Researchers develop predictive tool for kidney transplant complications

Researchers from CONICET and CEMIC have developed a predictive model designed to forecast the risk of organ rejection and infections in kidney transplant patients. The tool aims to facilitate personalized medicine by adjusting immunosuppression levels based on individual patient needs rather than standard blood concentration metrics.

The model combines clinical data with measurements of a common, non-pathogenic virus found in the general population. According to lead researcher Marcela Echavarría, the tool is particularly promising for identifying patients with a low probability of complications, while helping doctors make better-informed decisions for those at higher risk. This approach seeks to find the precise balance of immunosuppressive drugs required to prevent the immune system from attacking the transplanted kidney.