Thanks rich for that great overview of the A. G. P. And its applicability in clinical practice. I'd like to move now to a little bit different area on the G. P. And incorporating C. G. M. Based glucose patterns, insight reports for the so called G. P. I. R. And treatment prompts in type two diabetes. And what we want to focus on is refining and simplifying the clinical decision making based on C. G. M. Data. Now we've seen from Richard's presentation that C. G. M. Data has a wealth of information and transforming that data into information with the IGP is the the hallmark of what makes the IGP so useful. But despite that what we found is that when it comes to clinical decision making it may taste something a little bit more than just that information that's laid out. So let's kind of recap what my understanding of the GDP report is. It is a standardized report that's been developed by the I. D. C. And it shows a standard set of information and grafts. It does a wonderful job of taking a large data stream and converted into useful and actionable information. And some of the information that it presents is it gives you the time and range target values, the subject target time and range values using ag in the daily glucose figures. There's some updates to this report that will show the upper time and range metrics that will look sort of like the glucose patterns insight report and we're gonna go into that. Well why do we need a glucose patterns insight report first. Primary care clinicians, not just physicians, but non physician practitioners may not be diabetes specialists, but they treat patients who live with diabetes. And we'd like this technology be technology to be applicable and friendly for them. Primary care clinicians are also very busy and have very limited time to address their patients healthcare needs. And when you think about the typical primary care visit and we look at the reason for visits while diabetes is very important to all of us for them, it's probably number four, number five on the list. And there was actually a study done up in Canada by the Canadian Family physician association and printed about two or three years ago that actually shows this. Well, primary care clinicians would benefit from a way to make it easier faster and safer to make a better clinical decision for their patients with diabetes. And in the model of a useful performance improvement tool, you would like to permit this non expert primary care clinician to make a better clinical decision with minimal disruption to workflow, thereby making it easier with no more or less time faster and without adding additional risk for adverse events such as hypoglycemia. The safer part. So if we look at the glucose patterns, insight report over here on the right, we can see what that looks like while it looks similar to it is very different than the GDP. Some of the differences are again, recognizing that this is used for the non specialist uh diabetes patient caretaker. And I like to think of this as the simple point and shoot mode of the IGP which may be the more advanced mode. If we were taking a camera analogy, the care strategy is to identify and work on one or more pattern at a time and by this by doing this, we want to simplify the assessment and therapy changes processes by focusing on what we call the most important pattern. And hierarchically we think about lows being the most important than highs with some lows and then the highs. So we don't want to jump right away to treating the high glucose patterns at the expensive, making lows worse high variability, which is a concept that is not clearly understood by the non experts. Uh but we try to break that down into some useful therapeutic changes to include lifestyle changes and or medication changes that will help minimize variability. And we think about this in the context that when you see variability, there are certain things you want to think about. So if we look at the current the evolution of the glucose patterns insight report. We look at the current ADP report and we can see side by side to this is what is the glucose patterns insight report. You can see that there are some differences here that we removed the time and range consensus target up here at the top. Uh there's a different A GDP figure design here. This color coded that really relates to this time and range bar graphic up here and it shows the critical A G. P patterns right here, considerations for the clinician is highlighted in red hair and the red here. And we talk about lifestyle and medication changes and or suggestions and we've removed the daily glucose patterns bar again from this report. People can still go back and access the GDP report and see those if they like. And we've removed the variability figures that are here in the statistics. So the problem statement would be, does this report the glucose patterns insight report, improve primary care, clinician decision making. So we designed the study. And what we did is we took 10 patient cases from a clinical data set. We had those cases reviewed by some subject matter experts here and then we generated a G. P. Standard A G. P. Reports and the G. P. I. Report for each of these 10 cases. So there were 20 reports, one of each for each patient. And uh the the generating reports had to allow for a head to head comparison. So when we gave these to the clinicians, they got each one twice. And what we did is we had 35 primary care clinicians uh 17 in the first group here in round one, they read only a Gps read 10 a Gps and then they gave their assessment of that. And then the second group we had 18 who read all the G. P. I. R. Then we did a crossover design and we asked them for their first best therapy change. Okay didn't allow simultaneous changes in this because we wanted to emphasize a stepwise progression in the interpretation and therapeutic changes. And then we crossed them over for round two. All cases were reported. They had an A. One C. The current therapy and they had a maximum of 60 seconds one minute to make a suggestion. And you can see the demographic, the breakout here of the subjects. There were 20 physicians, 15 non physicians, 19 Males, 16 males 20 to practicing greater than 10 greater than equal to 10 years and 13 less than 10 years. So we had a pretty good representative group. Now this is an example of an A. G. P. Case with overnight low glucose. And we can see what the labs here they had they were presented with an A one c 7.5% maximum dose of metformin, maximum dose of a GLP one group aside does here as indicated breakfast and supper. And they were presented this GDP report and they say what would be the first best therapy that you would change? Did the same thing. But gave this same demographic same information. And gave him the glucose patterns insight report again, you can note here that they have the glucose patterns insight. They have the considerations for the clinicians here and this color coded glucose patterns. Uh A G. P. Profile. Well, here's the case breakdown. The most important pattern for five of the cases That this was intentional was a low glucose. And we wanted them to recognize low glucose and if they to determine if the IGP would help them recognize low glucose quickly, high glucose patterns. There were three there there were highs with some lows one and no pattern at all or good control. And the premise of this is that hypoglycemia is prevalent in patients with type two diabetes But it's rarely reported by patients, even though its prevalence is somewhere greater than 25% of insulin using patients with type two diabetes. And so even severe hypoglycemia. And there's a growing link between this hypoglycemia that's going largely unrecognized and therefore possibly untreated with cardiovascular disorders. So we wanted to analyze each patient each pattern subset separately for each case. We wanted them to either address the most important pattern. We wanted to determine if they address the most important pattern, if their action or their treatment recommendation worsen the most important pattern or if it prolongs the most important pattern. And we wanted to track their deliberation for time in each case and so they had basically three options for their care that they were there treatment recommendations and those options would either improve or address the most important pattern worsen it or prolong it. What do we learn? Well if we look at the breakdown and results here, the low glucose patterns, we told you there were five cases that had that therapy decisions of the GDP versus the glucose patterns inside improved with the glucose pattern insight to the therapy decision therapy decisions were better with the glucose patterns insight. And the time, which was another key component of this was better with the glucose patterns insight report for high glucose. No difference, highs with some lows, no difference in good control, no difference. So this clearly in my mind was a safety feature. If we look at the further breakdown of it to be addressed the hippos, there was a three times more likely to identify and treat hypoglycemia. Using the glucose patterns insight report. Additionally, they were 50% more likely to make a treatment decision that worsened 50% less likely to make a treatment decision that worsened hypoglycemia using the glucose patterns inside report. Statistically significant here And about 50% less likely to make a treatment decision that prolonged the hypoglycemia and typically that was no change when a change was indicated And the bonus in this is that the clinicians were faster to identify these patterns by about 10 seconds faster. If you look at and to identify and treat hypoglycemia with the glucose patterns insight report. So we got better decisions faster with this glucose patterns insight report. Now if we look at the perspectives of the those that took this study participated in this study, the glucose patterns insight report was preferred 2- one over the egg. 23 of 25, of 35 preferred that they felt that it was less busy than the IGP report cleaner and easier to interpret. They preferred the color coded A. G. P. To match the time in range metrics. They liked the boxes that highlighted the most important patterns within the IGP figure. Now this was very interesting learning because they, the people that use this overwhelmingly 2-1 felt that this was easier to interpret and they preferred it For those who chose the IGP. There were 12 of the 35. What features did they like? They like? The daily glucose traces six of the 12 used those in clinical decision making and they preferred the blue color palette for the A. G. P. Figure. So this highlights the point. While it is not the glucose patterns insight report over the A. G. P. It is the glucose patterns inside report with the A G. P. Because there's going to be something that we will learn from each of them. Well, what are some of the patterns that we use And I'll show you a couple of the individual cases that we use to highlight the useful utility of this And here was a case of an overnight low and you can see what the A G. P. Report looked like. Here are the medications and the lab values a one C was 7.2 Metformin GLP one insulin. And you can see all of that here and the A G. P. Was as such. And this was the glucose patterns insight report. And you can see here considerations for the clinicians were highlighted and right away your eyes drawn to this red box here and notes that there's overnight lows that need to be addressed. If we looked at the A G. P, The initial was 17 of the 35. Actually worsened hypoglycemia were only seven did that with half as many. More than half as many did better with the IGP with the GDP report. If we look at addressing hypoglycemia, which is the key here. three picked it up with a GDP report. Three of the of the 35 but 18 picked it up with the glucose patterns insight report. And these are some of the things that they did. They were decreasing that margin in this case, decrease glucose at dinnertime. So this highlights just as an example. In the second case we look at here, you can see the lab reports here, medicines here, this is the GDP report. This is the glucose patterns insight report again, your eye is drawn quickly to this red hypoglycemia overnight and you can see a G P. seven caught it right off 19 caught it with the G. P. I report. And of that 16 would have using the AGP would have acted to worsen hypoglycemia or 12 to prolonged hypoglycemia. Were half as many. Again more than half as many did better with the G. P. I. Report. So what this study I think shows is that the effect of this report design on the changes to decision making and there's going to be a great poster presentation On Sunday and this is the poster 79 late breaking. I would encourage you to go to the poster presentation to see more specific analysis and highlights of the differences that we saw in this study. But what are some of the lessons that we learned? The discordance between the quantity and kinds of therapies for type two diabetes and improved outcome highlights and unmet need for tools for primary care clinicians to make appropriate therapeutic adjustment. We set out to present a novel C. G. M based glucose patterns insight report the G. P. I. R. That identifies patterns of sub optimal glycemic control highlights the clinically most important pattern and offers therapy recommendations to address this most important pattern. To assess the utility of this glucose patterns, insight report in clinical decision making a reading study was conducted comparing it against the current standard glucose report for the And the clinical data from 10 subjects were used to generate complementary glucose patterns insight reports and a gps non specialists. It's important. These were non specialist primary care clinicians Evaluate each case in report design alongside an a one C medication regimens to make therapeutic changes to their recommendation. The therapy change recommendations were categorized by whether they address the most important pattern present with a priority on treating hypoglycemia. If it occurs coincident with other patterns in a given case, the primary care clinicians address the most important pattern equally well with each report in the cases presenting patterns other than hypoglycemia. Across all cases. In all subjects, therapy changes Brotherorizations were different in 79 instances With 67 of these instances presenting hypoglycemia. What I meant by that is that the PCP recommendation using one report addressed hypoglycemia while the that using the other report did not within this subset in all but one instance PC PS correctly addressed low glucose with the glucose patterns insight report when they did not for the same case using the G. P. These findings indicate that the glucose patterns insight report, AIDS in identification and treatment of hypoglycemia that would otherwise be missed. Using the current standard A GDP report. Thank you very much for your time and attention and we will
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