PROBIt-ProKids Version 1
Research type
Research Study
Full title
PROBIt: Identifying Predictors of Risk and Resilience for poor neuropsychological Outcome following childhood Brain InsulTs - Prospective Children
IRAS ID
222771
Contact name
Amanda Wood
Contact email
Sponsor organisation
Aston University
Duration of Study in the UK
3 years, 10 months, 30 days
Research summary
The impact of insults to the developing brain upon cognition and behaviour has far-reaching consequences for the child, their family, education and health care systems, and government expenditure. These brain insults may be exogenous (for example, trauma to the brain following head injury, exposure to toxicants or environmental factors that may be associated with neurodevelopmental difficulties such as autism, ADHD or specific learning disabilities) or endogenous (for example stroke, tumours, or congenital abnormalities, which collectively bring the child to attention of the health care system due to concerns about physical or cognitive well-being). 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 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 neurobehavioural outcomes following paediatric brain injury, and to identify those factors that combine optimally to classify outcomes. PROBIt-ProKids will prospectively recruit 225 children (75 controls and 150 cases; acquired postnatally) for baseline brain scans and later assessment of cognitive and behavioural outcomes (two years post-scan). PROBIt combines data from clinically relevant paediatric cognitive and behavioural assessment, neuroimaging and computational modelling in large cohorts of children with brain insults. Multivariate pattern analysis will be used to train a statistical classifier to reliably predict individual child outcomes across three core domains: achievement, behaviour and cognitive ability. First, we will determine whether the addition of brain imaging measures to the classifier improves the accuracy of prediction at the individual child level. Second, we will identify 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
Yorkshire & The Humber - Sheffield Research Ethics Committee
REC reference
17/YH/0299
Date of REC Opinion
17 Nov 2017
REC opinion
Further Information Favourable Opinion