Objective
The main concern of clinicians when addressing sick patients is to promptly identify -i.e. “not miss”- those at higher risk of severe disease, so as to prioritize their care and better target therapeutic interventions. Unfortunately, risk-stratification practices for infections remain suboptimal and prone to misclassification, leading to adverse outcomes and misallocation of resources, particularly in children (and even more so among newborns) from Sub-Saharan Africa (SSA). We recently developed “B-Triage”, a point-of-care rapid triaging test, designed for the quantitative assessment of sTREM-1, a biomarker of sepsis, and a highly performing prognostic marker, irrespective of underlying disease. Levels of sTREM-1 stand out as a quantitative and independent predictor of severity and death in all-cause infections, being superior to other markers and clinical scores, showing promise also for risk-stratification of non-communicable diseases. We propose to specifically validate B-Triage for risk-stratification of all cause sickness in the newborn, the age group concentrating ~50% of all child mortality. ACROBAT-newborns aims to continue and accelerate the valorisation of our device, with clinical studies in Mozambique, Ethiopia, Uganda and Gabon; the industrialization of its prototype; and a go-to market strategy for SSA. The project includes strong components of health economics and impact assessment, as well as socio-behavioural sciences (usability, acceptability, and feasibility studies), with the overarching aim of generating the necessary evidence to support B-Triage’s introduction to the African market. The proactive use of our device for risk-stratification of the sick newborn at first clinical presentation, will determine, objectively and with high precision, those at risk of severe outcome and death, resulting in improved outcomes and survival, and an optimized use of healthcare resources, including antibiotics and high value therapeutics.
Fields of science
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
Programme(s)
- HORIZON.2.1 - Health Main Programme
Topic(s)
Funding Scheme
HORIZON-JU-RIA - HORIZON JU Research and Innovation ActionsCoordinator
08036 Barcelona
Spain