Thank you, Ashley for that uh presentation. Uh My name is Eugene Wright. I'm a consulting associate in the Department of Medicine at Duke University Medical Center and the Medical Director for Performance Improvement at the South Piedmont Area Health Education Center here in Charlotte, North Carolina. So let's start this presentation by looking at this, this clinical scenario you have here where the labs are and the medications are presented on the left hand side of this. And the amatory glucose profile report is presented here. The question to you is what is the most important pattern here if I gave you an opportunity on a scorecard to select the first best change, looking at this ambulatory glucose profile, which would you choose? You can see the clinical characteristic down at the bottom and here are your choices here. Well, we talk about the A GP report. Why is this necessary? This is a standardized report that has been developed by the International Diabetes Center that shows a standard set of glucose information and graphs the time and range and the target values, the subject time and range values, the ambulatory glucose profile figure and the daily glucose profiles Now, the glucose patterns insight report is intended for primary care clinicians who are not diabetes specialists but who treat and care for patients with diabetes. The care strategy is to identify and work on one pattern at a time with the simplifying the assessment and therapy change process by focusing in on what's the most important pattern. With the priority of low patterns, then highs with some lows, then the high patterns. The strategy is to address the low patterns. First, if the low pattern is mitigated at the next visit, then address all the other patterns. You address the high patterns only when the low patterns have been mitigated, taking care not to make the lows worse when addressing the highs. Now, the high variability may present addressing highs without making lows worse by discussing with the patient lifestyle behaviors that may be contributing to this variability. And oftentimes we may consider a different therapy uh may be a better way to address variability. Well, we said that why do we need this report? Well, primary care clinicians like you may uh take care of diabetes patients, but aren't diabetes specialists, you're all very busy and have limited time to address the healthcare needs. And we've noticed that there's a discordance between the quantity and kinds of new therapies for type two diabetes and improved outcomes that highlights the unmet need for tools to help the primary care clinicians make a more appropriate therapeutic adjustments. Primary care clinicians would benefit from a way to make it easier, faster and safer to make a better clinical decision for patients living with diabetes. So we decided that a useful performance improvement tool would be to permit the non expert primary care clinician to make a better clinical decision with minimal disruption to workflow, taking no more or less time and without the additional risk for adverse events such as hypoglycemia, the glucose pattern, uh report updates from the old A GP report and you can see the old A GP report here and the glucose patterns up. Uh Insight report here. It removes some of the time and range consensus targets that are in the upper left hand corner. It has a little bit different ambulatory glucose profile figure that is color coordinate with the GP I that shows and it, and it highlights the critical patterns, medication or lifestyle considerations are noted in the middle section here and we've removed the daily glucose profile and removed the glucose variability numbers. It's important to note here that it's not one report or the other, but you have access to both reports in the report suite. So we decided to uh look at the problem statement. Does the glucose patterns insight report, improve primary care clinician decision making? We took 10 cases from a clinical database. We assessed them with a couple of specialists, looked at them and identified the most important pattern and what would be the most important uh clinical decision to make. We generated the A GP reports for each of these 10 cases and generated glucose patents insight report for each of these 10 cases. So there were 20 reports from 10 cases to review. And this allowed for a head to head comparison. We had primary care clinicians and you can see over on the right. There were 20 M DS, 15 non M DS to include nurse practitioners, physician associates and clinical pharmacists. And you can see some of their background here. Each one cases were presented with a report, the MA one C and their current therapy. In round one, you read the A GP, if you were in group one and in round two, you read the uh glucose patterns insight report and the same thing for group two. So this was a crossover design so that everybody got exposed to both a glucose patterns insight report and an A GP. Now, the key thing is here is that everyone, all the clinicians were asked to make their first best therapy change, not allowing simultaneous changes. And here's an example of a patient with an overnight lows. You can see that the patient has an A one C of 7.5% maximum dose of Metformin, maximum dose of A G LP one and a sulfon glipiZIDE breakfast at 5 mg and a dinner dose at 5 mg. You can see the scorecard that you saw earlier, that was here and everybody is asked to give their first best therapy change. The inventory glucose profile was before was reported here. The same data with the same opportunity to make the change was presented with a glucose patterns insight report. As you can see here, what we divided was the most important patterns. There were five cases of low glucose or hypoglycemic risk, three cases of high, high glucose. One case with highs with some lows in one case, it was actually in pretty good control hypoglycemia. Prevalence in patients with type two diabetes is rarely reported but is prevalent in greater than 25% of insulin using type two patients and they show severe hypoglycemia. There's a growing link between hypoglycemia and cardiovascular disorders in type two diabetes. What we ask is that each pattern would be analyzed of subset separately. For each case, they were asked to classify the therapy decisions as addressing most important pattern ie uh decreasing insulin to address the low glucose. Or they made a decision that would worsen the most important pattern. They would add insulin to address a low glucose or they made a decision that was uh prolonged. The most important pattern, low glucose was prolonged uh by their action. We also track their deliberation time for each case. Well, what do we learn when the most important pattern? The low glucose in five of the cases improved with the glucose patterns, insight report versus the A GP and the time to uh reach that decision was improved with the glucose patterns. Insight report for the highs, the highs with some lows and there was no pa when there was no pattern or g good glucose control, there was really no difference shown graphically using the glucose patterns. Insight report, the participants were three times more likely to identify and treat hypoglycemia. 50% less likely to make a treatment decision that worsen hypoglycemia and 50% less likely to make a treatment decision that prolonged hypoglycemia. But what was even more interesting I think is that the healthcare professionals were faster to identify and treat hypoglycemia using the glucose patterns, insight report versus the A GP. So making a better decision, safer decision took less time. Now, some of the uh the subject perspectives on the glucose patterns insight report and the A GP reports, the GP I was preferred 2 to 1 over the A GP. With about 23 of 20 of 35 of the participants. They commented that it was less busy than the A GP report. It was cleaner and easier to interpret the, they preferred the color coding of the A GP to match the time in range metrics. And they like the boxes that highlighted the most important pattern with the A GP figure within the A GP figure that really brought their caught their attention early for those who chose the A GP report, they like the daily glucose traces and those uh some preferred the blue color pattern of the A GP figure. Let's take a look at an individual case result. Here's the case and you can see the characters at the, at the bottom lab is 7.5% Metformin G LP one and G uh glipiZIDE. You have the A GP on the far left, you have the glucose patterns insight report in the middle. When we looked at this and we looked at and aggregated the data. The patients were 2.5 times more likely to identify hypergly identify and address hypoglycemia. Using the glucose patterns insight report. They were two times more likely to make a decision that worsened hypoglycemia using the A GP report than the glucose patterns insight report. And you can see down here that they were 12 out of 12 of them made a decision that would have made prolong the hypoglycemia using the A GP versus only nine using the glucose patterns insight report. Well, let's look at the effect of the report design on the changes to primary care clinicians and decision making. The clinicians addressed the most important pattern equally. Well, with each report in cases presenting with patterns other than hypoglycemia across all cases. And all subjects therapy change, categorizations were different in 79 instances. With 67 of these instances presenting hypoglycemia ie the clinician uh recommendation using one report addressed hypoglycemia. While that using the other report did not within this subset in all but one instance, 66 or 67 or 99% correctly addressed low glucose with the G glucose patterns insight report. When they did not for the same case, using the A GP, these findings indicate that the glucose patterns Insight report aids in identification and treatment of hypoglycemia that would otherwise be missed using the current standardized reports. Now, from the clinical trials to the front line of diabetes, how do we find this valuable tool? This glucose patterns insight report. Well, if you use the li bravi suite of reports, this is the landing page that you come, you'll see the button here in the upper right that says glucose reports. This immediately takes you to the ambulatory glucose profile report which you see here. And if you note the second report right beneath that is the glucose patterns insight report. So it is a very easy uh report to access in three clicks. Now let's talk a little bit about what's new and on the horizons, there's a lot going on in. Yeah, many of you who may have seen this original article that was published earlier this year that says a comparison of point accuracy between two widely used continuous glucose monitoring systems. The purpose of this uh paper was to assess the point accuracy of two widely used CG MS, the Dexcom G7 Continuous Glucose Monitoring System and the Freestyle Libre three sensors. This was a head to head comparison. This was a multi center single arm prospective study that enrolled adults with type one or type two diabetes. Each participant wore one sensor of each type on the back of the arm accuracy was assessed by comparing sensor data to laboratory reference values using yellow springs instrument or Y si and capillary glucose values by finger stick. The study had uh six clinic visits, a screening visit, uh visit one and a sensor application and oftentimes visit one and visit two were combined and then up to three in clinic visits for Y si analysis of, of venous blood glucose values uh levels and those were conducted at visit 34 and five and then sensor removal of the completion visit at visit six. And the study group uh each participant underwent three frequent samplings and you can see they were divided into groups, group one and group two had their samplings done on these days. All participants wore a Freestyle Libre three sensor and one Dexcom G7 sensor on the back of the upper arm following the instructions for use. And when possible uh sensors were placed on opposite arms. Each sensor had a corresponding app on a smartphone that was given to the participant. So they had the Freestyle Libre three app on the smartphone and the Dexcom uh 7 G7 app on the smartphone so that they were able to read and get notifications from each censor. But what were the outcome measures? The number and percentage of sensor glucose values within the plus or minus 20 mg per deciliter of reference glucose values for all glucose values less than 70 mg per deciliter and plus or minus 20% of reference glucose values for glucose values greater than or equal to 70 mg per deciliter. Also the marred or mean absolute relative difference between the central glucose values and laboratory reference values within the following glucose ranges less than 54 mg per deciliter 54 to 6970 to 1 81 81 to 250 greater than 250 mg per deciliter and the combined mar. So what do we see if we look at the accuracy during the 1st 12 hours compared with Y SS I reference? You can see here that the mean absolute relative difference from the G7 and the Freestyle Libre and the 0 to 12 hours are about the same 14.4 R and a 14.5. And the percentage you can see right next to that within the 20 to 20. When you look at the 12 to 24 hours after that 1st 12 hours, you can start to see some separation in the marred. If we looked at the overall agreement against Y si reference, you can see the marred here for the G7 is was recorded at 13.6% in the freestyle Libre three at 8.9%. Also similar uh findings here with the percentage uh within 2020. You'll also notice that the bias which really gives some directionality to the accuracy here was 9.4 for the G7 and 0.6 for the freestyle Libre. If we looked at the sensor sensor accuracy by day of wear, compared with Y si reference here and you look at MD and the percentage within the 2020. You can see that the overall MA RD here appeared to be better for the freestyle li bra three than compared to the G7. Now, as any study, this had some limitations and these are the limitations that were reported by the investigators said was not registered with clinical trials.gov. Their decision not to manipulate samples to achieve a minimum number of paired glucose values in the hypoglycemic and hyperglycemic ranges were a limitation. This was just pull off the shelf, put them on people see what you get. Third. They did not investigate the accuracy of either sensor during times of rapidly changing glucose in which interstitial glucose levels may fall and fail to keep pace with uh rapidly rising or falling blood glucose levels referred to as sensor lag. And then finally, the study was uh funded by uh Abbott. Now let's move on to another area. Diabetic ketoacidosis, which is a usually led by insulin deficiency that leads to ketone body formation and ketosis as ketosis wor worsens, diabetic ketoacidosis can occur. DK A is a leading cause of death among Children and adults with diabetes, 15 to 75% of youth present with DK A at diagnosis in Europe and North America. And when we look at the annual prevalence of DK A in those with established disease, it varies between 3 to 10% risk for adults and 1 to 10% risk for youth diabetic ketoacidosis varies by age. You can see in this graph here that, uh the greatest percentage is in those who are 26 and younger and that those who are older, 26 years of age and older tend to have fewer episodes of DK A. So this is primarily um by age, we see a lot of DK A. Now, our current home ketone monitoring, uh There are two methods to do it. We have a blood test that measures beta hydroxybutyrate, which is really the most accurate way to follow ketones. And we have a urine test that measures aceto acetate. The blood test is a quantitative where it measures discrete levels values. The urine test is a qualitative test which is a color meric test that you read a test strip and you get a range of values. The cost is an order of magnitude difference for the blood test currently, which is a blood test. And you can see it's read on a meter here such as the pre precision extra as opposed to the urine test strips, which you can see demonstrated in the upper right here. Now, when we look at the frequency of ketone monitoring. Uh How often do you ch this was question was asked and it comes from the type one diabetes exchange. How often do you check for ketones when you are nauseated or vomiting? I think the key takeaway here is for those who are in the youth, age group, ages 13 and below greater than 50% of the time you can see always is in white here, they are checking starting at about age 18 and above less than 50% of the time. Are they even checking for ketones? Similarly, in this same study from the T one D exchange often, do you check for ketones when your blood sugar is high, greater than 300 mg per deciliter again, greater than 50% when you are a youth at age six and younger and then it starts to taper off as you get older to uh grade or greater than age. 50 greater than equal to age. 50 less than 4% are checking always and probably only another seven or 8% are sometimes checking. Well, potential future methods for ketone measuring. So ketone monitors, continuous ketone monitors has always been something that's been uh out there. And something in this report in diabetes Science and technology from 2021 describes a continuous ketone monitor. They took 12 healthy participants on low carb diets. They wore three sensors uh per patient for 14 days and they compared their data to capillary ketone meter results. This was a single retrospective calibration and what they found there was a linear response over the 0 to 8 millimole range was noted between the continuous kone monitor and the capillary strips. This led to an announcement of a development of a novel continuous ketone monitoring system in uh uh June of 2022 which subsequently led to the uh FDA breakthrough re designation for this first of its kind bow wearable that will enable patients with diabetes to continuously monitor glucose and ketones. In one center, the so-called glucose ketone monitoring system. This is a dual sensor that will be the same size and form factors. A freestyle Libre three sensor and it will connect to the Abbot Digital Ecosystem, personal and caregiver. Mobile apps will be available. It will be cloud based data management software for remote monitoring by a health care professionals as well. A continuous ketone monitors is especially important for people with diabetes who may be at higher risk for developing diabetic ketoacidosis or DK A. And recent studies have shown that continuous ketone monitoring could help prevent DK A rising ketone levels can be detected early and with continuous monitoring as a warning of impending ketoacidosis and informed care so that DK A doesn't develop that would be really great. And in this study, this highlights uh what a study population that the placebo group. I think there were about 484 patients who were in this group and they followed them over six and 12 months and they did twice weekly blood capillary ketone measurement during the baseline period, there were 12 adjudicated cases over that 6 to 12 month period of time of DK A events. What their findings were that the maximum capillary blood ketone level of greater than equal to 0.8 millimoles had a three times greater risk of diabetic ketoacidosis. And the implications for this really show that although ketone levels of greater than 1.5 millimoles per liter during illness and hyperglycemia represent immediate progression to DK. A lower levels such as greater than are equal to 0.8 millimoles during routine measurement, carry a higher future DK A risk. And this offers an opportunity for clinical education, insulin dose adjustment and the future for continuous ketone monitoring technology. Thank you very much for your time and attention and I'll turn it over to my colleague, Doctor Eden Miller at this time.
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