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AuthorAwal, Md Abdul
AuthorLai, Melissa M.
AuthorAzemi, Ghasem
AuthorBoashash, Boualem
AuthorColditz, Paul B.
Available date2021-09-07T06:16:24Z
Publication Date2016
Publication NameClinical Neurophysiology
ResourceScopus
ISSN13882457
URIhttp://dx.doi.org/10.1016/j.clinph.2015.05.018
URIhttp://hdl.handle.net/10576/22850
AbstractObjectives Hypoxic ischaemic encephalopathy is a significant cause of mortality and morbidity in the term infant. Electroencephalography (EEG) is a useful tool in the assessment of newborns with HIE. This systematic review of published literature identifies those background features of EEG in term neonates with HIE that best predict neurodevelopmental outcome. Methods A literature search was conducted using the PubMed, EMBASE and CINAHL databases from January 1960 to April 2014. Studies included in the review described recorded EEG background features, neurodevelopmental outcomes at a minimum age of 12months and were published in English. Pooled sensitivities and specificities of EEG background features were calculated and meta-analyses were performed for each background feature. Results Of the 860 articles generated by the initial search strategy, 52 studies were identified as potentially relevant. Twenty-one studies were excluded as they did not distinguish between different abnormal background features, leaving 31 studies from which data were extracted for the meta-analysis. The most promising neonatal EEG features are: burst suppression (sensitivity 0.87 [95% CI (0.78–0.92)]; specificity 0.82 [95% CI (0.72–0.88)]), low voltage (sensitivity 0.92 [95% CI (0.72–0.97)]; specificity 0.99 [95% CI (0.88–1.0)]), and flat trace (sensitivity 0.78 [95% CI (0.58–0.91)]; specificity 0.99 [95% CI (0.88–1.0)]). Conclusion Burst suppression, low voltage and flat trace in the EEG of term neonates with HIE most accurately predict long term neurodevelopmental outcome. Significance This structured review and meta-analysis provides quality evidence of the background EEG features that best predict neurodevelopmental outcome.
SponsorLars Eriksson and Nicola Foxlee, librarians at The University of Queensland Health Science Library provided assistance in defining the search strategy. Dr. Robert Ware, senior biostatistical consultant, School of Population Health, The University of Queensland provided statistical assistance. This work was supported in part by a Grant from the Qatar National Research Fund under its National Priorities Research Program award number NPRP 6-885-2-364 .
Languageen
PublisherElsevier Ireland Ltd
SubjectBackground features
SubjectEEG
SubjectHIE
SubjectHypothermia
SubjectMeta-analysis
SubjectNeurodevelopmental outcome
SubjectNewborn
SubjectStructured review
TitleEEG background features that predict outcome in term neonates with hypoxic ischaemic encephalopathy: A structured review
TypeArticle
Pagination285-296
Issue Number1
Volume Number127


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