Hello and welcome to a. P. A. 2022. I'm Ashlyn smith, a position assistant in endocrinology and I have the pleasure of talking to you today about sensor based continuous glucose monitoring to optimize care for people living with diabetes. This program is not yet approved for CMI but the plan is to apply for 1.5 ap a category one CMI credits. And this program is sponsored by an educational grant from Abbott diabetes Care. I have the pleasure of being joined by some expert faculty. Today we have Dr Diana Isaacs from Cleveland Ohio who is an endocrine and diabetes specialist and she's here to give you your in her insights for today. And then we have dr Jeff unger from California who is a primary care specialist. Well versed in diabetes management. See GM technology. Here are my disclosures. I get to kick off this great program talking about really the fundamentals of C. G. M. Why there's such a need for C GM technology and what this advancement in technology can do to better serve our patients that are living with diabetes. First, I don't have to tell any of you guys about these statistics. I know you're all well versed in this. You're seeing diabetes at the front line in primary care. This disease state affects more than 37 million people in the United States that are living with with diabetes and this very complicated disease state is still the leading cause of new blindness and the leading cause of end stage renal disease in the US. And very importantly, we see between the two and eight fold increased risk of cardiovascular disease with diabetes and cardiovascular disease remains the most common cause of death in diabetes. We'll dive into that cardiovascular risk in a little bit here and what makes that so important in this disease state. I love showing this slide because it's such a good perspective as to where we were and where we are going in terms of monitoring glucose. Back in 1908, we have the first test for assessing glucose. It was a urine glucose test better known as Benedict's test. Back in 1908. Then we moved to blood glucose test strip monitoring. And this is not like we think of today with using a glucose meter. This was actually a test strip that had to be rinsed off. And then the the color was compared to the spectrum. Used to be below there. And in the 1970s we saw the emergence of actual glucose meters that gave a full number that actually told a patient what their glucose level was. And then as early as 1999, we saw the first emergence of continuous glucose monitors. That's an important thing to know. Is this is not a very new, you know, uh, elusive technology. This is actually something that's been in use for more than 20 years. So we're circle back to that idea of the increased risk of mortality with diabetes. So, we know that of course, the higher the A1C as you see here on the left, the higher the risk of all cause mortality and cardiovascular death. However, what's important to know is even for our patients that are reaching their A one C target of less than seven. There's still a two fold increased risk of mortality and cardiovascular death compared to the counterparts that do not have diabetes. So we know that even when we're seeing that A one C reach our goal, we do still have that residual risk. We can be tempted to think that if lowering the A. One C reduces some of that vascular risk, then we should maybe target even lower A one C. But in fact, we have some pretty significant landmark trials dating back to 2000 and eight for the accord and advanced trials in 2000 and nine for the V. A. Diabetes trial that looked at more intensive intervention versus the standard of care. For instance, accord looked at targeting an A. One C. Of six. Advanced looked at 6.3 and the V. A. D. T. Looked at an A one C. Of six as well importantly, there was really no huge difference in outcomes in terms of complications. And we see a very common theme across all three about issues with hypoglycemia and increased risk of death. In the accord. There was an increased risk of cardiovascular death and all cause mortality. And it was actually stopped prematurely because of the increased rate of death in the in the comparator arm. The the arm where we looked at intensive treatment and the advanced trials saw no difference in death and only a reduction in africa apathy, none of the other markers, but an increased risk of severe hypoglycemia and hospitalizations. Similarly with the V. A. D. T. Trial, there was no change in major adverse cardiovascular events but there was an increased risk of symptomatic symptomatic hypoglycemia, asymptomatic hypoglycemia and nocturnal hypoglycemia and even an increased risk of cardiovascular death. So across the board, If lowering the a. one c. is good, unfortunately lower doesn't necessarily mean better. And this was a pretty startling study back in 2000 and 18 that looked at the residual vascular risk even in folks that do meet their A one C targets. So you can see these very high percentages of residual vascular risk even when we consider the A. One C. At goal. So in this we really have to think beyond just the A. One C. Because if A one C targets leave this residual vascular risk, there's really more that needs to be done for this population. We're dealing with a very complicated disease with many variables. And effectively treating type two diabetes requires not only meeting are glycemic goal goals but making sure that we are not doing more damage like with increasing the risk of hypoglycemia. So to reach to reach our glycemic targets we want to reach that a one C target that is still important. We want to prevent complications. And so do our patients were motivated together in that we try to enact efforts that lower health through utilization and costs and of course reducing the burden and removing some of the those more restrictive regimens. There is a very real and very normal phenomenon called diabetes distress when we're dealing with the amount of burden related to managing this complex disease state. The way that I described this to my patients is diabetes distress is a response of all the things that I asked you to do in a day's time. All this long list of things that we ask our folks to do really does create this very normal phenomenon of diabetes distress. So anything that we can do to help reduce the risk and help reduce the burden promotes adherence and it promotes that that patient by into therapy. So that's very important. And of course patients and providers alike are looking to lower the risk of hypoglycemia. That helps reduce fear of hypoglycemia. It helps with medication initiation and filtration that so called clinical inertia that we're all faced against. It helps that that patient brian and adherence and ultimately helps reduce the mobility and health care utilization. But I want to point out here the study that was done in 2018 from it was published in diabetes care. So very reputable study looked at the current 18 of the the top glucose meters that were available And it looked to see if those top 18 m met the 2016 FDA guidance on accuracy. And this is a pretty startling number. Only six or one third Of those that were available met that guidance. What's important to know here is that in 2019 FDA actually put out even stricter guidance on the accuracy of commoners. So time will tell how many of the meters that are available. Do meet this new stricter guidelines. Some of the fundamental barriers that we see to achieving all of these targets that we're talking about are related to some of the metrics that we use and this term of glucose variability, which we'll talk a lot about throughout this program. It's important to know that not all agencies are created equal. We'll see this in just a moment that an agency of 7% is great but that may or may not be true diabetes control. It's important to pair that a one c with glucose data to really assess how in control the diabetes treatment is, but finger stick glucose monitoring as you know, it's just a snapshot in time. It just tells us at that moment what's going on. It doesn't show us trends and it certainly doesn't tell us what's happening the rest of the time with the glucose levels. This term glucose variability. It's the idea of that kind of roller coaster of glucose control. So we see lows and highs and and back and forth where we we see some adventure in our diabetes control and that's not a condition where we want there to be this unpredictable glucose pattern. So glucose variability drives complications. It interferes with adherence and it contributes to issues with clinical inertia and it does impact the disease burden. So if an individual doesn't feel like they're in control of their diabetes or that they can't really predict what's going to happen with their blood sugar, they're more likely to feel overwhelmed and burnt out from dealing with the disease. So we'll talk about this term coefficient of variation and that's really a measure of that google's variability. So we know that that this higher coefficient of variation contributes to an unfavorable metabolic profile, increases the risk of complications across the board, both micro and macro vascular complications and increases mortality. And what's so important here is that third bullet point on the right is that the association of the coefficient of variation of glucose was more consistent than a one C in predicting metabolic outcomes and complications. So this really does drive outcomes. If we have a high coefficient of variation, that more variable glucose pattern, we're going to have more complications and poor outcomes. This is a beautiful and very classic demonstration of how not all a one CS are created equal the way that I explain this to my patients is that we can average blood sugar of 30 and 300 and get a pretty decent a one c. But that's not good blood sugar control. So for example, our patient here on the left. If we look at this see GM data we can see that there are 100% of the time in range which is excellent. So I'm much less concerned about our patient on the left than our patient here on the right. Who seeing these these tall peaks and these deep valleys of glycemic control. They both have an A. One C. Of seven but the person on the right is going to fare much worse in terms of complications and overall outcomes. So to reduce that residual risk that we're talking about. One of the the measures to do that is to pair that a one C. With looking at time in range. So we'll talk a lot about that throughout this program to this idea of time in range or meeting our glucose targets. We have a few different options available for C. GM technology currently on the market. So we have the Medtronic Guardian sensor three or the Medtronic Guardian connect system and we have the decks com G six. We have a freestyle library too and we have the ever since E three which is the implantable C G M. I have a few of the specifications listed below but some key differences to know is that the Medtronic sensor does require between two and four finger stick calibrations per day. So just using the C. G. M. Does not mean we're free from finger sticks if we're using the medtronic. So if we aren't using at least those four finger stick glucose measures to calibrate, the accuracy starts to go down on the sensor, The deaths come G6 and live freestyle. We break to do not require finger stick calibrations. They are factory calibrated and what's very important to know and to educate our patients, we do not want to calibrate these with finger sticks. It actually makes these sensors less accurate if we're doing that And then they ever since the E three, the implantable CGM Requested two finger stick calibrations for the 1st 21 days and then just one finger stick calibration for the remainder of the six months that it's implanted. And a very important distinction across all of these. See GM technologies is your three C. G. M. On the right. Do you have non a non adjunctive therapy status, which means that you can make treatment changes based off of the glucose that show on the C. G. M. Without corroborating with the finger stick? So those are all the options. We've kind of laid the foundation for the problem and this need to address a one C with glucose variability in that time in range. But let's look at actually some studies that show this does it work. So we have a randomized control trial here for folks living with diabetes, type one diabetes. And these were the most at risk individuals. So these were folks living with type one diabetes that either had hypoglycemic unawareness or history of severe hypoglycemia. So those are big red flags, big risk factors here. So as you can see on the control group, there really was no difference as you can expect from before. Um they were studied to afterwards. So this control group only used finger stick blood glucose monitoring, contrast this to the right side, which is the C. G. M. Group. So you can see the dark blue here the dark blue here for the the baseline of where they were we were looking at on the Y axis here, the percentage and the X axis here of the number of hypoglycemic events. So we want to get as vertical as possible. We want to make sure that we're getting as close to zero for most of the folks as possible. So we see the baseline here in the dark blue on just finger stick like glucose monitoring and and then the improvement and reduction in hypoglycemia on the the follow up, which was this light blue color. So this is our most at risk folks who saw a reduction in hypoglycemia just by using C. Gm technology and then we can shift our focus a bit too randomized controlled trials with type two diabetes. So on your left here we have a randomized controlled trial of type two diabetes across the spectrum of therapies. So anywhere from diet and exercise alone to oral anti diabetic agents to injectable therapies like GLP one and Basil Insulin. Everything up to um and not including Crandall insolence. Everything else was fair game in this study. So the fault who are using in um in real time see GM saw a significant reduction in A one C. And the second point here is so crucial regardless of of medication adjustments. So this improvement in A one C occurred without a greater intensification of medication. So this is not one more pill or one more shot they have to take. This is not one more set of side effects they have to worry about. This was significant reduction in U. N. C. Just by being able to see their transit glucose and be able to adjust accordingly. Just that increased insight into their management and I don't know about you. But I know that sustaining change from my own experience and from a clinician perspective, sustaining change is very difficult. So I love that in this study, they actually continued to monitor these folks and even up to 40 weeks off of the C. G. M. That they showed sustained improvement in their glucose readings. So that insight that they gained stayed with them long after the C. G. M. Was removed. And then here on the right we have an open label randomized controlled trial of Type two diabetes on insulin. And across the board we saw significant reductions in hypoglycemia at every level, so level one level two to severe hypoglycemia, nocturnal hypoglycemia. Across the board, there were significant reductions in hypoglycemia and an under recognized metric of of diabetes improved in this group too. There was a significant improvement in treatment satisfaction using validated measures. And that is so important when it comes to to type two diabetes management. Because we really need to model a shared medical decision making process to help our patients really buy into therapy. So it's one thing to say this is what I recommend and this is what needs to happen. But to really have our patients feel confident and feel satisfied with their treatment, we need them to buy in. So if we're able to increase their satisfaction and treatment were more likely to be able to achieve those outcomes. Together, shifting gears here about we're looking at real world evidence for C. G. M. Use in Type two diabetes is a very busy slide and I won't be labor all of them. But this is to show that there's a really robust body of real world evidence for use in this population. And we have studies that look at diesel insulin and non insulin therapy. We have studies that look at subgroup analyses of younger population and older population men versus women high A one CS versus lower A one CS. And really across the board we're seeing improvements and outcomes regardless of subgroup were regardless of type of of modality used to treat their their diabetes. So really there's a strong body of evidence for real world evidence for PSI GM technology into diabetes. We have some guidelines that that talk about C. G. M. Use as well. So for the guidelines there's some pretty bold statements in this this guideline talking about diabetes technology and talking about how it gives this persons with diabetes to safely and effectively achieve glycemic targets. That's what we all want. What clinicians and patients want. We can see an improvement in quality of life, greater convenience, potentially reduce that burden of care we were talking about and offer a personalized approach to self management. So really some some powerful things that can come out of using diabetes technology. And similarly, we have guidelines from the A. D. A. Which talked about using real time glucose monitoring or intimately scanned continuous glucose monitoring and stating that it should be offered for diabetes management and adults with diabetes on M. D. I. Multiple daily injections or continue with subcutaneous insulin infusions. Notice that this does not specify type one or type two diabetes, but all of the folks who are living with multiple daily injections or an insulin infusion. And then, moreover, it can be offered in diabetes management for adults with diabetes who are on basil insulin. Again not specifying type one or type two. So really putting this all together, we're looking at randomized controlled trials, showing improvements across the board. We're looking at real world evidence for reductions and outcomes, and then really looking at guideline directed therapy and putting this all together to talk about when it's appropriate and why we should be using See GM technology.
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