study. Prothrombin time (PT) was determined as independent risk factor for clinical seizures (p=0.046) and the odds ratio for the effect of PT was found as 1.475 (%95 CI:1.006-2.299). PT (area under the curve [AUC]=0.764; p=0.041), and increased cardiac troponin-I (cTnI) (AUC=0.935; p=0.002) were found to be significant risk factors for predicting the occurrence of clinical seizures. The optimal PT cut-off value was 22.7 sec, with a sensitivity and specificity of 45.4% and 90%, respectively; as well as positive and negative predictive value of 83.3% and 60.0%, respectively. The chest compression in the delivery room, severely abnormal amplitude integrated electroencephalography and high encephalopathy score were also found risk factors for occurrence of clinical seizures.

CONCLUSION

Chest compression in the delivery room, high encephalopathy score, prolonged PT, and increased cTnI are significant factors for clinical seizures in newborns treated with WBC for HIE.

Identification of clinically relevant biomarkers of epileptogenesis - a strategic roadmap

Onset of many forms of epilepsy occurs after an initial epileptogenic insult or as a result of an identified genetic defect. Given that the precipitating insult is known, these epilepsies are, in principle, amenable to secondary prevention. However, development of preventive treatments is difficult because only a subset of individuals will develop epilepsy and we cannot currently predict which individuals are at the highest risk. Biomarkers that enable identification of these individuals would facilitate clinical trials of potential anti-epileptogenic treatments, but no such prognostic biomarkers currently exist. Several putative molecular, imaging, electroencephalographic and behavioural biomarkers of epileptogenesis have been identified, but clinical translation has been hampered by fragmented and poorly coordinated efforts, issues with inter-model reproducibility, study design and statistical approaches, and difficulties with validation in patients. These challenges demand a strategic roadmap to facilitate the identification, characterization and clinical validation of biomarkers for epileptogenesis. In this Review, we summarize the state of the art with respect to biomarker research in epileptogenesis and propose a five-phase roadmap, adapted from those developed for cancer and Alzheimer disease, that provides a conceptual structure for biomarker research.

Velamentous cord insertion, ischemic-hypoxic encephalopathy, and neurological rehabilitation: A case report

Hypoxic-ischemic encephalopathy is a frequent and important cause of neurological problems in term and preterm newborns. A sentinel event of this entity is the vasa previa, specifically when there is an abnormality of the placenta such as a velamentous cord insertion. Some reports have shown the association between these two entities, but those regarding the recovery process and the neurological prognosis of children with both conditions are scarce. We present the case of a patient with a history of velamentous cord insertion and hypoxicischemic encephalopathy who received therapeutic hypothermia (cool cap). We describe his neurological rehabilitation process and we calculated the percentage of probability of presenting this condition compared to the population without these factors. The patient was a five-year-old boy with an Apgar index at birth equal to zero at one minute and equal to two at fifteen minutes who developed severe hypoxic-ischemic encephalopathy secondary to a velamentous cord insertion without prenatal diagnosis and a marked initial neurological and multisystemic compromise. The recovery process included early multidisciplinary management in the neonatal intensive care unit and a focus on early neurological habilitation. The patient is currently in school and he undergoes comprehensive therapies; on physical examination, he presents no motor or sensory deficiencies. His neuropsychological test suggests the risk of attention deficit hyperactivity disorder. Children with severe hypoxicischemic encephalopathy usually have disabilities due to motor, cognitive, and/or behavioral deficiencies.

[Effect of blood glucose on quantitative electroencephalography parameters in preterm infants]

OBJECTIVE

To study the value of quantitative electroencephalography (qEEG) in evaluating the effect of blood glucose on the brain function of preterm infants.

METHODS

The preterm infants who were admitted to the Department of Neonatology, The Third Xiangya Hospital of Central South University, from January to December 2019 were enrolled. According to the level of blood glucose, they were divided into group 1 (blood glucose <4.95 mmol/L), group 2 (blood glucose 4.95 to <6.60 mmol/L), group 3 (blood glucose 6.60 to <8.55 mmol/L), and group 4 (blood glucose ≥8.55 mmol/L). The changes in qEEG parameters were compared between groups, and a correlation analysis was performed for blood glucose and qEEG parameters.

RESULTS

A total of 39 preterm infants were enrolled (84 blood glucose measurements). Compared with group 4, the other three groups had significant increases in the total spectral power of each brain region and the absolute power of each frequency band in the frontal and occipital regions (P<0.05). The total spectral power, δ/θ ratio, and (δ+θ)/(α+β) ratio of each brain region were negatively correlated with blood glucose level, while the relative power of θ frequency band was positively correlated with blood glucose level (P<0.05).

CONCLUSIONS

With the change in blood glucose, there are significant changes in the total spectral power of each brain region, the power of each frequency band, and the frequency spectrum composition on qEEG in preterm infants. qEEG may therefore become an important tool to monitor the effect of abnormal blood glucose on brain function in preterm infants.

Continuous Electroencephalography Monitoring in Critically Ill Infants and Children

Continuous video electroencephalography (CEEG) monitoring of critically ill infants and children has expanded rapidly in recent years. Indications for CEEG include evaluation of patients with altered mental status, characterization of paroxysmal events, and detection of electrographic seizures, including monitoring of patients with limited neurological examination or conditions that put them at high risk for electrographic seizures (e.g., cardiac arrest or extracorporeal membrane oxygenation cannulation). Depending on the inclusion criteria and clinical characteristics of the population studied, the percentage of pediatric patients with electrographic seizures varies from 7% to 46% and with electrographic status epilepticus from 1% to 23%. There is also evidence that epileptiform and background CEEG patterns may provide important information about prognosis in certain clinical populations. Quantitative EEG techniques are emerging as a tool to enhance the value of CEEG to provide real-time bedside data for management and prognosis. Continued research is needed to understand the clinical value of seizure detection and identification of other CEEG patterns on the outcomes of critically ill infants and children.

Prognostic Value of Continuous Electroencephalogram Delta Power in Neonates With Hypoxic-Ischemic Encephalopathy

The objective was to examine the discriminatory ability of electroencephalogram (EEG) delta power in neonates with hypoxic-ischemic encephalopathy (HIE) with well-defined outcomes. Prolonged continuous EEG recordings from term neonates with HIE during therapeutic hypothermia enrolled in a prospective observational study were examined. Adverse outcome was defined as death or severe brain injury by magnetic resonance imaging (MRI); favorable outcome was defined as normal or mild injury by MRI. Neonates were stratified by Sarnat grade of encephalopathy at admission. EEG was partitioned into 10-minute nonoverlapping artifact- and seizure-free epochs. Delta power was calculated and compared between the groups using receiver operating characteristic (ROC) analyses and Wilcoxon rank-sum tests. An area under the ROC curve >0.7 with P <.05 was considered a significant separation between groups. The favorable outcome group (n = 67) had higher delta power than the adverse outcome group (n = 28) across the majority of time periods from 9 to 90 hours of life. Delta power discriminated outcome groups for neonates with moderate encephalopathy (63 favorable and 14 adverse outcome) earlier in cooling (9-42 hours of life) than neonates with severe encephalopathy (21-42 hours of life). Outcome groups were differentiated after 81 hours of life in neonates with moderate and severe encephalopathy. Delta power can distinguish cooled HIE neonates with adverse outcome independently of the encephalopathy grade at presentation. Delta power may be a real-time continuous biomarker of evolving encephalopathy and brain injury/death in neonates with HIE.

Early Electroencephalogram Background Could Guide Tailored Duration of Monitoring for Neonatal Encephalopathy Treated with Therapeutic Hypothermia

OBJECTIVE

To evaluate whether features of the early electroencephalographic (EEG) background could guide the optimal duration of continuous video EEG monitoring for seizure detection in newborn infants treated with therapeutic hypothermia for hypoxic ischemic encephalopathy (HIE).

STUDY DESIGN

Retrospective cohort study of 114 consecutive infants treated with therapeutic hypothermia for moderate to severe HIE at a level IV neonatal intensive care unit (NICU) between 2012 and 2018. All infants were monitored with continuous video EEG through cooling and rewarming. Archived samples from the first 24 hours of these EEG traces were reviewed systematically and classified by background characteristics.

RESULTS

Electrographic seizures occurred in 56 of the 114 infants (49%). Seizure onset was within the first 24 hours after initiation of continuous video EEG in 49 if these 56 infants (88%), between 24 and 48 hours in 4 infants (7%), and >72 hours in 3 infants (5%). Infants with a normal or mildly abnormal EEG background either had seizure onset within the first 24 hours or never developed seizures. Four patients with seizure onset between 24 and 48 hours had markedly abnormal EEG backgrounds. The 3 patients with seizure onset beyond 72 hours had moderate or severely abnormal early continuous video EEG backgrounds.

CONCLUSIONS

The use of early continuous video EEG background categorization may be appropriate to guide the duration of continuous video EEG for infants with HIE treated with therapeutic hypothermia. Some infants may reasonably be monitored for 24 hours rather than throughout cooling and rewarming without a significant risk of missed seizures. This could have significant implications for continuous video EEG resource utilization.

Targeting Sentinel Proteins and Extrasynaptic Glutamate Receptors: a Therapeutic Strategy for Preventing the Effects Elicited by Perinatal Asphyxia?

Perinatal asphyxia (PA) is a relevant cause of death at the time of labour, and when survival is stabilised, associated with short- and long-term developmental disabilities, requiring inordinate care by health systems and families. Its prevalence is high (1 to 10/1000 live births) worldwide. At present, there are few therapeutic options, apart from hypothermia, that regrettably provides only limited protection if applied shortly after the insult.PA implies a primary and a secondary insult. The primary insult relates to the lack of oxygen, and the secondary one to the oxidative stress triggered by re-oxygenation, formation of reactive oxygen (ROS) and reactive nitrogen (RNS) species, and overactivation of glutamate receptors and mitochondrial deficiencies. PA induces overactivation of a number of sentinel proteins, including hypoxia-induced factor-1α (HIF-1α) and the genome-protecting poly(ADP-ribose) polymerase-1 (PARP-1). Upon activation, PARP-1 consumes high amounts of ATP at a time when this metabolite is scarce, worsening in turn the energy crisis elicited by asphyxia. The energy crisis also impairs ATP-dependent transport, including glutamate re-uptake by astroglia. Nicotinamide, a PARP-1 inhibitor, protects against the metabolic cascade elicited by the primary stage, avoiding NAD+ exhaustion and the energetic crisis. Upon re-oxygenation, however, oxidative stress leads to nuclear translocation of the NF-κB subunit p65, overexpression of the pro-inflammatory cytokines IL-1β and TNF-α, and glutamate-excitotoxicity, due to impairment of glial-glutamate transport, extracellular glutamate overflow, and overactivation of NMDA receptors, mainly of the extrasynaptic type. This leads to calcium influx, mitochondrial impairment, and inactivation of antioxidant enzymes, increasing further the activity of pro-oxidant enzymes, thereby making the surviving neonate vulnerable to recurrent metabolic insults whenever oxidative stress is involved. Here, we discuss evidence showing that (i) inhibition of PARP-1 overactivation by nicotinamide and (ii) inhibition of extrasynaptic NMDA receptor overactivation by memantine can prevent the short- and long-term consequences of PA. These hypotheses have been evaluated in a rat preclinical model of PA, aiming to identify the metabolic cascades responsible for the long-term consequences induced by the insult, also assessing postnatal vulnerability to recurrent oxidative insults. Thus, we present and discuss evidence demonstrating that PA induces long-term changes in metabolic pathways related to energy and oxidative stress, priming vulnerability of cells with both the neuronal and the glial phenotype. The effects induced by PA are region dependent, the substantia nigra being particularly prone to cell death. The issue of short- and long-term consequences of PA provides a framework for addressing a fundamental issue referred to plasticity of the CNS, since the perinatal insult triggers a domino-like sequence of events making the developing individual vulnerable to recurrent adverse conditions, decreasing his/her coping repertoire because of a relevant insult occurring at birth.

Early EEG power predicts MRI injury in infants with hypoxic-ischemic encephalopathy

OBJECTIVE

Early identification of infants with hypoxic-ischemic encephalopathy who have adverse outcomes despite neuroprotection with therapeutic hypothermia (TH) is urgently needed. Recent studies have found limited value of amplitude integrated EEG (aEEG) for predicting short-term outcomes in this population. Other quantitative electroencephalography (EEG) variables reflecting EEG amplitude, such as EEG power, could provide early stratification of a high-risk cohort in this population. The aim of the study was to evaluate and compare early EEG power and aEEG as predictors of magnetic resonance imaging (MRI) injury in neonatal hypoxic-ischemic encephalopathy.

STUDY DESIGN

We conducted a retrospective cohort analysis of 78 encephalopathic infants treated with TH between January 2009 and April 2013. About 56 infants had no/mild injury on MRI (group A), whereas 22 had moderate/severe MRI injury (group B). Total EEG power (TEP) and aEEG were obtained soon after initiation of hypothermia and then compared for their ability to predict future MRI injury.

RESULTS

TEP, calculated at a mean age of 8.9 h, was significantly higher in infants in group A as compared to group B (71.6±64.8 vs 26.9±65.3, P=0.02). Odds ratios for predicting moderate-severe MRI injury for TEP<10 μV², TEP<20 μV², burst Suppression or worse aEEG pattern were 55 (confidence interval (CI) 6.4 to 471), 12.5 (CI 3.8 to 40.7) and 6.7 (CI 2.0 to 19.8), respectively.

CONCLUSION

Early TEP is a reliable predictor of moderate-severe MRI injury in encephalopathic infants undergoing TH and may enable early stratification of infants who may benefit from adjuvant therapeutic interventions.