Developmental change of amplitude-integrated electroencephalographic activity in preterm infants with intraventricular hemorrhage

Trends in Amplitude-Integrated Electroencephalography in the Smallest Preterm Neonates

BACKGROUND

Amplitude-integrated electroencephalography is increasingly used for the neuromonitoring of premature infants. However, it is still not clear how bioelectrical activity changes in the smallest gestational age newborns. The aim of our study was to evaluate the bioelectrical activity of amplitude-integrated electroencephalograms in premature newborns of different gestational age to assess how gestational age and postnatal age influence patterns of amplitude-integrated electroencephalograms and to test the hypothesis of whether the bioelectrical activity of the brain matures faster after the birth of premature newborns than in utero.

METHODS

We prospectively included infants born before 32 weeks of gestational age between June 2020 and July 2022. Serial recordings of amplitude-integrated electroencephalograms were performed at three time points of age (days 1-3, 13-15, and 27-29). Recordings were analyzed for background patterns, the onset and appearance of cyclicity, and lower amplitude border and bandwidth, which were used to derive a composite Burdjalov score.

RESULTS

In total, 140 premature neonates were included in the study, and 112 of them completed the study. The median gestational age of the newborns enrolled in the study was 29 (27-30) weeks, and the mean weight was 1206 (350) g. Burdjalov scores increased with increasing gestational age. Higher scores were observed in every dimension of the amplitude-integrated electroencephalograms for newborns of lower gestational age when compared to newborns of higher gestational age of the same postmenstrual age. There was a significant correlation between gestational age and parameters of amplitude-integrated electroencephalograms at all time points.

CONCLUSIONS

A higher gestational age has a positive effect on the bioelectrical activity of amplitude-integrated electroencephalograms. Increasing postnatal age affected amplitude-integrated electroencephalograms more than gestational age. Our hypothesis that the bioelectrical activity of the brain matures faster for premature newborns after birth than in the womb was confirmed.

Neuroimaging of structural and functional connectivity in preterm infants with intraventricular hemorrhage

Preterm infants with intraventricular hemorrhage (IVH) are known to have some of the worst neurodevelopmental outcomes in all of neonatal medicine, with a growing body of evidence relating these outcomes to underlying disruptions in brain structure and function. This review begins by summarizing state-of-the-art neuroimaging techniques delineating structural and functional connectivity (diffusion and resting state functional MRI) and their application in infants with IVH, including unique technical challenges and emerging methods. We then review studies of altered structural and functional connectivity, highlighting the role of IVH severity and location. We subsequently detail investigations linking structural and functional findings in infancy to later outcomes in early childhood. We conclude with future directions including methodologic considerations for prospective and potentially interventional studies designed to mitigate disruptions to underlying structural and functional connections and improve neurodevelopmental outcomes in this high-risk population.

A practical approach toward interpretation of amplitude integrated electroencephalography in preterm infants

The developing preterm brain is vulnerable to injury, especially during periods of clinical instability; therefore, monitoring the brain may provide important information on brain health. Over the last 2 decades, a growing body of literature has been reported on preterm amplitude integrated electroencephalography (aEEG) with regards to normative data and associations with adverse outcomes. Despite this, the use of aEEG for preterm infants remains mostly a research tool with limited clinical applicability. In this article, we review the literature on normal and abnormal aEEG patterns in preterm infants and propose a stepwise clinical algorithm for aEEG assessment at the bedside that takes into account assessment of maturation and identification of pathological patterns.

CONCLUSION

This algorithm may be used by clinicians at the bedside for interpretation to integrate it in clinical practice for neurological surveillance of preterm infants.

WHAT IS KNOWN

• Studies have reported normative data on aEEG in preterm infants for different gestational ages. • Burst suppression pattern and absent sleep-wake cycling have been described to be associated with brain pathology and adverse outcomes in preterm infants.

WHAT IS NEW

• We have synthesized aEEG characteristics in preterm infants across the spectrum of prematurity reported in the literature. • We present a stepwise approach for clinically applicable interpretation of aEEG in preterm infants.

Amplitude-integrated electroencephalography signals in preterm infants with cerebral hemorrhage

OBJECTIVE

To evaluate whether preterm infants with cerebral hemorrhage show alterations of aEEG signals in the first four weeks of life.

STUDY DESIGN

Preterm infants (n = 536) born before 32 completed weeks of pregnancy at Innsbruck Medical University Hospital were included in the study. AEEG recordings were evaluated for the Burdjalov score and cerebral hemorrhage was diagnosed by cerebral ultrasound.

RESULTS

Eighty preterm infants with cerebral hemorrhage (median gestational age 28.9 weeks, median birth weight 1157 g) and 456 preterm infants without cerebral hemorrhage (median gestational age 30.0 weeks, median birth weight 1300 g) were investigated. Burdjalov total scores were significantly lower in infants with cerebral hemorrhage. Infants with mild cerebral hemorrhage showed higher Burdjalov total scores compared to infants with severe cerebral hemorrhage in the first days of life. A Burdjalov total score of seven or more was predictive for no development of a cerebral hemorrhage, with a highest area under the curve (0.613) at postnatal day three.

CONCLUSION

Preterm infants with cerebral hemorrhage show alterations in aEEG signals in the newborn period. In future aEEG could be used as a supplemental method to monitor preterm infants at risk for cerebral hemorrhage. The use of aEEG in early life could reduce the number of ultrasound examinations and limit cumulative stress and discomfort in preterm infants.

Early preterm infants with abnormal psychomotor neurodevelopmental outcome at age two show alterations in amplitude-integrated electroencephalography signals

INTRODUCTION

Recent studies showed that neurodevelopment in preterm infants can be predicted by using amplitude-integrated electroencephalography (aEEG)-derived parameters. In our previous study we demonstrated that aEEG could be useful in predicting neurodevelopmental outcome in very preterm infants at the corrected age of 2 years.

AIM

The aim of this study was to further evaluate aEEG for predicting neurodevelopmental outcome at the at the corrected age of 2 years in preterm infants.

METHODS

Between July 2010 and June 2016 440 very preterm infants were eligible for the study at Innsbruck Medical University Hospital. The aEEG was evaluated for the Burdjalov score in 306 preterm infants (mean gestational age 29.5 weeks; range: 24.1-31.9 weeks). At the corrected age of 2 years outcome was assessed by the Bayley Scales of Infant and Toddler Development.

RESULTS

The cohort was divided into three subgroups: 248 infants with normal outcome, 40 infants with delayed outcome and 18 infants with abnormal outcome. Burdjalov scores were lower in infants with delayed outcome than in infants with normal outcome and even lower in infants with abnormal outcome. Post-hoc analysis showed significant differences between normal and delayed psychomotor outcome at 18-24 h (5 (3;6) versus 3 (3;5), p = .024), 30-36 h (6 (4;8) versus 4 (4;6), p = .033), 42-48 h (7 (5;8.5) versus 4 (4;7), p = .003), 54-60 h (7 (6;9) versus 5 (4;7), p = .003), 66-72 h (8 (6;9) versus 6.5 (4.25;7.75), p = .027) and week one (8 (7;10) versus 6.5 (5;8), p = .021). Additionally, when comparing normal to abnormal outcome, a significant difference was found at week four (12 (9;12) versus 8 (7;10), p = .024). The Burdjalov score was only predictive for a delayed psychomotor outcome, presenting the highest area under the curve (0.690) at week two of life.

CONCLUSION

We observed differences in aEEG signals and neurodevelopmental outcome at the corrected age of 2 years, especially for psychomotor outcome. The predictive value of the Burdjalov score regarding neurodevelopmental outcome at the corrected age of 2 years in preterm infants was low.

Quantitative Preterm EEG Analysis: The Need for Caution in Using Modern Data Science Techniques

Hemodynamic changes during neonatal transition increase the vulnerability of the preterm brain to injury. Real-time monitoring of brain function during this period would help identify the immediate impact of these changes on the brain. Neonatal EEG provides detailed real-time information about newborn brain function but can be difficult to interpret for non-experts; preterm neonatal EEG poses even greater challenges. An objective quantitative measure of preterm brain health would be invaluable during neonatal transition to help guide supportive care and ultimately protect the brain. Appropriate quantitative measures of preterm EEG must be calculated and care needs to be taken when applying the many techniques available for this task in the era of modern data science. This review provides valuable information about the factors that influence quantitative EEG analysis and describes the common pitfalls. Careful feature selection is required and attention must be paid to behavioral state given the variations encountered in newborn EEG during different states. Finally, the detrimental influence of artifacts on quantitative EEG analysis is illustrated.

Impact of brain injury on functional measures of amplitude-integrated EEG at term equivalent age in premature infants

OBJECTIVE

To evaluate the association between qualitative and quantitative amplitude-integrated EEG (aEEG) measures at term equivalent age (TEA) and brain injury on magnetic resonance imaging (MRI) in preterm infants.

STUDY DESIGN

A cohort of premature infants born at <30 weeks of gestation and with moderate-to-severe MRI injury on a TEA MRI scan was identified. A contemporaneous group of gestational age-matched control infants also born at <30 weeks of gestation with none/mild injury on MRI was also recruited. Quantitative aEEG measures, including maximum and minimum amplitudes, bandwidth span and spectral edge frequency (SEF₉₀), were calculated using an offline software package. The aEEG recordings were qualitatively scored using the Burdjalov system. MRI scans, performed on the same day as aEEG, occurred at a mean postmenstrual age of 38.0 (range 37 to 42) weeks and were scored for abnormality in a blinded manner using an established MRI scoring system.

RESULTS

Twenty-eight (46.7%) infants had a normal MRI or mild brain abnormality, while 32 (53.3%) infants had moderate-to-severe brain abnormality. Univariate regression analysis demonstrated an association between severity of brain abnormality and quantitative measures of left and right SEF₉₀ and bandwidth span (β=-0.38, -0.40 and 0.30, respectively) and qualitative measures of cyclicity, continuity and total Burdjalov score (β=-0.10, -0.14 and -0.12, respectively). After correcting for confounding variables, the relationship between MRI abnormality score and aEEG measures of SEF₉₀, bandwidth span and Burdjalov score remained significant.

CONCLUSION

Brain abnormalities on MRI at TEA in premature infants are associated with abnormalities on term aEEG measures, suggesting that anatomical brain injury may contribute to delay in functional brain maturation as assessed using aEEG.

[Background patterns and sleep-wake cycles on amplitude-integrated electroencephalography in preterm infants with periventricular-intraventricular hemorrhage]

OBJECTIVE

To study the background patterns and sleep-wake cycles (SWC) on amplitude-integrated electroencephalography (aEEG) in preterm infants with different grades of periventricular-intraventricular hemorrhage (PIVH).

METHODS

Fifty-six preterm infants with a gestational age between 25 and 33 weeks who were diagnosed with PIVH and 31 gestational age-matched normal preterm without ICH were enrolled. According to Papile staging criteria, the infants with PIVH were subdivided into mild group (grades I and II) and moderate-severe group (grades III and IV). The results of the aEEG were compared between groups.

RESULTS

The moderate-severe PIVH group showed a decreased continuity of the voltage, an increased loss rate of SWC, and a lower aEEG score than the mild PIVH and control groups (P<0.017). There were no significant differences in these parameters between the mild PIVH and control groups.

CONCLUSIONS

The changes of background patterns and SWCs may be associated with the severity of PIVH in preterm infants.

Sleep-wake cycle on amplitude-integrated EEG and neuroimage outcomes in newborns

BACKGROUND

The aim of this study was to evaluate the results of sleep-wake cycle monitoring using amplitude-integrated EEG (aEEG) and neuroimaging in newborn infants with a possible perinatal hypoxic insult, investigate the correlation between the findings, and determine the relevance of the findings to reasonably predict neurological outcome.

METHODS

aEEG was recorded among newborn infants suspected of perinatal asphyxia between November, 2014 and June, 2015 in one neonatal intensive care unit facility. Brain imaging with serial ultrasonography and MRI when available were performed, and the infants were divided into two groups according to findings and potential neurological outcome: Group I (favorable findings) and Group II (severe findings such as high grade intraventricular hemorrhage, cerebral infarction or white matter injury). Established sleep-wake cycle times after birth was compared between the two groups.

RESULTS

Among 107 newborn infants, 85 subjects were classified as Group I and the remaining 22 subjects as Group II. The total number of aEEG sessions was 207 and recording time was 2,796 h with a mean of 14.43 ± 13.40 h per study. Estimated times of cyclicity were earlier in Group I (113.34 h, 95 % CI 82.31-144.37) as compared to Group II (504.39 h, 95 % CI 319.91-688.88; p < 0.001).

CONCLUSIONS

Delayed cyclicity on aEEG has a strong correlation with unfavorable brain neuroimages in newborns with possible perinatal asphyxia. If sleep-wake cycles do not appear during initial period after birth, follow-up aEEG studies are recommended.

TRIAL REGISTRATION

Retrospectively registered Registration number: BD 2015-148 Name of registry: amplitude integrated EEG in neonate Date of registration: September 9, 2015.

Guiding Antiepileptic Therapy in a Pediatric Patient with Severe Meningoencephalitis and Decompressive Craniectomy with the Use of Amplitude-Integrated Electroencephalography

Introduction Amplitude-integrated electroencephalography (aEEG) is one of the most widely used neuromonitoring tools in neonatology today. However, little is known about its clinical indications and potential benefits in pediatric intensive care patients. Based on limited experience, its impact on therapeutic decision-making in this patient population is unclear. Case Description We report the case of a 16-year-old boy who, after a pansinusitis, developed a severe meningoencephalitis and intracranial empyema with increased intracranial pressure that required drainage and decompressive craniectomy. He subsequently developed status epilepticus despite a combination of various anticonvulsants. Only after the initialization of an aEEG, we were able to adequately diagnose and continuously monitor his seizure activity and titrate the effect of the antiepileptic drugs. During his hospital stay, we were able to clearly monitor and guide our therapy by accurately identifying the termination of status epilepticus and the recurrence of seizures. Discussion With the help of aEEG, it was easy to identify the nonconvulsive status epilepticus (NCSE) and the ongoing seizure activity in this teenage patient. NCSE is a clinical problem with an effect on the outcome of the patient and is often underdiagnosed. AEEG enabled a rapid detection and management of seizure activity and thereby reduced the overall seizure burden, which was associated with better neurologic outcome.

Early amplitude-integrated electroencephalography predicts brain injury and neurological outcome in very preterm infants

Early amplitude-integrated electroencephalography (aEEG) has been widely used in term infants with brain injury to predict neurodevelopmental outcomes; however, the prognostic value of early aEEG in preterm infants is unclear. We evaluated how well early aEEG could predict brain damage and long-term neurodevelopmental outcomes in very preterm infants compared with brain imaging assessments. We found that severe aEEG abnormalities (p=0.000) and aEEG total score<5 (p=0.006) within 72 h after birth were positively correlated with white-matter damage, but aEEG abnormalities were not associated with intracranial hemorrhage (p=0.186). Severe abnormalities in aEEG recordings, head ultrasound, and cranial magnetic resonance imaging (MRI) were all positively correlated with poor outcome at 18 months corrected age. The predictive power of poor outcomes of the aEEG and MRI combination was the same as the aEEG, MRI, and head ultrasound combination with a sensitivity of 52.4%, specificity of 96.2%, positive predictive value of 78.6%, and negative predictive value of 88.4%. These results indicate that severely abnormal aEEG recordings within 72 h after birth can predict white-matter damage and long-term poor outcomes in very preterm infants. Thus aEEG can be used as an early marker to monitor very preterm infants.

Systems approach to the study of brain damage in the very preterm newborn

Background: A systems approach to the study of brain damage in very preterm newborns has been lacking.

Methods: In this perspective piece, we offer encephalopathy of prematurity as an example of the complexity and interrelatedness of brain-damaging molecular processes that can be initiated inflammatory phenomena.

Results: Using three transcription factors, nuclear factor-kappa B (NF-κB), Notch-1, and nuclear factor erythroid 2 related factor 2 (NRF2), we show the inter-connectedness of signaling pathways activated by some antecedents of encephalopathy of prematurity.

Conclusions: We hope that as biomarkers of exposures and processes leading to brain damage in the most immature newborns become more readily available, those who apply a systems approach to the study of neuroscience can be persuaded to study the pathogenesis of brain disorders in the very preterm newborn.