Novel AI-driven model validated to predict risk of chronic kidney disease progression in large U.S. study. _ Boehringer.
Boehringer Ingelheim and Carelon Research have conducted a validation study of the Klinrisk model, a machine-learning tool developed to predict the risk of chronic kidney disease (CKD) progression at all stages of the disease.
Using data from a diverse population of over 4 million U.S. adults, the model was more than 80% accurate in predicting CKD progression over a five-year period.
These findings were presented in an oral session at the American Society of Nephrology (ASN) Kidney Week conference in Philadelphia, being held from November 1-5, 2023.
The validation study used data provided by Carelon Research from a diverse population of 4.6 million U.S. adults enrolled in commercial, Medicare and Medicaid insurance plans to assess that the Klinrisk model can predict risk of CKD progression. The model correctly predicted CKD progression in 80-83% of individuals over two years and in 78-83% of individuals over five years, depending on the insurance provider. When urinalysis data was available, the model correctly predicted CKD progression in 81-87% of individuals over two years and in 80-87% of individuals over five years.
“The model is a useful tool to help identify people with high-risk CKD early, before kidney function is lost,” said Navdeep Tangri, M.D., scientific founder of Klinrisk. “We look forward to advancing this model as we aim to bring it to U.S. physicians.”
Learning Zones
The Learning Zones are an educational resource for healthcare professionals that provide medical information on the epidemiology, pathophysiology and burden of disease, as well as diagnostic techniques and treatment regimens.
1 mins