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.

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.

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.

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.

An Introduction to Neonatal EEG.

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

Supported Discharge Teams for older people in hospital acute care: a randomised controlled trial.

Background: Supported Discharge Teams aim to help with the transition from hospital to home, whilst reducing hospital length-of-stay. Despite their obvious attraction, the evidence remains mixed, ranging from strong support for disease-specific interventions to less favourable results for generic services. Objective: To determine whether older people referred to a Supported Discharge Team have: (i) reduced length-of-stay in hospital; (ii) reduced risk of hospital readmission; and (iii) reduced healthcare costs. Methods: Randomised controlled trial with follow-up to 6 months; 103 older women and 80 men (n = 183) (mean age 79), in hospital, were randomised to receive either Supported Discharge Team or usual care. Home-based rehabilitation was delivered by trained Health Care Assistants up to four times a day, 7 days a week, under the guidance of registered nurses, allied health and geriatricians for up to 6 weeks. Results: Participants randomised to the Supported Discharge Team spent less time in hospital during the index admission (mean 15.7 days) in comparison to usual care (mean 21.6 days) (mean difference 5.9: 95% CI 0.6, 11.3 days: P = 0.03) and spent less time in hospital in the 6 months following discharge home. Supported discharge group costs were calculated at mean NZ$10,836 (SD NZ$12,087) compared to NZ$16,943 (SD NZ$22,303) in usual care. Conclusion: A Supported Discharge Team can provide an effective means of discharging older people home early from hospital and can make a cost-effective contribution to managing increasing demand for hospital beds.

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

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

In Vivo Measurement of Cerebral Mitochondrial Metabolism Using Broadband Near Infrared Spectroscopy Following Neonatal Stroke.

Neonatal stroke presents with features of encephalopathy and can result in significant morbidity and mortality. We investigated the cerebral metabolic and haemodynamic changes following neonatal stroke in a term infant at 24 h of life. Changes in oxidation state of cytochrome-c-oxidase (oxCCO) concentration were monitored along with changes in oxy- and deoxy- haemoglobin using a new broadband near-infrared spectroscopy (NIRS) system. Repeated transient changes in cerebral haemodynamics and metabolism were noted over a 3-h study period with decrease in oxyhaemoglobin (HbO2), deoxy haemoglobin (HHb) and oxCCO in both cerebral hemispheres without significant changes in systemic observations. A clear asymmetry was noted in the degree of change between the two cerebral hemispheres. Changes in cerebral oxygenation (measured as HbDiff=HbO2-HHb) and cerebral metabolism (measured as oxCCO) were highly coupled on the injured side of the brain.

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.

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.

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.

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.

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.

Spindle-AI: Sleep Spindle Number and Duration Estimation in Infant EEG.

OBJECTIVE: Sleep spindle features show developmental changes during infancy and have the potential to provide an early biomarker for abnormal brain maturation. Manual identification of sleep spindles in the electroencephalogram (EEG) is time-consuming and typically requires highly-trained experts. Automated detection of sleep spindles would greatly facilitate this analysis. Research on the automatic detection of sleep spindles in infant EEG has been limited to-date. METHODS: We present a random forest-based sleep spindle detection method (Spindle-AI) to estimate the number and duration of sleep spindles in EEG collected from 141 ex-term born infants, recorded at 4 months of age. The signal on channel F4-C4 was split into a training set (81 ex-term) and a validation set (30 ex-term). An additional 30 ex-term infant EEGs (channel F4-C4 and channel F3-C3) were used as an independent test set. Fourteen features were selected for input into a random forest algorithm to estimate the number and duration of spindles and the results were compared against sleep spindles annotated by an experienced clinical physiologist. RESULTS: The prediction of the number of sleep spindles in the independent test set demonstrated 93.3% to 93.9% sensitivity, 90.7% to 91.5% specificity, and 89.2% to 90.1% precision. The duration estimation of sleep spindle events in the independent test set showed a percent error of 5.7% to 7.4%. CONCLUSION AND SIGNIFICANCE: Spindle-AI has been implemented as a web server that has the potential to assist clinicians in the fast and accurate monitoring of sleep spindles in infant EEGs.

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.

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.

Electroencephalographic 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.

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.

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.