Video Optimizing Use of Sensor-Based CGM in Persons with Diabetes: What Improvements in Patient Outcomes, Well-Being, and Satisfaction Can You Expect? Play Pause Volume Quality 1080P 720P 576P Fullscreen Captions Transcript Chapters Slides Optimizing Use of Sensor-Based CGM in Persons with Diabetes: What Improvements in Patient Outcomes, Well-Being, and Satisfaction Can You Expect? Overview thanks so much for joining me today. I am Dr Eden miller. I am a family practitioner, i a dermatologist and I am a diplomat of the american board of Obesity medicine. Today, we're going to have a really nice discussion about how to optimize the use of sensor based C. G. M. In persons with diabetes, what improvements and patient outcomes and well being and the satisfaction that I know you can expect both for yourself and for your patient. We're really going to go through it in a practical kind of case based roadmap to how to deploy C. G. M. And optimize it for both you and your patients. So here are a bit about me. I work in bend Oregon. I'm the co founder of diabetes nation and nonprofit for performance improvement for healthcare providers and I have found a diabetes and obesity care where I practice. I'm affiliated with ST Charles Hospital in Bend Oregon. We have current challenges and outpatient management of type two diabetes. I know we know that I know there are times we we talk about this and and we're like, yes, we understand that diabetes is a hard disease. I often indicate it's a marathon, not a sprint. I'd like to sometimes tease my patients saying having diabetes is like having a two year old that never stops crying and some of that challenge is to stay engaged for a lifetime because diabetes is progressive, it expands, it changes. We need to keep pace with them. We need to intensify the treatment at the same time, making the patient feel a part of this process and ourselves as health care providers not getting too burned out with it. You know, when we have that lack of intervention, the lack of timely follow up of touchpoints with persons with diabetes, we see what's called clinical inertia. It's very prevalent in the management of type two diabetes with the longest delays really being reported. When we talk about insulin initiation but also tie tradition. I would also agree that just even medication expansion, you know, going from one drug to another, we we see data that if a person's agency is greater than seven it takes years Years to change that medication intervention. If they have a name and see greater than nine, it's 18 months on average before something is done about it and we really need to overcome that. I mean there's many reasons for that because we we usually put together intensification with hypoglycemic risk and patients express that to us and all it takes is one severe hypoglycemic episode for us as providers to really try and distance ourselves through that. Unfortunately we were misinformed that if you increase the A one C you're going to protect against hypoglycemia. That that's not the case. We also see with everything going on in people's lives increased diabetes distress. One of my comments that I often make and educating my providers, my colleagues um is that those with high levels of diabetes distress are very, very un engaged. They're apathetic because they are so overwhelmed by their disease. There's very few people that have an absolute death wish who don't want to interact with their health care. So if you ever see somebody who is un engaged in totally apathetic, you really need to address their level of distress because that ongoing lack of lifestyle and treatment adherence really can persist and it can set what we call a legacy effect. When that occurs, we have this trickle down, increase healthcare resource utilization and costs because the patient is not attending to their disease and then not attending to their disease. The disease has its way with them. In fact, I often say when you ignore diabetes that's in charge and I really want to empower persons with diabetes to have diabetes rather than it have them. I think one other component in terms of scientific, especially in our type two population is we are not aware of the silent or what we call a symptomatic hypoglycemia. This will often happen in the middle of the night and we're going to explore that today in one of those cases and you're going to see how this isn't always known or isn't always illuminated or rather it can hide in other symptom Atala ji that is really hypoglycemia in sheep's clothing. So when we talk about a one c it has its value. It really is a universally accepted standard for both diagnosis. Now, when we look at, you know, prediabetes going to diabetes, it's a it's a good enough metric to have a statistical significance for the diagnosis. It's also used for monitoring of diabetes. But there is a lot of ongoing debate about what target is. I know you realize this, but diabetes is the only chronic disease that we treat that has three separate metrics. If you talk about the, you know, american college medicine, it's an A one C. Of eight if you do the A. D. A. At seven, if you go to the american College of Endocrinology, it's less than 6.5. But it is also an interesting comment that diabetes is the only disease were normal is not the goal. And that could be for many reasons because at the time, the tools we had had too much risk, right? And we looked at that risk of hypoglycemia. We looked at that target based on the person of how long they were going to live with diabetes. What are their comorbidities? What's their life expectancy? You know, But sometimes we try to do a one size fits all. And we can't take somebody who's in their eighties, who might be on diabetes, hospice or other kinds of hospice related issues and have a target. That's the same as somebody who's 25 who just walked in the office the other day with new onset type two diabetes. We have to be very mindful of the person in front of us. And so one of the things I have kind of tried to present out in the educational community is that we should still use A one C. But we should standardize it. And what I mean by that is it should be validated by time and range because you can have different A one CS and they they convey different Realities because in a one c. is an average metric, it doesn't tell the whole story. One of the things I'm becoming more aware of as I do more analysis and integration of C. G. M. And clinical practices this glucose variability. The highs and the lows that surround the A. One C. Right surround the average. The highs and the lows and that probably is really what drives complications including hypoglycemia. Hypoglycemia is because of the highs and the loves and that we don't get that variability in A one C. And the other obvious is that we don't see those short term variations. We see a point in time. I usually say, a person, you know, takes off their blindfold, they see what their current glucose is by self monitoring blood glucose. They see what their averages, but it's a retrospective analysis and it isn't anything current or prospective going forward. It really misses a lot of what we see in the variability of the world, of the world of all the different glucose is somebody visits. Now, if we talk about in a one C. They're not the same concept? We're kind of saying a dozen, you know, this person has this a dozen. But how big are those dozen cookies are they little are they big? And so when we say in A one C. If we look at three patients here A. B. And see and they all have the same agency of seven, it's erroneous to assume that patient A. With an A one C. Of seven A target. That means 100% of their time is between 70 and 1 80. No, because that average could be various combinations of different policy mia We look at patient bu as the same A one C. But They're only in time and range between 70 and 1, 80, of the time and the hypoglycemia less than 70 kind of negates the hyperglycemia, 29%. Now, if we go even further, you can even separate the data with higher variability even beyond patient b. We now have an individual who only is in time in range 24% of the time and 18% of the time they're hypoglycemic and most of the time they're above that target of 1.80. And so this is a person that has a high degree of glucose variability but yet they're the same. They're the same May one see Eden but they're not. And so that's why talking about validating an A one C by time and range. Now you can know the A one C. But not necessarily know the time and range that you can know the time and range on C. G. M. And no the a. one c. It's interesting how that is should be a complement to it. So the question comes up. You know who do you see? Gm? You know who am I going to choose for? C. G. M. Uh understand that You want to look at those with C. G. M. Because it is often just an average if you have a patient with the same A one C. But you're just not quite certain about what they need to do. We need to illuminate or magnify the glucose. It really will take diabetes out of the past in a retrospective fashion. Put it in the present and also be predictive. It's for those who just don't make sense. You know you get an A. One C. Or or they tell you there's a self monitoring blood glucose is 1 20 in the morning. Everyone sees eight. So that's that individual. I also use it for somebody who is very un engaged in their diabetes. Not tracking you might say, what do you mean? You're adding another thing. No, I'm illuminating to them because remember I told you highly un engaged patients really are have a high level of distress and by having a level of engagement that gives them empowering to minimize that distress. That's what you're looking for and that's why CGM is so imperative. Because it has a patient forward facing and a provider facing side as well, I believe. I think the for the probable hierarchy, alot of recommendations for G c g M is every person with type one diabetes should have a C G. M. Every person with type two diabetes who is on insulin, I don't care if it's just basil should have a C. G. M. In addition, if they're on cell phone area. In other words, anybody for danger of hypoglycemia, but don't put C G. M in a box, you can't just say C g. M is for people to prevent hypoglycemia. No, C g M has a very good job of doing that. But what if somebody is not at risk for hypoglycemia, why would you see GM increase engagement awareness of the effects? So don't LTD when you look at C G. M. Ask yourself what it can do for that person in front of you. Is it a safety issue? Is it attracting issue? Is an engagement issue? Is it for you because you we can't figure out what the patient needs, what what kind of additional meds, what kind of penetration do we need to do? So I really love how C G. M fills in the gaps. If we were to look at the person, you know, look at the graphic on the left and we say, okay, these are all a one C's, you know, with minimal glucose testing and they determine, you know that 2 to 3 month averages retrospective. You know, we see these different points in time. Okay? So so we've taken a one C and we add four or five glucose testing per day. Right? So we go from a monthly or or a three month average to a daily self monitoring blood glucose. But if we looked at that individual who had a particular A one C and they were testing this is somebody testing quite a bit. I would even say only four points per day because very few people even do beyond one, let alone be on four. Because Medicare and Medicaid will may allow four. But look at all the different glucose is we are missing on the far right hand side. I say C G M. Is the gps of diabetes it tells you where you're at, where you've been and where you're going and it fills in all of those data gaps and in filling in those data gaps we can illuminate, personalized care and personalized directive for advancing of therapy. So this is one of my favorite studies. This actually, to me change the way we looked at diabetes. There was a real world update. It was using the freestyle library system. It was an analysis between the frequency of scanning, Right scanning how many swipes per day. So that's on the bottom. So if you look at all of that, that's how many swipes. zero swipes. 10 2030, 40, 50 Swipes. Yeah, 50 swipes a day. You know, nobody got to that point. But if we looked at how much a person engaged, let's call it engagement opportunities, how many times they engage with the media? And then did that have an effect on their rate of hypoglycemic? In the first table? Their rate of hyper glycemic in the second table. And how did that correlate to time and range in addition. On the other axis. We looked at The A. one c. So what am I really trying to say? Well first of all this was done with the original freestyle library system that did not have an alarm. So we really have often thought that alarm systems are the only way to detect hyperglycemia. But if you know what you are without an alarm and you're engaging in your glucose, you can prevent hypoglycemia. So the first thing it demonstrated is that just engagement in the glitzy mia prevents hypoglycemia. And we see on the first graphic that the more the scans they had, the less hypoglycemia they had and that there was a sweet spot. So let's call it engagement, whether it's looking at your CGM swiping your CGM engaging with the data that that sweet spot really was at around 18 engagements per ticket when he went beyond that it just became slightly neurotic. But it's still actually improves the hypoglycemia crate. Okay. And we saw that that engagement Parallored or Mirrored the A one C. So wait a minute you're telling me eating that the A. One C. Improved to a very very low level Of like 6.7 yet the hypoglycemia dropped. So that metric right there turned that information on the head. So if there is one thing you get from this presentation, the destination A. One C. Does not inherently have a risk of hypoglycemia. It sets you how you get there. It's what you do getting there. It's that you know if your hypoglycemia and so if you illuminate the listening to the patient they don't get hypoglycemia even though they improved drastically their A. One C. Now the same thing happens as the second graphic. Their hyperglycemia make the more they scan the more they engage the lower their a. one c. gets in the lower the hyperglycemia episodes occur. Big surprise. I know you're kind of saying well this makes intuitive sense. So of course dr miller but at the same time many of you are elevating the A. One C. To protect against hypoglycemia. And if you see on the far left quarter there that anyone see is 8.2 it has the highest rate of hyperglycemia because they're blind to the glucose. So if on the far right if we superimpose both both of those as we improve the amount of scans we improve time and range. So knowing is control knowing is power its power for you and its power for the patient. Now let's talk about some of the studies that demonstrated this. Yes we want to give you evidence for the utility of this and we're telling you that C. G. M. Is not just for the type one diabetic it's also for the type two diabetic. And we looked at about 1300 patients male and female different ages and we looked at their baseline A. One C. At about 86. And what we found is that the real world demonstrated the use of this particular um C. G. M. The freestyle libre system resulted in improved well being. They had an improvement in their quality score of quality of life. They had decreased in the disease burden are distressed and they had improvement in the A. One C. There was also a decrease in absenteeism uh from work and diabetes-related hospital admission from 18.5% to 7.7 in the type one population and from 13.7% to 2.3. So this study showed not only did it improve a one C. It improves the patient's quality of life, it improved the workforce. It also decreased costs by limiting those diabetes related events and these were both for Type one and Type two persons. Now this particular study I was involved with did a presentation for the A. D. A. Last year session and it really was to looking at the A. One C. Reduction after you start a free celebrate person with type two on whether or not they were on basil insulin or no insulin at all. Okay so we took type twos. They were on basil. They were on oral anti diabetic agents. You're gonna ask me if they're on GOP one's. Yes they were so basil insulin. No insulin. And we looked and laura and gene and I looked at this data and evaluated the change in A one C. Baseline to six months in baseline to 12 months. And we did the data. There's limitations you know because it's a perspective data. We indexed it. We didn't have all the particular necessary metrics of how often they used it. But we looked at the library view which is the platform for data demo. We did the A. One C. By the quest diagnostics and we reconciled medications and ongoing utilization. So we needed ebony was greater and equal to 65 within the six months prior they couldn't have you see Gm. And we looked at the 180 the 360 days. And this is what we saw. Remember these are type two persons. The left hand side group is those that were in all of the group. The whole group right? All lumped together. We saw in the first six months in an A one C. Drop a 10.8 at six months that anyone see drop a 60.6. But what if we took out just the persons who are on oral anti diabetic agents? So the group to the left is everybody together including the basil group. But if we took those out that were just on oral anti diabetic agents, they had the greatest drop, you gotta be kidding me. So what does that do to its due to engagement in their own like xenia participation in their own disease modifications of treatment based on results. Because generally we wouldn't tell these people to even test yet. Real world ongoing see GM analysis is so highly beneficial. It's beneficial in a different way. And so if we kind of continue to go on, we look at type two diabetes and the use of real time glucose monitoring. We looked at this particular uh paper from Jackson and Dr Andy Almond. It was the role of C. G. M. As a teaching tool to improve lifestyle management. In addition we looked at those with Type two diabetes. This was kind of taking you know those um who were on particular therapy and whether you know, it was beneficial for those who maybe don't just use insulin because we've often, you know, compartmentalized see GM for those insulin users. But it has a profound impact and real potential for preventing diabetes complications. And all persons with Type two diabetes. And so what it really is is a lifestyle tool or a personalized tool, you get to see how food and stress and medication adherence and all the different things affect glucose. It really is an ownership for that. And so this was one of those particular studies that looked at that benefit outside what we typically see. And they go on to say the authors go on to say wouldn't that be very helpful early on in type two diabetes? And heaven forbid you know, pre diabetes where they can start to see different foods and activities that have either negative or positive impact of their overall glycemic control. And so you know, IRL Hirsch and I did analysis as well and we were looking at both Type one and type two diabetes. So all comers on C. G. M. And we were comparing the freestyle libre Rey as well as the competitor dex calm. And we kind of had equal cohorts around 303 50 or so individuals. And we randomized them to being on the C. G. M. Looking back actually retrospective looking at a one C for those on decks, comment those on freestyle libre because we want to know is there any difference now granted this is a, you know, a comparison of looking at that and what we found is that, you know, there was no difference between that and what we see is that the C. G. M. Participants either on the freestyle libre or the decks com whether they were type one and type two, they didn't have any differences in terms of their a one C change. They were not statistically different. What's not presented here. Because I know the data and I can tell you this is that more individuals who had lower your social economic, more minorities and more type two more individuals who saw primary care uh utilize the freestyle libre system versus decks comdex calm was more consistent with um caucasians, those in endocrinology practices and those on insulin. And so they were kind of interesting to see those differences percolate out. Although that trial was not looking at that, we got to see differences. But when boots on the ground occur, bull systems are effective in lowering A one C. You know, this is a trial that I'm happy to report. I have made some presentations earlier. This just came out and this is the result of the mobile trial. So this is dex calms um analysis as actually an RCT. It's a randomized controlled trial. Looking at those persons with type two diabetes who are on basal insulin. And so they were placed on the decks. Com CGM system to see what the effect of the continuous glucose monitoring had on that. And so the question was, is if you have an individual adult with poorly controlled type two who's on basil insulin with or without Grandal in without Crandall insulin. So in other words, just on basil, we want to see if just a basil can improve your A one C. And so the findings were 175 adults and they a one C. Was a greater decrease over eight months with C. G. M. Versus those who had that clinical trial effect. So we saw a minus 1.1% in that cohort on C. G. M versus a 0.6 percent. And so the meaning is that C. G. M monitoring resulted in better glycemic control then self monitoring blood glucose and adults with poorly controlled type two diabetes who were treated on basil insulin. And they didn't even do mealtime insulin. And that's just using C. G. M. For uh for a person on basil. Not only that there were significant protection against hypoglycemia as well because basil insulin does possess that. And so here we're kind of some of the graphic results of the mobile trial. You can see that the blue line is those with self monitoring blood glucose. And you can see the C. G. M. And that's the mean glucose by the hour of the day as the compiled data. So we see less variability and we see better improvement of control. And we see minimal risk of hypoglycemia by just placing a C. G. M. On a person. So this was a study that I was involved in the U. S. And Canada. It was a joint study but this is the Canadian publication of it. It's called the refer basil. It's the freestyle libre 14 day retrospective analysis by looking at those patients on the freestyle libre system who are just on basil. No no postprandial, no mealtime insulin. Just basil insulin. And this is the Canadian group that have already published their data, ours is forthcoming and so it will be combined. Canada us group similar findings of improvement in glycemic control, slightly different between the two. I I really think it's because of how we prescribe basal insulin more here in the US. But by looking at this retrospective real world chart review, what we saw is that the A. One C. When adding a freestyle libre two person on basil insulin improved by, You know, .9% in those individuals significant decreases up to 1.1%. And these were just individuals who we looked back. We didn't even it wasn't a prospective trial. We just essentially identified those individuals on basal insulin, identified those who got the freestyle libre system, made sure nobody was added mealtime insulin during that time. And we looked at that result of a one C. At three months and six months after starting the device. And at that three month time frame we saw 1.1% drop that continued and extended out, you know 0.9 to one at that 3 to 6 month time frame. And so it really showed again with a different system that positivity for C. G. M. Even in the basil insulin world. So now I'm going to shift gears a little bit because I I think I've been very clear of the utility of C. G. M. And one of the things is that there's no question that the person gets improvement with it. Uh Just even you know immediately out of the gates the protection, the engagement. But as clinicians we get a large value out of it as well in terms of analyzing the data and I think this is where a lot of the learning curve is the steepest because you get these reports and you need to make sense of them. What I can tell you is their patterns and that each drug has a fingerprint and it kind of reminds you back in med school when we did scaled scaled insulin doses and we were doing insulin curves and that kind of thing. So I need you to really work on becoming familiar with how this nomenclature is what it can provide you and understand that the proof for the direction is in the map in the glucose map. So we're going to review through a couple of cases of how beneficial it was for us to know these C. G. M. S. And then what we did to take action with them. So the first case is a 63 year old female. These are all real people by the way that I see in my practice here and she had type two diabetes for 3.5 years. She comes in as a consult because her diabetes area when she's at 84. She has a proverbial hypertension hyper lymphedema, she has Class two obesity. Her current diabetes really a medication is Metformin which is what we do right first start with Metformin. But she really talks about poor medication adherence and engagement. You know she'll take it for a few days and she won't because she gets gi related side effects for primary care provider. Uh didn't really uh ascertain her adherence and discuss why she had had poor adherence with the medication. She was kind of reluctant to do any other uh interventions of medicine which many of our patients are. And so I said hey why don't you wear a C. G. M. Why don't we give you this personal real time C. G. M. Not a pro but a personal one so she can engage with the data. So she really is aware of what her glucose values are. So this is our baseline report. So you know we had her come in in two weeks now. It's interesting member I told you here when she was 8.4 that was when she came in that three-month retro. This is her baseline meaning I put it on her. I had her come back in two weeks if you can see the data looking at the chart. You see something called a glucose management indicator that G. M. I is just a rough estimation of the A. One C. With this two weeks of data going forward. Like if she kept it the same way for the next three months free when she would be around 7.4? So even before I was able to bring her back in the office, right two weeks, bring her back in the office, I see improvement in our over glycemic management. We see that there's a fair amount of variability, that's the width, you know, So when you look at these reports, you first look at hypoglycemia, does she have any hypoglycemia less than seven? Pretty Much No, Maybe one episode. Uh what is her variability? What's the time of the day that has the highest durability? It's actually for her in the afternoon, What is her time in range? You know she's only at 56% time and range time above range. But she doesn't have really high placing as a big burden. Big surprise. She's on metformin. But look at just the level of engagement in the first two weeks. She is like wow, I am seeing these kind of effects. And so as a result of this report, I said to her, what do you want to do? And she said, you know I'm really having troubles with my Metformin, I really don't want to keep taking it. So it's like fine let's get discontinue it And she reports that she is so more aware of the effect of food and stress and lack of her adherence? Her variability of her glucose is and I said Why don't we start a GLP 1? You know something that you don't have to adhere to as often write once a week. That is what I chose with her. And she says she still wanted to be using the freestyle libre Rey in this particular case that she was using it. She calls it her diabetes, diabetes accountability partner. I was like okay sounds good. And so you know 14 months of initial baseline you might say did you see her before that? Absolutely saw her before that. But this is kind of the, once we learned once we tie traded the GLP one, once we got to where we wanted to get this is what we have her glucose management indicators 6.6. And that was because she was doing really good right before she comes and see me her rapidly when seeing the office was right around 71 so we still have a little bit of room to go. She was very adherent to the mid range dose of GLP one. Since then higher doses have come out and we have increased that are variability has massively improved and our time and range now Is that 90 and and look at what this did for the person. Look at what it did for me, look at what it did for her variability and also you know look at her a one C R A one C is 71. Yet her time in range is very very good. And so the question is you know is that good enough for her or do we need to push the envelope a little bit more? Okay let's go to another case which I think you will find very illuminating. Also a patient of mine elderly woman I've seen for years with diabetes. She's 72. She takes 12 minutes of charging in the P. M. And three in the am I know you're like why are you spending the large in that? That's what she's been on. I know it's not FDA approved but this is what she's been doing. She was taking 10 units of liberal with lunch and dinner. She had an SCL T. Two in the background. But the big thing is is that I got the appointment scheduled. She came in because she was confused in the morning and so her a one c. 74. Her G. Fr is you know class three A renal failure. So you always have to be mindful of those individuals with renal failure and diabetes and just things just didn't make sense. She was also sometimes eating a low carb diet so sometimes she wouldn't take any insulin with lunch sometimes she would take it with dinner and her daughter was here and says you know I just noticed that some of the times are worse than others when she wakes up. And so at that initial appointment I'm like okay I'm gonna put a C. G. M. On her. She's on insulin. I don't know what's going on here. We have a name and see of 74. She told me maybe she had hypoglycemic awareness once or twice a week but she didn't know how low it was. And so I put a C. G. M. On and I said come back in two weeks come back in two weeks. I want to look at the data. I'm going to show you what the first download in the office was. Here. It is this is massive. Look at this severe hypoglycemia. Now you might say you know there is gaps here that data gap is if you don't swipe the freestyle libre every eight hours you get a small data gap because it has to hand off the data. But look at this this is a you know get on the ski lift. Remember where you go to the top of the mountain and fall off the mountain. So now let me show you something else as well. Imagine if she was doing self monitoring blood glucose. Imagine And you had her check her blood sugar at 8:00 in at 9:00 AM. Sometimes she would be less than 70 year ago. The known hypoglycemic convince other times she would be right on target. Imagine if you were checking their blood sugar in the morning and tight trading her long acting insulin to that fasting blood sugar. You have no idea That 22% of the time. She's less than 70 and 12% of the time. She's less than 54. So I don't need a neurology visit for mental status change. I need to massively affect this individual's rate of hypoglycemia because it could be detrimental, cognitively cardiac wise. This is an elderly woman who's having unrecognized severe hypoglycemia. And if we were to just stop at the A. One C. Of 74 and try to titrate more basil, we wouldn't have seen this. This is an immensely valuable data set for this patient. So what do we do with it immediately? Immediately decrease the basil insulin don't have as much. I added the GLP one. Why? Because she's older. She needs some simplicity. I wanted to back off of the insulin and just do it with dinner. Right. Just do it with dinner. So what is the C. G. M. Show me, what does it show me? It shows me that I don't have the ski lift as much. Still a little bit with dinners. There's some variability there we have to address. I still see some hypoglycemia. I see it in two areas. Sometimes in the early morning we see it at six a.m. There and then sometimes again in the evening Hur Ray one. She's the same at 7 3. But her rate of hypoglycemia was 12% less than 54 and a woman like that in a 72 year old. It needs to be zero. So we still have some things that need to be done. We need to actually back off on our basil probably a little bit more. We need to really watch the perennial insulin for dinner. We might be able to increase our GLP one and get rid of the perennial insulin altogether. But you see how this change this individual and a rate of hyperglycemia, there's still work to be done. This is just the, you know, two month follow up for this individual after this. And and so we're still improving in terms of our overall direction. So case number three is a little bit of old school insulin for many of you who are trying to save a buck by saving your patients money while you're spending their life. This individual came to me 13 years of diabetes hispanic, 45 year old male probably thought some insulin resistance hypertension. Class three obesity over B. M. I. Of over 40. And he's using Nph twice a day. So his PCP was giving them mph twice a day. Total daily dose was over 60 units. You know, I think he was probably 30 at some 32 in the morning, 30 at night, but around 60 units. Um he didn't check his blood sugar because he was told not to. He was told just to split the dose and he was on the Metformin 1000 mg twice a day is anyone see baseline with 796 months prior to the appointment. I didn't have it right there at the time. Uh And we initiated the freestyle. The brave for glucose awareness with what he's currently doing. And what I try what I did is because he really wanted to lose weight. He didn't like all the insulin. And so what I did is I before even getting a C G. M, I added a GLP one receptor agonist and I did what's called reverse filtration of the mph. That means every morning he was to check his sugar and every evening he was to check his sugar. And if he was less than 1 40 in the morning and less than 1 40 the evening, he would subtract a unit of NPH. So as I went up on the GLP when I went down on the mph. So he knew how to do that. He was swiping as his blood sugar. So he was tight trading off the mph as he was adding the GLP one because he wanted to lose weight. So here's his base line, A G. P. That came back two weeks and so granted the GLP one hadn't quite kicked in it. It did start to kick in. But you know, his a one C was a little bit higher than his 79 that we got six months prior. So his glucose management indicators. 83 doesn't have a lot of variability. You know, I mean he's high and and narrow, high and narrow glucose is high but is data is narrow So he's not having hypoglycemia for sure. But it's time and range is pretty bad. I mean he's only 29% in range not getting hypoglycemia but his above range is a good 70-plus%. And so as a result of this, you know, really encouraged me that I needed to add that GLP one. We were going to reverse titrate as mph. She might need a little bit for basil coverage. Uh And we had him come back after I gave him the instructions of adding the GLP one type, trading the GLP one. And what he said is he he's he reversed, I traded his Nph Until he said he didn't need it anymore. It's always 10 units. When the patient gets the 10 units they're like, hey well that's the starting dose. So I'm just gonna pull it off. You know, his a one c. At that six month follow up was not quite at goal. And so we wanted him less than seven. He was 72 and his post he was getting postprandial hyperglycemia assassins were doing good. And so what we did is we now have him on met foreman a GLP one. He was off his insulin and so I added an s guilty too. And the patient continued on the freestyle libre and we had him follow up six months later was our next encounter and this is what is recent G. P. Was so we had an A. One C. Of 6.5 a rapid A. One C. In the office. His variability was slightly a little bit more as time and target range was 79%. Um There's still some work that needs to be done because he's not scanning. He's having data gaps in the middle of the night. How do you get rid of those? You scan right before you go to bed. You scan right when you wake up and if you get up in the middle of the night to peace can he has a little bit of room improvement he can have with postprandial with lunch Or if it's a late breakfast. So I use that instead of changing meds. I said to him I need you to look at your diet with dinner and diet with lunch or with breakfast. Actually this is a holdover from breakfast and that's what he was working on. But this was an amazing kind of turnaround from a therapy to oh and the patient lost about £35. And so there's a lot of benefit that comes through this particular individual. So it's kind of summarized what the individual can get with continuous glucose monitoring. You know real time. See GM brings diabetes from the past into the present and it helps the person look forward to the future. It very much is individually driven and so patients get out of it, what they put into it. But it's a lot of ease in order to get that much data. You want to scan, you want to engage and you want to see what your glucose is. It gives them that ability to see the trend arrows. That's the predictive or forward looking glossy mia. Whether they're going up, they're going down. You need to orient your patients to what those arrows mean. You need to tell your patient to anticipate effects of glossy mia of food to create a log book. I just saw a patient yesterday morning. I know you might think you're making this stuff up. Dr miller just saw a patient yesterday morning. I'm basil insulin. I placed him on a C. G. M. He comes in for his two week follow up to look at it and I go, what did you learn? And he said, oatmeal does not like me. And here he was trying to do something healthy. And what he found is when he ate oatmeal, his glassy mia went up very, very high, Well over 200. So now he's eating a for tada. He does egg whites and and and vegetables roasted and blood sugars are great. He also knows by looking at the at the time of day for exercise or different carbs based on the time of day. He knows how activity level or illness affects his glossy mia and his wife says, oh my gosh, I love this. She says I can just scan them. I totally know what he is and it's really that peace of mind. And so whenever you can do something for the patient to increase their engagement to increase their comfort level to increase our quality of life. To get the results we want plus as a provider getting that improvement and targeted and when c without increasing risk that's a win win win for everybody. So what do we get as providers? These are this is the time where you don't want to hesitate in interacting with the data. We get an increased engaged individual and ownership of the disease without further disease burden. It actually unburden them. We get protection for hypoglycemia and prevention of it. We reveal the therapeutic impact that these medications have. I'm here to tell you therapies have a C. G. M. Signature a C. G. M fingerprint. And as you get used to that you will look at a C. G. M. And you will know what you need to add to that individual. It has that printable data revealing their individual journey. They're hypo their glycemic excursions, their variability, their daily modal. You can build for it. You can build for every month if you want to download it. You can build for it as a cpt you don't even have to have an encounter per se but you can add it onto an in and visit create a workflow where you incorporate this. Not only that be compensated for that time that you're doing. So here's some of that summary and key takeaway Managing Type two persons on insulin is challenging. It doesn't have to be so see GM provides that essential tool. You're on insulin in any fashion for a type two. You're on so far in your ears. You need to put them on a C. G. M. But don't just limit it there. It illuminates the whole ischemia to the person as well as the provider. It gives you a complete picture, as I mentioned earlier. It's the GPS for diabetes management. I've shown you there are clinical benefits. Looking at a one c looking at the studies, looking at what population all cause hospitalizations, improvement in work, absenteeism, not alone acute related events. As well as metrics. You really need to think of C. G. M. Beyond the real time glucose monitoring and begin to use it as that retrospective prospective and predictive tool that it really is. I hope that this has been encouraging, illuminating, insightful and I thank you so much for your attention Published December 21, 2021 Created by
