Assessment of neonatal EEG background and neurodevelopment in full-term small for their gestational age infants

Early cognitive assessment in premature infants: the discriminatory value of eye-tracking vs. Bayley Scales

Introduction

The testing of visuocognitive development in preterm infants shows strong interactions between perinatal characteristics and cognition, learning and overall neurodevelopment evolution. The assessment of anticipatory gaze data of object-location bindings via eye-tracking can predict the neurodevelopment of preterm infants at the age of 3 years; little is known, however, about the early cognitive function and its assessment methods during the first year of life.

Methods

The current study presents data from a novel assessment tool, a Delayed Match Retrieval (DMR) paradigm via eye-tracking was used to measure visual working memory (VWM) and attention skills. The eye-tracking task that was designed to measure infants' ability to actively localize objects and to make online predictions of object-location bindings. 63 infants participated in the study, 39 preterm infants and 24 healthy full term infants - at a corrected age of 8-9 months for premature infants and similar chronological age for full term infants. Infants were also administered the Bayley Scales of Infant and Toddler Development.

Results

The analysis of the Bayley scores showed no significant difference between the two groups while the eye-tracking data showed a significant group effect on all measurements. Moreover, preterm infants' VWM performance was significantly lower than full term's. Birth weight affected the gaze time on all Areas Of Interest (AOIs), overall VWM performance and the scores at the Cognitive Bayley subscale. Furthermore, preterm infants with fetal growth restriction (FGR) showed significant performance effects in the eye-tracking measurements but not on their Bayley scores verifying the high discriminatory value of the eye gaze data.

Conclusion

Visual working memory and attention as measured via eye-tracking is a non-intrusive, painless, short duration procedure (approx. 4-min) was found to be a significant tool for identifying prematurity and FGR effects on the development of cognition during the first year of life. Bayley Scales alone may not pick up these deficits. Identifying tools for early neurodevelopmental assessments and cognitive function is important in order to enable earlier support and intervention in the vulnerable group of premature infants, given the associations between foundational executive functional skills and later cognitive and academic ability.

Quantitative electroencephalogram in term neonates under different sleep states

Electroencephalogram (EEG) can be used to assess depth of consciousness, but interpreting EEG can be challenging, especially in neonates whose EEG undergo rapid changes during the perinatal course. EEG can be processed into quantitative EEG (QEEG), but limited data exist on the range of QEEG for normal term neonates during wakefulness and sleep, baseline information that would be useful to determine changes during sedation or anesthesia. We aimed to determine the range of QEEG in neonates during awake, active sleep and quiet sleep states, and identified the ones best at discriminating between the three states. Normal neonatal EEG from 37 to 46 weeks were analyzed and classified as awake, quiet sleep, or active sleep. After processing and artifact removal, total power, power ratio, coherence, entropy, and spectral edge frequency (SEF) 50 and 90 were calculated. Descriptive statistics were used to summarize the QEEG in each of the three states. Receiver operating characteristic (ROC) curves were used to assess discriminatory ability of QEEG. 30 neonates were analyzed. QEEG were different between awake vs asleep states, but similar between active vs quiet sleep states. Entropy beta, delta2 power %, coherence delta2, and SEF50 were best at discriminating awake vs active sleep. Entropy beta had the highest AUC-ROC ≥ 0.84. Entropy beta, entropy delta1, theta power %, and SEF50 were best at discriminating awake vs quiet sleep. All had AUC-ROC ≥ 0.78. In active sleep vs quiet sleep, theta power % had highest AUC-ROC > 0.69, lower than the other comparisons. We determined the QEEG range in healthy neonates in different states of consciousness. Entropy beta and SEF50 were best at discriminating between awake and sleep states. QEEG were not as good at discriminating between quiet and active sleep. In the future, QEEG with high discriminatory power can be combined to further improve ability to differentiate between states of consciousness.

Critical Windows of Maternal Exposure to Biothermal Stress and Birth Weight for Gestational Age in Western Australia

BACKGROUND

There is limited and inconsistent evidence on the risk of ambient temperature on small for gestational age (SGA) and there are no known related studies for large for gestational age (LGA). In addition, previous studies used temperature rather than a biothermal metric.

OBJECTIVES

Our aim was to examine the associations and critical susceptible windows of maternal exposure to a biothermal metric [Universal Thermal Climate Index (UTCI)] and the hazards of SGA and LGA.

METHODS

We linked 385,337 singleton term births between 1 January 2000 and 31 December 2015 in Western Australia to daily spatiotemporal UTCI. Distributed lag nonlinear models with Cox regression and multiple models were used to investigate maternal exposure to UTCI from 12 weeks preconception to birth and the adjusted hazard ratios (HRs) of SGA and LGA.

RESULTS

Relative to the median exposure, weekly and monthly specific exposures showed potential critical windows of susceptibility for SGA and LGA at extreme exposures, especially during late gestational periods. Monthly exposure showed strong positive associations from the 6th to the 10th gestational months with the highest hazard of 13% for SGA (HR = 1.13 ; 95% CI: 1.10, 1.14) and 7% for LGA (HR = 1.07 ; 95% CI: 1.03, 1.11) at the 10th month for the 1st UTCI centile. Entire pregnancy exposures showed the strongest hazards of 11% for SGA (HR = 1.11 ; 95% CI: 1.04, 1.18) and 3% for LGA (HR = 1.03 ; 95% CI: 0.95, 1.11) at the 99th UTCI centile. By trimesters, the highest hazards were found during the second and first trimesters for SGA and LGA, respectively, at the 99th UTCI centile. Based on estimated interaction effects, male births, mothers who were non-Caucasian, smokers, ≥ 35 years of age, and rural residents were most vulnerable.

CONCLUSIONS

Both weekly and monthly specific extreme biothermal stress exposures showed potential critical susceptible windows of SGA and LGA during late gestational periods with disproportionate sociodemographic vulnerabilities. https://doi.org/10.1289/EHP12660.

Application of bidirectional long short-term memory network for prediction of cognitive age

Electroencephalography (EEG) measures changes in neuronal activity and can reveal significant changes from infancy to adulthood concomitant with brain maturation, making it a potential physiological marker of brain maturation and cognition. To investigate a promising deep learning tool for EEG classification, we applied the bidirectional long short-term memory (BLSTM) algorithm to analyze EEG data from the pediatric EEG laboratory of Taipei Tzu Chi Hospital. The trained BLSTM model was 86% accurate when identifying EEGs from young children (8 months-6 years) and adolescents (12-20 years). However, there was only a modest classification accuracy (69.3%) when categorizing EEG samples into three age groups (8 months-6 years, 6-12 years, and 12-20 years). For EEG samples from patients with intellectual disability, the prediction accuracy of the trained BLSTM model was 46.4%, which was significantly lower than its accuracy for EEGs from neurotypical patients, indicating that the individual's intelligence plays a major role in the age prediction. This study confirmed that scalp EEG can reflect brain maturation and the BLSTM algorithm is a feasible deep learning tool for the identification of cognitive age. The trained model can potentially be applied to clinical services as a supportive measurement of neurodevelopmental status.

A Class-Imbalance Aware and Explainable Spatio-Temporal Graph Attention Network for Neonatal Seizure Detection

Seizures are the most prevalent clinical indication of neurological disorders in neonates. In this study, a class-imbalance aware and explainable deep learning approach based on Convolutional Neural Networks (CNNs) and Graph Attention Networks (GATs) is proposed for the accurate automated detection of neonatal seizures. The proposed model integrates the temporal information of EEG signals with the spatial information on the EEG channels through the graph representation of the multi-channel EEG segments. One-dimensional CNNs are used to automatically develop a feature set that accurately represents the differences between seizure and nonseizure epochs in the time domain. By employing GAT, the attention mechanism is utilized to emphasize the critical channel pairs and information flow among brain regions. GAT coefficients were then used to empirically visualize the important regions during the seizure and nonseizure epochs, which can provide valuable insight into the location of seizures in the neonatal brain. Additionally, to tackle the severe class imbalance in the neonatal seizure dataset using under-sampling and focal loss techniques are used. Overall, the final Spatio-Temporal Graph Attention Network (ST-GAT) outperformed previous benchmarked methods with a mean AUC of 96.6% and Kappa of 0.88, demonstrating its high accuracy and potential for clinical applications.

A comprehensive wireless neurological and cardiopulmonary monitoring platform for pediatrics

Neurodevelopment in the first 10 years of life is a critical time window during which milestones that define an individual's functional potential are achieved. Comprehensive multimodal neurodevelopmental monitoring is particularly crucial for socioeconomically disadvantaged, marginalized, historically underserved and underrepresented communities as well as medically underserved areas. Solutions designed for use outside the traditional clinical environment represent an opportunity for addressing such health inequalities. In this work, we present an experimental platform, ANNE EEG, which adds 16-channel cerebral activity monitoring to the existing, USA FDA-cleared ANNE wireless monitoring platform which provides continuous electrocardiography, respiratory rate, pulse oximetry, motion, and temperature measurements. The system features low-cost consumables, real-time control and streaming with widely available mobile devices, and fully wearable operation to allow a child to remain in their naturalistic environment. This multi-center pilot study successfully collected ANNE EEG recordings from 91 neonatal and pediatric patients at academic quaternary pediatric care centers and in LMIC settings. We demonstrate the practicality and feasibility to conduct electroencephalography studies with high levels of accuracy, validated via both quantitative and qualitative metrics, compared against gold standard systems. An overwhelming majority of parents surveyed during studies indicated not only an overall preference for the wireless system, but also that its use would improve their children's physical and emotional health. Our findings demonstrate the potential for the ANNE system to perform multimodal monitoring to screen for a variety of neurologic diseases that have the potential to negatively impact neurodevelopment.

Abnormal Maternal Body Mass Index and Customized Fetal Weight Charts: Improving the Identification of Small for Gestational Age Fetuses and Newborns

BACKGROUND

Obesity and thinness are serious diseases, but cases with abnormal maternal weight have not been excluded from the calculations in the construction of customized fetal growth curves (CCs).

METHOD

To determine if the new CCs, built excluding mothers with an abnormal weight, are better than standard CCs at identifying SGA. A total of 16,122 neonates were identified as SGA, LGA, or AGA, using the two models. Logistic regression and analysis of covariance were used to calculate the OR and CI for adverse outcomes by group. Gestational age was considered as a covariable.

RESULTS

The SGA rates by the new CCs and by the standard CCs were 11.8% and 9.7%, respectively. The SGA rate only by the new CCs was 18% and the SGA rate only by the standard CCs was 0.01%. Compared to AGA by both models, SGA by the new CCs had increased rates of cesarean section, (OR 1.53 (95% CI 1.19, 1.96)), prematurity (OR 2.84 (95% CI 2.09, 3.85)), NICU admission (OR 5.41 (95% CI 3.47, 8.43), and adverse outcomes (OR 1.76 (95% CI 1.06, 2.60). The strength of these associations decreased with gestational age.

CONCLUSION

The use of the new CCs allowed for a more accurate identification of SGA at risk of adverse perinatal outcomes as compared to the standard CCs.

International Consensus Guideline on Small for Gestational Age (SGA): Etiology and Management from Infancy to Early Adulthood

This International Consensus Guideline was developed by experts in the field of SGA of 10 pediatric endocrine societies worldwide. A consensus meeting was held and 1300 articles formed the basis for discussions. All experts voted about the strengths of the recommendations. The guideline gives new and clinically relevant insights into the etiology of short stature after SGA birth, including novel knowledge about (epi)genetic causes. Besides, it presents long-term consequences of SGA birth and new treatment options, including treatment with gonadotropin-releasing hormone agonist (GnRHa) in addition to growth hormone (GH) treatment, and the metabolic and cardiovascular health of young adults born SGA after cessation of childhood-GH-treatment in comparison with appropriate control groups. To diagnose SGA, accurate anthropometry and use of national growth charts are recommended. Follow-up in early life is warranted and neurodevelopment evaluation in those at risk. Excessive postnatal weight gain should be avoided, as this is associated with an unfavorable cardio-metabolic health profile in adulthood. Children born SGA with persistent short stature < -2.5 SDS at age 2 years or < -2 SDS at age of 3-4 years, should be referred for diagnostic work-up. In case of dysmorphic features, major malformations, microcephaly, developmental delay, intellectual disability and/or signs of skeletal dysplasia, genetic testing should be considered. Treatment with 0.033-0.067 mg GH/kg/day is recommended in case of persistent short stature at age of 3-4 years. Adding GnRHa treatment could be considered when short adult height is expected at pubertal onset. All young adults born SGA require counseling to adopt a healthy lifestyle.

Neonatal quantitative electroencephalography and long-term outcomes: a systematic review

AIM

To evaluate quantitative electroencephalogram (EEG) measures as predictors of long-term neurodevelopmental outcome in infants with a postconceptional age below 46 weeks, including typically developing infants born at term, infants with heterogeneous underlying pathologies, and infants born preterm.

METHOD

A comprehensive search was performed using PubMed, Embase, and Web of Science from study inception up to 8th January 2021. Studies that examined associations between neonatal quantitative EEG measures, based on conventional and amplitude-integrated EEG, and standardized neurodevelopmental outcomes at 2 years of age or older were reviewed. Significant associations between neonatal quantitative EEG and long-term outcome measures were grouped into one or more of the following categories: cognitive outcome; motor outcome; composite scores; and other standardized outcome assessments.

RESULTS

Twenty-four out of 1740 studies were included. Multiple studies showed that conventional EEG-based absolute power in the delta, theta, alpha, and beta frequency bands and conventional and amplitude-integrated EEG-related amplitudes were positively associated with favourable long-term outcome across several domains, including cognition and motor performance. Furthermore, a lower presence of discontinuous background pattern was also associated with favourable outcomes. However, interpretation of the results is limited by heterogeneity in study design and populations.

INTERPRETATION

Neonatal quantitative EEG measures may be used as prognostic biomarkers to identify those infants who will develop long-term difficulties and who might benefit from early interventions.

Electroencephalographic studies in growth-restricted and small-for-gestational-age neonates

Foetal growth restriction (FGR) and being born small for gestational age (SGA) are associated with neurodevelopmental delay. Early diagnosis of neurological damage is difficult in FGR and SGA neonates. Electroencephalography (EEG) has the potential as a tool for the assessment of brain development in FGR/SGA neonates. In this review, we analyse the evidence base on the use of EEG for the assessment of neonates with FGR or SGA. We found consistent findings that FGR/SGA is associated with measurable changes in the EEG that present immediately after birth and persist into childhood. Early manifestations of FGR/SGA in the EEG include changes in spectral power, symmetry/synchrony, sleep-wake cycling, and the continuity of EEG amplitude. Later manifestations of FGR/SGA into infancy and early childhood include changes in spectral power, sleep architecture, and EEG amplitude. FGR/SGA infants had poorer neurodevelopmental outcomes than appropriate for gestational age controls. The EEG has the potential to identify FGR/SGA infants and assess the functional correlates of neurological damage. IMPACT: FGR/SGA neonates have significantly different EEG activity compared to AGA neonates. EEG differences persist into childhood and are associated with adverse neurodevelopmental outcomes. EEG has the potential for early identification of brain impairment in FGR/SGA neonates.

Evidence of changes in the oral language in children born full-term and small for gestational age: a systematic review

Abstract Objective: To perform a systematic review in order to verify the association between full-term birth of small for gestational age (SGA) children and the outcomes in the development of oral language. Data source: Articles from MEDLINE/PubMed, Web of Science, Embase, Lilacs, SciELO and Cochrane Library databases were identified, selected and critically evaluated by two independent reviewers and a judge, blindly, without language restriction and publication period. The PRISMA tool was used, and original studies with a theme involving children born full-term and SGA were included, outcome related to aspects of oral language development, as well as the use of tests, scales and/or specific questionnaires for the investigation, whose methodology was described in full, with children as the target population. Data synthesis: The researchers included nine articles based on the eligibility criteria. Studies have shown that being born SGA can interfere in aspects related to language and reported greater chances of under performance in SGA children when compared to children with appropriate size for gestational age. It was observed that the different studies did not have a uniform design, and the objectives were quite diverse. Furthermore, few of them had as focus issues related to the assessment of language, as well as the variability of instruments used to investigate this domain. Conclusions: The effects of low weight for gestation age in full-term infants continue beyond the neonatal period and may impact on children’s performance, mainly with regard to oral language development.

Evidências de alterações na linguagem oral de crianças nascidas a termo pequenas para a idade gestacional: uma revisão sistemática

Resumo Objetivo: Realizar uma revisão sistemática para verificar a associação entre o nascimento a termo de crianças pequenas para a idade gestacional (PIG) e os desfechos no desenvolvimento da linguagem oral. Fontes de dados: Artigos dos bancos de dados MEDLINE/PubMed, Web of Science, Embase, LILACS, SciELO e Cochrane Library foram identificados, selecionados e avaliados criticamente por dois revisores independentes e um juiz, às cegas, sem restrições de idioma e período de publicação. A ferramenta PRISMA foi utilizada e foram incluídos estudos originais envolvendo crianças nascidas a termo e PIG, desfechos relacionados a aspectos do desenvolvimento da linguagem oral, bem como o uso de testes, escalas e/ou questionários específicos para a investigação, cuja metodologia estava descrita na íntegra, com crianças como população-alvo. Síntese dos dados: Nove artigos foram incluídos a partir dos critérios de elegibilidade. Os estudos demonstraram que nascer PIG pode interferir em aspectos relacionados à linguagem e relataram que as chances de crianças PIG apresentarem um desempenho inferior são maiores quando comparadas as com tamanho adequado para a idade gestacional. Observou-se que os diferentes estudos não tinham um delineamento uniforme e seus objetivos eram bastante diversificados. Além disso, poucos focavam em questões relacionadas à avaliação da linguagem e foi possível notar uma variabilidade de instrumentos utilizados para investigar esse domínio. Conclusões: Os efeitos do baixo peso ao nascer em nascidos a termo persistem além do período neonatal e podem ter impacto no desempenho infantil, principalmente no que se refere ao desenvolvimento da linguagem oral.

Weekly-specific ambient fine particular matter exposures before and during pregnancy were associated with risks of small for gestational age and large for gestational age: results from Project ELEFANT

BACKGROUND

Investigations on the potential effects of ambient fine particulate matter (PM2.5) on large for gestational age (LGA) are limited. Furthermore, no study has explored weekly-specific susceptible exposure windows for small for gestational age (SGA) and LGA. This study evaluated the associations of exposure to ambient PM2.5 over the preconception and entire-pregnancy periods with risks of SGA and LGA, as well as explored critical weekly-specific exposure windows.

METHODS

10 916 singleton pregnant women with 24-42 completed gestational weeks from the Project Environmental and LifEstyle FActors iN metabolic health throughout life-course Trajectories between 2014 and 2016 were included in this study. Distributed lag models (DLMs) incorporated in Cox proportional-hazards models were applied to explore the associations of maternal exposure to weekly ambient PM2.5 throughout 12 weeks before pregnancy and pregnancy periods with risks of SGA and LGA after controlling for potential confounders.

RESULTS

For a 10-μg/m3 increase in maternal exposure to PM2.5, positive associations with SGA were observed during the 1st to 9th preconceptional weeks and the 1st to 2nd gestational weeks (P<0.05), with the strongest association in the 5th preconceptional week [hazard ratio (HR), 1.06; 95% confidential interval (CI), 1.03-1.09]. For LGA, positive associations were observed during the 1st to 12th preconceptional weeks and the 1st to 5th gestational weeks (P<0.05), with the strongest association in the 7th preconceptional week (HR, 1.10; 95% CI, 1.08-1.12).

CONCLUSIONS

Exposure to high-level ambient PM2.5 is associated with increased risks of both SGA and LGA, and the most susceptible exposure windows are the preconception and early-pregnancy periods.

Term Birth Weight and Neurodevelopmental Outcomes

BACKGROUND

Preterm birth is an important risk factor for neurodevelopmental disabilities. The vast majority of these disabilities occur, however, among term births. The role of fetal growth restriction specifically among term babies has been incompletely described.

METHODS

We conducted a population-based study of term birth weight and its link to a range of neurodevelopmental outcomes using Norwegian health registries. To remove the influence of preterm birth, we restricted our analyses to 1.8 million singleton babies born during a narrow range of term gestational age (39-41 weeks). Babies with malformations were excluded. We adjusted analyses simply for year of birth, as further adjustments for sex, parity, maternal age, smoking, marital status, immigrant status, and parental education had trivial influence. An additional sibling analysis controlled for unmeasured family-based confounding.

RESULTS

The risk of neurodevelopmental disabilities at term steadily increased at birth weights lower than 3.5 kg. Using the category of 3.5-3.9 kg as the reference, the odds reached 25-fold for cerebral palsy at the smallest weights (95% confidence interval 8.0, 79), 16-fold for vision/hearing disability (4.0, 65), 11-fold for intellectual impairment (6.9, 17), 7-fold for schizophrenia (1.0, 50), 5.4-fold for epilepsy (2.6, 12), and 3.5-fold for autism spectrum (1.3, 9.4) and behavioral disorders including attention-deficit hyperactivity disorder (2.1, 5.4). Associations remained robust with sibling controls.

CONCLUSIONS

Reduced fetal growth is a powerful predictor of a wide variety of neurodevelopmental disabilities independent of preterm delivery.

Cerebral cortical autonomic connectivity in low-risk term newborns

PURPOSE

The mature central autonomic network includes connectivity between autonomic nervous system brainstem centers and the cerebral cortex. The study objective was to evaluate the regional connectivity between the cerebral cortex and brainstem autonomic centers in term newborns by measuring coherence between high-density electroencephalography and heart rate variability as measured by electrocardiography.

METHODS

Low-risk term newborns with birth gestational age of 39-40 weeks were prospectively enrolled and studied using time-synced electroencephalography and electrocardiography for up to 60 min before discharge from the birth hospital. The ccortical autonomicc nervous system association was analyzed using coherence between electroencephalography-delta power and heart rate variability. Heart rate variability measured the parasympathetic tone (root mean square of successive differences of heart rate) and sympathetic tone (standard deviation of heart rate).

RESULTS

One hundred and twenty-nine low-risk term infants were included. High coherence delta-root mean square of successive differences was found in central, bitemporal, and occipital brain regions, with less robust coherence delta-standard deviation in the central region and bitemporal areas.

CONCLUSIONS

Our findings describe a topography of ccortical autonomicc connectivity present at term in low-risk newborns, which was more robust to parasympathetic than sympathetic brainstem centers and was independent of newborn state.

Early Diagnosis of Brain Injury in Premature Infants Based on Amplitude-Integrated EEG Scoring System

Analyzing and discussing the relationship between brain injury in preterm infants and related risk factors can provide evidence for perinatal prevention and early intervention of brain injury in preterm infants, thereby improving the quality of life of preterm infants. This paper selects term preterm infants diagnosed with preterm infant asphyxia in the NICU of a university's First Affiliated Hospital from January 2018 to February 2019 as the research object. In addition, healthy term infants born at the same time in the obstetric department of this hospital are selected as the control group. Both groups of premature infants were monitored for brain function within 6 hours after birth. The aEEG results range from background activity (continuous normal voltage, discontinuous normal voltage, burst suppression, continuous low voltage, and plateau) and sleep-wake cycle (no sleep-wake cycle, immature, and mature sleep-wake cycle) to epileptic activity (single seizures, recurrent seizures, and status epilepticus), three aspects to judge. Statistical analysis uses SPSS 17.0 software. Amplitude-integrated EEG is a simplified form of continuous EEG recording. The trace of the trace represents the voltage change signal of the entire EEG background activity, which can reflect the EEG amplitude, frequency, burst-inhibition, and other pieces of information. aEEG can reflect the degree of HIE lesions in premature infants and the long-term prognosis. It is easy to operate and effective in diagnosis and can be continuously monitored. It is worthy of clinical popularization. There is a good correlation between the expression of EEG and biomarkers. Combining multiple methods can diagnose HIE earlier and evaluate the prognosis.