Visual and Quantitative Electroencephalographic Analysis in Healthy Term Neonates Within the First Six Hours and the Third Day of Life

Conde, José Ramón Castro; Barrios, Desiré González; Campo, Candelaria González; González, Nieves Luisa González; Millán, Beatriz Reyes; Sosa, Alejandro Jiménez

doi:10.1016/j.pediatrneurol.2017.04.024

Cited by 10 publications

(16 citation statements)

References 40 publications

(50 reference statements)

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“…Some aEEG studies conducted in neonates with IUGR have been associated with brain function immaturity. 7,8,29 Our results provide new data, until now unreported, that contribute to a better knowledge on brain function maturation in these children. The analysis of the well-recognized EEG patterns of maturity in the clinical setting such as discontinuity, delta brushes, IBI duration, asymmetry, asynchrony or transients may have clinical relevance on the evaluation of SGA neonates.…”

Section: Visual Analysissupporting

confidence: 52%

“…The definitions of these variables were strictly adjusted to those used previously to analyze the EEG in healthy term neonates: 8 Interburst intervals of inactivity or hypoactivity (IBI). Epochs with an EEG activity <30 µV on all channels for >1 s.…”

Section: Visual Analysismentioning

confidence: 99%

“…The software settings complied with previous studies. 8,21 Spectral analysis included relative power spectrum in the frequency bands: δ (0.5-4 Hz); θ (4-8 Hz); α (8-13 Hz); and β (13-30 Hz). Relative power spectrum was defined as the absolute power spectrum for each frequency band divided by the sum of absolute power spectrum of all frequencies, expressed as a percentage.…”

Section: Spectral Analysismentioning

confidence: 99%

“…When the sleep state has been defined by EEG and other polygraph channels, previous studies in term infants have found proportions of QS significantly reduced and increased in IS with great difficulty in exactly distinguishing sleep states in the first hours of life. 8,19,27 For this, in the present work, for spectral analysis we selected EEG segments with discontinuous and/or alternating tracings regardless of behavioral state. Given the existence of asymmetry, asynchrony and transients, long epochsanalysis that included all bursts during a stable period of sleep would allow to obtain spectral values more objective than those obtained from short periods of tracing EEG arbitrarily selected.…”

Section: Spectral Analysismentioning

confidence: 99%

“…6 These maturational EEG changes continue in the postnatal life and are especially pronounced in the first 3 days of life as a result of adaptation to postnatal life. 7,8 The most recent studies in the development of brain activity have relied on quantitative analyses of EEG activity. [9][10][11] Spectral EEG analysis and neonatal aEEG findings have found delayed maturation and less optimal scores on early EEG in preterm 12,13 and full-term SGA neonates.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2019

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BACKGROUND: Delayed brain function development in small-gestational-age (SGA) infants has been reported. We aimed to quantify rates of immature neonatal EEG patterns and their association with neurodevelopment in SGA full-term neonates. METHODS: Using a cohort design, 50 SGA (birthweight <10th percentile) and 44 appropriate-gestational-age (AGA) term neonates underwent continuous video-EEG recordings lasting >3 h. Seventy-three of them were assessed at 2-years-old using Bayley-III-Scales. For EEG analysis, several segments of discontinuous/alternating EEG tracings were selected. Main outcomes measured: (1) Visual analysis (patterns of EEG maturity); (2) Power spectrum in δ, θ, α and β frequency bands; and (3) scores in motor, cognitive and language development. RESULTS: (1) SGA infants, compared to AGA, showed: (a) higher percentages of discontinuous EEG, both asynchrony and interhemispheric asymmetry, and bursts with delta-brushes, longer interburst-interval duration and more transients/hour; (b) lower relative power spectrum in δ and higher in α; and (c) lower scores on motor, language and cognitive neurodevelopment. (2) Asymmetry >5%, interburst-interval >5 s, discontinuity >11%, and bursts with delta-brushes >11% were associated with lower scores on Bayley-III. CONCLUSIONS: In this prospective study, SGA full-term neonates showed high rates of immature EEG patterns. Low-birthweight and immaturity EEG were both correlated with low development scores.

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Section: Visual Analysissupporting

confidence: 52%

Section: Visual Analysismentioning

confidence: 99%

Section: Spectral Analysismentioning

confidence: 99%

Section: Spectral Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

et al. 2019

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Quantitative electroencephalogram in term neonates under different sleep states

Yuan,

Georgostathi,

Zhang

et al. 2023

J Clin Monit Comput

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Electroencephalogram (EEG) can be used to assess anesthetic depth, 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 needed to determine changes in anesthetic depth during neonatal anesthesia. We aimed to determine the range of QEEG in neonates during awake, active sleep and quiet sleep states, and identi ed the ones best at discriminating between the three states. MethodsNormal neonatal EEG from 37-46 weeks were analyzed and classi ed as awake, quiet sleep, or active sleep.After processing and artefact removal, total power, power ratio, coherence, and 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.Results 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 AUC-ROC > 0.69, lower than the other comparisons. ConclusionWe 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 combinations to further improve ability to differentiate between states of consciousness.

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Relationship between EEG spectral power and dysglycemia with neurodevelopmental outcomes after neonatal encephalopathy

Damien,

Vannasing,

Tremblay

et al. 2024

Clinical Neurophysiology

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Visual and Quantitative Electroencephalographic Analysis in Healthy Term Neonates Within the First Six Hours and the Third Day of Life

Cited by 10 publications

References 40 publications

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

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

Quantitative electroencephalogram in term neonates under different sleep states

Relationship between EEG spectral power and dysglycemia with neurodevelopmental outcomes after neonatal encephalopathy

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