Automated cot-side tracking of functional brain age in preterm infants

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Stevenson , N J , Oberdorfer , L , Tataranno , M-L , Breakspear , M , Colditz , P B , de Vries , L S , Benders , M J N L , Klebermass-Schrehof , K , Vanhatalo , S & Roberts , J A 2020 , ' Automated cot-side tracking of functional brain age in preterm infants ' , Annals of Clinical and Translational Neurology , vol. 7 , no. 6 , pp. 891-902 .

Title: Automated cot-side tracking of functional brain age in preterm infants
Author: Stevenson, Nathan J.; Oberdorfer, Lisa; Tataranno, Maria-Luisa; Breakspear, Michael; Colditz, Paul B.; de Vries, Linda S.; Benders, Manon J. N. L.; Klebermass-Schrehof, Katrin; Vanhatalo, Sampsa; Roberts, James A.
Contributor organization: HUS Medical Imaging Center
Kliinisen neurofysiologian yksikkö
Department of Neurosciences
Children's Hospital
HUS Children and Adolescents
Helsinki University Hospital Area
University of Helsinki
Date: 2020-06
Language: eng
Number of pages: 12
Belongs to series: Annals of Clinical and Translational Neurology
ISSN: 2328-9503
Abstract: Objective A major challenge in the care of preterm infants is the early identification of compromised neurological development. While several measures are routinely used to track anatomical growth, there is a striking lack of reliable and objective tools for tracking maturation of early brain function; a cornerstone of lifelong neurological health. We present a cot-side method for measuring the functional maturity of the newborn brain based on routinely available neurological monitoring with electroencephalography (EEG). Methods We used a dataset of 177 EEG recordings from 65 preterm infants to train a multivariable prediction of functional brain age (FBA) from EEG. The FBA was validated on an independent set of 99 EEG recordings from 42 preterm infants. The difference between FBA and postmenstrual age (PMA) was evaluated as a predictor for neurodevelopmental outcome. Results The FBA correlated strongly with the PMA of an infant, with a median prediction error of less than 1 week. Moreover, individual babies follow well-defined individual trajectories. The accuracy of the FBA applied to the validation set was statistically equivalent to the training set accuracy. In a subgroup of infants with repeated EEG recordings, a persistently negative predicted age difference was associated with poor neurodevelopmental outcome. Interpretation The FBA enables the tracking of functional neurodevelopment in preterm infants. This establishes proof of principle for growth charts for brain function, a new tool to assist clinical management and identify infants who will benefit most from early intervention.
3112 Neurosciences
3124 Neurology and psychiatry
Peer reviewed: Yes
Rights: cc_by
Usage restriction: openAccess
Self-archived version: publishedVersion

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