Acute kidney injury (AKI) is an extremely complex life-threatening disease with high mortality and chronic kidney/non-kidney consequences. AKI is characterised by (1) the (current) inability to predict its development before the insult, even in well-controlled and frequent clinical settings such as cardiac surgery or chemotherapy, and (2) the huge heterogeneity of the kidney response even after an insult of similar intensity.

The aim of SpareKid is to better predict the development of AKI to allow dedicated primary prevention and reduce its costs.

The innovative concept of SpareKid is to define a so-called non-invasive Kidney Resilience Index (KRI), modeling AKI as a maladaptive kidney response to the insult. The KRI will be defined based on in-depth and multiscale molecular and clinical data using a holistic big data-based strategy to integrate high throughput urinary and plasma proteomic, immunologic mRNA and cell population signatures, genetic whole genome sequencing (WGS) signatures and detailed clinical parameters to optimally model the complexity of AKI.

Last, using data from the National Systems of Health, we will model the cost-effectiveness of the KRI to determine the cost sparing of a preventive strategy.