PREDICT-CP: study protocol of implementation of comprehensive surveillance to predict outcomes for school-aged

Roslyn N Boyd1,2, Peter Sw Davies3, Jenny Ziviani2,4

  • 1Queensland Cerebral Palsy and Rehabilitation Research Centre (QCPRRC), The University of Queensland, Brisbane, Queensland, Australia.

BMJ Open
|July 15, 2017
PubMed

Insights

PREDICT-CP investigates how brain structure and other factors impact outcomes for children with cerebral palsy (CP). This study aims to predict long-term needs and tailor interventions for improved quality of life.

Area of Science:

  • Neuroscience
  • Developmental Pediatrics
  • Rehabilitation Medicine

Background:

  • Cerebral palsy (CP) is the leading cause of childhood physical disability globally, incurring substantial care costs and impacting well-being.
  • Existing research highlights the need for comprehensive surveillance to predict long-term outcomes and healthcare needs in children with CP.
  • The PREDICT-CP study builds upon previous cohorts, extending follow-up to provide a deeper understanding of CP's trajectory from early childhood to school age.

Purpose of the Study:

  • To investigate the influence of brain structure, body composition, diet, physical activity, and musculoskeletal development on motor, cognitive, and functional outcomes in children with CP.
  • To predict motor attainment, cognition, communication, participation, and quality of life in school-aged children with CP.
  • To analyze the relationship between brain lesion severity and clinical outcomes, informing tailored interventions and healthcare utilization projections.

Main Methods:

  • A population-based cohort study involving state-wide surveillance of 245 children with CP born in Queensland (2006-2009).
  • Classification using Gross Motor Function Classification System, Manual Ability Classification System, Communication Function Classification System, and Eating and Drinking Ability Classification System.
  • Detailed phenotypical data collection including motor function, musculoskeletal development, upper limb function, communication, swallowing, nutrition, body composition, quality of life, and healthcare resource use, correlated with 3 Tesla MRI brain imaging.

Main Results:

  • The study is designed to provide detailed phenotypic data and correlate it with brain macrostructure and microstructure.
  • Multilevel mixed-effects models will be used to analyze relationships between brain lesion severity and various outcomes.
  • Longitudinal data from 1.5-5 years and 8-12 years will enable prediction of outcomes and healthcare needs.

Conclusions:

  • The PREDICT-CP study protocol is prospectively registered and ethically approved.
  • Combining clinical assessments with advanced neuroimaging will enable prediction of outcomes and healthcare needs for children with CP.
  • Findings will be essential for tailoring interventions, including rehabilitation, surgery, and nutritional support, to optimize outcomes and manage healthcare utilization.
Abstract

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