Regional variability in therapeutic hypothermia eligibility criteria for neonatal hypoxic-ischemic encephalopathy

Early induced therapeutic hypothermia represents the cornerstone treatment in neonates with probable hypoxic-ischemic encephalopathy. The selection of patients for treatment usually involves meeting criteria indicating evidence of perinatal hypoxia-ischemia and the presence of moderate or severe encephalopathy. In this review, we highlight the variability that exists between some of the different regional and national eligibility guidelines. Determining the potential presence of perinatal hypoxia-ischemia may require either one, two or three signs amongst history of acute perinatal event, prolonged resuscitation at delivery, abnormal blood gases and low Apgar score, with a range of cutoff values. Clinical neurological exams often define the severity of encephalopathy differently, with varying number of domains required for determining eligibility and blurred interpretation of findings assigned to different severity grades in different systems. The role of early electrophysiological assessment is weighted differently. A clinical implication is that infants may receive different care depending on the location in which they are born. This could also impact epidemiological data, as inference of rates of moderate-severe encephalopathy based on therapeutic hypothermia rates are misleading and influenced by different eligibility methods used. We would advocate that a universally endorsed single severity staging of encephalopathy is vital for standardizing management and neonatal outcome. IMPACT: Variability exists between regional and national therapeutic hypothermia eligibility guidelines for neonates with probable hypoxic-ischemic encephalopathy. Differences are common in both criteria indicating perinatal hypoxia-ischemia and criteria defining moderate or severe encephalopathy. The role of early electrophysiological assessment is also weighted unequally. This reflects in different individual care and impacts research data. A universally endorsed single severity staging of encephalopathy would be crucial for standardizing management.

Temporal evolution of electrographic seizures in newborn infants with hypoxic-ischaemic encephalopathy requiring therapeutic hypothermia: a secondary analysis of the ANSeR studies

BACKGROUND

Despite extensive research on neonatal hypoxic-ischaemic encephalopathy, detailed information about electrographic seizures during active cooling and rewarming of therapeutic hypothermia is sparse. We aimed to describe temporal evolution of seizures and determine whether there is a correlation of seizure evolution with 2-year outcome.

METHODS

This secondary analysis included newborn infants recruited from eight European tertiary neonatal intensive care units for two multicentre studies (a randomised controlled trial [NCT02431780] and an observational study [NCT02160171]). Infants were born at 36+0 weeks of gestation with moderate or severe hypoxic-ischaemic encephalopathy and underwent therapeutic hypothermia with prolonged conventional video-electroencephalography (EEG) monitoring for 10 h or longer from the start of rewarming. Seizure burden characteristics were calculated based on electrographic seizures annotations: hourly seizure burden (minutes of seizures within an hour) and total seizure burden (minutes of seizures within the entire recording). We categorised infants into those with electrographic seizures during active cooling only, those with electrographic seizures during cooling and rewarming, and those without seizures. Neurodevelopmental outcomes were determined using the Bayley's Scales of Infant and Toddler Development, Third Edition (BSID-III), the Griffiths Mental Development Scales (GMDS), or neurological assessment. An abnormal outcome was defined as death or neurodisability at 2 years. Neurodisability was defined as a composite score of 85 or less on any subscales for BSID-III, a total score of 87 or less for GMDS, or a diagnosis of cerebral palsy (dyskinetic cerebral palsy, spastic quadriplegia, or mixed motor impairment) or epilepsy.

FINDINGS

Of 263 infants recruited between Jan 1, 2011, and Feb 7, 2017, we included 129 infants: 65 had electrographic seizures (43 during active cooling only and 22 during and after active cooling) and 64 had no seizures. Compared with infants with seizures during active cooling only, those with seizures during and after active cooling had a longer seizure period (median 12 h [IQR 3-28] vs 68 h [35-86], p<0·0001), more seizures (median 12 [IQR 5-36] vs 94 [24-134], p<0·0001), and higher total seizure burden (median 69 min [IQR 22-104] vs 167 min [54-275], p=0·0033). Hourly seizure burden peaked at about 20-24 h in both groups, and infants with seizures during and after active cooling had a secondary peak at 85 h of age. When combined, worse EEG background (major abnormalities and inactive background) at 12 h and 24 h were associated with the seizure group: compared with infants with a better EEG background (normal, mild, or moderate abnormalities), infants with a worse EEG background were more likely to have seizures after cooling at 12 h (13 [54%] of 24 vs four [14%] of 28; odds ratio 7·09 [95% CI 1·88-26·77], p=0·0039) and 24 h (14 [56%] of 25 vs seven [18%] of 38; 5·64 [1·81-17·60], p=0·0029). There was a significant relationship between EEG grade at 12 h (four categories) and seizure group (p=0·020). High total seizure burden was associated with increased odds of an abnormal outcome at 2 years of age (odds ratio 1·007 [95% CI 1·000-1·014], p=0·046), with a medium negative correlation between total seizure burden and BSID-III cognitive score (rS=-0·477, p=0·014, n=26).

INTERPRETATION

Overall, half of infants with hypoxic-ischaemic encephalopathy had electrographic seizures and a third of those infants had seizures beyond active cooling, with worse outcomes. These results raise the importance of prolonged EEG monitoring of newborn infants with hypoxic-ischaemic encephalopathy not only during active cooling but throughout the rewarming phase and even longer when seizures are detected.

FUNDING

Wellcome Trust, Science Foundation Ireland, and the Irish Health Research Board.

Neurodevelopmental outcome of low-risk moderate to late preterm infants at 18 months

Background

Of the 15 million preterm births that occur worldwide each year, approximately 80% occur between 32 and 36 + 6 weeks gestational age (GA) and are defined as moderate to late preterm (MLP) infants. This percentage substantiates a need for a better understanding of the neurodevelopmental outcome of this group.

Aim

To describe neurodevelopmental outcome at 18 months in a cohort of healthy low-risk MLP infants admitted to the neonatal unit at birth and to compare the neurodevelopmental outcome to that of a healthy term-born infant group.

Study design and method

This single-centre observational study compared the neurodevelopmental outcome of healthy MLP infants to a group of healthy term control (TC) infants recruited during the same period using the Griffith's III assessment at 18 months.

Results

Seventy-five MLP infants and 92 TC infants were included. MLP infants scored significantly lower in the subscales: Eye-hand coordination (C), Personal, Social and Emotional Development (D), Gross Motor Development (E) and General Developmental (GD) (p < 0.001 for each) and Foundations of Learning (A), (p = 0.004) in comparison to the TC infant group with Cohen's d effect sizes ranging from 0.460 to 0.665. There was no statistically significant difference in mean scores achieved in subscale B: Language and Communication between groups (p = 0.107).

Conclusion

MLP infants are at risk of suboptimal neurodevelopmental outcomes. Greater surveillance of the neurodevelopmental trajectory of this group of at-risk preterm infants is required.

Electroencephalography Quality and Application Times in a Pediatric Emergency Department Setting: A Feasibility Study

BACKGROUND

Status epilepticus is the most common neurological emergency presenting to pediatric emergency departments. Nonconvulsive status epilepticus can be extremely challenging to diagnose, however, requiring electroencephalographic (EEG) confirmation for definitive diagnosis. We aimed to determine the feasibility of achieving a good-quality pediatric EEG recording within 20 minutes of presentation to the emergency department.

METHODS

Single-center prospective feasibility study in Cork University Hospital, Ireland, between July 2021 and June 2022. Two-channel continuous EEG was recorded from children (1) aged <16 years and (2) with Glasgow Coma Scale <11 or a reduction in baseline Glasgow Coma Scale in the case of a child with a neurodisability.

RESULTS

Twenty patients were included. The median age at presentation was 65.8 months (interquartile range, 23.2 to 119.0); 50% had a background diagnosis of epilepsy. The most common reason for EEG monitoring was status epilepticus (85%) followed by suspected nonconvulsive status (10%) and reduced consciousness of unknown etiology (5%). The mean length of recording was 93.1 minutes (S.D. 47.4). The mean time to application was 41.3 minutes (S.D. 11.7). The mean percent of artifact in all recordings was 19.3% (S.D. 15.9). Thirteen (65%) EEGs had <25% artifact. Artifact was higher in cases in which active airway management was ongoing.

CONCLUSIONS

EEG monitoring can be achieved in a pediatric emergency department setting within one hour of presentation. Overall, artifact percentage was low outside of periods of airway manipulation. Future studies are required to determine its use in early seizure detection and its support role in clinical decision-making in these patients.

Quantitative analysis of high-frequency activity in neonatal EEG

OBJECTIVE

To determine the presence and potential utility of independent high-frequency activity recorded from scalp electrodes in the electroencephalogram (EEG) of newborns.

METHODS

We compare interburst intervals and continuous activity at different frequencies for EEGs retrospectively recorded at 256 Hz from 4 newborn groups: 1) 36 preterms (<32 weeks' gestational age, GA); 2) 12 preterms (32-37 weeks' GA); 3) 91 healthy full terms; 4) 15 full terms with hypoxic-ischemic encephalopathy (HIE). At 4 standard frequency bands (delta, 0.5-3 Hz; theta, 3-8 Hz; alpha, 8-15 Hz; beta, 15-30 Hz) and 3 higher-frequency bands (gamma1, 30-48 Hz; gamma2, 52-99 Hz; gamma3, 107-127 Hz), we compared power spectral densities (PSDs), quantitative features, and machine learning model performance. Feature selection and further machine learning methods were performed on one cohort.

RESULTS

We found significant (P < 0.01) differences in PSDs, quantitative analysis, and machine learning modelling at the higher-frequency bands. Machine learning models using only high-frequency features performed best in preterm groups 1 and 2 with a median (95% confidence interval, CI) Matthews correlation coefficient (MCC) of 0.71 (0.12-0.88) and 0.66 (0.36-0.76) respectively. Interburst interval-detector models using both high- and standard-bandwidths produced the highest median MCCs in all four groups. High-frequency features were largely independent of standard-bandwidth features, with only 11/84 (13.1%) of correlations statistically significant. Feature selection methods produced 7 to 9 high-frequency features in the top 20 feature set.

CONCLUSIONS

This is the first study to identify independent high-frequency activity in newborn EEG using in-depth quantitative analysis. Expanding the EEG bandwidths of analysis has the potential to improve both quantitative and machine-learning analysis, particularly in preterm EEG.

Parent-led massage and sleep EEG for term-born infants: A randomized controlled parallel-group study

AIM

To examine the impact of parent-led massage on the sleep electroencephalogram (EEG) features of typically developing term-born infants at 4 months.

METHOD

Infants recruited at birth were randomized to intervention (routine parent-led massage) and control groups. Infants had a daytime sleep EEG at 4 months and were assessed using the Griffiths Scales of Child Development, Third Edition at 4 and 18 months. Comparative analysis between groups and subgroup analysis between regularly massaged and never-massaged infants were performed. Groups were compared for sleep stage, sleep spindles, quantitative EEG (primary analysis), and Griffiths using the Mann-Whitney U test.

RESULTS

In total, 179 out of 182 infants (intervention: 83 out of 84; control: 96 out of 98) had a normal sleep EEG. Median (interquartile range) sleep duration was 49.8 minutes (39.1-71.4) (n = 156). A complete first sleep cycle was seen in 67 out of 83 (81%) and 72 out of 96 (75%) in the intervention and control groups respectively. Groups did not differ in sleep stage durations, latencies to sleep and to rapid eye movement sleep. Sleep spindle spectral power was greater in the intervention group in main and subgroup analyses. The intervention group showed greater EEG magnitudes, and lower interhemispherical coherence on subgroup analyses. Griffiths assessments at 4 months (n = 179) and 18 months (n = 173) showed no group differences in the main and subgroup analyses.

INTERPRETATION

Routine massage is associated with distinct functional brain changes at 4 months.

WHAT THIS PAPER ADDS

Routine massage of infants is associated with differences in sleep electroencephalogram biomarkers at 4 months. Massaged infants had higher sleep spindle spectral power, greater sleep EEG magnitudes, and lower interhemispherical coherence. No differences between groups were observed in total nap duration or first cycle macrostructure.

Neuro-Specific and Immuno-Inflammatory Biomarkers in Umbilical Cord Blood in Neonatal Hypoxic-Ischemic Encephalopathy

OBJECTIVES

The aim of the study was to evaluate neuronal injury and immuno-inflammatory biomarkers in umbilical cord blood (UCB) at birth, in cases with perinatal asphyxia with or without hypoxic-ischemic encephalopathy (HIE), compared with healthy controls and to assess their ability to predict HIE.

STUDY DESIGN

In this case-control study, term infants with perinatal asphyxia were recruited at birth. UCB was stored at delivery for batch analysis. HIE was diagnosed by clinical Sarnat staging at 24 h. Glial fibrillary acidic protein (GFAP), the neuronal biomarkers tau and neurofilament light protein (NFL), and a panel of cytokines were analyzed in a total of 150 term neonates: 50 with HIE, 50 with asphyxia without HIE (PA), and 50 controls. GFAP, tau, and NFL concentrations were measured using ultrasensitive single-molecule array (Simoa) assays, and a cytokine screening panel was applied to analyze the immuno-inflammatory and infectious markers.

RESULTS

GFAP, tau, NFL, and several cytokines were significantly higher in newborns with moderate and severe HIE compared to a control group and provided moderate prediction of HIE II/III (AUC: 0.681-0.827). Furthermore, the levels of GFAP, tau, interleukin-6 (IL-6), and interleukin-8 (IL-8) were higher in HIE II/III cases compared with cases with PA/HIE I. IL-6 was also higher in HIE II/III compared with HIE I cases.

CONCLUSIONS

Biomarkers of brain injury and inflammation were increased in umbilical blood in cases with asphyxia. Several biomarkers were higher in HIE II/III versus those with no HIE or HIE I, suggesting that they could assist in the prediction of HIE II/III.

Reference centiles for infant sleep parameters from 4 to 16 weeks of age: findings from an Irish cohort

OBJECTIVES

To establish unconditional reference centiles for sleep parameters in infants 4-16 weeks of age.

DESIGN AND SETTING

Secondary data analysis of sleep parameters recorded at 4-16 weeks of age in a longitudinal randomised controlled trial (RCT) (BabySMART).

PATIENTS

Healthy term infants assigned to the non-intervention arm of the RCT.

MAIN OUTCOME MEASURES

Infants' sleep duration was recorded by parents/guardians daily, from week 2-16 of age using a sleep diary. Reference centiles for total, daytime, night-time and longest sleep episode duration were estimated using multilevel modelling.

RESULTS

One hundred and six infants, mean (SD) gestational age of 39.9 (1.2) weeks and mean (SD) birth weight of 3.6 (0.5) kg had sleep recorded contributing 1264 measurements for each sleep parameter. Between 4 and 16 weeks of age total sleep duration in a 24-hour period, night-time sleep duration in a 12-hour period and infant's longest sleep episode duration increased, while daytime sleep duration in a 12-hour period decreased.

CONCLUSIONS

Reference centiles up to 4 months of age in infants highlight the gradual decrease in daytime sleep and large increases in night-time sleep, which occur in tandem with increasing lengths of sleep episodes. These reference centiles provide useful sleep values for infant sleep trajectory occurring in early life and may be helpful for parents and clinicians.

TRIAL REGISTRATION NUMBER

NCT03381027.

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.

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.

Sleep state organisation of moderate to late preterm infants in the neonatal unit

BACKGROUND

Sleep supports neurodevelopment and sleep architecture reflects brain maturation. This prospective observational study describes the nocturnal sleep architecture of healthy moderate to late preterm (MLP) infants in the neonatal unit at 36 weeks post menstrual age (PMA).

METHODS

MLP infants, in the neonatal unit of a tertiary hospital in Ireland from 2017 to 2018, had overnight continuous electroencephalography (cEEG) with video for a minimum 12 h at 36 weeks PMA. The total sleep time (TST) including periods of active sleep (AS), quiet sleep (QS), indeterminate sleep (IS), wakefulness and feeding were identified, annotated and quantified.

RESULTS

A total of 98 infants had cEEG with video monitoring suitable for analysis. The median (IQR) of TST in the 12 h period was 7.09 h (IQR 6.61-7.76 h), 4.58 h (3.69-5.09 h) in AS, 2.02 h (1.76-2.36 h) in QS and 0.65 h (0.48-0.89 h) in IS. The total duration of AS was significantly lower in infants born at lower GA (p = 0.007) whilst the duration of individual QS periods was significantly higher (p = 0.001).

CONCLUSION

Overnight cEEG with video at 36 weeks PMA showed that sleep state architecture is dependent on birth GA. Infants with a lower birth GA have less AS and more QS that may have implications for later neurodevelopment.

IMPACT

EEG provides objective information about the sleep organisation of the moderate to late preterm (MLP) infant. Quantitative changes in sleep states occur with each week of advancing gestational age (GA). Active sleep (AS) is the dominant sleep state that was significantly lower in infants born at lower GA. MLP infants who were exclusively fed orally had a shorter total sleep time and less AS compared to infants who were fed via nasogastric tube.

Heart rate variability analysis for the prediction of EEG grade in infants with hypoxic ischaemic encephalopathy within the first 12 h of birth

Background and aims

Heart rate variability (HRV) has previously been assessed as a biomarker for brain injury and prognosis in neonates. The aim of this cohort study was to use HRV to predict the electroencephalography (EEG) grade in neonatal hypoxic-ischaemic encephalopathy (HIE) within the first 12 h.

Methods

We included 120 infants with HIE recruited as part of two European multi-centre studies, with electrocardiography (ECG) and EEG monitoring performed before 12 h of age. HRV features and EEG background were assessed using the earliest 1 h epoch of ECG-EEG monitoring. HRV was expressed in time, frequency and complexity features. EEG background was graded from 0-normal, 1-mild, 2-moderate, 3-major abnormalities to 4-inactive. Clinical parameters known within 6 h of birth were collected (intrapartum complications, foetal distress, gestational age, mode of delivery, gender, birth weight, Apgar at 1 and 5, assisted ventilation at 10 min). Using logistic regression analysis, prediction models for EEG severity were developed for HRV features and clinical parameters, separately and combined. Multivariable model analysis included 101 infants without missing data.

Results

Of 120 infants included, 54 (45%) had normal-mild and 66 (55%) had moderate-severe EEG grade. The performance of HRV model was AUROC 0.837 (95% CI: 0.759-0.914) and clinical model was AUROC 0.836 (95% CI: 0.759-0.914). The HRV and clinical model combined had an AUROC of 0.895 (95% CI: 0.832-0.958). Therapeutic hypothermia and anti-seizure medication did not affect the model performance.

Conclusions

Early HRV and clinical information accurately predicted EEG grade in HIE within the first 12 h of birth. This might be beneficial when EEG monitoring is not available in the early postnatal period and for referral centres who may want some objective information on HIE severity.

The Architecture of Early Childhood Sleep Over the First Two Years

INTRODUCTION

The architecture and function of sleep during infancy and early childhood has not been fully described in the scientific literature. The impact of early sleep disruption on cognitive and physical development is also under-studied. The aim of this review was to investigate early childhood sleep development over the first two years and its association with neurodevelopment.

METHODS

This review was conducted according to the 2009 PRISMA guidelines. Four databases (OVID Medline, Pubmed, CINAHL, and Web of Science) were searched according to predefined search terms.

RESULTS

Ninety-three studies with approximately 90,000 subjects from demographically diverse backgrounds were included in this review. Sleep is the predominant state at birth. There is an increase in NREM and a decrease in REM sleep during the first two years. Changes in sleep architecture occur in tandem with development. There are more studies exploring sleep and early infancy compared to mid and late infancy and early childhood.

DISCUSSION

Sleep is critical for memory, learning, and socio-emotional development. Future longitudinal studies in infants and young children should focus on sleep architecture at each month of life to establish the emergence of key characteristics, especially from 7-24 months of age, during periods of rapid neurodevelopmental progress.

Deep-spindle: An automated sleep spindle detection system for analysis of infant sleep spindles

BACKGROUND

Sleep spindles are an indicator of the development and integrity of the central nervous system in infants. Identifying sleep spindles manually in EEG is time-consuming and typically requires experienced experts. Automated detection of sleep spindles would greatly facilitate this analysis. Deep learning methods have been widely used recently in EEG analysis.

METHOD

We have developed a deep learning-based automated sleep spindle detection system, Deep-spindle, which employs a convolutional neural network (CNN) combined with a bidirectional Long Short-Term Memory (LSTM) network, which could assist in the analysis of infant sleep spindles. Deep-spindle was trained on the EEGs of ex-term infants to estimate the number and duration of sleep spindles. The ex-term EEG on channel F4-C4 was split into training (N=81) and validation (N=30) sets. An additional 30 ex-term EEG and 54 ex-preterm infant EEGs (channel F4-C4 and F3-C3) were used as an independent test set.

RESULT

Deep-spindle detected the number of sleep spindles with 91.9% to 96.5% sensitivity and 95.3% to 96.7% specificity, and estimated sleep spindle duration with a percent error of 13.1% to 19.1% in the independent test set. For each detected spindle event, the user is presented with amplitude, power spectral density and the spectrogram of the corresponding spindle EEG, and the probability of the event being a sleep spindle event, providing the user with insight into why the event is predicted as a sleep spindle to provide confidence in the predictions.

CONCLUSION

The Deep-spindle system can reduce physicians' workload, demonstrating the potential to assist physicians in the automated analysis of sleep spindles in infants.

Informed consent and assent guide for paediatric clinical trials in Europe

OBJECTIVE

Clinical trial sponsors spend considerable resources preparing informed consent (IC) and assent documentation for multinational paediatric clinical trial applications in Europe due to the limited and dispersed patient populations, the variation of national legal and ethical requirements, and the lack of detailed guidance. The aim of this study was to design new easy-to-use guide publicly available on European Medicines Agency's, Enpr-EMA website for all stakeholders.

METHODS

Current EU legal, ethical and regulatory guidance for paediatric clinical trials were collated, analysed and divided into 30 subject elements in two tables. The European Network of Young Person's Advisory Group reviewed the data and provided specific comments. A three-level recommendation using 'traffic light' symbols was designed for four age groups of children, according to relevance and the requirements.

RESULTS

A single guide document includes two tables: (1) general information and (2) trial-specific information. In the age group of 6-9 years old, 92% of the trial-specific subject elements can be or should be included in the IC discussion. Even in the youngest possible age group (2-5 years old children), the number of elements considered was, on average, 52%.

CONCLUSION

The EU Clinical Trial Regulation (2014) does not contain specific requirements exclusively for paediatric clinical trials. This work is the first to extensively collate all the current legal, regulatory and ethical documentation on the IC process, together with input from adolescents. This guide may increase the ethical standards in paediatric clinical trials.

Neonatal Seizure Management: Is the Timing of Treatment Critical?

OBJECTIVE

To assess the impact of the time to treatment of the first electrographic seizure on subsequent seizure burden and describe overall seizure management in a large neonatal cohort.

STUDY DESIGN

Newborns (36-44 weeks of gestation) requiring electroencephalographic (EEG) monitoring recruited to 2 multicenter European studies were included. Infants who received antiseizure medication exclusively after electrographic seizure onset were grouped based on the time to treatment of the first seizure: antiseizure medication within 1 hour, between 1 and 2 hours, and after 2 hours. Outcomes measured were seizure burden, maximum seizure burden, status epilepticus, number of seizures, and antiseizure medication dose over the first 24 hours after seizure onset.

RESULTS

Out of 472 newborns recruited, 154 (32.6%) had confirmed electrographic seizures. Sixty-nine infants received antiseizure medication exclusively after the onset of electrographic seizure, including 21 infants within 1 hour of seizure onset, 15 between 1 and 2 hours after seizure onset, and 33 at >2 hours after seizure onset. Significantly lower seizure burden and fewer seizures were noted in the infants treated with antiseizure medication within 1 hour of seizure onset (P = .029 and .035, respectively). Overall, 258 of 472 infants (54.7%) received antiseizure medication during the study period, of whom 40 without electrographic seizures received treatment exclusively during EEG monitoring and 11 with electrographic seizures received no treatment.

CONCLUSIONS

Treatment of neonatal seizures may be time-critical, but more research is needed to confirm this. Improvements in neonatal seizure diagnosis and treatment are also needed.

Case Report: Early Neonatal EEG in Two Infants with Pallister Killian Syndrome (PKS)

Pallister Killian Syndrome (PKS) is a rare genetic disorder caused by a mosaic tetrasomy of the short arm of chromosome 12. The syndrome is characterised by typical craniofacial dysmorphism, congenital anomalies and intellectual disability. Epilepsy is a known complication, with onset usually occurring in early childhood and characterised most commonly by spasms and myoclonic seizures. To the best of our knowledge, there have been no cases describing the early neonatal EEG in PKS and  electrographic seizures, to date. Here, we report two cases of PKS presenting in the neonatal period with distinctive EEG features and seizures.

Does Early Cerebral Near-Infrared Spectroscopy Monitoring Predict Outcome in Neonates with Hypoxic Ischaemic Encephalopathy? A Systematic Review of Diagnostic Test Accuracy

INTRODUCTION

Hypoxic ischaemic encephalopathy (HIE) remains one of the top 10 contributors to the global burden of disease. Early objective biomarkers are required. Near-infrared spectroscopy (NIRS) may provide a valuable insight into cerebral perfusion and metabolism. We aimed to determine whether early NIRS monitoring (<6 h of age) can predict outcome as defined by grade of encephalopathy, brain MRI findings, and/or neurodevelopmental outcome at 1-2 years in infants with HIE.

METHODS

We searched PubMed, Scopus, Web of Science, Embase, and The Cochrane Library databases (July 2019). Studies of infants born ≥36+0 weeks gestation with HIE who had NIRS recording commenced before 6 h of life were included. We planned to provide a narrative of all the studies included, and if similar clinically and methodologically, the results would be pooled in a meta-analysis to determine test accuracy.

RESULTS

Seven studies were included with a combined total of 161 infants. Only 1 study included infants with mild HIE. A range of different oximeters and probes were utilized with varying outcome measures making comparison difficult. Although some studies showed a trend towards higher cSO2 values before 6 h in infants with adverse neurodevelopmental outcomes, in the majority, this was not significant until beyond 24 h of life.

CONCLUSION

Very little data currently exists to assess the use of early NIRS to predict outcome in infants with HIE. Further studies using a standardized approach are required before NIRS can be evaluated as a potential objective assessment tool for early identification of at-risk infants.

Protocol for the Birth Asphyxia in African Newborns (Baby BRAiN) Study: a Neonatal Encephalopathy Feasibility Cohort Study

BACKGROUND: Neonatal encephalopathy (NE) is a leading cause of child mortality worldwide and contributes substantially to stillbirths and long-term disability. Ninety-nine percent of deaths from NE occur in low-and-middle-income countries (LMICs). Whilst therapeutic hypothermia significantly improves outcomes in high-income countries, its safety and effectiveness in diverse LMIC contexts remains debated. Important differences in the aetiology, nature and timing of neonatal brain injury likely influence the effectiveness of postnatal interventions, including therapeutic hypothermia. METHODS: This is a prospective pilot feasibility cohort study of neonates with NE conducted at Kawempe National Referral Hospital, Kampala, Uganda. Neurological investigations include continuous video electroencephalography (EEG) (days 1-4), serial cranial ultrasound imaging, and neonatal brain Magnetic Resonance Imaging and Spectroscopy (MRI/ MRS) (day 10-14). Neurodevelopmental follow-up will be continued to 18-24 months of age including Prechtl's Assessment of General Movements, Bayley Scales of Infant Development, and a formal scored neurological examination. The primary outcome will be death and moderate-severe neurodevelopmental impairment at 18-24 months. Findings will be used to inform explorative science and larger trials, aiming to develop urgently needed neuroprotective and neurorestorative interventions for NE applicable for use in diverse settings. DISCUSSION: The primary aims of the study are to assess the feasibility of establishing a facility-based cohort of children with NE in Uganda, to enhance our understanding of NE in a low-resource sub-Saharan African setting and provide infrastructure to conduct high-quality research on neuroprotective/ neurorestorative strategies to reduce death and disability from NE. Specific objectives are to establish a NE cohort, in order to 1) investigate the clinical course, aetiology, nature and timing of perinatal brain injury; 2) describe electrographic activity and quantify seizure burden and the relationship with adverse outcomes, and; 3) develop capacity for neonatal brain MRI/S and examine associations with early neurodevelopmental outcomes.

The impact of perinatal inflammation on the electroencephalogram in preterm infants: a systematic review

BACKGROUND

To summarise the association between perinatal inflammation (PI) exposure and electroencephalography (EEG) features in preterm infants.

METHODS

This systematic review included clinical studies of preterm infants born <37 weeks of gestational age (GA), who had both a PI exposure and an EEG assessment performed during the neonatal period. Studies were identified from Medline and Embase databases on the 15th of September 2021. PI was defined by histological chorioamnionitis, clinical chorioamnionitis, or early-onset neonatal infection (EONI). The risk of bias in included studies was assessed using the Joanna Briggs Institute (JBI) appraisal tool. A narrative approach was used to synthesise results. This review followed the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) 2020 statement.

RESULTS

Two cross-sectional studies enrolling 130 preterm children born <32 weeks of GA assessed with one-channel amplitude-integrated EEG (aEEG) during the first four days of life were included. A PI exposure was described in 39 (30%) infants and was associated with a decrease in amplitude and a reduced incidence of sleep-wake cycling patterns.

CONCLUSION

These results should be interpreted with caution because of the small number of included studies and their heterogeneity. Further clinical studies evaluating the association of PI with EEG findings are needed.

IMPACT

A method to assess developmental trajectories following perinatal inflammation is required. Insufficient data exist to determine EEG features associated with perinatal inflammation. Further clinical studies evaluating this association are needed.

Case Report: Electroencephalography in a neonate with isolated sulfite oxidase deficiency - a case report and literature review

Isolated sulfite oxidase deficiency (ISOD) is a rare autosomal recessive neuro-metabolic disorder caused by a mutation in the sulfite oxidase (SUOX) gene situated on chromosome 12. Due to the deficiency of this mitochondrial enzyme (sulfite oxidase), the oxidative degradation of toxic sulfites is disrupted. The most common form of this disease has an early onset (classical ISOD) in the neonatal period, with hypotonia, poor feeding and intractable seizures, mimicking hypoxic-ischaemic encephalopathy. The evolution is rapidly progressive to severe developmental delay, microcephaly and early death. Unfortunately, there is no effective treatment and the prognosis is very poor.

In this article, we described the evolution of early continuous electroencephalography (EEG) in a case of ISOD with neonatal onset, as severely encephalopathic background, with refractory seizures and distinct delta-beta complexes. The presence of the delta-beta complexes might be a diagnostic marker in ISOD. We also performed a literature review of published cases of neonatal ISOD that included EEG monitoring.

EEG sleep macrostructure and sleep spindles in early infancy

Study Objectives

Sleep features in infancy are potential biomarkers for brain maturation but poorly characterized. We describe normative values for sleep macrostructure and sleep spindles at 4–5 months of age.

Methods

Healthy term infants were recruited at birth and had daytime sleep electroencephalograms (EEGs) at 4–5 months. Sleep staging was performed and five features were analyzed. Sleep spindles were annotated and seven quantitative features were extracted. Features were analyzed across sex, recording time (am/pm), infant age, and from first to second sleep cycles.

Results

We analyzed sleep recordings from 91 infants, 41% females. Median (interquartile range [IQR]) macrostructure results: sleep duration 49.0 (37.8–72.0) min (n = 77); first sleep cycle duration 42.8 (37.0–51.4) min; rapid eye movement (REM) percentage 17.4 (9.5–27.7)% (n = 68); latency to REM 36.0 (30.5–41.1) min (n = 66). First cycle median (IQR) values for spindle features: number 241.0 (193.0–286.5), density 6.6 (5.7–8.0) spindles/min (n = 77); mean frequency 13.0 (12.8–13.3) Hz, mean duration 2.9 (2.6–3.6) s, spectral power 7.8 (4.7–11.4) µV², brain symmetry index 0.20 (0.16–0.29), synchrony 59.5 (53.2–63.8)% (n = 91). In males, spindle spectral power (µV²) was 24.5% lower (p = .032) and brain symmetry index 24.2% higher than females (p = .011) when controlling for gestational and postnatal age and timing of the nap. We found no other significant associations between studied sleep features and sex, recording time (am/pm), or age. Spectral power decreased (p < .001) on the second cycle.

Conclusion

This normative data may be useful for comparison with future studies of sleep dysfunction and atypical neurodevelopment in infancy.

Clinical Trial Registration: BABY SMART (Study of Massage Therapy, Sleep And neurodevelopMenT) (BabySMART)

URL: https://clinicaltrials.gov/ct2/show/results/NCT03381027?view=results.

ClinicalTrials.gov Identifier: NCT03381027

Novel Point-of-Care Diagnostic Method for Neonatal Encephalopathy Using Purine Nucleosides

Background: Evidence suggests that earlier diagnosis and initiation of treatment immediately after birth is critical for improved neurodevelopmental outcomes following neonatal encephalopathy (NE). Current diagnostic tests are, however, mainly restricted to clinical diagnosis with no molecular tests available. Purines including adenosine are released during brain injury such as hypoxia and are also present in biofluids. Whether blood purine changes can be used to diagnose NE has not been investigated to date.

Methods: Blood purines were measured in a mouse model of neonatal hypoxia and infants with NE using a novel point-of-care diagnostic technology (SMARTChip) based on the summated electrochemical detection of adenosine and adenosine metabolites in the blood.

Results: Blood purine concentrations were ∼2–3-fold elevated following hypoxia in mice [2.77 ± 0.48 μM (Control) vs. 7.57 ± 1.41 μM (post-hypoxia), p = 0.029]. Data in infants with NE had a 2–3-fold elevation when compared to healthy controls [1.63 ± 0.47 μM (Control, N = 5) vs. 4.87 ± 0.92 μM (NE, N = 21), p = 0.0155]. ROC curve analysis demonstrates a high sensitivity (81%) and specificity (80%) for our approach to identify infants with NE. Moreover, blood purine concentrations were higher in infants with NE and seizures [8.13 ± 3.23 μM (with seizures, N = 5) vs. 3.86 ± 0.56 μM (without seizures, N = 16), p = 0.044].

Conclusion: Our data provides the proof-of-concept that measurement of blood purine concentrations via SMARTChip technology may offer a low-volume bedside test to support a rapid diagnosis of NE.

Can EEG accurately predict 2-year neurodevelopmental outcome for preterm infants?

OBJECTIVE

Establish if serial, multichannel video electroencephalography (EEG) in preterm infants can accurately predict 2-year neurodevelopmental outcome.

DESIGN AND PATIENTS

EEGs were recorded at three time points over the neonatal course for infants <32 weeks' gestational age (GA). Monitoring commenced soon after birth and continued over the first 3 days. EEGs were repeated at approximately 32 and 35 weeks' postmenstrual age (PMA). EEG scores were based on an age-specific grading scheme. Clinical score of neonatal morbidity risk and cranial ultrasound imaging were completed.

SETTING

Neonatal intensive care unit at Cork University Maternity Hospital, Ireland.

MAIN OUTCOME MEASURES

Bayley Scales of Infant Development III at 2 years' corrected age.

RESULTS

Sixty-seven infants were prospectively enrolled in the study and 57 had follow-up available (median GA 28.9 weeks (IQR 26.5-30.4)). Forty had normal outcome, 17 had abnormal outcome/died. All EEG time points were individually predictive of abnormal outcome; however, the 35-week EEG performed best. The area under the receiver operating characteristic curve (AUC) for this time point was 0.91 (95% CI 0.83 to 1), p<0.001. Comparatively, the clinical course AUC was 0.68 (95% CI 0.54 to 0.80, p=0.015), while abnormal cranial ultrasound was 0.58 (95% CI 0.41 to 0.75, p=0.342).

CONCLUSION

Multichannel EEG is a strong predictor of 2-year outcome in preterm infants particularly when recorded around 35 weeks' PMA. Infants at high risk of brain injury may benefit from early postnatal EEG recording which, if normal, is reassuring. Postnatal clinical complications can contribute to poor outcome; therefore, we state that a later EEG around 35 weeks has a role to play in prognostication.

Activin A and Acvr2b mRNA from Umbilical Cord Blood Are Not Reliable Markers of Mild or Moderate Neonatal Hypoxic-Ischemic Encephalopathy

BACKGROUND

Activin A protein and its receptor ACVR2B have been considered viable biomarkers for the diagnosis of hypoxic-ischemic encephalopathy (HIE). This study aimed to assess umbilical cord blood (UCB) levels of Activin A and Acvr2b messenger RNA (mRNA) as early biomarkers of mild and moderate HIE and long-term neurodevelopmental outcome.

METHODS

One-hundred and twenty-six infants were included in the analyses from the BiHiVE2 cohort, a multi-center study, recruited in Ireland and Sweden (2013 to 2015). UCB serum Activin A and whole blood Acvr2b mRNA were measured using enzyme-linked immunosorbent assay and quantitative polymerase chain reaction, respectively.

RESULTS

Activin A analysis included 101 infants (controls, n = 50, perinatal asphyxia, n = 28, HIE, n = 23). No differences were detected across groups (p = 0.69). No differences were detected across HIE grades (p = 0.12). Acvr2b mRNA analysis included 67 infants (controls, n = 22, perinatal asphyxia, n = 23, and HIE, n = 22), and no differences were observed across groups (p = 0.75). No differences were detected across HIE grades (p = 0.58). No differences were detected in neurodevelopmental outcome in infants followed up to 18 to 36 months in serum Activin A or in whole blood Acvr2b mRNA (p = 0.55 and p = 0.90, respectively).

CONCLUSION

UCB Activin A and Acvr2b mRNA are not valid biomarkers of infants with mild or moderate HIE; they are unable to distinguish infants with HIE or infants with poor neurodevelopmental outcomes.

Hypotension in Preterm Infants (HIP) randomised trial

OBJECTIVE

To determine whether restricting the use of inotrope after diagnosis of low blood pressure (BP) in the first 72 hours of life affects survival without significant brain injury at 36 weeks of postmenstrual age (PMA) in infants born before 28 weeks of gestation.

DESIGN

Double-blind, placebo-controlled randomised trial. Caregivers were masked to group assignment.

SETTING

10 sites across Europe and Canada.

PARTICIPANTS

Infants born before 28 weeks of gestation were eligible if they had an invasive mean BP less than their gestational age that persisted for ≥15 min in the first 72 hours of life and a cerebral ultrasound free of significant (≥ grade 3) intraventricular haemorrhage.

INTERVENTION

Participants were randomly assigned to saline bolus followed by either a dopamine infusion (standard management) or placebo (5% dextrose) infusion (restrictive management).

PRIMARY OUTCOME

Survival to 36 weeks of PMA without severe brain injury.

RESULTS

The trial terminated early due to significant enrolment issues (7.7% of planned recruitment). 58 infants were enrolled between February 2015 and September 2017. The two groups were well matched for baseline variables. In the standard group, 18/29 (62%) achieved the primary outcome compared with 20/29 (69%) in the restrictive group (p=0.58). Additional treatments for low BP were used less frequently in the standard arm (11/29 (38%) vs 19/29 (66%), p=0.038).

CONCLUSION

Though this study lacked power, we did not detect major differences in clinical outcomes between standard or restrictive approach to treatment. These results will inform future studies in this area.

TRIAL REGISTRATION NUMBER

NCT01482559, EudraCT 2010-023988-17.

Predictive modelling of hypoxic ischaemic encephalopathy risk following perinatal asphyxia

Hypoxic Ischemic Encephalopathy (HIE) remains a major cause of neurological disability. Early intervention with therapeutic hypothermia improves outcome, but prediction of HIE is difficult and no single clinical marker is reliable. Machine learning algorithms may allow identification of patterns in clinical data to improve prognostic power. Here we examine the use of a Random Forest machine learning algorithm and five-fold cross-validation to predict the occurrence of HIE in a prospective cohort of infants with perinatal asphyxia. Infants with perinatal asphyxia were recruited at birth and neonatal course was followed for the development of HIE. Clinical variables were recorded for each infant including maternal demographics, delivery details and infant's condition at birth. We found that the strongest predictors of HIE were the infant's condition at birth (as expressed by Apgar score), need for resuscitation, and the first postnatal measures of pH, lactate, and base deficit. Random Forest models combining features including Apgar score, most intensive resuscitation, maternal age and infant birth weight both with and without biochemical markers of pH, lactate, and base deficit resulted in a sensitivity of 56-100% and a specificity of 78-99%. This study presents a dynamic method of rapid classification that has the potential to be easily adapted and implemented in a clinical setting, with and without the availability of blood gas analysis. Our results demonstrate that applying machine learning algorithms to readily available clinical data may support clinicians in the early and accurate identification of infants who will develop HIE. We anticipate our models to be a starting point for the development of a more sophisticated clinical decision support system to help identify which infants will benefit from early therapeutic hypothermia.

Grading hypoxic-ischemic encephalopathy in neonatal EEG with convolutional neural networks and quadratic time-frequency distributions

OBJECTIVE

To develop an automated system to classify the severity of hypoxic-ischaemic encephalopathy injury (HIE) in neonates from the background electroencephalogram (EEG).

METHOD

By combining a quadratic time{frequency distribution (TFD) with a convolutional neural network, we develop a system that classifies 4 EEG grades of HIE. The network learns directly from the two- dimensional TFD through 3 independent layers with convolution in the time, frequency, and time{frequency directions. Computationally efficient algorithms make it feasible to transform each 5 minute epoch to the time-frequency domain by controlling for oversampling to reduce both computation and computer memory. The system is developed on EEG recordings from 54 neonates. Then the system is validated on a large unseen dataset of 338 hours of EEG recordings from 91 neonates obtained across multiple international centres.

RESULTS

The proposed EEG HIE-grading system achieves a leave-one-subject-out testing accuracy of 88.9% and kappa of 0.84 on the development dataset. Accuracy for the large unseen test dataset is 69.5% (95% confidence interval, CI: 65.3 to 73.6%) and kappa of 0.54, which is a significant (P < 0.001) improvement over a state-of-the-art feature-based method with an accuracy of 56.8% (95% CI: 51.4 to 61.7%) and kappa of 0.39. Performance of the proposed system was unaffected when the number of channels in testing was reduced from 8 to 2|accuracy for large validation dataset remained at 69.5% (95% CI: 65.5 to 74.0%).

SIGNIFICANCE

The proposed system outperforms the state-of-the-art machine learning algorithms for EEG grade classification on a large multi-centre unseen dataset, indicating the potential to assist clinical decision making for neonates with HIE.

Up-Regulation of Nfat5 mRNA and Fzd4 mRNA as a Marker of Poor Outcome in Neonatal Hypoxic-Ischemic Encephalopathy

OBJECTIVE

To evaluate umbilical cord messenger RNA (mRNA) expression as biomarkers for the grade of hypoxic-ischemic encephalopathy (HIE) and long-term neurodevelopment outcome.

STUDY DESIGN

Infants were recruited from the BiHiVE1 study, Ireland (2009-2011), and the BiHiVE2 study, Ireland, and Sweden (2013-2015). Infants with HIE were assigned modified Sarnat scores at 24 hours and followed at 18-36 months. mRNA expression from cord blood was measured using quantitative real-time polymerase chain reaction.

RESULTS

We studied 124 infants (controls, n = 37; perinatal asphyxia, n = 43; and HIE, n = 44). Fzd4 mRNA increased in severe HIE (median relative quantification, 2.98; IQR, 2.23-3.68) vs mild HIE (0.88; IQR, 0.46-1.37; P = .004), and in severe HIE vs moderate HIE (1.06; IQR, 0.81-1.20; P = .003). Fzd4 mRNA also increased in infants eligible for therapeutic hypothermia (1.20; IQR, 0.92-2.37) vs those who were ineligible for therapeutic hypothermia group (0.81; IQR, 0.46-1.53; P = .017). Neurodevelopmental outcome was analyzed for 56 infants. Nfat5 mRNA increased in infants with severely abnormal (1.26; IQR, 1.17-1.39) vs normal outcomes (0.97; IQR, 0.83-1.24; P = .036), and also in infants with severely abnormal vs mildly abnormal outcomes (0.96; IQR, 0.80-1.06; P = .013). Fzd4 mRNA increased in infants with severely abnormal (2.51; IQR, 1.60-3.56) vs normal outcomes (0.74; IQR, 0.48-1.49; P = .004) and in infants with severely abnormal vs mildly abnormal outcomes (0.97; IQR, 0.75-1.34; P = .026).

CONCLUSIONS

Increased Fzd4 mRNA expression was observed in cord blood of infants with severe HIE; Nfat5 mRNA and Fzd4 mRNA expression were increased in infants with severely abnormal long-term outcomes. These mRNA may augment current measures as early objective markers of HIE severity at delivery.

Multichannel EEG abnormalities during the first 6 hours in infants with mild hypoxic-ischaemic encephalopathy

BACKGROUND

Infants with mild HIE are at risk of significant disability at follow-up. In the pre-therapeutic hypothermia (TH) era, electroencephalography (EEG) within 6 hours of birth was most predictive of outcome. This study aims to identify and describe features of early EEG and heart rate variability (HRV) (<6 hours of age) in infants with mild HIE compared to healthy term infants.

METHODS

Infants >36 weeks with mild HIE, not undergoing TH, with EEG before 6 hours of age were identified from 4 prospective cohort studies conducted in the Cork University Maternity Services, Ireland (2003-2019). Control infants were taken from a contemporaneous study examining brain activity in healthy term infants. EEGs were qualitatively analysed by two neonatal neurophysiologists and quantitatively assessed using multiple features of amplitude, spectral shape and inter-hemispheric connectivity. Quantitative features of HRV were assessed in both the groups.

RESULTS

Fifty-eight infants with mild HIE and sixteen healthy term infants were included. Seventy-two percent of infants with mild HIE had at least one abnormal EEG feature on qualitative analysis and quantitative EEG analysis revealed significant differences in spectral features between the two groups. HRV analysis did not differentiate between the groups.

CONCLUSIONS

Qualitative and quantitative analysis of the EEG before 6 hours of age identified abnormal EEG features in mild HIE, which could aid in the objective identification of cases for future TH trials in mild HIE.

IMPACT

Infants with mild HIE currently do not meet selection criteria for TH yet may be at risk of significant disability at follow-up. In the pre-TH era, EEG within 6 hours of birth was most predictive of outcome; however, TH has delayed this predictive value. 72% of infants with mild HIE had at least one abnormal EEG feature in the first 6 hours on qualitative assessment. Quantitative EEG analysis revealed significant differences in spectral features between infants with mild HIE and healthy term infants. Quantitative EEG features may aid in the objective identification of cases for future TH trials in mild HIE.

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.

Random Forest-based Algorithm for Sleep Spindle Detection in Infant EEG

Sleep spindles are associated with normal brain development, memory consolidation and infant sleep-dependent brain plasticity and can be used by clinicians in the assessment of brain development in infants. Sleep spindles can be detected in EEG, however, identifying sleep spindles in EEG recordings manually is very time-consuming and typically requires highly trained experts. Research on the automatic detection of sleep spindles in infant EEGs has been limited to-date. In this study, we present a novel supervised machine learning-based algorithm to detect sleep spindles in infant EEG recordings. EEGs collected from 141 ex-term born infants and 6 ex-preterm born infants, recorded at 4 months of age (adjusted), were used to train and test the algorithm. Sleep spindles were annotated by experienced clinical physiologists as the gold standard. The dataset was split into training (81 ex-term), validation (30 ex-term), and testing (30 ex-term + 6 ex-preterm) set. 15 features were selected for input into a random forest algorithm. Sleep spindles were detected in the ex-term infant EEG test set with 92.1% sensitivity and 95.2% specificity. For ex-preterm born infants, the sensitivity and specificity were 80.3% and 91.8% respectively. The proposed algorithm has the potential to assist researchers and clinicians in the automated analysis of sleep spindles in infant EEG.

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

BACKGROUND

Despite the availability of continuous conventional electroencephalography (cEEG), accurate diagnosis of neonatal seizures is challenging in clinical practice. Algorithms for decision support in the recognition of neonatal seizures could improve detection. We aimed to assess the diagnostic accuracy of an automated seizure detection algorithm called Algorithm for Neonatal Seizure Recognition (ANSeR).

METHODS

This multicentre, randomised, two-arm, parallel, controlled trial was done in eight neonatal centres across Ireland, the Netherlands, Sweden, and the UK. Neonates with a corrected gestational age between 36 and 44 weeks with, or at significant risk of, seizures requiring EEG monitoring, received cEEG plus ANSeR linked to the EEG monitor displaying a seizure probability trend in real time (algorithm group) or cEEG monitoring alone (non-algorithm group). The primary outcome was diagnostic accuracy (sensitivity, specificity, and false detection rate) of health-care professionals to identify neonates with electrographic seizures and seizure hours with and without the support of the ANSeR algorithm. Neonates with data on the outcome of interest were included in the analysis. This study is registered with ClinicalTrials.gov, NCT02431780.

FINDINGS

Between Feb 13, 2015, and Feb 7, 2017, 132 neonates were randomly assigned to the algorithm group and 132 to the non-algorithm group. Six neonates were excluded (four from the algorithm group and two from the non-algorithm group). Electrographic seizures were present in 32 (25·0%) of 128 neonates in the algorithm group and 38 (29·2%) of 130 neonates in the non-algorithm group. For recognition of neonates with electrographic seizures, sensitivity was 81·3% (95% CI 66·7-93·3) in the algorithm group and 89·5% (78·4-97·5) in the non-algorithm group; specificity was 84·4% (95% CI 76·9-91·0) in the algorithm group and 89·1% (82·5-94·7) in the non-algorithm group; and the false detection rate was 36·6% (95% CI 22·7-52·1) in the algorithm group and 22·7% (11·6-35·9) in the non-algorithm group. We identified 659 h in which seizures occurred (seizure hours): 268 h in the algorithm versus 391 h in the non-algorithm group. The percentage of seizure hours correctly identified was higher in the algorithm group than in the non-algorithm group (177 [66·0%; 95% CI 53·8-77·3] of 268 h vs 177 [45·3%; 34·5-58·3] of 391 h; difference 20·8% [3·6-37·1]). No significant differences were seen in the percentage of neonates with seizures given at least one inappropriate antiseizure medication (37·5% [95% CI 25·0 to 56·3] vs 31·6% [21·1 to 47·4]; difference 5·9% [-14·0 to 26·3]).

INTERPRETATION

ANSeR, a machine-learning algorithm, is safe and able to accurately detect neonatal seizures. Although the algorithm did not enhance identification of individual neonates with seizures beyond conventional EEG, recognition of seizure hours was improved with use of ANSeR. The benefit might be greater in less experienced centres, but further study is required.

FUNDING

Wellcome Trust, Science Foundation Ireland, and Nihon Kohden.

Temporally Altered miRNA Expression in a Piglet Model of Hypoxic Ischemic Brain Injury

Hypoxic ischemic encephalopathy (HIE) is the most frequent cause of acquired infant brain injury. Early, clinically relevant biomarkers are required to allow timely application of therapeutic interventions. We previously reported early alterations in several microRNAs (miRNA) in umbilical cord blood at birth in infants with HIE. However, the exact timing of these alterations is unknown. Here, we report serial changes in six circulating, cross-species/bridging biomarkers in a clinically relevant porcine model of neonatal HIE with functional analysis. Six miRNAs—miR-374a, miR-181b, miR-181a, miR-151a, miR-148a and miR-128—were significantly and rapidly upregulated 1-h post-HI. Changes in miR-374a, miR-181b and miR-181a appeared specific to moderate-severe HI. Histopathological injury and five miRNAs displayed positive correlations and were predictive of MRS Lac/Cr ratios. Bioinformatic analysis identified that components of the bone morphogenic protein (BMP) family may be targets of miR-181a. Inhibition of miR-181a increased neurite length in both SH-SY5Y cells at 1 DIV (days in vitro) and in primary cultures of rat neuronal midbrain at 3 DIV. In agreement, inhibition of miR-181a increased expression of BMPR2 in differentiating SH-SY5Y cells. These miRNAs may therefore act as early biomarkers of HIE, thereby allowing for rapid diagnosis and timely therapeutic intervention and may regulate expression of signalling pathways vital to neuronal survival.

Identifying tracé alternant activity in neonatal EEG using an inter-burst detection approach

Electroencephalography (EEG) is an important clinical tool for reviewing sleep-wake cycling in neonates in intensive care. Tracé alternant (TA)-a characteristic pattern of EEG activity during quiet sleep in term neonates-is defined by alternating periods of short-duration, high-voltage activity (bursts) separated by lower-voltage activity (inter-bursts). This study presents a novel approach for detecting TA activity by first detecting the inter-bursts and then processing the temporal map of the bursts and inter-bursts. EEG recordings from 72 healthy term neonates were used to develop and evaluate performance of 1) an inter-burst detection method which is then used for 2) detection of TA activity. First, multiple amplitude and spectral features were combined using a support vector machine (SVM) to classify bursts from inter-bursts within TA activity, resulting in a median area under the operating characteristic curve (AUC) of 0.95 (95% confidence interval, CI: 0.93 to 0.98). Second, post-processing of the continuous SVM output, the confidence score, was used to produce a TA envelope. This envelope was used to detect TA activity within the continuous EEG with a median AUC of 0.84 (95% CI: 0.80 to 0.88). These results validate how an inter-burst detection approach combined with post processing can be used to classify TA activity. Detecting the presence or absence of TA will help quantify disruption of the clinically important sleep-wake cycle.

Machine learning without a feature set for detecting bursts in the EEG of preterm infants

Deep neural networks enable learning directly on the data without the domain knowledge needed to construct a feature set. This approach has been extremely successful in almost all machine learning applications. We propose a new framework that also learns directly from the data, without extracting a feature set. We apply this framework to detecting bursts in the EEG of premature infants. The EEG is recorded within days of birth in a cohort of infants without significant brain injury and born <; 30 weeks of gestation. The method first transforms the time-domain signal to the time-frequency domain and then trains a machine learning method, a gradient boosting machine, on each time-slice of the time-frequency distribution. We control for oversampling the time-frequency distribution with a significant reduction (<; 1%) in memory and computational complexity. The proposed method achieves similar accuracy to an existing multi-feature approach: area under the characteristic curve of 0.98 (with 95% confidence interval of 0.96 to 0.99), with a median sensitivity of 95% and median specificity of 94%. The proposed framework presents an accurate, simple, and computational efficient implementation as an alternative to both the deep learning approach and to the manual generation of a feature set.

The impact of short-term predominate breastfeeding on cognitive outcome at 5 years

AIM

Breastfeeding is associated with IQ, school attendance and income. Despite the known benefits of breastfeeding, the rate of exclusive breastfeeding up to 6 months is low globally. We examined the effect of short-term breastfeeding on long-term IQ.

METHODS

In this secondary analysis of the prospective Cork BASELINE Birth Cohort Study, children were categorised as predominantly breastfed (n = 288) versus exclusively formula-fed (n = 254) at 2-months of age. Infants (n = 404) receiving mixed feeding were excluded. Outcome was assessed using the KBIT-II at 5 years. Multivariable linear regression was used to adjust for confounding variables.

RESULTS

Following adjustment for confounding variables, children, predominately breastfed at 2 months of age, demonstrated increased overall IQ (2.00 points (95% CI: 0.35 to 3.65); P = .018) and non-verbal IQ at 5 years of age (1.88 points (95% CI: 0.22 to 3.54); P = .027) compared with those never breastfed. No significant relationship was found with verbal IQ (P = .154).

CONCLUSION

A significant increase in composite and non-verbal IQ at 5 years of age was associated with short-term breastfeeding. This study adds to a growing body of evidence that short-term breastfeeding promotes healthy cognitive development.

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

AIM

To investigate the effect of a musical intervention on neonatal stress response to venepuncture as measured by salivary cortisol levels and pain profile scores.

METHODS

In a randomised control crossover trial, participants were randomised to both a control arm (sucrose) and intervention arm (sucrose and music) for routine venepuncture procedures. Salivary swabs were collected at baseline, 20 minutes post-venepuncture and 4 hours post-venepuncture. Pain levels were assessed using the Premature Infant Pain Profile (PIPP). A total of 16 preterm neonates participated in both arms to complete the study.

RESULTS

Cortisol values were elevated at all timepoints in the intervention arm (baseline, 20 minutes, and 4 hours post-procedure) but not significantly so (P = .056, P = .3, and P = .575, respectively). Median change in cortisol values from baseline was +128.48 pg/mL (-47.66 to 517.02) at 20 minutes and +393.52 pg/mL (47.88-1221.34) at 4 hours post-procedure in the control arm compared to -69.564 pg/mL (-860.96 to 397.289) and +100.48 pg/mL (-560.46 to 842.99) at 20 minutes and 4 hours post-procedure in the intervention arm. There was no statistically significant difference observed between groups (P = .311 at 20 minutes, and P = .203 at 4 hours post-procedure). PIPP scores were not significantly different between study arms.

CONCLUSION

Our findings did not support the additional benefit of music intervention on neonatal stress response to venepuncture in preterm infants.

Validation of Altered Umbilical Cord Blood MicroRNA Expression in Neonatal Hypoxic-Ischemic Encephalopathy

Importance

Neonatal hypoxic-ischemic encephalopathy (HIE) remains a significant cause of neurologic disability. Identifying infants suitable for therapeutic hypothermia (TH) within a narrow therapeutic time is difficult. No single robust biochemical marker is available to clinicians.

Objective

To assess the ability of a panel of candidate microRNA (miRNA) to evaluate the development and severity of encephalopathy following perinatal asphyxia (PA).

Design, Setting, and Participants

This validation study included 2 cohorts. For the discovery cohort, full-term infants with PA were enrolled at birth to the Biomarkers in Hypoxic-Ischemic Encephalopathy (BiHiVE1) study (2009-2011) in Cork, Ireland. Encephalopathy grade was defined using early electroencephalogram and Sarnat score (n = 68). The BiHiVE1 cohort also enrolled healthy control infants (n = 22). For the validation cohort, the BiHiVE2 multicenter study (2013-2015), based in Cork, Ireland (7500 live births per annum), and Karolinska Huddinge, Sweden (4400 live births per annum), recruited infants with PA along with healthy control infants to validate findings from BiHiVE1 using identical recruitment criteria (n = 80). The experimental design was formulated prior to recruitment, and analysis was conducted from June 2016 to March 2017.

Main Outcomes and Measures

Alterations in umbilical cord whole-blood miRNA expression.

Results

From 170 neonates, 160 were included in the final analysis. The BiHiVE1 cohort included 87 infants (21 control infants, 39 infants with PA, and 27 infants with HIE), and BiHiVE2 included 73 infants (control [n = 22], PA [n = 26], and HIE [n = 25]). The BiHiVE1 and BiHiVE2 had a median age of 40 weeks (interquartile range [IQR], 39-41 weeks) and 40 weeks (IQR, 39-41 weeks), respectively, and included 56 boys and 31 girls and 45 boys and 28 girls, respectively. In BiHiVE1, 12 candidate miRNAs were identified, and 7 of these miRNAs were chosen for validation in BiHiVE2. The BiHiVE2 cohort showed consistent alteration of 3 miRNAs; miR-374a-5p was decreased in infants diagnosed as having HIE compared with healthy control infants (median relative quantification, 0.38; IQR, 0.17-0.77 vs 0.95; IQR, 0.68-1.19; P = .009), miR-376c-3p was decreased in infants with PA compared with healthy control infants (median, 0.42; IQR, 0.21-0.61 vs 0.90; IQR, 0.70-1.30; P = .004), and mir-181b-5p was decreased in infants eligible for TH (median, 0.27; IQR, 0.14-1.41) vs 1.18; IQR, 0.70-2.05; P = .02).

Conclusions and Relevance

Altered miRNA expression was detected in umbilical cord blood of neonates with PA and HIE. These miRNA could assist diagnostic markers for early detection of HIE and PA at birth.

Bag of Patterns for Nearest Neighbour Neonatal EEG Recall

Clinical neurophysiologists often find it difficult to recall rare EEG patterns despite the fact that this information could be diagnostic and help with treatment intervention. Traditional search methods may take time to retrieve the archived EEGs that could provide the meaning or cause of the specific pattern, which is undesirable as time can be critical for sick neonates. If neurophysiologists had the ability to quickly recall similar patterns, the prior occurrence of the pattern may help make an earlier diagnosis. This paper presents a system that may be used to assist a clinical neurophysiologist in the recall of neonatal EEG patterns. This paper compares two brute force approaches for the task of neonatal EEG recall and looks at the performance accuracy, speed and memory requirements. This system was tested on six different neonatal EEG pattern types with 430 events in total and the results are presented in this paper.

Impact of therapeutic hypothermia on infantile spasms: an observational cohort study

AIM

To establish the incidence of infantile spasms in children in the southern region of the Republic of Ireland and to compare the incidence of infantile spasms before and after the introduction of therapeutic hypothermia in infants with hypoxic-ischemic encephalopathy (HIE).

METHOD

Children born between 2003 and 2015 and diagnosed with infantile spasms (epileptic spasms with or without hypsarrhythmia) in the first 2 years of life were identified through audits of electroencephalography reports and paediatric neurology patient lists. Data on live births were obtained from the regional hospital statistics databases. Medical charts of infantile spasm cases were reviewed for demographic information, diagnostic workup results, treatment response, disease course, and developmental outcome.

RESULTS

Forty-two infants with infantile spasms were identified. The cumulative incidence of infantile spasms up to the age of 2 years was 4.01 per 10 000 live births. Difference due to sex was minimal (22 males, 20 females) and most infants were delivered at or near term with gestational ages ranging between 30.0 and 41.8 weeks (median [interquartile range] 39.6wks [38.1-40.0wks]). The aetiology for infantile spasms was identified in almost two-thirds of cases, with HIE being the single most common cause (n=7). Other causes included chromosomal and monogenetic abnormalities (n=8). Infantile spasms occurred in moderate and severe grades of HIE, with a significantly higher incidence in those with severe HIE (p=0.029). Infants with severe HIE who did not receive therapeutic hypothermia were six times more likely to develop infantile spasms compared to those who did, but the difference was not statistically significant (4 out of 16 vs 1 out of 24, p=0.138).

INTERPRETATION

This study provides detailed information about infantile spasms before and after the introduction of therapeutic hypothermia. HIE severity is a risk factor for the development of infantile spasms. The introduction of therapeutic hypothermia may have had an impact, but the effect was hard to ascertain in this cohort due to the small number of infants.

WHAT THIS PAPER ADDS

The incidence of infantile spasms and patient characteristics in the southern region of the Republic of Ireland is similar to internationally published data. None of the infants with a history of mild hypoxic-ischemic encephalopathy (HIE) developed infantile spasms. The risk of infantile spasms was higher in infants with severe HIE. Infantile spasms were more frequent in infants with severe HIE not treated with therapeutic hypothermia.

Two-Year Neurodevelopmental Outcomes After Mild Hypoxic Ischemic Encephalopathy in the Era of Therapeutic Hypothermia

IMPORTANCE

Therapeutic hypothermia reduces risk of death and disability in infants with moderate to severe hypoxic ischemic encephalopathy (HIE). Randomized clinical trials of therapeutic hypothermia to date have not included infants with mild HIE because of a perceived good prognosis.

OBJECTIVE

To test the hypothesis that children with mild HIE have worse neurodevelopmental outcomes than their healthy peers.

DESIGN, SETTING, AND PARTICIPANTS

Analysis of pooled data from 4 prospective cohort studies in Cork, Ireland, and Stockholm, Sweden, between January 2007 and August 2015. The dates of data analysis were September 2017 to June 2019. Follow-up was performed at age 18 to 42 months. In this multicenter cohort study, all children were born or treated at the tertiary centers of Cork University Maternity Hospital, Cork, Ireland, or Karolinska University Hospital, Stockholm, Sweden. In all, 690 children were eligible for this study.

EXPOSURES

At discharge, all children were categorized into the following 5 groups using a modified Sarnat score: healthy controls, perinatal asphyxia (PA) without HIE, mild HIE, moderate HIE, and severe HIE.

MAIN OUTCOMES AND MEASURES

Cognitive, language, and motor development were assessed with the Bayley Scales of Infant and Toddler Development, Third Edition (BSITD-III). The BSITD-III scores are standardized to a mean (SD) of 100 (15), with lower scores indicating risk of developmental delay.

RESULTS

Of the 690 children eligible for this study, 2-year follow-up data were available in 471 (mean [SD] age at follow-up, 25.6 [5.7] months; 54.8% male), including 152 controls, 185 children with PA without HIE, and 134 children with HIE, of whom 14 had died. Infants with mild HIE (n = 55) had lower cognitive composite scores compared with controls, with a mean (SD) of 97.6 (11.9) vs 103.6 (14.6); the crude mean difference was -6.0 (95% CI, -9.9 to -2.1), and the adjusted mean difference was -5.2 (95% CI, -9.1 to -1.3). There was no significant difference in the mean cognitive composite scores between untreated children (n = 47) with mild HIE and surviving children with moderate HIE (n = 53) treated with therapeutic hypothermia, with a crude mean difference for mild vs moderate of -2.2 (95% CI, -8.1 to 3.7).

CONCLUSIONS AND RELEVANCE

This study's findings suggest that, at age 2 years, the cognitive composite scores of children with a history of mild HIE may be lower than those of a contemporaneous control group and may not be significantly different from those of survivors of moderate HIE treated with therapeutic hypothermia.

A standardised assessment scheme for conventional EEG in preterm infants

OBJECTIVE

To develop a standardised scheme for assessing normal and abnormal electroencephalography (EEG) features of preterm infants. To assess the interobserver agreement of this assessment scheme.

METHODS

We created a standardised EEG assessment scheme for 6 different post-menstrual age (PMA) groups using 4 EEG categories. Two experts, not involved in the development of the scheme, evaluated this on 24 infants <32 weeks gestational age (GA) using random 2 hour EEG epochs. Where disagreements were found, the features were checked and modified. Finally, the two experts independently evaluated 2 hour EEG epochs from an additional 12 infants <37 weeks GA. The percentage of agreement was calculated as the ratio of agreements to the sum of agreements plus disagreements.

RESULTS

Good agreement in all patients and EEG feature category was obtained, with a median agreement between 80% and 100% over the 4 EEG assessment categories. No difference was found in agreement rates between the normal and abnormal features (p = 0.959).

CONCLUSIONS

We developed a standard EEG assessment scheme for preterm infants that shows good interobserver agreement.

SIGNIFICANCE

This will provide information to Neonatal Intensive Care Unit (NICU) staff about brain activity and maturation. We hope this will prove useful for many centres seeking to use neuromonitoring during critical care for preterm infants.

Extracting transients from cerebral oxygenation signals of preterm infants: a new singular-spectrum analysis method

Many infants born prematurely develop brain injury within the first few days after birth. Near infrared spectroscopy (NIRS) is a safe technology that can continuously monitor the varying levels of oxygenation in the brain. Analysis of this signal has the potential to detect the onset of brain injury. We develop a method that extracts transient waveforms from the oxygenation signal. This method uses the cosine transform and singular-spectrum analysis to decompose the signal. We test different procedures to select a threshold for estimating the transient component. As part of the development of the method, we build a model of the cerebral oxygenation signals combining clusters of transient waveforms and nonstationary coloured noise. After development, we test on cerebral oxygenation recordings from 10 extremely preterm infants. We find that using the decomposition method to remove the transient components improves detection performance of brain injury, from an area-under the receiver operator characteristic of 0.91 to 1.00. These findings highlight the importance of specific signal processing methods for the cerebral oxygenation signal and the potential for NIRS as a neuromonitoring technology in neonatal intensive care.

Neonatal Seizures-Are We there Yet?

Neonatal seizures are the most prevalent and distinctive sign of neurologic dysfunction in early life and pose an immense challenge for clinicians. Improvements in neonatal care have increased the survival rate of extremely premature infants, considerably changing the spectrum of underlying etiologies, and instigating a gradual shift from mortality to morbidity. Recognizing neonatal seizures can be challenging due to variability in presentation but clinical features can often provide valuable clues about etiology. Yet, the majority of neonatal seizures are subclinical. Even though conventional electroencephalography (EEG) with simultaneous video detection of seizures still represents the diagnostic gold standard, continuous monitoring using a one- to two-channel amplitude-integrated EEG with concurrent unprocessed EEG can be crucial for early recognition and intervention. Furthermore, tremendous progress has been made in neuroimaging, and all infants with seizures should have a magnetic resonance imaging (MRI) to help identify the underlying etiology. While the majority of neonatal seizures are caused by hypoxic-ischemic events, stroke, hemorrhage, or infection, approximately 15% of patients will require more sophisticated algorithms for diagnostic workup, including metabolic and genetic screening. These recent developments have led to renew interest in the classification of neonatal seizures, which aim to help identify etiology and guide appropriate therapeutic and prognostic decisions. In this review, we outline recent progress made in the etiology, diagnosis, and treatment of neonatal seizures and highlight areas that deserve further research.