Hey, thanks, everybody, for joining me today for optimizing the use of sensor based glucose monitoring in persons across the diabetes risk continuum, it's really the intersection of monitoring, therapy and technology. This is a year 2021. Best practice technology based advanced programs in diabetes care for our road maps to clinical success in diabetes management. So today are learning objectives are applying C g m metrics that time and range glucose management indicator and a GP reports to persons with diabetes on aural anti diabetic drugs. We're gonna explore how see g m optimizes health metrics and overall management of diabetes and persons on aural medications. I am Dr Eden Miller. I'm the director of diabetes and obesity care. I'm a board certified family practitioner, a Diabate ologists, and I have my diplomat status in obesity medicine. Here are my disclosures. So let's get started. So see GM systems are more than just new monitors or new self blood glucose monitoring. They really move us beyond that point in time care, and they go into this predictive glucose measurement. It's more data and more insights into the individual person with diabetes, but understand that monitoring and all the different methods of continuous glucose doesn't mean that you're necessarily managing it. So we should really think of C g m. As beyond that really time glucose meter. It's going to be used as a predictive in a retrospective and therapeutic tool. I believe it is going from a 30,000 ft view of diabetes to a very individualized, personalized metrics for control and monitoring. And as we become more familiar with us, it will only enable us to individualize and specifically care for those persons with diabetes. So the question often is to see GM or not to see GM understand it would see is just an average. And I know it's a metric we're very used. Teoh. I don't think it's going to go anywhere soon, but it really is a retrospective three month average of control. I often use the funny adage of if I was speeding in my hometown and I was going 30 and a 20 and the police officer pulled me over and said, Dr Miller, you're going 30. But I told him my average speed is 20. He doesn't really care, because at the time I was going beyond that recommended limit And so it's how the numbers that encompass in a one C can also represent that it's just this average. And we don't know if that a one C average has been validated by those different glucose range is what we termed the time and range, and so we can see persons with diabetes have the same. They would see the very vastly different glucose ranges and risk of hyper and hypoglycemia, and it really takes diabetes out of the past into the present. And sometimes things just don't make sense when we're looking at a person who we would consider see GM for because the one c seems very disc uncork didn't thio what the patient is reporting or if they're just testing once per day. In addition, I find it to be a tool that patients can increase their own engagement. They're really not tracking and participating in their disease, and oftentimes is because they just don't know what direction to go in. And so this can often improve that patient engagement. It's also very specifically for those even they have alarms systems of C G M for those individuals that are at risk for hypoglycemia because it really is an independent risk factor, and we need minimize this. We probably have no real concept of the risk of hypoglycemia, even for people who are on aural agents that have a tendency for hypoglycemia to incur now. Often time I've asked, you know, what can health care providers benefit from using C. G M? Because we look at it is, you know, time is our biggest commodity and many of my colleagues were like, Oh, but it's more time, but it actually with the input of some time and training, it will give you so much mawr information that will actually improve your contact with individuals. It will actually, in some cases, allow for an improved a time saving or more efficient interaction. As I mentioned earlier, it really gives our patients and opportunity for increased engagement. Understand, If you haven't engaged patient, they tend to do better. They can also shoulder some of the burden of their own disease, and you're equipping them to do that. It provides increased hypoglycemic awareness that can lead to prevention because we don't even fully grasp the cost of hypoglycemia in the clinical setting. I think one of the things that would become quite evident as we really unpacked. The role of C. G. M. And how we manage persons with diabetes is we really don't have a good sense of how each therapy, how each drug or each, you know, stress or diet are all those things impact glucose management. And instead of you know, all therapies being the same, they really will have their own fingerprint. So we also see this compiled printable data. Those air those a GP reports that we'll talk about They show the hypoglycemic risk. They show the glycemic excursion. The hide alot the variability, Which means how much around the average glucose is this person? Are they going straight up to these very high peaks and down to these valleys? What about those risks of hippo that they're having? At what time are they having them? And so these compiled principal data allow us to really get a personal insight into the individual. So, as I mentioned earlier, equal a one sees do not equal time and range, and this is kind of just a graphic representation. If you have a patient A on the left, with anyone see of seven and their Onley checking their sugar one time per day, or even if they're not even checking their glucose at all. We assume that that a one c of seven says they're 100% time and range, but in reality we don't have any idea based on the a m N. C. What it's made up, what those glucose is are made up with. And so when we look at patient be they have a name one c of seven. But their time and range is only 63% as indicated by the green graphic. But they're having hypoglycemia of a percent, you know, less than 70. And they're having hyperglycemia above target greater than 1 80 29% of the time. But if we go to patients, see within a one C that is identical. That individual has a blood sugar 18% of the time, less than 70 which has a much increased risk with it beyond what those recommendations are. The time and Ranger only is 24% with hyperglycemia representing 58%. And so you can see that the hypoglycemia well, we'll take away from the over overall glycemic average, and it just isn't represented by the A. One C. And that's why I really am impassioned and believe that a one C should be validated by time and ranger validated by C G m. To determine if that individual is at that appropriate target. Now here is an example of an ambulatory glucose profile. We turn them a GP. They're kind of like a heads up display of the glass, Xenia, and to orient you a little bit. You will see this a lot. During this presentation. We have that center dark, thick line which is called the Line of Congruity, which is the Amalgamated Glucose data. So it's easier for us to interpret to see that, on average during this two week profile that the patient's blood sugar can be seen during the daily model we see, the rate of hypoglycemia is represented on the bottom, where they approach that threshold, why they're at risk for it, and what happened previous to that with those trends, the up and down and then we see the variability, which is the glucose deviation from the mean called the standard deviation. In addition, we see the hyperglycemia. We call that the cloud you know, and we want to be mindful of the cloud. But all of these components will help us look at the individual to see what glucose is they're experiencing, giving particular a one C and so the a. G P report, which is that the actual data driven into kind of the sub headings are those that were starting to kind of unpack. We see that the person wore the C G. M for about 14 days. They were adherents about 100% of the time. We see the target range is on the left hand side. That air recommended for a particular individual, and we will go over those briefly in just a moment. We see the average glucose, which understand the average is just a knave ridge, which is then also represented by what's called the glucose management indicator on the left side. Now you may look at that and think, Wow, that looks a lot like an a one C. But what we need to be mindful of is that that glucose management indicator is an average a one C or G m. I. Based on the data for the two weeks, it will not necessarily be identical two and a one C. That's a retrospective three months. But you could say that a person in their current therapy, if it continued, may have a possible a one c very close to this we see below that that's a variability. The variability really represents inconsistencies. When the glucose is very tight, we know that they're very consistent, just like data points in statistical significance. The tighter the data is, the more reliable it is, the more variable it is, it means that other things are happening in the person, whether they're not eating at appropriate times, where they're exercising differently or they're skipping meals or they're skipping medications. And so that's where variability comes in. And then on the right, we get our little thermometer read and very crimson. The red being are low and very low, and those air those thresholds of low being less than 70 and very low being less than 54. We have that target range, which is established by the T IR Committee that looked at What are we trying to accomplish with people to get the best normal glycemic range and then we have the high and very high, respectively, so you see that you get this both visual report as well as the data compiled into meaningful metrics. Now can we correlate time and range in a onesie? I say this a lot. You can know the A one C, but you don't necessarily know your time and range. But if you know your time and range, you can know you're a one C and so we can see here that the confidence interval depending on time and range. You know it is by very correlated with the A one C, as I just mentioned. But understand that I think the greater metric to be aware of is knowing a person's a one. C. It shows a quite random amount of time in range. And so that's why there's this big push for us to get a better perspective of glassy me. I go beyond the metric of a one c and look at this time in range. So here, before you hear the international consensus for time and range that was published in diabetes care and this is recommended for the individuals and persons with diabetes on the left, you see those with type one and type two who have not as many risk factors per se for hypoglycemia, and you could see the recommended time and range percentages percentages below 70 and etcetera. Now, if you move to the second graphic, we see those older higher risk both type one and type two persons, and that their time and range targets are little, not as tight. We minimize the hypoglycemia, but we're still trying to get mawr. We're still trying to get a fairly on average levels in the target range, but we will tolerate blood sugars less than 250 at a different metric. Now those in pregnancy the tightness with type one are quite tight, and we know that is we correlate with close glucose management control. We have better pregnancy outcomes and then in gestational or type two diabetes. There's even a tighter recommendation and a slightly different tolerance with our rate of hypoglycemia. Most of these are embedded in the A. G. P Reports, for the most part, will see the metric to the left of type one and type two, and you'll have to do your own additional recommendations for those special populations that we have discussed. So how do we interpret and a GP. You know, I kind of use this check off list that several of my colleagues that I've worked with previously have provided, and I first look for adequate data. I mean, if you have an individual who is either using a particular type of sensor where you scan or swipe where interaction is critical for data or individuals who are just not wearing their c g. M. We wanna look and make sure that we can make type of conjectures about data and appropriately interpret. And so I look for that adequate data I'm really looking for, you know, greater than about 80% of that where and that engagement. And it could be an opportunity to just stop right there and say, You know, I really want you to engage with your C g m a little bit more because it's kind of like you have a speedometer, but you never look at it or you have a gas gauge and you never determine if you're out of gas. And so that's part of that engagement. So that way, the data that I have can be appropriate interpretations. I always print off the A G p usually in black and white, because that's primary care. We can't afford color printers, but I mark it up. I have the patients sit there. I discuss with them. When do you eat dinner? Tell me about your medications. Do you ever miss them? How many times per week do you miss them? Which ones? What are your habits of exercise or sleep? And I market up there to be very personalized for them. Then I say, Well, what are you seeing here when I show you this report, and I often direct them to their own technology devices or ways to be able to see this even when they're on their own, I talk with them about patterns of lows, and I see Do you see where this these lows are? We? I think we should first address lows because of their risk of inherent complications and danger to the individual. I also talked to them about those directional arrows that many of them show on their their you know, devices. They're what we call their receivers, whether it's their phone or an external device or other types of technology. And then I illuminate those high blood sugars I tell them a particular time of day when they're most at risk for it. And then I discuss the variability as I mentioned earlier. Variability is inconsistencies when someone isn't consistent with life for their meals or their medications. And I asked, Are there ways that we could become a little more consistent? And so I reflect on what we have illuminated for this individual. I often will mark different medications as well, certain or ALS or injectable GOP ones and how they have their impact. And then we agree on an action plan. I, off them, give them a copy of that with all of my different scratch on it. And then we'll embed that other piece in the E h r, either through image or other importing, such as a PdF file. And you can see this is kind of these nine steps for effectively interpreting. So I'd like to go over a case real quick about an individual who was currently on Met Foreman. Azan Orel related medication, and she comes in. She's 63. She has had Type two diabetes for about 3.5 years. She has the proverbial secondary risk factors of hypertension, hyper lymphedema in class to a big city on When I asked her about her adherence to her medication, she says, is that sometimes poor because she has G I related effects and social often not get her dinner dose. And so when she came in three months prior with our initial appointment, she had a name when she have a 30.4. And so what I asked her to Dio is to wear this continuous glucose monitor, and I wanted her to follow up with me in the next two weeks on what was amazing is that this two week follow up again, this is you can see in the left upper hand corner 14 days of data, but only 80% of the time activated. And so we kind of got her a little bit before the 14 days. But it's definitely above that, you know, 75 to 80%. Her glucose management indicator shows that if we were to measure in a onesie with all of these sugars going forward, she would be at a 7.4 on. What the patient indicated is that she had never knew all the different sugars she was visiting in a day. She had this immediate, you know, see GM effect to the patient. I hadn't even had an opportunity to discuss with her about medications or advancing. We hadn't added anything we had. Actually, she reported to me that she could see how food with her breakfast would raise her blood sugars. How with dinner she would sometimes spike up and then come down. And she even noticed that times where she almost was near hypoglycemia. And she said, But how is that possible? I'm on a normal medication, and I said, But remember, you still have an intact pancreas, so your body, when you have too much carbohydrate, can kind of overdo the insulin on its own native. And so for her, it provided her that increased engagement and awareness of those glucose values. And so what we ended up doing because we discussed the fact that she still had these issues with metformin adherence, and so we decided to fully discontinue it. She was not taking the medication. In addition, we added a GOP one receptor agonist to the patient because she initially was, you know, above eight. She had the secondary effects of cardiovascular risk even though she didn't have coronary artery disease. She reported that significant increase of awareness of the effect personal, effective food, different foods for this individual stress and activities, as well as what the lack of adherence that the previous Met Foreman was providing. So we brought her back several weeks later, and her rapidly. When CIA that the appointment was 6.8, she indicated the adherence to a weekly GLP one was quite easy to Dio. She had no risks of hypoglycemia, despite having an A one c going from 84 to 68 And that's just this great opportunity where you can't tell if you're having hypoglycemia by just looking at the name one C or what your risk factors are. Her time and range was an exceptional 90% her high was at 10% and her management variability was at two 22 it's interesting her a once he was very close to her glucose management indicator. But remember, it's not supposed to be a substitution. It's just supposed to let you know in this two week period with those glucose is this is what we could expect and I love to use the G. M. I is a great motivator for patients because I could say, Look, if we were to look at your sugars now, this is if you were to continue it This is what you would have And so that's a really nice feedback for them now if we were to transition to somebody different who is a 72 year old male? This individual had diabetes for about nine years. They had secondary coronary artery disease, so established coronary artery disease. They had neuropathy, stage three kidney disease. They were on gloomy pure ride there on 8 mg daily, there on a statin and an ace. And they came to me with a blood sugar with anyone see of 9% of course, you know, slightly overweight blood pressure. Okay, but GF are mildly impaired, but no glucose management indicator on this particular one that we did for the individual. And that's because you can see in the upper part that the C G. M. Where they interacted with this particular one called the Freestyle Liberate that they only had 47% of interaction, even though they wore it for 14 days. Because this particular see GM requires a patient to scanner interact so you can see it. The ends of the A g. P. We have what are called data gaps. And when we have data gaps, we really can't make great conjecturing about what is occurring. But we can see a little bit of a picture. We see this overall person has elevated glucose is we see that they rise as they go towards their day and eat and they will come down as they wake up in the morning. We don't see any risk of hypoglycemia, but you can't really determine that because the amount of activity time I'm sorry, C g m is not very robust. And so what? This is what we would do in this particular person. We would say. You know what? We don't really have enough adequate data. And so I would like you to swipe more because we're using this library. We need to know when the medication is taken and its effect. I want you to make a mental note. If you're taking your medicine in the morning or what are those different activities and I want you later on. We're going to see if we can see this effect when you're engaging and looking at your sensor. I also want you to be aware of any lows or any arrows down or anything that you find yourself increasing that hypoglycemic risk, whether it was any exercise or what you did to correct for those. We also want to be aware of the high sugars that you're having as you interact and swipe, figure out if it's after meals or if it's overall elevated. And so then we will discuss later when we redo that A GP about some of the treatment, our lifestyle interventions that we can do for this individual. You know, maybe we need post meal reduction by adding a postprandial. Maybe we need to lower the fasting, but with blood sugar by other means. But we don't want to increase the risk of hypoglycemia in this individual. We want to keep all those co morbidity is in mind. So because of that initial A GP, we weren't going to make some specific recommendations because of the lack of data. But we knew that we really were having issues related with overall glassy me. Um, so this particular provider I chose the DPP four and we kept the Sophonie Arria the same. Now we could do other options, right? We don't know if the patient was intolerant to metformin is very possible. We could possibly add a national T to given his coronary artery disease risk factors. Right? We know those have secondary benefit. We can add a GOP one to that individual. Maybe it was possible. The patient where is having issues regarding injection, fear and phobia, which we always want to overcome Those inertia barriers. But for whatever reason, the patient was chosen at the DPP four. Maybe it was the kidney disease, which I don't really know for sure of. Why this individual chose that. But a short interval follow up was was requested by the patient, really wanted to avoid that inertia. And we wanted to make sure that they were swiping. We gave them a copy of the A G P, and we had them come back. So when they came back, we still saw there was a lack of engagement. We had a little bit more data, but there was a lot of being missed, especially which we call at the fringes or the edges. That's because This particular device only holds about eight hours worth of data, and so we want to make sure that they're swiping and interacting. We did see that there was a risk for hypoglycemia in the morning. And if you were only checking your sugars in the morning, you would miss all the elevated glucose is that were occurring even beyond, you know, 200 to 50. So we again discussed with them about how we need to make sure that we avoid those data gaps. We are seeing some hypoglycemia in the morning, but we're seeing this very high postprandial due toa lack of meal coverage. And so, with this current cerebral A C v A and coronary artery disease but no dirt in recent deficit that this patient just had were considering adding an SLT two and remove the soften area. Because this individual is having risk of hypoglycemia now with this salt and we don't want to really perpetuate that, especially with his cardiovascular disease. We could also add switch from a d. P. P four and add a GLP one because of his robust postprandial, so you can see based on the c g m. The fact that there's an increased hypo risk. He has coronary artery disease, a recent cerebral vascular disease. We should at least consider those that have cardiovascular risk reduction. Rami removing the DPP four, which really has no secondary benefit. Maybe eliminating the sofa in your area because of the risk of hypoglycemia. And so they aim for us is to really look at what does see GM provide for people who are not on insulin therapy or in maybe a basil insulin setting. And so, as you can see here, this very topic I actually presented for the A d A. This year with my partners Eugene Right, and Laura Bradner and the aim was to evaluate the change in a one C from baseline at six months to 12 months after starting a freestyle library system in type two persons on either long acting insulin. Just basil or no insulin therapy at all. So they included Orel agents in GLP one therapy, and you can see we the claims analysis retrospective Look at Quest Diagnostics. We looked at these inclusion criteria that we had below, and we obtained those. A one sees Clucas closest to that six month and 12 months. And what What did we see? Well, the reduction in a one C after Freestyle Libre initiation was seen in all persons with diabetes at six months and at 12 months as a cohort, as that involved cohort a 0.8% at six months and 60.6% at 12 months on the left. But the greatest statement see reduction in the Freestyle Libera users was seen in the non insulin group at 0.9% at six months and 60.7 at 12 months. You know, many of my colleagues right now are like I didn't consider see GM For individuals who are not on insulin or not at risk for hypoglycemia, it's because see GM is more than just for us. It's for the person with diabetes. It's also illuminating things that have been hidden for quite some time in their overall glucose management. And so I hope that this has been quite encouraging to you and illuminating to you for the utility of using C, G M and clinical practice for those individuals who are on aural non insulin agents. Thank you so much
