Congenital Hemiplegia clinical trials

Combining biomArkers and Tele-health Solutions for Delivering at Home and in the Community Precision Medicine for the Upper Limb in cHildren With HEMIplegia Due to Stroke

Paediatric (including perinatal) stroke has an incidence of between 1.3 and 13.0 per 100.000 yearly in Europe. 1/3 of children with neonatal and 50% of post-natal stroke will develop a hemiplegia with upper limb being generally more affected than lower limb and a severe impact on children's participation and quality of life. Opportunities to advance scientific knowledge of the influence of genomic variation on the pattern, presentations and prognosis of paediatric stroke are lacking. Conversely, the discovery could have an enormous potential to drive the rehabilitation that is the major component of the stroke patient's care and to achieve a good functional outcome. The present proposal aims to change the current management of care and intervention of children with hemiplegia due to stroke, by identifying relevant biomarkers coming from four different areas (omics, clinical assessment, neuroimaging, Information and Communication Technologies) in order to stratify the children and to create a novel transdisciplinary patient-centred model to optimize and tailor the rehabilitation treatment. As a diagnostic tool, the new workflow allows the set-up for planning an individualized treatment based on patient specific needs, creating a model for an evidence-based clinical decision-making process that starts from the measurements of specific biomarkers, clinical measurements and effective use of patient's Upper Limb. The feasibility of the planned approach can be applied for deeply analysing and understanding results of previous researches and in new pilot studies on already available rehabilitative treatments. The results will provide an example of how different kinds of integrated assessments can contribute to create a plan for the management of children with hemiplegia due to stroke, thus leading to a better understanding of the correlation between genetic and phenotypic data. Finally, the Health Technology Assessment will provide estimates of its national and regional cost effectiveness.