Video Going Beyond A1c: How Do Flash Glucose Monitoring and Ambulatory Glucose Profile (AGP)-Driven Care Take Diabetes Care to the Next Step? Play Pause Volume Quality 720P 720P 576P Fullscreen Captions Transcript Chapters Slides Going Beyond A1c: How Do Flash Glucose Monitoring and Ambulatory Glucose Profile (AGP)-Driven Care Take Diabetes Care to the Next Step? Overview Continue To Test Back to Symposium Thank you very much Emma, that was a wonderful presentation. Now we come to my presentation. My name is Ramsey A Gin. I work in leeds in the UK and I have an interest in continuous glucose monitoring. And half of my research is in this area. So I'm going to talk to you about going beyond HB one C Has been with us for a while but I think we've got now new metrics I would like to discuss with you in the next 20 minutes. So first of all is HBOC useful, I would say. Absolutely because it predicts complications. It is very easy to understand and also explain to the patient. We've got some clear cut targets. Well mostly we've got clear cut targets and we are familiar with H beyonc is has been with us for many decades now. It is useful glycemic management but also used for diagnostic purposes. And we know that these are the data from the U K P. D. S. Showing you that both microvascular and macro vascular complications are closely linked to HB one C. The higher it is the higher risk of these diabetes complications. Now the question is, does it have weaknesses? Indeed it does. There are several factors that can affect accuracy of H B. O and C. It is one of the drawbacks from my point of view, it is quite slow at assessing the effectiveness of new treatment. So when you start a new therapy you need to wait a bit to see that drop in HB one C. It fails to provide data on the role of daily activities on glucose control. And this is something that is very important to our patients because patients like to know if I do something, how does that affect my glucose levels and of course tells us very little or actually nothing In relation to hypoglycemia and glycemic variability, which are important measures and I'm going to discuss why they are important in the next 510 minutes. So let's focus initially on the accuracy of HB one C. Now HBO N. C is affected by red blood cell lifestyle. If you think about it, what is it? It relies on average glucose, It relies on the uptake of glucose by the red cells and then the red cell lifespan. So if you have an average blood glucose and an average red bloods lifespan, you will have the H B one C. As this yellow dot in that red cell. However, if you have a short red blood cell lifespan for a similar glucose exposure, that yellow dot becomes smaller. So your hb one C will be lower. And the problem with that you can under treat and there is a risk of complications in such patients. Now conversely when you have a longer red blood cell lifespan, the HB one C is going to be higher and the risk here is that you over treat and you precipitate hypoglycemia and we published last year a paper on this showing you that according to the red blood cell lifespan, you can have a difference in HB one C. Anything between 10 to 20 million more per mole wanted to percent. So this is quite an important issue. So so something else that affects the glucose HBOC relationship is race and age. Now, if you look in the top right hand corner here, you can see that people of black origin, which is the red line, do have a higher HB one C for a similar average glucose compared with the white population, which is the blue line. If you go to the bottom left hand corner, you can see that age has an effect because the younger population, the blue line will have a lower H. B. O. N. C. For a given average glucose compared with the older population which is the red line. And the gray the gray line is sort of the adult population in between. But you also see. In addition to that, you can see massive individual variability even within the same race and within the same age group. And this is all related related to a gr the apparent location ratio that takes into account uptake of glucose by the red cells and the red cell lifespan. So, I'm trying to say here that H. B. O. C. Can be affected by non glycemic factors. It's not only when it comes to management but also diagnosis and this is a short oral presentation. We are presenting actually at the es de that shows you that in people of black origin for a fasting glucose is of seven million more per liter HB one C is higher than people of hispanic or white origin. So it can also cause problems with the diagnosis. If you're only relying on it for the diagnosis and you know, we have known for years that there are multiple factors affecting H B. O. N. C. And you'll be pleased to know I'm not going to go through every single one of them. But just this demonstrates how many factors affect A one C. And we chose to ignore that to some extent because we did not have anything else, any any other measures that are better than A one C. And more accurate than A one C. But now we do have other measures. So the question is should we just abandon altogether? My view is no or at the very least not yet. Why? Because it's easy to measure, understand it's relatively affordable and as I said before it does pretty complications. But what we need to do is to refine HBO on see we need this younger generation of glycemic markers to help this aging glycemic market that really has been off of tremendous help to us so far. We need to refine the H. B. N. C. By the use of GM I glucose management indicator, timing range T ir time below range and glycemic variability. So let's talk about the G. m. i. 1st. So we have known now for quite a while that if you have a mismatch between HBO one C. And average glucose levels which what GM I measures that has got implications for the complication in patients. So you can have a positive mismatch where the HB one C. Is higher than predicted which is the yellow bit. Or you can have a negative mismatch when the h beyonc is lower than predicted from average glucose levels. And what has been shown before is that if you have a positive mismatch, so if you don't have a mismatch let's start with no mismatch which is the green line. Then you have HBO complications. But if you have a positive mismatch right then the complication rate is higher which is the yellow line. And if you have a negative mismatch then the complication rate is lower. So it does help you this hb on C. G. M. I mismatch at predicting whether the complication the risk of complication is higher than expected in this particular person. About time in range. Now we have been using timing range more and more in the past few years. And what is the evidence for the timing range predicting complications? I think the best evidence that we have so far is from the D. C. C. T. But you've got to remember this wasn't see Gm derived data but seven point sMB g testing and that shows you very clearly that the higher the time in range the lower the risk of complications. Now some argue that there's not much of a difference between 40 to 70% time in range in relation to the risk of complications. And this is because this wasn't proper C. G. M. Data and we of course need more data on time in range to fully understand how it predicts complications. It was shown actually in this particular work in subsequent analysis that timing range was not superior to HBO predicting complications in the D. C. Ct. However that doesn't mean that timing range is not useful because there is a another piece of work showing that timing range was an independent risk for hospitalization for diabetes ketoacidosis and hypoglycemia in type one diabetes patients on sensor augmented pump therapy. So timing range is certainly useful but we do need more data to fully understand its significance in terms of predicting complications when it comes to the type two diabetes group. Remember the D. C. City was on top one diabetes. So in the type two diabetes this is a study looking at the relationship with retinopathy and you can see the higher the timing range the lower the risk of complications or risk of retinopathy in people with Type two diabetes. And this was done in 3000 patients but it was only three days of C. G. M. So again we need more data. We've got some additional data here as well on all cause mortality. And you can see that if your timing range is high above 85%. The green line then the all cause mortality is quite low or much lower than timing range less than 50%. Of course the 50 to 85% are in between. But again this is only three days C. G. M. So we need a lot more data in this area. Now. The one of the issues that I always talk about is the importance of long term studies. So I think we need to pull together as a scientific community and have more observational studies. Looking at the relationship between time and range and long term complications in both Type one and type two diabetes patients. What about time below range or hypoglycemia? Now as I said before HBO N. C. Does not address hypoglycemia. Hypoglycemia is an important marker of future problems. And these are data from the leader trials showing you that if you have severe hypoglycemia, hypoglycemia requiring third party intervention you have a much higher risk of base major adverse coronary events which is on top and in the bottom you've got death much higher risk of death. And what they've done what I really like this word because they divided the events according to when they happened in relation to the severe hypoglycemia. So the highest risk is within a week. But you can see that even after the year following that severe hypoglycemia you still have high risk of mace and a high risk of all cause death. So the effect of hypoglycemia, not just instantaneous, they have a long term effect. Why is that now? We have shown this is one of the one of the papers that we published when we looked at the relationship between hypoglycemia and fiber rural ISIS, which we know is an important traumatic marker. And these were people who underwent clamp studies and we've done you glycemic clamp as well as hypoglycemic clamps. And you can see that the license of the blood clot was longer when the same individuals underwent hypoglycemic clamps and the effects were still there a week after the hypoglycemic clamp compared with the U. Glycemic lamp. Remember these are the same individuals And a very recent study has shown something very similar in terms of pro inflammatory markers following hypoglycemia. In people with type two diabetes. So it's not only that from both, his risk is increased but inflammation is increased and is prolonged. It's not instantaneous. Now we have conducted a study in the past looking at mortality following severe hypoglycemia and this is hypoglycemia that required ambulance call out. So people had a really good going hypoglycemia. And this was the type to group. And when we excluded people above the age of 75 to exclude fragility as a cause of mortality. What we found is that the mortality within a year following severe hypoglycemia was almost 14%, which was identical to mortality in people with type two diabetes who sustained a myocardial infarction in our area, as you can see they've been matched for age. And what is very interesting here that we subsequently conducted a pilot study to see whether this is modifiable or not because if it is not modifiable there's not much you can do about it. But actually in the type one diabetes, the mortality was not affected by the intervention. But when we did the intervention in type two diabetes which consisted of a simple nurse led education and follow up. So there was intensive nurse follow up for three months following the hypoglycemic effect. And then a very light touch for up to a year. And you can see that the people who received this nurse led intervention had much lower risk of mortality. So survival was improved and that was because of an improvement in cardio vascular mortality because of the intervention. So this pilot study, of course this was a single center study. So we need a much bigger studies to confirm the findings suggest that this is actually a modifiable risk factor. So that's why glucose variability. Again, glucose variability does not detect it at all. But I've got some problems with glucose variability because we've got far too many measures. There are endless measures of glycemic variability. We may lead the coefficient of variation and standard deviation or are widely used. These are the ones that everybody understands quite easy to calculate. But some studies use other measures sometimes because C. V. And S. D. Were negative or there could be some valid reasons for using other measures. The other thing I wanted to warn you about is the fact that glycemic variability has been assessed as beyonc variability, fasting glucose variability, smb G variability and C G M variability. And really you need a lot of glucose leader to assess variability properly. So the best usually is the data derived from C G M. Finally, the other thing I wanted to say about glycemic variability, that there's a close relationship between G. V. And hypoglycemia and sometimes you can't tell which one is causing the adverse effects. But having said all that, having said all that, there's a study that I quite like that looked at glucose variability in people with type two diabetes sustaining a cuticle re syndrome. So these guys had the mind calling function, then G. V was assessed as standard deviation from sMB G data. So unfortunately not C G M S N B G data, they were followed up for 17 months with major major adverse cory event occurring in a quarter of patients. But what they found that people with G V above 2.7 had a two fold increase risk of mace and in the bottom you can see the various turtles of G V. So if you're in the third turtle, your risk of mace triples. So there was a nice relationship there. So you would say well that's all nice. But are there any mechanisms linking hippos and G. V. To mortality or adverse outcome? Now I already talked about hypoglycemia how it affects thrombosis and inflammation. But let's just recap on everything. So glycemic variability can cause neuronal degeneration. It increases the robotic environment, increases inflammation, increases reactive oxygen species production and smooth muscle cell proliferation in the material. Warm hypoglycemia. We know about the arrhythmias again from bosses, inflammation and endothelial cell dysfunction. So these are sort of because long term effects that can cause vascular events heart failure and death in the long term. But as I said before there's a cross relationship between the two and sometimes it's difficult to disentangle which one is causing. Which Now in addition to the glycemic data there are some hard outcome data with the use of C. G. M. Devices. Now there have been some really nice studies from the States and type two diabetes patients. But this is a study that is presented at the Estate this year on people with type two diabetes that is coming from France. It is from europe and a retrospective study on the french national database and what they've done. They looked at 12 months before starting C. G. M. And up to 24 months after the initiation of flash glucose monitoring. And they had good numbers. Almost 6000 tattoo diabetes patients 79%. Where on both basal insulin and other hypoglycemic agents. 40% were on surface area. So a lot of patients on cellphone Algeria still. And what they found that in the 12 months before the flash glucose monitoring, 2% experienced hospitalization for any diabetes related event 12 months after the flash glucose monitoring. This dropped from 2 to 9.75% and at two years to no .6%. So there was a clear cut reduction in D. K. Admissions as well as hypoglycemic admissions because of the use of freestyle libre. So these are the data what what you see on the right of the slide is what I already told you. So the dark blue is the pre flash and the red is one year post flash and the light blue is two years post flash. And you can see DK reduced hypoglycemia reduced comas reduced and hypoglycemia also reduced or having said that that was the least affected compared with the others. These are admissions for all these emergencies. So to conclude while hBOC served us well we should use additional glycemic markers to optimize management in diabetes. And I think more research is needed to understand the prognostic values of glycemic measures in different diabetes populations. So I can't believe this but it's been eight years since I said at the E. S. D. That we should use the triangle of diabetes care to manage our patients e improved lycee mia but avoid hypoglycemia and limit glucose variability. And a lot happened since my colleagues have come up with some fantastic, clear cut recommendations of how we should do that in terms of timing range, which would be improving glucose levels, reduce hypoglycemia and keep that glucose variability to a minute. So I'm going to stop here. Thank you very much for your attention. Published September 14, 2022 Created by Related Presenters Ramzi Ajjan, MD, PhD Professor of Metabolic MedicineConsultant in Diabetes and EndocrinologyUniversity of Leeds and Leeds Teaching Hospitals TrustLeeds, United Kingdom
