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.

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.

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.

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.

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.

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.

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).Approach. 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 min 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 h of EEG recordings from 91 neonates obtained across multiple international centres.Main 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%-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%-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 the large validation dataset remained at 69.5% (95% CI: 65.5%-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.

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.

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

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

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

OBJECTIVE: The aim of this multicentre study was to describe detailed characteristics of electrographic seizures in a cohort of neonates monitored with multichannel continuous electroencephalography (cEEG) in 6 European centres. METHODS: Neonates of at least 36 weeks of gestation who required cEEG monitoring for clinical concerns were eligible, and were enrolled prospectively over 2 years from June 2013. Additional retrospective data were available from two centres for January 2011 to February 2014. Clinical data and EEGs were reviewed by expert neurophysiologists through a central server. RESULTS: Of 214 neonates who had recordings suitable for analysis, EEG seizures were confirmed in 75 (35%). The most common cause was hypoxic-ischaemic encephalopathy (44/75, 59%), followed by metabolic/genetic disorders (16/75, 21%) and stroke (10/75, 13%). The median number of seizures was 24 (IQR 9-51), and the median maximum hourly seizure burden in minutes per hour (MSB) was 21 min (IQR 11-32), with 21 (28%) having status epilepticus defined as MSB>30 min/hour. MSB developed later in neonates with a metabolic/genetic disorder. Over half (112/214, 52%) of the neonates were given at least one antiepileptic drug (AED) and both overtreatment and undertreatment was evident. When EEG monitoring was ongoing, 27 neonates (19%) with no electrographic seizures received AEDs. Fourteen neonates (19%) who did have electrographic seizures during cEEG monitoring did not receive an AED. CONCLUSIONS: Our results show that even with access to cEEG monitoring, neonatal seizures are frequent, difficult to recognise and difficult to treat. OBERSERVATION STUDY NUMBER: NCT02160171.

Phenobarbital reduces EEG amplitude and propagation of neonatal seizures but does not alter performance of automated seizure detection.

OBJECTIVE: Phenobarbital increases electroclinical uncoupling and our preliminary observations suggest it may also affect electrographic seizure morphology. This may alter the performance of a novel seizure detection algorithm (SDA) developed by our group. The objectives of this study were to compare the morphology of seizures before and after phenobarbital administration in neonates and to determine the effect of any changes on automated seizure detection rates. METHODS: The EEGs of 18 term neonates with seizures both pre- and post-phenobarbital (524 seizures) administration were studied. Ten features of seizures were manually quantified and summary measures for each neonate were statistically compared between pre- and post-phenobarbital seizures. SDA seizure detection rates were also compared. RESULTS: Post-phenobarbital seizures showed significantly lower amplitude (p<0.001) and involved fewer EEG channels at the peak of seizure (p<0.05). No other features or SDA detection rates showed a statistical difference. CONCLUSION: These findings show that phenobarbital reduces both the amplitude and propagation of seizures which may help to explain electroclinical uncoupling of seizures. The seizure detection rate of the algorithm was unaffected by these changes. SIGNIFICANCE: The results suggest that users should not need to adjust the SDA sensitivity threshold after phenobarbital administration.

Short-Term Effects of Phenobarbitone on Electrographic Seizures in Neonates.

BACKGROUND: Phenobarbitone is the most common first-line anti-seizure drug and is effective in approximately 50% of all neonatal seizures. OBJECTIVE: To describe the response of electrographic seizures to the administration of intravenous phenobarbitone in neonates using seizure burden analysis techniques. METHODS: Multi-channel conventional EEG, reviewed by experts, was used to determine the electrographic seizure burden in hourly epochs. The maximum seizure burden evaluated 1 h before each phenobarbitone dose (T-1) was compared to seizure burden in periods of increasing duration after each phenobarbitone dose had been administered (T+1, T+2 to seizure offset). Differences were analysed using linear mixed models and summarized as means and 95% CI. RESULTS: Nineteen neonates had electrographic seizures and met the inclusion criteria for the study. Thirty-one doses were studied. The maximum seizure burden was significantly reduced 1 h after the administration of phenobarbitone (T+1) [-14.0 min/h (95% CI: -19.6, -8.5); p < 0.001]. The percentage reduction was 74% (IQR: 36-100). This reduction was temporary and not significant within 4 h of administrating phenobarbitone. Subgroup analysis showed that only phenobarbitone doses at 20 mg/kg resulted in a significant reduction in the maximum seizure burden from T-1 to T+1 (p = 0.002). CONCLUSIONS: Phenobarbitone significantly reduced seizures within 1 h of administration as assessed with continuous multi-channel EEG monitoring in neonates. The reduction was not permanent and seizures were likely to return within 4 h of treatment.

Validation of an automated seizure detection algorithm for term neonates.

OBJECTIVE: The objective of this study was to validate the performance of a seizure detection algorithm (SDA) developed by our group, on previously unseen, prolonged, unedited EEG recordings from 70 babies from 2 centres. METHODS: EEGs of 70 babies (35 seizure, 35 non-seizure) were annotated for seizures by experts as the gold standard. The SDA was tested on the EEGs at a range of sensitivity settings. Annotations from the expert and SDA were compared using event and epoch based metrics. The effect of seizure duration on SDA performance was also analysed. RESULTS: Between sensitivity settings of 0.5 and 0.3, the algorithm achieved seizure detection rates of 52.6-75.0%, with false detection (FD) rates of 0.04-0.36FD/h for event based analysis, which was deemed to be acceptable in a clinical environment. Time based comparison of expert and SDA annotations using Cohen's Kappa Index revealed a best performing SDA threshold of 0.4 (Kappa 0.630). The SDA showed improved detection performance with longer seizures. CONCLUSION: The SDA achieved promising performance and warrants further testing in a live clinical evaluation. SIGNIFICANCE: The SDA has the potential to improve seizure detection and provide a robust tool for comparing treatment regimens.

Early postnatal EEG features of perinatal arterial ischaemic stroke with seizures.

BACKGROUND: Stroke is the second most common cause of seizures in term neonates and is associated with abnormal long-term neurodevelopmental outcome in some cases. OBJECTIVE: To aid diagnosis earlier in the postnatal period, our aim was to describe the characteristic EEG patterns in term neonates with perinatal arterial ischaemic stroke (PAIS) seizures. DESIGN: Retrospective observational study. PATIENTS: Neonates >37 weeks born between 2003 and 2011 in two hospitals. METHOD: Continuous multichannel video-EEG was used to analyze the background patterns and characteristics of seizures. Each EEG was assessed for continuity, symmetry, characteristic features and sleep cycling; morphology of electrographic seizures was also examined. Each seizure was categorized as electrographic-only or electroclinical; the percentage of seizure events for each seizure type was also summarized. RESULTS: Nine neonates with PAIS seizures and EEG monitoring were identified. While EEG continuity was present in all cases, the background pattern showed suppression over the infarcted side; this was quite marked (>50% amplitude reduction) when the lesion was large. Characteristic unilateral bursts of theta activity with sharp or spike waves intermixed were seen in all cases. Sleep cycling was generally present but was more disturbed over the infarcted side. Seizures demonstrated a characteristic pattern; focal sharp waves/spike-polyspikes were seen at frequency of 1-2 Hz and phase reversal over the central region was common. Electrographic-only seizure events were more frequent compared to electroclinical seizure events (78 vs 22%). CONCLUSIONS: Focal electrographic and electroclinical seizures with ipsilateral suppression of the background activity and focal sharp waves are strong indicators of PAIS. Approximately 80% of seizure events were the result of clinically unsuspected seizures in neonates with PAIS. Prolonged and continuous multichannel video-EEG monitoring is advocated for adequate seizure surveillance.