In the first large-scale study of its kind in the US, the Klinrisk model, a machine-learning tool developed to predict the risk of chronic kidney disease (CKD), was more than 80% accurate in predicting the advancement of the disease over a five-year period using data from a diverse population of more than 4 million US adults, study sponsors Boehringer Ingelheim and Carelon Research say.
Nephrologist Navdeep Tangri, the scientific founder of the Klinrisk model, told Medtech Insight that providers need validated tools like the Klinrisk to fight against CKD.