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Machine-Learning Test For Kidney Failure & Diabetes

Doctorpedia Editorial Team Doctorpedia Editorial Team July 9, 2021
Medically reviewed by Susan Kerrigan, MD and Marianne Madsen

Patients with diabetes are among those most at risk of developing kidney failure. In 2014, 44% of new End-Stage Renal Disease (ESRD) cases were caused by diabetes. In addition, the National Kidney Foundation states that around 30% of patients with Type 1 diabetes and between 10-40% of those with Type 2 diabetes will eventually suffer from kidney failure. These statistics mean that doctors and specialists are looking to find ways to test the possible risk of kidney failure for diabetic patients.

 

Blood Test for Kidney Disease

 

The current standard test for diabetic kidney disease uses a combination of blood and urine tests.

 

The blood test is used to check how well your kidneys filter your blood and is recorded as your estimated glomerular filtration rate (eGFR). This is done by examining the amount of creatinine in your blood. Creatinine is a waste product that is filtered out of your blood by your kidneys. Seeing how much creatinine is contained in your blood makes it possible to estimate your eGFR.

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Test for Kidney Function

Test for Kidney Function

If you have a baseline eGFR of 60 or above, you have a normal renal function and don’t have kidney disease. However, if your eGFR is below 60, that may be a sign of kidney disease. An eGFR decline is irreversible, and your doctor will advise on how best to monitor your condition. 

 

When you have an eGFR of less than 15, it typically indicates kidney failure. You will then need either a kidney transplant or dialysis.

 

Urine Test for Kidney Disease

 

The urine test for kidney failure checks for a protein found in your blood called albumin, which a healthy kidney will filter out. If albumin is found in your urine, it is usually a sign of kidney damage.

 

Your doctor will use one of two methods to check for albumin. The first is a simple dipstick test, where a strip of chemically treated paper is placed in your urine sample. The paper will change color if albumin is present. The other method is testing the urine albumin-to-creatinine ratio (UACR). By comparing the albumin-to-creatinine ratio in your urine, it is possible to estimate how much albumin will be found in your urine in 24 hours. Anything below 30 mg/g is considered a normal level. Above this amount may be a sign of kidney disease.

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Urine - What You Need to Know

Urine - What You Need to Know

Machine Learning Test

 

Blood and urine testing provide adequate results when assessing if a patient has already developed kidney disease. However, it is not as effective at making an accurate prediction of rapid kidney function decline (RKFD). Therefore, providers have been looking at developing new ways of assessing kidney failure.

 

KidneyIntelX is an in vitro diagnostic test that uses blood-based plasma biomarkers, genetics, and medical records taken from electronic health record systems. This information is input into an AI-based computer program that assesses the data and uses machine learning algorithms to calculate your unique risk score for kidney disease.

 

Initial testing of the new method has shown a considerable improvement compared to blood and urine testing in predicting whether a patient will develop RKFD. 

 

In 2019, the FDA granted KidneyIntelX a “Breakthrough Device” designation. This designation grants additional funding to help bring a device to healthcare providers sooner. The funding is to speed up the development, assessment, and review process. In March 2021, a new study was begun at Mount Sinai Hospital in New York to assess KidneyIntelX’s real-world effectiveness. This study is estimated to last until December 2026.

 

The hope for primary care physicians and healthcare providers is that machine-based learning tests will become more common in diagnosing end-stage renal disease. This will potentially help in making the correct decisions in terms of patient treatment.

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