Kidney Disease :: Simple model to predict chronic kidney disease

Chronic kidney disease (CKD), a serious and progressive medical condition, has been and remains under-identified. While it is easy and inexpensive to test for kidney function, people who are at high risk for CKD are not routinely screened.

To better identify those at increased risk for potentially undiagnosed CKD, a team of public health and medical researchers from Weill Cornell Medical College and the University of North Carolina (UNC) at Chapel Hill performed the first study of its kind to develop a tool to identify patients who are most at risk for CKD.

“Kidney disease often occurs in conjunction with a number of other conditions, including diabetes and high blood pressure, but many patients and their family members are not aware of this association,” says Dr. Heejung Bang, assistant professor in the Division of Biostatistics and Epidemiology in the Department of Public Health at Weill Cornell Medical College.

Dr. Bang is the primary author of the study, which is published in today’s Archives of Internal Medicine.

Patients with CKD can be identified early by a test that measures the level of creatinine in the blood. (Serum creatinine, a breakdown product of muscle, is elevated in people with impaired kidney function.) They can then be given treatments that will significantly delay the progression to end-stage kidney disease. Early detection and treatment of CKD can also lessen cardiovascular complications that sometimes occur with the condition.

“Unfortunately, many patients do not find out they have CKD until it has progressed to end-stage kidney disease,” says Dr. Abhijit V. Kshirsagar, of the Kidney Center and Division of Nephrology, University of North Carolina School of Medicine, the senior author and major medical investigator of the research project. “The purpose of the study was to determine which patient characteristics are most associated with CKD, and to develop a simple method to identify individuals who should be screened in a variety of different settings in real life.”


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