PROBIt_RetroKids_Version1

  • Research type

    Research Study

  • Full title

    PROBIt: Identifying Predictors of Risk and Resilience for poor neuropsychological Outcome following childhood Brain InsulTs – Retrospective Children

  • IRAS ID

    233424

  • Contact name

    Amanda G Wood

  • Contact email

    a.wood4@aston.ac.uk

  • Sponsor organisation

    Aston University

  • Duration of Study in the UK

    3 years, 5 months, 2 days

  • Research summary

    The impact of insults to the developing brain upon cognition and behavior has far-reaching consequences for the child, their family, education and healthcare systems, and government expenditure. Many variables (illness, environmental) contribute to different outcomes following similar insults, and they exert their influence via the child’s developing brain. Predicting which child will recover from an early brain insult and identifying those at risk of poor outcome represents a major challenge, with significant health economic implications. An unexplored question is whether direct measurement of the structure and function of the developing brain can improve our ability to predict outcomes in the long-term. Thus, PROBIt aims to assess the utility of brain imaging biomarkers to predict individual neuropsychological and neurobehavioral outcomes following pediatric brain injury, and to identify those factors that combine optimally to classify outcomes.

    PROBIt-RetroKids will recruit 225 children (75 controls and 150 cases) who had MRI scans taken at Birmingham Children’s Hospital between 2003 and 2017. Children will be aged 6 to 15 years at the time of recruitment. We will ask for permission to acquire all their previous brain imaging data and will conduct post-scan follow-up assessments of cognitive and behavioral outcomes.

    PROBIt combines data from clinically relevant pediatric cognitive and behavioral tests, brain scans and computer simulations in large groups of children with brain insults. A statistical model will be used to differentiate between children that are likely to develop with either a 'poor' or 'good' outcome across three domains: achievement, behavior and cognitive ability. First, we will determine whether adding brain imaging measures to the model improves the accuracy of prediction at the individual child level. Second, we will identify the features that confer risk and resilience to ‘good’ and ‘poor’ neurodevelopmental outcomes, which has important implications for clinical diagnosis and rehabilitation of children with early brain insults.

  • REC name

    London - Bloomsbury Research Ethics Committee

  • REC reference

    18/LO/0990

  • Date of REC Opinion

    2 Aug 2018

  • REC opinion

    Further Information Favourable Opinion