The amplitude-integrated EEG (aEEG)in the early prediction of outcome in the very preterm newborn

Amplitude-integrated electroencephalogram (aEEG) is a readily available and practical tool for the assessment of time-compressed electroencephalogram (EEG) trend at the bedside. Its interpretation and its learnability are considerably easier compared to those of conventional EEG. For those reasons, aEEG is now a daily part of clinical surveillance for continuous brain function monitoring of critically ill patients in some neonatal intensive care units (NICU). Another reason for the growing interest in this tool for electrophysiological measures is explained by the fact that continuous brain function monitoring early after birth may represent the possibility to early assess the neurological integrity of the newborn and thus, to early select patient needing neuroprotective intervention and to predict outcome. This has been largely demonstrated for the asphyxiated full-term, but not in similar extent for the preterm newborn, whose aEEG background pattern differs sensibly from that of the full-term newborn. Early detection of newborns at particular risk for cerebral injury and further neurodevelopmental disability (ND) still represents one of the major challenges of preterm medical care. At bedside, the aEEG assessment focuses theoretically on the amplitude variations of the raw EEG, and practically on the recognition of the dominant background pattern of activity, the presence and maturational aspect of cycling activity and the presence of seizure activity. Pathological changes in the aEGG tracing are characterized by a depression of the background pattern, a lack or an inadequate maturation of the cycling activity, and the occurrence of seizures. Today, clinicians increasingly use aEEG also in preterms, an ever-growing NICU patient population at high risk for cerebral injury and thus ND. Recent studies showed that changes in the aEEG pattern are associated with poor outcome in the preterm newborns. However, it still remains to be elucidated how and under which conditions aEEG tracing evolves during the very early life period in this patient population, especially in unstable health condition. Although the subject of the present work is the aEEG, this thesis firstly discusses recent data on the outcome of preterm infants born in Switzerland, in order to bring this population of patients into the reader’s focus and to define the consequences of prematurity. Thanks to a solid collaboration between perinatal and follow up centres and an established follow up program in Switzerland we are now able to better analyse representative data concerning the development of preterm newborns on a national level. Swiss outcome data of 2 years old former extremely preterms show that, although more than a third of infants still suffer from moderate or severe ND, the rate of survival without major neurologic sequelae has increased significantly over the last decade, while the mortality rate decreased. Interestingly, while neonatal mortality is predominantly dependent on gestational age, birth weight and antenatal corticosteroids, the outcome at two years of age in children surviving the neonatal period is best predicted by neonatal morbidities like, among others, major brain lesions. There is concern whether prematurity and ND affect late outcome. We provided data on quality of life of former extremely low birth weight preterms at young adulthood born in Switzerland in the early 1980s, showing overall satisfactory results though some observable differences between preterms and community norms. This thesis delineates and discusses the application, the clinical utility of the aEEG as well as its predictive value in terms of short- and long-term outcome of preterm newborns. First, technical aspects concerning the methodology and the assessment of the aEEG tracing are explained, with special focus on the potential aEEG signal confounders that interfere with a correct tracing evaluation. We added information in particular on the influence of sedatives on the course of the aEEG tracing in newborns. Second, the prediction of neonatal and further outcome of the preterm newborn is detailed discussed. Early recognition of preterm patients at higher risk for adverse outcome is important in order to better setup neonatal care and post-discharge intervention. Neuroprotective studies in preterm infants are being conducted to improve long-term outcome and robust biomarkers would help to guide such interventional strategies and to help parental counselling. This thesis demonstrates that changes in the aEEG background activity can predict short-term outcome in preterm infants. The maturational aspect of the early aEEG background tracing in preterm infants relates to structural brain maturation at term equivalent age as assessed qualitatively by magnetic resonance imaging. A delay in the maturation of cyclic aEEG activity in the preterm newborn may be a sign of the development of a major brain lesion. A review of the results of other studies on the predictive value of aEEG for outcome at early childhood is finally included. In conclusion the results of this thesis indicate that aEEG is a valuable neurophysiologic diagnostic tool for early continuous bedside monitoring of brain function and that its background activity can predict short-term outcome in preterm infants. The assessment of the tracing evolution and the detection of sensitive markers of brain lesion during aEEG monitoring could prove critical for implication of therapeutic assistance. Several clinical conditions and artefactual features may however, alter the aEEG tracing and interfere with its interpretation and consequently the prognostic evaluation. Training in the aEEG assessment and knowledge of the potential aEEG signal confounders is therefore needed in order to better further implement this promising neuromonitoring tool in the NICU.