00:01 Hello, and thank you for joining our webinar today, Stelo 101: From Setup to Insight. My name is Sarah, and I'm one of the registered dietitians and diabetes educators here with Dexcom's Clinical Education team.
00:16 Over the next 15 minutes, I'll highlight how easy it is to get started with Stelo, the glucose biosensor, as well as highlight some of its key features that can help support people by translating their glucose information into actionable insights.
00:34 Now let's get started.
00:37 So what is the problem? We know that glucose matters, as today, approximately two in five U.S. adults have prediabetes, and more than 80% don't know it.
00:50 Also, without meaningful interventions, as many as 70% of them may eventually progress to type 2 diabetes. Additionally, we know that prediabetes is associated with an increased risk of cardiovascular events, and it's these statistics that highlight why we're invested in trying to improve this picture.
01:10 At the same time, we know glucose is influenced by more than nutrition alone. Sleep quality, stress, medications, activity, all of that can contribute.
01:22 The challenge is that much of this happens beneath the surface, and it isn't captured through routine testing like A1c and fasting glucose.
01:31 And this is where Stelo can provide an opportunity to make those invisible patterns visible.
01:38 Let's meet Sandra. Her story may be familiar.
01:42 She's 52, experiencing menopause, has a BMI of 32, and an A1c of 6.1%, consistent with prediabetes diagnosed six months ago.
01:54 She's got a history of gestational diabetes. She's taking a GLP-1 and also a statin for her high cholesterol.
02:02 Her healthcare professional advised her to make changes to her physical activity and her dietary intake, and she's tried doing so, but she feels no different, and so she's not sure if what she's doing is working.
02:15 She seems motivated. She's initiated yoga every week, and she's also been walking her dog, but she doesn't know if her GLP-1 is helping her.
02:25 And at a recent visit, she reports that, "I know I need to change what I eat, but I can't seem to get this right."
02:34 Now, it's no secret that most of the effort required to make behavior changes happens outside the clinic when people are making those day-to-day choices around meals and activity.
02:44 So her doctor recommends Stelo to help bridge the gap between this appointment and the next one by showing Sandra how her everyday choices affect her glucose, helping turn that general advice into personalized learning.
03:00 So let's meet Stelo, the glucose biosensor for those not using insulin and not at risk for problematic hypoglycemia.
03:08 It does not require a prescription, and the system includes the Stelo app seen on the left and the applicator with a built-in sensor.
03:17 The applicator inserts the sensor and is approved to be worn on the back of the upper arm. Sandra checked her phone was compatible at stelo.com/compatibility and ordered her Stelo.
03:31 Once it arrived, she downloads the Stelo app, which successfully walks her through the entire setup, including inserting it on the back of her upper arm and pairing it to her smartphone.
03:41 After a 30-minute warm-up, the sensor continuously gathers glucose data and sends it to her app.
03:50 She can wear it for up to 15 days plus a 12-hour grace period so that she can change that sensor when it's convenient for her on that last day.
04:01 During setup, the app personalizes the glucose target range based upon the user's health status.
04:06 As she has prediabetes, Sandra chose a target of 70 to 140 milligrams per deciliter. Other target ranges include 70 to 180 for those with type 2 diabetes not using insulin.
04:22 There's also a customized range, and targets can be adjusted at any time in the app settings.
04:30 After that short warm-up, Sandra begins to see her data on the Daily tab.
04:36 At the top of the screen, she can explore personalized daily insights.
04:41 Here, the app is turning her data into this meaningful daily summary, along with some quick tips and some encouragement.
04:50 Below that on the left is her time in range, and right now we can see she's doing quite well. She's been staying in range 92% of the time so far today.
05:02 Across from that, we see a glucose value of 121, along with a trend arrow that is pointing steadily to the right.
05:13 The trend arrow gives the speed and direction of how her glucose is changing, and this can help Sandra react quickly.
05:22 For instance, if she notices the glucose is rising after lunch, instead of sitting at her desk, she could perhaps build in a short walk to manage that post-meal spike.
05:37 In the center is her trend graph, and this shows those little dots that indicate her glucose tracings, so she can look back at her glucose patterns over time and see how the readings compared with her target range.
05:52 On the bottom row of that graph, there's a few icons, and these are timestamps of any logged events, such as meals or activity, and this can help provide Sandra with context to connect the glucose changes with her behaviors throughout the day.
06:11 If she wants to, she can also tap for a deeper dive into the core pillars of health, such as her nutrition, activity, and sleep, to see more details there.
06:25 Notice the tabs on the bottom row of the app. These help her easily navigate to other features.
06:32 She could tap the Log button to see any events that she entered throughout the day, such as meals and activity. She could also ask the AI coach questions about her data and find educational content there.
06:50 An important concept to convey to patients who are starting to learn about their glucose is that fluctuations are normal, and levels are constantly changing.
07:01 So with Stelo, Sandra can see that there are many factors that affect her readings, from her biology to food, lifestyle choices, and medication, to name just a few.
07:14 Food certainly impacts her glucose, but it is only one piece of the puzzle, and this begins to hit home for Sandra.
07:22 By seeing her data, it may help her gain a broader picture of what's affecting her levels and encourage her curiosity instead of judgment.
07:32 Before using Stelo, she felt kind of lost because she didn't know if what she was doing was really working. But after starting Stelo, she becomes more engaged, and she's paying closer attention to her glucose responses.
07:45 Things are starting to make sense to her.
07:50 One of the most powerful Stelo features is the meal logging, and it's really simple. There are several ways for Sandra to log her food intake.
07:59 One is to snap a photo of her meal, and the app will automatically generate a description along with the nutrition information, and this information is pulled from validated nutrition sources.
08:12 So not only does it provide that information, but it helps Sandra visualize how her meal and snack choices are impacting her levels.
08:22 It can also give her a glucose response score two hours after her meal, and we're going to take a look at those details in a few more minutes.
08:32 Here's where that logging has made a difference for Sandra.
08:35 At the top, she logged a breakfast that she assumed was healthy, of granola and a banana. However, she noticed a significant glucose rise up to 185 after she ate that.
08:49 On another day, she decided to experiment with a different type of breakfast, and this time she chose a little bit of whole grain toast, some peanut butter, and berries, and this time her glucose remained much more stable.
09:03 This personalized learning allowed Sandra to see the cause and the effect of her behavior on her glucose levels. It gives her that feedback and that reinforcement that she was lacking.
09:17 I'd like to dig a little further into how Stelo connects Sandra's food choices to her glucose. And over on the left side of the screen, we can see how she snapped a photo of her lunch, and by doing so, it was able to then pull in the nutrition facts for that meal.
09:34 Two hours later, Stelo generated a glucose response score. This is what I was mentioning a few minutes ago, using a scale of one to 10, where a higher score indicates a more favorable glucose outcome.
09:48 You can see here she scored an eight, and so she quickly starts to connect how well her body responded to her lunch. She can also tap on that screen to learn a little bit more.
10:03 And so right here in the center of my slide, we can see that Sandra gets some AI-powered insights, and this shows how that meal content affected her glucose. It also gives a snapshot of the trend graph showing data that will support the insight.
10:18 There's also a simple breakdown of how the score was calculated, and that's based on four factors, and we're going to look at those on the next slide.
10:27 Lastly, there's a few other highlights, such as how much time was spent above her target, her peak glucose, and any other related events that could contribute to a score, things like any walking or even how much sleep she had the night before.
10:45 Here are those four factors that contribute to the glucose response score.
10:50 Following the logged meal, Stelo will analyze the glucose patterns over the two-hour window and evaluate it using these four components.
10:58 First is the rise rate, so how fast the glucose rose; the rise amount, which looks at the peak glucose elevation; the recovery, so how effectively glucose returns toward the pre-meal level; and then lastly, the total change.
11:16 As physical activity is one of the core pillars of health, Stelo can also help Sandra understand how her activity affects her levels.
11:26 Now, her smartphone was already tracking her physical activity, and when she set up the Stelo app, she was able to easily connect that tracking to Stelo. So it's going to automatically log any of her movement for her.
11:41 In one example here at the top of the slide, we can see where Sandra ate a lunch, and she was kind of sedentary that afternoon, and she notices how the glucose rose and stayed elevated.
11:54 On another day, though, she decided to take a short walk about two hours after the meal. You can see that in the middle of the slide, and she saw some improvement there after taking the walk.
12:06 But not satisfied, she decided on another day that she was going to walk pretty much right after lunch, and she was able to see a much better glucose response.
12:16 And it's these types of visual comparisons that can help reinforce these healthy behaviors because Sandra can actually see the benefit.
12:25 She's learning to replicate the behaviors that impact her glucose in a much more positive way.
12:33 Stelo's built-in AI coach feature is designed to give Sandra information to reflect upon. The coach transforms her data into something more personal by identifying her patterns and giving her insights that are tied to her unique glucose experiences.
12:51 So Sandra could tap the Coach tab and ask it something like, "Am I trending better today than I did yesterday?" Or even, "Why does the same food affect me differently on different days?"
13:05 It is important to know that the AI is not replacing her clinician, and it is built with guardrails to guide her back to her healthcare professional for any type of medical advice.
13:15 But it is helping Sandra stay curious and ask better questions about her data that could lead to increased understanding and engagement.
13:26 It can give insights about her information, things like what may have caused a rise in her level, or how pairing something like vegetables and physical activity could be something to try next time to bring out a better response.
13:44 Let's see how Stelo's features have impacted Sandra's results.
13:49 At her three-month visit, she returns more informed, more motivated, and she's ready to tell her doctor what she has learned.
13:57 This is much different than how she presented months ago.
14:01 And it's because she actually sees that doing things like walking her dog has been helping her post-meal glucose responses, and her yoga has been bringing down her stress level.
14:11 She actually enjoys that activity and has been adding even more things like some strength training and cardio exercises.
14:21 She was also able to recognize how her GLP-1 medicine has been decreasing her appetite. She's been logging her meals and snacks and noticing that she's not as hungry and always searching for snacks like she used to.
14:37 As a result, her A1c has moved from 6.1 back down to 5.7, so it's recommended that she keep up with the healthy changes she has already made and, of course, continue with her Stelo because it's helped provide that visibility that she needed to support her lifestyle decisions.
14:59 Getting started with Stelo is really simple.
15:02 Individuals can purchase it through stelo.com, Amazon, or walmart.com. And remember, there is no prescription needed.
15:12 There's options between a one-time purchase or subscription models, and it is FSA and HSA eligible.
15:22 It arrives with two sensors in the box, so that would be a one-month supply, along with some educational materials.
15:30 And there's also a wholesale option for healthcare professionals to explore on the Stelo website.
15:38 There's also tons of online resources that will support the setup.
15:43 So within the app, it walks the user through the entire setup, but there's also learning for all different stages within the app as well as at stelo.com.
15:57 Today, we've seen how easy it is to get started with Stelo and how it can empower people like Sandra to connect the dots between their glucose information and their daily behaviors.
16:11 We truly value your opinion, and I would love for you to answer two quick survey questions. This can help us tailor future educational webinars for you.
16:22 Thank you again for joining, and I appreciate your participation.
