12 Jan Equations Use Routine Data To Predict Risk of Kidney Failure
MedicalResearch.com Interview with:
Navdeep Tangri, MD, PhD FRCPC
Department of Medicine
Seven Oaks General Hospital
University of Manitoba
Medical Research: What is the background for this study? What are the main findings?
Dr. Tangri: Chronic kidney disease is common and its end stage of kidney failure requiring dialysis can be devastating for patients and families. While 26 million North Americans are affected by CKD, the vast majority of them will not experience kidney failure during their lifetime. Predicting the risk of kidney failure for an individual patient can help doctors plan treatment, improve shared decision making, and provide patients with piece of mind.
In 2011, we developed equations that accurately predict the risk of dialysis in more than 8,000 Canadian patients with CKD. While these equations are widely used, global implementation has been limited due to a lack of validation in other countries/health systems. The current study addresses all of these concerns by comprehensively validating the risk equations in more than 700,000 participants spanning 30+ countries, and demonstrating its accuracy in predicting the risk of dialysis.
Medical Research: What should clinicians and patients take away from your report?
Dr. Tangri: Clinicians and patients should be aware that the 2-5 year risk of kidney failure can be accurately predicting using risk equations that rely on routinely collected data. These equations are easy to use, and are available online for both patients and providers.
Medical Research: What recommendations do you have for future research as a result of this study?
Dr. Tangri: We believe that the next steps in this field involve implementation of the risk equations in electronic health records and laboratory information systems, and studies on the impact of the equations in clinical care. We are conducting some of these studies and trying to move the field forward.
Navdeep Tangri, MD, PhD FRCP (2015). Equations Use Routine Data To Predict Risk of Kidney Failure