Role of DKD Progression Screening Tools

EP: 1.Prevalence of Diabetic Kidney Disease (DKD)

EP: 2.Current Screening Guidelines for DKD

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EP: 3.Role of DKD Progression Screening Tools

EP: 4.Use of KidneyIntelX in Patients With DKD

EP: 5.KidneyIntelX in DKD Study Population Characteristics

EP: 6.Referral of High- and Low-Risk Groups in DKD

EP: 7.Improved Diabetes and Kidney Function Control With KidneyIntelX

Aida Vega, MD: You mentioned this a little bit earlier on. What's the role of the urine albumin-to- creatinine ratio and the eGFR in current kidney disease progression screening practices? What do you think about how this is…we touched on this, but for us, this is all that we have.

Fernando Carnavali, MD: We are using it. It’s concerning. We will review literature. The literature is showing that it's not being used as much. When we're talking about the albumin-to-creatinine ratio, it's not used as much as one would think that it should be used. And the more we know, and we spoke before, perhaps about the limitations of these 2 tests, again, very useful, but with different variabilities. When we're talking about the estimated GFR, we know that at the very beginning it can be false – at the beginning of kidney failure, it can be falsely elevated and that can create a false sense that everything is correct when we know that it's the opposite. And we spoke about the urinary albumin-to-creatinine ratio and the variabilities, some of the physiological variabilities, that one can find. Again, useful, but not giving us the answer that we need for the patients that present with early kidney disease.

Aida Vega, MD: It's interesting that even though these guidelines are there, and it's recommended that we check the patient's urine albumin-creatinine ratio and eGFR yearly, at least, for the diabetics, we still have practice guidelines that track the physicians to do this because it's not always utilized by physicians in primary care. In general, overall getting the physicians to do something throughout the day because they're so busy, as you pointed out, is essential to have a tool that assesses risks and is visible to the physician early on.

Aida Vega, MD: Do you know if there are any other biomarkers that can be employed to better predict potential progressive kidney function decline?

Fernando Carnavali, MD: We know that there are. And they're well studied and so we think about this soluble tumor necrosis factor 1, 2; the kidney injury molecule-1. So, we know that they are there and they're well studied. But we haven't been using it as the way that this new tool that we'll talk about later is using it. And that provides us the next level of early diagnosis of chronic kidney injury, so, chronic kidney disease. So yes, they are, and it's taking us to the next level.

Aida Vega, MD: And they're well-validated tools. It's interesting that it took Mount Sinai to develop something to integrate this into our clinical practice, because these are very well-validated tools of kidney injury. Can advances and risk assessment and screening practices for kidney disease progression help guide and optimize the prevention and management of this condition?

Fernando Carnavali, MD: There sure would be, yes. But what we know, and the fascinating part of all this, is how tools like the one that we'll talk about now is creating a revolution in the field of screening. And that part we'll see more of is the role of machine learning in this. What we're talking about is pulling items that have been well studied and bringing them to the next level, creating these algorithms that will take all the information, including clinical information, the information from the electronic health records, the molecules that we just mentioned, and putting all that together, and creating a risk stratification, predicting for the primary care physician, and giving the physician the tools that is needed to take the next steps and to take these next steps in a timely manner before patients do progress. And as we said before, with 50,000 new people having the need to either be in dialysis or perhaps transplant. So, fundamental changes, I think that we're optimizing the prevention of chronic kidney disease utilizing these new tools.

Aida Vega, MD: For us in primary care, we spend all day and not only seeing patients and looking at lab results and spending a lot of time reviewing data. So, the integration with machine learning as well as labs into also what's already documented in the record for the patient is essential in terms of being able to get us to get our work done throughout the day, but also to do an excellent job of taking care of patients. That's, definitely, risk assessment strategies and screening in diabetic kidney disease are essential for the modern-day physician in primary care.

Transcript edited for clarity