Negative central activity in extremely preterm newborns: EEG characterization and relationship with brain injuries and neurodevelopmental outcome.

OBJECTIVE: To characterize Negative Central Activity (NCA), an overlooked electroencephalographic activity of preterm newborns and investigate its relationship with brain injuries, dysfunction, and neurodevelopmental outcome. METHODS: 109 preterm infants (23-28 weeks) were retrospectively included. NCA were selected at the negative peak on EEG. Individual averaged NCA were automatically characterized. Brain structural data were collected from cranial ultrasounds (cUS). The neurodevelopmental outcome at two years of age was assessed by the Denver Developmental Screening Test-II. RESULTS: Thirty-six (33%) children showed NCA: 6,721 NCA were selected, a median of 75 (interquartile range, 25/157.3) per EEG. NCA showed a triphasic morphology, with a mean amplitude and duration of the negative component of 24.6-40.0 µV and 222.7-257.3 ms. The presence of NCA on EEG was associated with higher intraventricular haemorrhage (IVH) grade on the first (P = 0.016) and worst neonatal cUS (P < 0.001) and poorer neurodevelopmental outcome (P < 0.001). CONCLUSIONS: NCA is an abnormal EEG feature of extremely preterm newborns that may correspond to the functional neural impact of a vascular pathology. SIGNIFICANCE: The NCA relationships with an adverse outcome and the presence/severity of IVH argue for considering NCA in the assessment of pathological processes in the developing brain network and for early outcome prediction.

Predicting the Neurodevelopmental Outcome in Extremely Preterm Newborns Using a Multimodal Prognostic Model Including Brain Function Information.

Importance: Early assessment of the prognosis of preterm newborns is crucial for accurately informing parents and making treatment decisions. The currently available prognostic models rarely incorporate functional brain information from conventional electroencephalography (cEEG). Objective: To examine the performance of a multimodal model combining (1) brain function information with (2) brain structure information (cranial ultrasonography), and (3) perinatal and (4) postnatal risk factors for the prediction of death or neurodevelopmental impairment (NDI) in extremely preterm infants. Design, Setting, and Participants: Preterm newborns (23-28 weeks' gestational age) admitted to the neonatal intensive care unit at Amiens-Picardie University Hospital were retrospectively included (January 1, 2013, to January 1, 2018). Risk factors from the 4 categories were collected during the first 2 weeks post delivery. Neurodevelopmental impairment was assessed at age 2 years with the Denver Developmental Screening Test II. No or moderate NDI was considered a favorable outcome. Death or severe NDI was considered an adverse outcome. Data analysis was performed from August 26, 2021, to March 31, 2022. Main Outcomes and Measures: After the selection of variables significantly associated with outcome, 4 unimodal prognostic models (considering each category of variable independently) and 1 multimodal model (considering all variables simultaneously) were developed. After a multivariate analysis for models built with several variables, decision-tree algorithms were run on each model. The areas under the curve for decision-tree classifications of adverse vs favorable outcomes were determined for each model, compared using bootstrap tests, and corrected for type I errors. Results: A total of 109 newborns (58 [53.2% male]) born at a mean (SD) gestational age of 26.3 (1.1) weeks were included. Among them, 52 (47.7%) had a favorable outcome at age 2 years. The multimodal model area under the curve (91.7%; 95% CI, 86.4%-97.0%) was significantly higher than those of the unimodal models (P < .003): perinatal model (80.6%; 95% CI, 72.5%-88.7%), postnatal model (81.0%; 95% CI, 72.6%-89.4%), brain structure model (cranial ultrasonography) (76.6%; 95% CI, 67.8%-85.3%), and brain function model (cEEG) (78.8%; 95% CI, 69.9%-87.7%). Conclusions and Relevance: In this prognostic study of preterm newborns, the inclusion of brain information in a multimodal model was associated with significant improvement in the outcome prediction, which may have resulted from the complementarity of the risk factors and reflected the complexity of the mechanisms that interfered with brain maturation and led to death or NDI.

The prognostic value of neonatal conventional-EEG monitoring in hypoxic-ischemic encephalopathy during therapeutic hypothermia.

AIM: To determine the prognostic value of conventional electroencephalography (EEG) monitoring in neonatal hypoxic-ischemic encephalopathy (HIE). METHOD: In this multicentre retrospective study, 95 full-term neonates (mean of 39.3wks gestational age [SD  1.4], 36 [38%] females, 59 [62%] males) with HIE (2013-2016) undergoing therapeutic hypothermia were divided between favourable or adverse outcomes. Background EEG activity (French classification scale: 0-1-2-3-4-5) and epileptic seizure burden (epileptic seizure scale: 0-1-2) were graded for seven 6-hour periods. Conventional EEG monitoring was investigated by principal component analysis (PCA), with clustering methods to extract prognostic biomarkers of development at 2 years and infant death. RESULTS: Eighty-one per cent of infants with an adverse outcome had a French classification scale equal to or greater than 3 after H48 (100% at H6-12). The H6-12 epileptic seizure scale was equal to or greater than 1 for 39%, increased to 52% at H30-36 and then remained equal to or greater than 1 for 39% after H48. Forty-five per cent of infants with a favourable outcome had a H6-12 French classification scale equal to or greater than 3, which dropped to 5% after H48; 13% had a H6-12 epileptic seizure scale equal to or greater than 1 but no seizures after H48. Clustering methods based on PCA showed the high efficiency (96%) of conventional EEG monitoring for outcome prediction and allowed the definition of three prognostic EEG biomarkers: H6-78 French classification scale mean, H6-78 French classification scale slope, and H30-78 epileptic seizure scale mean. INTERPRETATION: Early lability and recovery of physiological features is prognostic of a favourable outcome. Seizure onset from the second day should also be considered to accurately predict neurodevelopment in HIE and support the importance of conventional EEG monitoring in HIE in infants cooled with therapeutic hypothermia. WHAT THIS PAPER ADDS: Comprehensive analysis showed the high prognostic efficiency (96%) of conventional electroencephalography (EEG) monitoring. Prognostic EEG biomarkers consist of the grade of background EEG activity, its evolution, and the mean seizure burden. Persistent seizures (H48) without an improvement in background EEG activity were consistently associated with an adverse outcome.