Video The Actionability of Ambulatory Glucose Profiles (AGP) for Guiding Therapeutic Decisions on T2DInteractive Case-Based Clinic with CGM Experts Board Play Pause Volume Quality 1080P 720P 576P Fullscreen Captions Transcript Chapters Slides The Actionability of Ambulatory Glucose Profiles (AGP) for Guiding Therapeutic Decisions on T2DInteractive Case-Based Clinic with CGM Experts Board Overview CONTINUE TO TEST Back to Symposium Now, I'd like to continue this discussion of using CGM to optimize glycemic management and focus on the A GP and a case to optimize glucose control, learning how to use uh our CGM metrics. So these are my disclosures again, haven't changed since the last talk. And now let's get right to the A GP that I think all of you are probably familiar with the three panels of metrics, the profile, the daily views, the ad A said this is a good uh standard view to recommend a starting point. Um 2022 2023 in the standards, 2024 updated it to the color version of the latest version of the A GP that you'll be seeing more and more of. But it's the same principles, timing range, bar, glucose metrics, a profile with at a, at a glance, you can tell where someone may be hypoglycemia by the red. And then the daily views when we review the metrics again that I talked about just a moment ago, but just putting the, the, the 10 metrics that I hope all of you are becoming very familiar with. There's actually eight metrics and maybe two um uh uh uh measures of, is there adequate data? But you see, I left a little blank there and all of us as a diabetes community are gonna need to decide, do we fill in another key metric with time and tight range that I just discussed? And we'll come back to, I'm sure more in discussion of the cases. Um But if we have these metrics and we define them, we really want to know what are we shooting for. And so you are all familiar again, I just put what the targets are for these metrics. Um greater than 70% in range and less than 4% under 70 less than 1% under 54. Um And those are the levels that uh they equate to and this is still to be decided. Is it as recommended? Uh 50 or I've heard 55% for a time and tight range. We need a consensus on that before we put it in to the A GP if uh if that's the decision that's made, but at least you're all uh there hearing this dialogue and I hope contributing to it. Now, I just want to be sure that we don't forget about average glucose and the CV and the glucose management indicator. And I'm gonna focus a little bit on two of these that help us move that time and range where we want it and the time below range as low as possible. OK. Now I'm going to show you this and I'm, I'm just waiting for all the groans in the audience. I know this is a slide. No one should ever ever show because it's so dense. But I can just tell you when you have a chance to see this. This is in the paper. Um, uh, one of the papers that came out with the 20,000 patients I talked about before, if you put 20,000 people with diabetes into a grid that matches their glucose variability to their average glucose and you plot out at each one of those intersections. What the time and range is the time and tight range and time below range. That's what this grid is. And it has different colors because if you're in the green, that means your time and range and time below range are both in target. If you're in the red, that means both of them are out of target. You have too much hyperglycemia and too much hypoglycemia. So you wanna be in the green and this and the brown and the yellow are sort of on the side. But this is actually an amazing correlation of data that if you have two of these variables, you can figure out the third. Um If you have the average glucose and variability, I can tell you the time and range. If you have the time and range of the average glucose, I can tell you the glucose variability, something I never really realized was possible. So please bear with me and you'll dig into this later, I'm sure and appreciate it. So let's say, what are the current standards? Remember, the, the A GP says less than 36 for the variability and trying to get uh time and range down around a one C of 6.9 or GM I or an average glucose of 150. And, and that's where we are. What does it turn out to be? It turns out that your time and range is 70 your time below range is four when you're at 36 and 150 for 20,000 patients, those who fit into this, this segment. So that's pretty amazing that they all line up that way that because we picked them independently, we said 36 makes sense and uh um 70% time and range makes sense. Well, that correlates uh nicely. So there's my patient and they're there. And now what do you do to improve that person's care? Well, you can't just increase uh reduce their average glucose because they're gonna get hypoglycemic. And, and you don't want to let up on their average glucose or they're gonna have uh less time and range. So you've gotta move in this direction. You've gotta, you've gotta increase their, you gotta reduce their variability like from 36 down to 32. If you got to the same average glucose of 150 but you have a variability of 32 you have 73% time and range and only 2% below time and range. So you're in the green. So I really think that we pick 36 but these 20,000 patients and more are telling us you need to be somewhere under 34 under around 32. And if you actually wanna get to an estimated a one cagm I of 6.4 an average glucose of 130 you've got to be less than 32. So um when you get down to an average glucose of 140 you're 80% time and range almost at 3% hypo. So, so I think, and you tell me if you agree, it's probably changed time to think about revising the glucose variability metric to be closer to 32 or less than 32. So if you hear that discussion going, it really comes out of correlations like this. Now, that are possible because of all the CGM data that we have. All right back to the A GP. Um Here's one with a variability of 45 way too high. Um How do you attack an A GP in three steps? You determine if you need action if your time above range. Uh If, if, if your time in range is too low, if your time below range is too high, this person needs attention, where do they need attention? They need it where you see the red, wherever your, your spread is the highest, wherever there's more variability because you want this to look like this, you want it to be tight and narrow and in range, flat, narrow and in range. And you wanna set up a follow up to keep monitoring and adjusting to get there. So determine where to act those three steps. We'll get you a long way to knowing what you need to do. And it's not just you, the patient needs, the patient has the phone, the patient has this data available. They need to know their targets that they see on the phone. With the glucose data. They need to think about food and activity and medications and well being. This is that very similar to the grid. I showed you about uh glucose variability because a patient can reduce that variability. And here's what they do. Now, here's what we hope they'll do with your training and teaching. They'll look at their profile and they'll say, why don't I try something different at one or two or three of these meals and get a profile like this. It's amazing how that can work. How about on the clinician side where we talk about more retrospective looking at the data when it's aggregated into an A TP report. And the clinicians say, oh, but I've got so much to deal with, I've gotta deal with more than just glucose. I gotta deal with weight and with complications. Well, that brings me to the case, putting all this together. I'm gonna present this case and I'll do a little few twists on it. And here's a person who's 66 with two, diabetes for eight years, £250 A BM I of 37 A one C of 8.7 with some cardiovascular risks. Um, and, uh, abnormal, um, uh, kidney function just slightly spilling more protein. So they're on Metformin uh alone. So this is not an insulin patient. They're on Metformin with an A one C at 8.7 shows up in your office overweight, high risk for cardiovascular disease. What do you do? Well, we can all talk about it but A G LP one seems like a really good choice and there's many good ones out here. This, this one was selected to the glut, uh SG uh uh A G LP one receptor agonist. Also CGM was ordered and a referral to a diabetes educator that is always a smart move um uh to get the team involved. So what happens? Patient had an A one C at 87 and you started this medication. Here's their first profile. Now, I don't have a profile before you started. So this is now on dulaglutide, uh G LP one receptor agonist for a number of weeks and their profile looks like this. So it's still abnormal, but you'll see the A one C came down from 87 to about eight based on the CGM. So I bet they looked worse than this to start with, but here's what we've got. Um And here's the blow it up, there are 51% in range and no hypo. So they really need to work on tightening up that time and range. So, what would you do? So we know the problem, but what do you do uh with this patient? Um So they're not a goal, I'm bringing back my grid just one more time just to show you where this person sits and show you how amazing it is. So this grid predicts for an average glucose of 194 um uh and a glucose variability of 26 that they're gonna be around uh between between 45 and 53. So around around uh around 50 which is exactly where they are at 51. And how do you improve this patient? Well, you can't, you can't uh you can't just say let's let's uh increase the le let's read, let's have less variability because if they have less variability, they stay about the same. This patient has a pretty tight variability. It's all just high. So you've gotta reduce the average glucose. And so what would you do to reduce the average glucose and to deal with those hyperglycemia? I think they're on a good drug. Let's just go up on the dose. Now, you're on uh 1.5 mg per day of the. And let's see what the profile looks like in this patient. So here's the, here's the profile now in the patient on 1.5 mg and you see, it starts to flatten out a little bit. The hyperglycemia comes down, the average glucose went down from 194 to 167. The A one C is 73, but you're still, you still have uh 64% time and range. So you, you're making good progress. What would you do next? Well, I think you're on a good roll. Actually, I welcome others comments, but I think you just go up further because you're really making good progress. So let's go up to 3 mg and look at the curve now again, more time and range uh up to 73% A one C estimated 7.1. So now you say, gosh, I've made my target of over 70. Um and this is where the patient is. The variability didn't change, but the average glucose got better. So you're making, you're making really good progress at 3 mg, but there's still room for improvement. So why not go up to the next dose and ask them a little bit about what they're eating because there's a little room at lunch. You can see and at dinner, uh maybe if we plotted it time and tight range, you'd see those uh show up even better. But I'm recommending we go up to 4.5 mg, the maximum dose of this G LP one receptor agonist. And let's look at what happens. Now we have, I think what you'd say is an incredibly acceptable 76% time and range um barely above 180. Um And the patient is way over here, we tightened up the variability even. We kept them at about the same average glucose. But look how tight it is. So, are we done? Well, first you got to summarize and talk to your patient and say 87 to 73. That's remarkable. You still have a albumin creatinine ratio of spilling more protein than normal, which as you know is 30 you're treating your heart by taking the G LP one. How about the kidney? Why not, why not just add um a SGLT two inhibitor to this and see what would happen? And we did that. And um this is one of those rare times you really have the CG MS in sequence. And here's what we got to now a time and range of 88% because the SGOT two just took off those values mostly over 180. And the, and the, and the patient has more green uh and they're pretty flat, narrow and in range. Uh and that's where the patient ended up uh with a, an average glucose of just around 140 a very tight coefficient of variation. So incredible progress increased to 88% patients pleased and they've helped their kidney and their heart uh risks in incredibly. So I hope that case was instructive for your information in the ha in the some in the att D. You're gonna see some abstracts this one by Eden Miller. Really? Right. On the same topic. I just thought it was a perfect fit. If you have time, just go and look how G LP ones plus um A freestyle Libre sensor versus G LP ones alone reduced the A one C even more. So people who were um using a G LP one and AC GM had about a 0.4% more reduction. And if you're on insulin, same thing, you just get a little added benefit by using CGM in addition to a G LP one receptor agonist and the last one by Dr Eugene Wright also will be shown during this meeting and people who are on a G LP one and they're, and they're, and they're struggling. Um even adding a AC GM to them, got a significant reduction, whether it just encourage them to make more lifestyle choices, encouraged them to take their medicine. Um and each of the, each of the CG MS, each of the G LP ones uh had a benefit by adding CGM. So CGM, um I think does add to uh moving you in the right direction to optimal control. So in closing, it takes a team to manage uh diabetes and there's a lot to deal with. Yes, we focused a little more on glycemia today. But you could see, I touched on cardiovascular and weight. Here's the goal again. Let's get everybody who could benefit access. Let's get them more green and less red and time and range and maybe even time and tight range and get the curves as flat and narrow and in range as possible. And I'll finish with. The goal is to get to these targets. And the action is you saw me emphasizing move that average glucose down, tighten up the CV. So these are sort of um equal components of measurement and management. And I I I hope you enjoyed this interaction of all these metrics as much as I learned from uh reading these recent papers. So thank you for your attention and look forward to your questions. Published Created by Related Presenters Richard Bergenstal, MD Executive DirectorPark Nicollet International Diabetes CenterAdjunct Professor, Department of MedicineUniversity of MinnesotaSt. Louis Park, MN
