Thank you very much for the kind introduction and it's a pleasure to have an opportunity to present today. I'd also like to welcome you to this session and I'm particularly fond of this title. C. G. M. As a foundational principle in the management of diabetes. So I hope in the next 20 minutes we can work through this together and determine how foundational C. G. M. Really is to the management of diabetes. Here's my disclosures. If you were asked to define, well what do we mean by diabetes management, how would you organize it? How would you put it into buckets? Well here's how I decided to do it. I thought that for good diabetes management in 2023 particularly focusing on type two diabetes. We need to monitor the glucose. We need to know what the therapies are and optimized insulin and non insulin therapy. We have to figure out for those on insulin how to deliver that insulin with the devices and over on the right side. I know it's kind of a big bucket but it's really important healthy eating and weight and activity and diabetes distress and health equity and social determinants of health. All of those go into diabetes management. So let's just start over with these pillars. I might some people are calling them pillars these days of monitoring meds delivery of insulin all the external environmental influences. If we start with glucose monitoring 50 years. We've had the A. One C. You just heard a brilliant discussion about beyond A. One C. And but we've had it for 50 years with B. G. M. And we did the D. C. C. T. It's interesting this year. It's 40 years ago that it started it 30 years ago the D. C. C. T. Ended the U. K. P. D. S. Started a little before D. C. C. T. Ended a little after it. But the message was clear we can get a good a. one c. With these tools that we've had for a long time but the risk of Hypo is still quite high. And so then along comes see GM some 15 years ago you might say. But really in the last five years we've seen a huge pickup in the clinical use of C. G. M. So is C. G. M. Able to deliver on what we're really trying to aim for. As you just heard high time and range with a low time below range. That's really the metrics that we're looking for um in our glycemic management of diabetes. So is C. G. M. This tool we have really foundational for this whole management structure. I've just shown you if it's foundational then it should have some influence on the meds we pick it has had some influence on the insulin delivery. It should have some influence on this whole big category. So let me just run down that to try to build the case for the foundational nature of C. G. M. Let's look. First just at a couple of these. Not all of these but healthy eating diabetes distress, health equity can see Gm play a role in optimizing these. So we start with healthy eating and I show you the mobile study and you might say well wait a minute you got that wrong. That was an insulin titrate asian study. Not a lifestyle study. But you remember what it showed 100 75 patients uh C. G. M. Versus B. G. M. And the C. G. M. Did better by 750.4 it changed the standard of care. It started saying yes see GM should be used for people on basil insulin. But what you may not remember. I'm sure you do though because you're all well informed in this area. But the mobile study the average insulin dose actually did not change. That doesn't mean we didn't go up on some and down on a few. But when people stop and look at it they said well wait if you didn't change the insulin but you got a nice separation in the A. One C. With C. G. M. Was it lifestyle was this really a lifestyle um study that showed that C. G. M. Is really valuable in changing our diet and our food intake and it helps the A. One C. Well many of us have gone down this road and said boy we're going to start teaching people how to look at their phones with their with their C. G. M. Data. And we're going to teach them how to look at those spikes and look at what they were eating and maybe change those foods and see if you can level it off. So I am a big believer that C. G. M. Has a significant impact on our food intake. Um and our choices if we allow the patient to really look at it and guide them a little bit. So that's that column. How about diabetes distress? I'll just say that diabetes distress the burden of diabetes is real. The more there is of the distress, the higher the a. one c. But see GM tends to lower the diabetes distress gives people confidence and peace of mind. And so I think it is foundational there. How about the third the health equity for this I think is a work in progress but I think the whole telehealth issue we are now able to reach people we never could before. We can mail them A C. G. M. And they can get started and and they don't have to come in to visit. So it's not a transportation issue or where you live issue we can help people. So I'm pretty confident with more data we're gonna break that that equity barrier to as long as we're able to get them the devices and it's paid for. I think we're gonna we're gonna break down that barrier. So yes I think it does work over in that column. How about C. G. M. On insulin delivery. Well this is a slam dunk. I mean this is pretty easy this is I know type one diabetes but the C. G. M. Is the instrumental component of the closed loop system. Um Without it it doesn't matter how smart your algorithm or your pump is. You need the glucose data. So if you haven't read it yet had a chance to look at this endocrine reviews. Really nice summary of what is A. I. D. And and who should have it. And how do we really use automated delivery and where is it going in the future? So I recommend you you look at that. But there's no question that C. G. M. Is foundational for our insulin delivery systems to work effectively. How about on the medication side I know you might look at this and ask this question. Well what does C. G. M. Have to do with type two diabetes algorithm and management selection of the appropriate therapies? Well here's an algorithm. I know you all have seen it. It's an amazing algorithm really. And if this review of it really said the clarity and wisdom in this one paper is remarkable but what does it really show what this algorithm did was say? We have these five columns and yes I'll use the word pillars again we have these five pillars. CVD heart failure, kidney disease, glycemic control and weight loss. They're all actually equally important and need to be individualized and you need to use more GLP ones and more S. G. L. T. Two inhibitors and for all of those out there you know that the more you have a team helping you the better it is. GLP ones were everywhere. SGL T two s were everywhere. You don't see a whole lot of C. G. M. Mentioned here. But let me show you one example why I think C. G. M. Is foundational and actually getting to the right diabetes medications for type two diabetes. And this is an on duo remote virtual clinic where they took people with type two diabetes and did a CGM on them at baseline and then said what do we see what would be the best medication for you? And four months later in this large number of people they got a 1.6% reduction in a one c 10% increase in the time and range. But the important part of this slide of this study was the fact that they stopped the medicines that really less high value the clippers. I the civic Lipton. They increased the ones that that A. D. A. Algorithm we just looked at said were foundational were critical increased the GLP one started SGL T two insulin plus or minus if you need to decrease the insulin and decrease the insulin so you can get these organs saving a medical medications like GLP one and S. G. O. T. Two is in. So yes I think C. G. M is going to turn out to be critical even in the type two diabetes management space. Maybe it's not every day of the year but real time intermittently at least. So can we move from that left to the right? Can we move from this glucose profile to this profile? And we're going to look at profiles in a minute. But this is a lot of variability to less variability and a lot of hypo 10% down to 1%. How do you get there? That's the big question. It sounds like, well that's easy if I have this picture I know what to do but do you know what to do? So the whole field has really been moving quickly. Well maybe not quick enough for some of us but the data had to be standardized organized then we could really appropriately analyze it. So the standardization came with coming up with a one page report instead of 20 to 30 pages and putting it in three panels with the metrics on the top and the profile of the middle and daily views on the bottom. And if I just show you that top panel I think we're all becoming familiar I hope with the A G. P. Report and with this time and range bar which is so critical. Um And and we have what percentage each patient had and we have a table to say what the targets are. Um And then we have we have other metrics um as well and there's 10 of them that are sort of core to just saying yep I know how to dig into a C. G. M. Report. And these are the 10 that the A. D. A. has put in their standards of care after consensus of many of you in the audience, I'm sure. And those around the globe we need to know how many days so we have a good report that we have confidence in. We look at the mean glucose, we look at the G. M. I. I hope you know the G. M. I. Now it's that estimated A one C. Is another term for it. But Gm I came about because it's all based on C. G. M. Data to estimate what the A. One C. Would be if you took this mean glucose and continued it for the next 90 days. So estimated a one C. Personalized a one C. Which you just heard all about. Um So that's not my goal today. But I just wanted to say that I do think looking at the G. M. I is important. Uh We wrote a paper about it a few years back when we coined the name with the help of the F. D. A. And we show that some match up exactly others deviate from the from the A one C. A one C. To the G. M. I. As many as 30% were 300.5 different. Um That was our original study. Earl hurst said I want to check that out. And his clinic um in Seattle he did the same thing but you know when when he has a clinic he has tough patience of liver disease and renal disease and hemoglobin. Open these and iron deficiency. And he showed even a bigger gap that 50% had over 500.5 difference between their lab A. One C. And their estimated or G. M. I. Or estimated A one C. So I just want to leave you with the message I know you've heard already but this mismatch this gap is important can be clinically meaningful. So I would advise you to take a close look at that Gm. I it's the actual glucose levels the tissue exposure to glucose not dependent on the red cell lifespan and location and genetics. So just pay attention to it and treat to that G. M. I. If you have it available glucose variability. I'll just show you one Bit of interesting data that's coming up at this meeting. Yes. We decided on CV in less than 36 there's an abstract coming up by young gen U. Um and it's he he took a large group of patients um 29,000 and they looked at type one and type two and they looked at the CV and they looked at the time and range and there's a bunch of high math that I tried to understand But here's how I'll simplify it because I'm a clinician. Your many of most of you are clinicians. What they said is these 29,000 patients with an average glucose of 1 20. If they had an average glucose of 1 20 look how the C. V. Stacks up, you can have the same glucose. But if your Cv, if you're variability is low you can get a really good time in range. You expect that with the average glucose at 1 20. But when the CV goes up meaning you're going up and down and here you're really on the roller coaster. Even with your average glucose being Good your time and range goes down over 20%. So getting that variability down, getting rid of that hypoglycemia is really critical. So pay attention to that abstract when it's presented if you have a chance. Finally there's five time and ranges and in range above range and below range. All are important for us to keep track of 70% time and range about an A one C. Of 7 50% time and range about an A one C of eight. Yes, I know there is variability on both sides but it's nice to peg it to at least have an indicator. And then thanks to the leadership of dr battellino. We added targets to the time and ranges. It's nice to know where you are but it's even better to know where you should be shooting for over 70% in the standard 70 to 1 80 time in range and less than 4% for under 70 or 3.9 million moles. Less than 1% for under 54 or three million moles per liter. Those are really important numbers, particularly those three for me, 74 1. So here's the A. G. P. Profile, the three panels, metrics a profile in the middle with the median and the inter quartile range and and 90% of the values within this cloud and then the daily views A. D. A. Said that's a pretty good standard report. We'll put it in our standards of care in 2022 2023. It's updated you. You may start seeing this you're probably seeing it now. You'll see it more. The A. G. P. Now in color. It's really the same. But I think I hope you agree with me that at a glance you would say well that helps to line it up with the time and range bar because when I'm low here overnight um I can see it right on the on the profile. It grabs my attention and I think it grabs patients attention to if you share it with them and you look out here for the orange for the hyperglycemia. So it helps guide decisions and it helps in this process to get to this analysis part to really analyze it. So we went to our primary care physicians and many of you, I know we're seeing patients every day and you want to know how to interpret the A G. P. And a few years ago we did the nine step method and I thought it was pretty good, pretty comprehensive just understanding it. But nine steps sounds intimidating. There was a five step method that organized the data in a similar manner but put it in this nice flow that Diana Isaacs helped lead the charge on. But even that our primary care doctor said okay that's good. But I only got five minutes or two minutes to deal with this. Can you make it even simpler or faster? So that got us thinking to say well what do we really need to look at? And the variability I just told you I thought it was really important and of course I think the G. M. I. Is important. But the variability correlates with the hypo really well strong strong strong correlation. So look at it as you wish. But it does correlate and the G. M. I. And the average glucose really do reflect the time and range. So we could put those aside for a moment and the time above range really correlates with the time in range 0.94% or or or 0.94 for for an R. Squared. So I really come down to saying if you have these two numbers that the green and the red the time and range and time below range, you can really tell at a glance if you've got an issue if you've got a problem that you need to deal with. Either one of them or both of them need adjustment. So those are the three steps is action needed to optimize. Look at the green and red, you'll know in an instant if you're reaching your targets or not, this patient's not reaching them on either. So there is a problem. Let's see where the action is needed. First the hypo we address then the hyper but this keeps us going to try to get this into a flat narrow and in range curve. And you might say I haven't really heard that name before. Flat narrow and in range. But it's just something we came up with because patients always asked what should my profile look like? And we're trying to say this is what it should look like. Pretty flat, pretty narrow within this range. It's not easy. But together step by step we can get there. And that step by step means which adjustment do I make first, then I need to follow up and keep adjusting. So please don't schedule this on a six month basis but follow up adjust, adjust adjust. Okay, so That's the that's the plan. But now the clinician said, can you make this a little more actionable, tell me exactly what to adjust. So we just went back and said, Okay remember the time in range 70 and instead of four make it 3% because you want a little leeway. If you're going to adjust you can't already be at the edge of the target and then find out what category you're in. By category. I mean the green and the red can either both be green or both be red or one green and one red. And each one of those categories of time and range and time below range has a different treatment plan. So I don't have time today to discuss that whole treatment plan. But I just want to show you this one page that we're giving all of our primary care providers who are using C. G. M. To work through and just look at the time and range. Bar the green and the red find which category you're in. Then we have some very specific suggestions continue what you're doing. You're doing a great job. Think about stopping yourself on your area. If they're on one, if they're not on one, think about decreasing the basal insulin. We're gonna tell you a suggested amount of how much um start a GLP one or G. I. P. G. L. P. One and S. G. L. T. To remember. I said those were critical and these are the patients you want to do it in that they're they're not making their time and range but they don't have too much hypo yet let's just put this in and get them going then adjust the insulin later uh if needed. And then and then the final category is get a team to help you with. Both of them are out of rage. Really need a regimen readjustment and I hope we can apply some of these principles when we do cases in just a minute. So that's what I wanted to go through of trying to convince myself and you that C. G. M. Was foundational to the management and I think it is I think the C. G. M. Influences all of these management principles um to one extent or another. And we finally started to organize and analyze the data. Some of us are working to integrate it into the record to make it even easier. But what we really want to do is act on that data and I hope we've given you a little bit of information today so you can do that action and we'll do that when we do the cases. So the A. G. P. Is there we have some guided decision uh tools for the clinicians. So thank you very much for your attention and I look forward to your questions coming up in just a minute
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