The suppression curve as a quantitative approach for measuring brain maturation in preterm infants

Dereymaeker, A; Koolen, Ninah; Jansen, Katrien; Vervisch, Jan; Ortibus, Els; Vos, Maarten De; Huffel, Sabine Van; Naulaers, Gunnar

doi:10.1016/j.clinph.2016.05.362

Cited by 17 publications

(19 citation statements)

References 45 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Firstly, the discontinuity pattern of neonatal EEG changes with age. Especially, the oldest neonates (moderate to late preterm) are characterized by a much more continuous EEG pattern (tracé continue) compared to the younger neonates (extremely to very preterm; tracé discontinue) [30]. A more continuous EEG can result in a more pronounced increase in IBI duration after propofol, potentially explaining the more pronounced loss in signal interaction observed among the oldest neonates in the group of study.…”

Section: Mabp-eeg Pairwisementioning

confidence: 90%

See 1 more Smart Citation

Using Graph Theory to Assess the Interaction between Cerebral Function, Brain Hemodynamics, and Systemic Variables in Premature Infants

et al. 2018

View full text Add to dashboard Cite

Graphs can be used to describe a great variety of real-world situations and have therefore been used extensively in different fields. In the present analysis, we use graphs to study the interaction between cerebral function, brain hemodynamics, and systemic variables in premature neonates. We used data from a propofol dose-finding and pharmacodynamics study as a model in order to evaluate the performance of the graph measures to monitor signal interactions. Concomitant measurements of heart rate, mean arterial blood pressure, arterial oxygen saturation, regional cerebral oxygen saturation-measured by means of near-infrared spectroscopy-and electroencephalography were performed in 22 neonates undergoing INSURE (intubation, surfactant administration, and extubation). The graphs used to study the interaction between these signal modalities were constructed using the RBF kernel. Results indicate that propofol induces a decrease in the signal interaction up to 90 minutes after propofol administration, which is consistent with clinical observations published previously. The clinical recovery phase is mainly determined by the EEG dynamics, which were observed to recover much slower compared to the other modalities. In addition, we found a more pronounced loss in cerebral-systemic interactions with increasing propofol dose.

show abstract

Section: Mabp-eeg Pairwisementioning

confidence: 90%

“…However, this discontinuous pattern evolves towards a more continuous trace with increasing PMA. Therefore, some studies have investigated the use of the length of the IBIs as a marker for maturation [29,30].…”

Section: Methodsmentioning

confidence: 99%

Using Graph Theory to Assess the Interaction between Cerebral Function, Brain Hemodynamics, and Systemic Variables in Premature Infants

et al. 2018

View full text Add to dashboard Cite

show abstract

“…4a) and decrease in IBI during QS is seen from 34 weeks (Fig. 4b) [4]. QS periods are defined as still discontinuous or semi-continuous in infants of 35–36 weeks GA and can be differentiated of AS with continuous tracing, episodes of REM and specific age-related transients.…”

Section: Development Of Neonatal Sleepmentioning

confidence: 99%

“…Serial electro-encephalography (EEG) monitoring over time can document actual normal or altered brain function and provides insight into the progress of brain maturation during this period of intensive neonatal care [1,4,5], with the ultimate goal to improve therapeutic interventions and long-term neurodevelopmental outcome.…”

Section: Introductionmentioning

confidence: 99%

Review of sleep-EEG in preterm and term neonates

Dereymaeker

Pillay

Vervisch

et al. 2017

Early Human Development

109

117

View full text Add to dashboard Cite

Neonatal sleep is a crucial state that involves endogenous driven brain activity, important for neuronal survival and guidance of brain networks. Sequential EEG-sleep analysis in preterm infants provides insights into functional brain integrity and can document deviations of the biologically pre-programmed process of sleep ontogenesis during the neonatal period. Visual assessment of neonatal sleep-EEG, with integration of both cerebral and non-cerebral measures to better define neonatal state, is still considered the gold standard. Electrographic patterns evolve over time and are gradually time locked with behavioural characteristics which allow classification of quiet sleep and active sleep periods during the last 10weeks of gestation. Near term age, the neonate expresses a short ultradian sleep cycle, with two distinct active and quiet sleep, as well as brief periods of transitional or indeterminate sleep. Qualitative assessment of neonatal sleep is however challenged by biological and environmental variables that influence the expression of EEG-sleep patterns and sleep organization. Developing normative EEG-sleep data with the aid of automated analytic methods, can further improve our understanding of extra-uterine brain development and state organization under stressful or pathological conditions. Based on those developmental biomarkers of normal and abnormal brain function, research can be conducted to support and optimise sleep in the NICU, with the ultimate goal to improve therapeutic interventions and neurodevelopmental outcome.

show abstract

“…Like burst dynamics, Dereymaeker et al proposed 'suppression curve', a measure of discontinuity of preterm EEG [216]. However, in the case of term infants, not only burst-suppression patterns but other abnormal patterns exist.…”

Section: What Is the Contribution Of This Study?mentioning

confidence: 99%

Design and optimisation of time-frequency analysis for multichannel neonatal EEG background features in term neonates with hypoxic ischaemic encephalopathy: characterisation, classification and neurodevelopmental outcome prediction

Awal¹

View full text Add to dashboard Cite

Neonatal Hypoxic Ischaemic Encephalopathy (HIE) is a major cause of morbidity and mortality in newborns throughout the world with an incidence of 1-8/1000 newborns in developed countries and up to 26/1000 newborns in developing countries. It causes one million neonatal deaths globally per year. Electroencephalography (EEG) is a useful method for assessment of brain activity in newborns with HIE. EEG performs well in the early diagnosis and classification of HIE severity and in predicting neurodevelopmental outcome. A normal EEG is highly predictive of a normal outcome and various abnormal EEG features are associated with neurological abnormalities or death.A systematic review and meta-analysis of the literature was undertaken to determine which specific background features of the EEG best predict outcome (Aim 1). Automatic detection and classification

show abstract

The suppression curve as a quantitative approach for measuring brain maturation in preterm infants

Abstract: The suppression curve facilitates automated assessment of EEG maturation. Clinical applicability is straight forward since values for IBIs according to PMA are generated automatically.

Cited by 17 publications

References 45 publications

Using Graph Theory to Assess the Interaction between Cerebral Function, Brain Hemodynamics, and Systemic Variables in Premature Infants

Using Graph Theory to Assess the Interaction between Cerebral Function, Brain Hemodynamics, and Systemic Variables in Premature Infants

Review of sleep-EEG in preterm and term neonates

Design and optimisation of time-frequency analysis for multichannel neonatal EEG background features in term neonates with hypoxic ischaemic encephalopathy: characterisation, classification and neurodevelopmental outcome prediction

Contact Info

Product

Resources

About