Health
Research team develops predictive model for diabetes complications

about. His 40% of diabetic patients develop chronic kidney disease, with gradual deterioration of kidney function and even complete loss of kidney function. Until now, it was not possible to predict whether or how much kidney disease would progress. Early detection is essential to delay or avoid renal failure requiring dialysis. As part of an international research project led by MedUni Vienna, a tool has been developed that can predict up to 5 years ahead, enabling timely preventative action. The results of this research were recently published in the specialized journal “JAMA Network Open.”
For their study, a team led by Rainer Oberbauer, Head of the Department of Nephrology and Dialysis, MedUni Vienna’s 3rd School of Medicine, and Mariella Gregorich, MedUni Vienna’s Center for Medical Data Science, used data from major international studies. used. This allowed us to include 13 baseline values routinely collected from 4,637 of her 18 to 75-year-olds with type 2 diabetes with mild to moderate renal impairment. rice field. In addition to the most important values for assessing renal function (estimated glomerular filtration rate, eGFR), age, sex, body mass index, smoking behavior, hemoglobin and cholesterol levels, and medication were selected as predictors. rice field. Based on this, the research team developed a predictive model based on tested statistical methods. It is already ready for clinical use.
The strength of our study compared to previous studies on this topic lies not only in our sophisticated methodology, but also in our large amount of data. This gives you a high level of confidence in your findings. Therefore, this predictive tool has been proven to be reliable and predictive of renal function decline based on eGFR for up to 5 years from baseline. ”
Mariella Gregorich, first author
However, the study also revealed that individual courses depended on other as-yet-unknown factors.
Early detection and treatment management
Chronic kidney disease (CKD) is one of the most common complications of diabetes and the most common cause of renal failure requiring dialysis. Since CKD does not have subjective symptoms in the early stages, it is often discovered after the deterioration of renal function has progressed considerably. Early detection and consistent therapeutic management can delay or prevent kidney damage, especially in controlling metabolism and blood pressure in diabetes. Currently, renal function in diabetic patients is mainly monitored by regular measurement of eGFR. “Our predictive tool will support continuous monitoring of disease progression and allow us to identify patients at high risk of worsening kidney function in the years to come,” said study leader Rainer Oberbauer, predicting It highlights the important clinical relevance of the tool. His web-enabled version of the model is already under construction and will be available soon for further independent validation. https://beatdkd.shinyapps.io/shiny/
sauce:
Journal reference:
Gregory, M., and others. (2023) Development and validation of a predictive model for future estimated glomerular filtration rate in patients with type 2 diabetes and chronic kidney disease. JAMA network opened. doi.org/10.1001/jamanetworkopen.2023.1870.
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