Neonatal Brain Research Group - Journal Articles

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    Non-invasive cardiac output monitoring in neonates
    (Frontiers Media S.A., 2021-01) O'Neill, Roisin; Dempsey, Eugene M.; Garvey, Aisling A.; Schwarz, Christoph E.; Deutsche Forschungsgemeinschaft; National Children's Research Centre
    Circulatory monitoring is currently limited to heart rate and blood pressure assessment in the majority of neonatal units globally. Non-invasive cardiac output monitoring (NiCO) in term and preterm neonates is increasing, where it has the potential to enhance our understanding and management of overall circulatory status. In this narrative review, we summarized 33 studies including almost 2,000 term and preterm neonates. The majority of studies evaluated interchangeability with echocardiography. Studies were performed in various clinical settings including the delivery room, patent ductus arteriosus assessment, patient positioning, red blood cell transfusion, and therapeutic hypothermia for hypoxic ischemic encephalopathy. This review presents an overview of NiCO in neonatal care, focusing on technical and practical aspects as well as current available evidence. We discuss potential goals for future research.
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    A machine-learning algorithm for neonatal seizure recognition: a multicentre, randomised, controlled trial
    (Elsevier, 2020-10) Pavel, Andreea; Rennie, Janet M.; de Vries, Linda S.; Blennow, Mats; Foran, Adrienne; Shah, Divyen K.; Pressler, Ronit; Kapellou, Olga; Dempsey, Eugene M.; Mathieson, Sean R.; Pavlidis, Elena; van Huffelen, Alexander C.; Livingstone, Vicki; Toet, Mona C.; Weeke, Lauren C.; Finder, Mikael; Mitra, Subhabrata; Murray, Deirdre M.; Marnane, William P.; Boylan, Geraldine B.; Wellcome Trust; Science Foundation Ireland; Nihon Kohden America
    Background: Despite the availability of continuous conventional electroencephalography (cEEG), accurate diagnosis of neonatal seizures is challenging in clinical practice. Algorithms for decision support in the recognition of neonatal seizures could improve detection. We aimed to assess the diagnostic accuracy of an automated seizure detection algorithm called Algorithm for Neonatal Seizure Recognition (ANSeR).Methods: This multicentre, randomised, two-arm, parallel, controlled trial was done in eight neonatal centres across Ireland, the Netherlands, Sweden, and the UK. Neonates with a corrected gestational age between 36 and 44 weeks with, or at significant risk of, seizures requiring EEG monitoring, received cEEG plus ANSeR linked to the EEG monitor displaying a seizure probability trend in real time (algorithm group) or cEEG monitoring alone (non algorithm group). The primary outcome was diagnostic accuracy (sensitivity, specificity, and false detection rate) of health-care professionals to identify neonates with electrographic seizures and seizure hours with and without the support of the ANSeR algorithm. Neonates with data on the outcome of interest were included in the analysis. This study is registered with ClinicalTrials.gov, NCT02431780.Findings: Between Feb 13, 2015, and Feb 7, 2017, 132 neonates were randomly assigned to the algorithm group and 132 to the non-algorithm group. Six neonates were excluded (four from the algorithm group and two from the non-algorithm group). Electrographic seizures were present in 32 (25.0%) of 128 neonates in the algorithm group and 38 (29.2%) of 130 neonates in the non-algorithm group. For recognition of neonates with electrographic seizures, sensitivity was 81.3% (95% CI 66.7-93.3) in the algorithm group and 89.5% (78.4-97.5) in the non-algorithm group; specificity was 84.4% (95% CI 76.9-91.0) in the algorithm group and 89.1% (82.5-94.7) in the non-algorithm group; and the false detection rate was 36.6% (95% CI 22.7-52.1) in the algorithm group and 22.7% (11.6-35.9) in the non-algorithm group. We identified 659 h in which seizures occurred (seizure hours): 268 h in the algorithm versus 391 h in the non algorithm group. The percentage of seizure hours correctly identified was higher in the algorithm group than in the non-algorithm group (177 [66.0%; 95% CI 53.8-77.3] of 268 h vs 177 [45.3%; 34.5-58.3] of 391 h; difference 20.8% [3.6-37.1]). No significant differences were seen in the percentage of neonates with seizures given at least one inappropriate antiseizure medication (37.5% [95% CI 25.0 to 56.3] vs 31.6% [21.1 to 47.4]; difference 5.9% [-14.0 to 26.3]).Interpretation ANSeR, a machine-learning algorithm, is safe and able to accurately detect neonatal seizures. Although the algorithm did not enhance identification of individual neonates with seizures beyond conventional EEG, recognition of seizure hours was improved with use of ANSeR. The benefit might be greater in less experienced centres, but further study is required.
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    Altered inflammasome activation in neonatal encephalopathy persists in childhood
    (John Wiley and Sons Ltd, 2021-07) Kelly, Lynne A.; O'Dea, Mary I.; Zareen, Zunera; Melo, A. M.; McKenna, Ellen; Strickland, Tammy; McEneaney, V.; Donoghue, Veronica; Boylan, Geraldine B.; Sweetman, Deirdre; Butler, J.; Vavasseur, Claudine; Miletin, Jan; El-Khuffash, Afif; O'Neill, Luke; O'Leary, John; Molloy, Eleanor J.; National Children's Research Centre; Health Research Board
    Neonatal encephalopathy (NE) is characterized by altered neurological function in term infants and inflammation plays an important pathophysiological role. Inflammatory cytokines interleukin (IL)-1 beta, IL-1ra and IL-18 are activated by the nucleotide-binding and oligomerization domain (NOD)-, leucine-rich repeat domain (LRR)- and NOD-like receptor protein 3 (NLRP3) inflammasome; furthermore, we aimed to examine the role of the inflammasome multiprotein complex involved in proinflammatory responses from the newborn period to childhood in NE. Cytokine concentrations were measured by multiplex enzyme-linked immunosorbent assay (ELISA) in neonates and children with NE in the absence or presence of lipopolysaccharide (LPS) endotoxin. We then investigated expression of the NLRP3 inflammasome genes, NLRP3, IL-1 beta and ASC by polymerase chain reaction (PCR). Serum samples from 40 NE patients at days 1 and 3 of the first week of life and in 37 patients at age 4-7 years were analysed. An increase in serum IL-1ra and IL-18 in neonates with NE on days 1 and 3 was observed compared to neonatal controls. IL-1ra in NE was decreased to normal levels at school age, whereas serum IL-18 in NE was even higher at school age compared to school age controls and NE in the first week of life. Percentage of LPS response was higher in newborns compared to school-age NE. NLRP3 and IL-1 beta gene expression were up-regulated in the presence of LPS in NE neonates and NLRP3 gene expression remained up-regulated at school age in NE patients compared to controls. Increased inflammasome activation in the first day of life in NE persists in childhood, and may increase the window for therapeutic intervention.
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    Multichannel EEG abnormalities during the first 6 hours in infants with mild hypoxic-ischaemic encephalopathy
    (Springer Nature, 2021-07) Garvey, Aisling A.; Pavel, Andreea; O'Toole, John M.; Walsh, Brian; Korotchikova, Irina; Livingstone, Vicki; Dempsey, Eugene M.; Murray, Deirdre M.; Boylan, Geraldine B.; Science Foundation Ireland; Molecular Medicine Ireland; Health Research Board; National Children’s Research Centre; Wellcome Trust
    Background: Infants with mild HIE are at risk of significant disability at follow-up. In the pre-therapeutic hypothermia (TH) era, electroencephalography (EEG) within 6 hours of birth was most predictive of outcome. This study aims to identify and describe features of early EEG and heart rate variability (HRV) (<6 hours of age) in infants with mild HIE compared to healthy term infants. Methods: Infants >36 weeks with mild HIE, not undergoing TH, with EEG before 6 hours of age were identified from 4 prospective cohort studies conducted in the Cork University Maternity Services, Ireland (2003-2019). Control infants were taken from a contemporaneous study examining brain activity in healthy term infants. EEGs were qualitatively analysed by two neonatal neurophysiologists and quantitatively assessed using multiple features of amplitude, spectral shape and inter-hemispheric connectivity. Quantitative features of HRV were assessed in both the groups. Results: Fifty-eight infants with mild HIE and sixteen healthy term infants were included. Seventy-two percent of infants with mild HIE had at least one abnormal EEG feature on qualitative analysis and quantitative EEG analysis revealed significant differences in spectral features between the two groups. HRV analysis did not differentiate between the groups. Conclusions: Qualitative and quantitative analysis of the EEG before 6 hours of age identified abnormal EEG features in mild HIE, which could aid in the objective identification of cases for future TH trials in mild HIE. Impact: Infants with mild HIE currently do not meet selection criteria for TH yet may be at risk of significant disability at follow-up. In the pre-TH era, EEG within 6 hours of birth was most predictive of outcome; however, TH has delayed this predictive value. 72% of infants with mild HIE had at least one abnormal EEG feature in the first 6 hours on qualitative assessment. Quantitative EEG analysis revealed significant differences in spectral features between infants with mild HIE and healthy term infants. Quantitative EEG features may aid in the objective identification of cases for future TH trials in mild HIE.
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    Can EEG accurately predict 2-year neurodevelopmental outcome for preterm infants?
    (BMJ Publishing Group, 2021-09) Lloyd, Rhodri O.; O'Toole, John M.; Livingstone, Vicki; Filan, Peter; Boylan, Geraldine B.; Science Foundation Ireland
    Objective: Establish if serial multichannel video electroencephalography (EEG) in preterm infants can accurately predict 2-year neurodevelopmental outcome. Design and patients: EEGs were recorded at three time points over the neonatal course for infants <32 weeks’ gestational age (GA). Monitoring commenced soon after birth and continued over the first 3 days. EEGs were repeated at approximately 32 and 35 weeks’ postmenstrual age (PMA). EEG scores were based on an age- specific grading scheme. Clinical score of neonatal morbidity risk and cranial ultrasound imaging were completed. Setting: Neonatal intensive care unit at Cork University Maternity Hospital, Ireland. Main outcome measures: Bayley Scales of Infant Development III at 2 years’ corrected age. Results: Sixty- seven infants were prospectively enrolled in the study and 57 had follow- up available (median GA 28.9 weeks (IQR 26.5–30.4)). Forty had normal outcome, 17 had abnormal outcome/died. All EEG time points were individually predictive of abnormal outcome; however, the 35- week EEG performed best. The area under the receiver operating characteristic curve (AUC) for this time point was 0.91 (95% CI 0.83 to 1), p<0.001. Comparatively, the clinical course AUC was 0.68 (95% CI 0.54 to 0.80, p=0.015), while abnormal cranial ultrasound was 0.58 (95% CI 0.41 to 0.75, p=0.342). Conclusion: Multichannel EEG is a strong predictor of 2- year outcome in preterm infants particularly when recorded around 35 weeks’ PMA. Infants at high risk of brain injury may benefit from early postnatal EEG recording which, if normal, is reassuring. Postnatal clinical complications can contribute to poor outcome; therefore, we state that a later EEG around 35 weeks has a role to play in prognostication.