International Society for Pediatric and Adolescent Diabetes (ISPAD)

October 30-November 2, 2019; Boston, MA; Full Report - Draft

Executive Highlights 

  • ISPAD 2019 has wrapped, and we were impressed from all we learned at the diverse sessions.

  • Telehealth and machine learning are among burgeoning diabetes management and diagnostic technologies. Telehealth shined in the CoYoT1 trial, showing that telehealth can greatly boost clinical visit attendance, improve diabetes distress, and change the field of diabetes management for young adults. Dr. Raymond’s CoYoT1 telehealth-based care model delivered extremely impressive results in a pilot study, with the intervention group averaging 3.5 visits/year, compared to just 1.1/year in the control group. Machine learning is also of promise, having shown ~50% positive predictive value of 3-month A1c rise based on EMR data alone. Prediction rose to ~60% after incorporating diabetes device data, marking machine learning as an upcoming diagnostic resource.  
  • The promise of CGM and automated insulin delivery (AID) was a huge excitement generator for ISPAD attendees. Tandem presented very strong Basal-IQ real-world data, showing a remarkable 0.9% of time <70 mg/dl – just 13 minutes/day! Dr. Bruce Buckingham shared a few new details about the hotel study of Omnipod Horizon (hybrid closed loop) in young adults (ages 2-6), while Dr. Roy Beck pushed glycemia metrics forward beyond A1c, asking his audience, “Would you rather have [an ambulatory glucose profile] or would you rather have one number that reflects someone’s average over the last three months, and may not even be an accurate average?”
  • In a near-packed symposium in the conference’s largest room, Drs. Bruce Perkins, Chantal Mathieu, and Simeon Taylor discussed SGLT inhibitors’ potential use in pediatrics diabetes management. According to the AdDIT study, ACE inhibitors and statins may prevent vascular complications. Sanofi’s EDITION JUNIOR trial also showed that treatment with Toujeo (insulin glargine U300) showed non-inferiority in A1c reduction and fewer severe hypoglycemic events compared to Lantus (insulin glargine U100).

  • Dr. Graham Ogle from Life for a Child shared some inspiring data on the potential for “intermediate” levels of diabetes care in low-resources countries to hugely change mortality and complications rates: in Mali, Dr. Ogle estimated that moving from minimal care to intermediate care could improve 30-year survival rates by more than five times. Other noteworthy presentations centered on the socio-behavioral and psychological aspects of type 1 diabetes management. Dr. Colin Hawkes discussed the promise in community health worker interventions that go beyond diabetes management education to improve glycemic control. Dr. Regitze Pals outlined the challenges pre-teens with type 1 diabetes and their families face in diabetes care, while Drs. Angela Galler and Julia Blanchette talked about the benefit of psychological care for type 1 and the burden finances may have on preventing emerging adults from accessing this ancillary treatment, respectively.

Greetings from Beantown, where the 45th Congress of the International Society for Pediatric and Adolescent Diabetes (ISPAD) just wrapped! Below you’ll find our top highlights from the meeting separated into: (i) Diabetes Technology, (ii) New Type 1 Therapies, and (iii) Prevention and Pathophysiology. Happy reading!

Table of Contents 

Diabetes Technology Highlights

1. Lessons from CoYoT1 Trial: Telehealth Can Greatly Boost Clinic Visit Attendance, Improve Diabetes Distress; Young Adults Must Be Cared for Differently

To a packed ballroom, Dr. Jennifer Raymond (Children’s Hospital Los Angeles) gave an inspiring presentation on lessons learned from the CoYoT1 (Colorado Young Adults with Type 1; pronounced “coyote”) care model, which demonstrated huge increases in number of clinic visits (3.5 vs. 1.1 per year; p<0.001). The CoYoT1 care model substitutes traditional in-person clinic visits with a video telemedicine visit with a provider for 20-30 minutes and a group appointment where multiple young adult peers discuss issues related to their transition from childhood to adulthood (e.g., managing diabetes at work or college, managing personal relationships, etc.). The audience seemed very excited to hear so much success surrounding peer support in particular, as that is being more widely prescribed today, as we understand it. This model was piloted in Colorado with 42 self-selected participants and 39 control participants (traditional, in-person visits) around 20 years old at baseline. Results were published in DT&T in 2018, showed incredibly strong results: for the CoYoT1 group, the number of clinic visits attended per year rose from 2.6 the year before the study to 3.5 during the study. In the control group, this number decreased from 2.3 visits the year before the study to 1.1 during the study (p<0.001). Diabetes distress scale ratings dropped from 2.1 at baseline to 1.8 at the end of the study, compared to a rise from 2.0 to 2.2 for the control group (p=0.03; Bakhach et al., 2019). Additionally, despite the increases in number of clinic visits, there were no significant total cost differences between the CoYoT1 and control groups (Wen et al., 2019). This was explained by a decreased number of non-endocrinologist and hospitalization visits in the intervention group, shifting costs from acute care to preventive care – a huge win for patients and the system. After a successful pilot in Colorado, Dr. Raymond and her team worked on translating the model to Los Angeles for a lower socioeconomic status, minority population. That trial ( will be run for one year as an RCT with type 1 patients ages 16-25. It is currently recruiting, and the first visits started in July this year.

  • In addition to the telehealth component of CoYoT1, the California version involves shared-decision making, self-efficacy, goal setting, and monthly debriefing. Before each visit, patients fill out a shared-decision making worksheet, in which the patient fills out topics they “definitely want to talk about” and topics they “could wait to talk about.” Brilliant! We’d say that idea could be extended to most patients in most offices as an option! Similarly, at the end of the appointment, a goal-setting worksheet is provided, giving a summary of the visit and between-visit goals. The California version of CoYoT1 also added a slightly older type 1 peer to facilitate the group visits. Interestingly, Dr. Raymond found that young adult patients often preferred having video-summaries for the visit, rather than written-form summaries. Lastly, the provider groups also met monthly with audio recordings of visits to discuss how they could make their visits more patient-centered.

  • Comparing the CoYoT1 care model to existing models, CoYoT1 is sustainable and cost-effective, while delivering improved psychosocial outcomes without the need for any additional resources (e.g., time, staff, rooms, etc.). Additionally, while patient burnout and stress from diabetes are common, Dr. Raymond also emphasized the high number of providers who experience burnout and stress. Provider experiences could be improved by moving away from current models of care, which Dr. Raymond characterized as labor and resource intensive, expensive, and not universally applicable.

  • Dr. Raymond identified several challenges and potential solutions to more widely implemented virtual care visits. For patients, providers, and institutions, learning a care model is a huge challenge; for this, Dr. Raymond emphasized that extensive practice was key, along with availability of a dedicated team for onboarding. She noted that, in her experience, telehealth visits were much more likely to be on time compared to in-person visits (due to driving times, finding parking, getting checked in, etc.), and recommended that providers stick to exclusively telehealth or in-person visits for this reason. Implementing virtual care visits may also require shuffling staff roles, as the need for employees at the front desk may be reduced, but new staff may be needed to help set up and facilitate the virtual visits.

Selected Questions and Answers

Q: What happens in between the visits? Between the three months, it’s tempting to do more, and do the patients expect you to do more? How do you deal with this?

A: Great questions. I would say young adults are really engaged when people are there and present for them. They’re reaching out more often, they’re wanting people to be able to answer their questions, they’re wanting people to trust. And as that comes to fruition, they are more engaged.

It’s challenging to plan for increased frequency of visits when you’re thinking about a clinical model. Providers often don’t have availability for more frequent appointments, and although that is the ideal, sometimes the appointments just are not available. Sometimes, there is an option to increase intensity by adding visits with additional staff members (e.g. nurses, dietitians, social workers, psychologists), and there are some easy ways to do that with a telehealth platform …

Additionally, I find that virtually, young adults are more comfortable and more honest about their care. I think there’s something about being in their setting, their own place, and being comfortable that results in a better patient-provider connection and increased sharing.

As for the questions about frequency of in-person appointments, and critical physical exam components,  if needed, we have partnered with primary care providers or asked young adults to use local pharmacies for blood pressure checks. However, we have found once per year sufficient. I actually don’t think we need frequent in-person visits to be able to support our young adults with diabetes.

Q: When patients go for each visit, is it the same person they’re seeing?

A: I think that’s something important for young adults (and likely all patients) – the need for trust and continuity. High risk patients who miss appointments or need to be seen more frequently are often added as soon as they can be – when there’s any provider available – which often means they have a different team member each time. Sometimes, I think that can be tough on these patients who likely need even more continuity. Our goal is to see the same provider at least every three months.

Q: What kind of software do you use? Is it safe and secure? Can you maintain it?

A: There are multiple different platforms that are available for virtual care that are HIPAA-secure and would be approved by a medical legal team. Risk Management and Data Safety Management experts have been involved with our platform selection. I have used different platforms at different times, and they all seem to work similarly. Working with your institution to select or learn about various platforms is important.

Q: How much time does it take to analyze the data through the virtual visit?

A: In regard to analyzing diabetes data virtually, I will just walk through how we review data during appointment. I pull up the telehealth platform, the electronic medical record system, the shared-decision making documents (both provider and patient), and then the website we’re using to download diabetes data or maybe their Clarity report. Then, you can share your appropriate computer window, so the patient and I can be looking at one another and also looking at data on my screen. We’ll go back and forth between the decision-making pieces and set the agenda for the appointment, and then we’ll switch to the diabetes data.

As providers, we’re often used to drawing on the paper downloads during in-person visits – and you can do something similar with the computer mouse, but it is a shift for providers and patients – which is why practice is important. Of note, some clinics do have diabetes data downloaded into their electronic medical record. Unfortunately, we don’t have integration with our electronic medical record yet, which is the reason for using a separate platform.

2. Machine Learning Model Can Predict Future A1c: For 3-Month A1c Rise of 0.6%, Positive Predictive Value of ~50% Using EMR Data Alone, ~60% With EMR Data + Diabetes Device Data

During a rapid-fire afternoon session on ways to improve clinical care delivery, Dr. Mark Clements (Glooko / Children’s Mercy Kansas City) presented promising data on a machine learning-based model for predicting A1c at the next visit, based on the last A1c value, discrete EMR data, and available diabetes device data. The model, which is a random forest (i.e., a “forest” of many decision trees), was fitted and tested using data from 1,743 youth (≥9 years old) who recorded 9,643 visits. Discrete EMR data (vs. free-form text fields), patient reported outcomes (PROs) from an electronic intake form, and diabetes device data were used to feed the model, along with the last recorded A1c value. The machine-learning (ML) model outperformed both a null prediction model and a linear prediction model (i.e., future A1c rise will be the same as the most recent A1c rise) at predicting A1c rise at the next clinic visit. Using EMR and PRO data alone to predict patients whose A1c would rise 0.6%, the model’s PPV was ~50%, meaning about half of the cases that the model identified actually saw an A1c rise of ≥0.6%. In comparison, the PPV for an A1c rise of 0.6% was just 30% using a linear model, i.e., 30% of the cases identified by the linear model actually had an A1c rise of ≥0.6%. For an A1c rise of 0.3% over 3-months, the PPV was 56%, with a sensitivity of 21% (i.e., the model was able to identify one-fifth of all participants who actually saw a 0.3% A1c increase). When 2-weeks of diabetes device data were added into the model, PPV was improved to ~60% for an A1c rise of 0.6%. Unsurprisingly, the model performed better with device data that was more recent. Using the model, a clinic is able to identify at-risk youth to clinicians so that preventive action can be taken. Children’s Mercy is using the information to perform video “micro-visits” every 2-3 weeks and encourage data sharing and peer mentoring for identified patients.

Table 1. ML-model performance using EMR-data to predict 0.3% A1c rise over 90 days


Estimate (%)

95% CI

Sensitivity (what percentage of all true positives was the model able to flagged)


18%, 25%

Specificity (what percentage of all true negatives was correctly unflagged)


83%, 89%

Positive predictive value (what percentage of flagged cases was true positive)


49%, 62%

Negative predictive value (what percentage of unflagged cases was true negative)


54%, 60%

  • Using data from diabetes registry data, Dr. Clements identified five typical tracks for population mean A1c from ages 8 to 18. For ~20% of the registry population, A1c rose greatly from ages 8 to 18, while mean A1c stayed flat for the remaining ~80% of the groups. Referencing the infamous T1D Exchange graph of population mean A1c over time, Mr. Clements noted that the A1c peak for teenagers and young adults was driven primarily by this ~20% of the population. Thus, the ability to identify these higher-risk individuals could be the key to flattening the A1c rise seen in adolescents and young adults.

Selected Question and Answer

Q: What are some of the modifiable risk factors identified by the model?

A: Well, there are some risk factors that aren’t modifiable, like ZIP code, but there were modifiable risk factors. From the device data, we were able to parse out the number of fingersticks/day, insulin boluses/day - each of these had a significant weight and could be the targets for interventions.

3. 10-Year SWEET Type 1 Registry (Europe, Australia, Canada, and India) Data: Median A1c Dropped 0.4% and Pump Use Increased From 38% to 46%

Dr. Thomas Danne (Hannover Medical School), seemingly present everywhere at ISPAD, gave a quick update on data from the SWEET type 1 registry, showing median A1c dropped from 8.2% to 7.8% from 2008-2010 to 2016-2019. The SWEET registry data, compiled from 21 centers across Europe, Australia, Canada, and India from type 1s under the age of 25, also showed an increase in pump use from 38% to 46% over the ten years. The first observation period, from 2008 to 2010, was composed of 4,772 patients (mean age 11 with diabetes duration of 3 years). The second observation period, from 2016 to April 2019, had data from 12,750 patients (mean age 13 with diabetes duration of 4 years). Notably, the mean A1c showed statistically significant decreases across all age groups, as shown in the table below. Lastly, during Q&A, Dr. Danne shared that data from the first ~1,000 patients on CGM had been gathered, showing an average time-in-range of 51%.

Age Group

Median A1c, 2008-2010

Median A1c, 2016-2019

<6 years



6-<12 years



12-<16 years



>16 years



Questions and Answers

Q: Have you looked at the lag between change in A1c and pump use. You would think A1c changes on a clinic-visit to clinic-visit basis, while pump use is probably more systematic. If pump is leading A1c change, you should see pump use increase before the A1c decline.

A: It’s difficult to adjust for all these things. I’d guess your hypothesis is right, but I cannot support it yet with data. We will certainly look into that. Just to give you a feel, we have the initial 1000 patients’ data on CGM, and it has an average time-in-range of 51%.

Q (Dr. Tadej Battelino): The T1D Exchange showed a worsening A1c, and the SWEET is showing a significant improvement, yet there are actually more pumps used in the T1D Exchange. Do you have explanation?

A: One point is that the T1D Exchange is not necessarily representative of the centers. They have select data in their centers and for any type of benchmarking, the completeness of data and looking at things like loss to follow-up are very important. Also, SWEET has peer-review to look into how centers are collecting their data and their healthcare delivery. This is also a point of improvement within the center, which is extremely important. There’s a whole package that SWEET is offering. The T1D Exchange is now starting a quality improvement initiative also that we hope will be successful. We’re looking for possibilities to work together and I’m very optimistic that we’ll find ways to do so.

4. Real-World Pediatric Data from Basal-IQ (n=2,696): 0.9% of Time <70 mg/dl, Mean ~5 Insulin Delivery Suspensions/Day

A poster demonstrated the effectiveness of Tandem’s low glucose suspend algorithm, Basal-IQ, in 2,696 real-world pediatric (ages 6-17) t:slim X2 users. The data, uploaded to t:connect between August 2018 and March 2019, showed 0.9% of time spent under 70 mg/dl, or just 13 minutes per day! On average, the Basal-IQ algorithm suspended insulin delivery 4.9 times/day for an average of 15.5 minutes per suspension. On average, users’ glucose values were at 111 mg/dl when suspension was initiated and 100 mg/dl when insulin delivery resumed. The 0.9% of time spent in hypoglycemia was even lower than the 1.2% reported in Tandem’s first round of real-world data from Basal-IQ shared at ATTD 2019.

  • Before and after Basal-IQ initiation data was available from 491 users. That subgroup showed a reduction in time <70 mg/dl from 1.6% to 1.1% (~7 minutes/day; 31% relative reduction, p<0.001). The ability to significantly reduce hypoglycemia from an already-low baseline is certainly a major testament to Basal-IQ’s effectiveness. In just 5% of insulin suspensions, the suspension was manually overridden by users. Time-in-range before and after Basal-IQ remained approximately the same, at 53%-54%, though the percentage of time >300 mg/dl decreased slightly by ~9 minutes/day (p=0.007). These nine minutes total an hour per week – we’re sure patients will take this!

This real-world pre-post relative reduction in hypoglycemia exactly matches Basal-IQ’s pivotal trial result, presented at ATTD 2018. Both data sets show a 31% relative reduction in time <70 mg/dl, from a baseline of 4.5% in the pivotal and 1.6% in the real-world subgroup. As a reminder, Basal-IQ looks ahead 30 minutes and suspends insulin when glucose is predicted to drop below 80 mg/dl or if glucose is currently below 70 mg/dl and falling. The system resumes insulin once glucose values start to rise

4. Dr. Roy Beck: “The Only Value of HbA1c if CGM is Available is for Historical Purposes”

A leading voice in the beyond A1c movement, Dr. Roy Beck (Jaeb Center), made a strong case for time-in-range (TIR) over A1c, summarizing his argument by showing an ambulatory glucose profile and asking, “Would you rather have this or would you rather have one number that reflects someone’s average over the last three months, and may not even be an accurate average?” Dr. Beck’s talk touched on many facets of the beyond A1c movement, including consensus targets for CGM metrics, measures of glycemic variability, and the relationship between TIR and complication rates.

  • Dr. Beck discussed the international consensus on CGM metric targets, which was presented as a late-breaking poster at ADA 2019. Interestingly, Dr. Beck noted that the consensus group chose to use time above 180 mg/dl and 250 mg/dl as the measures of hyperglycemia, rather than area under the curve or high blood glucose index, which might be more intuitive measures given that they are weighted by severity of hyperglycemia. Ultimately, Dr. Beck stated that it was not important, as all these metrics correlate extremely highly with each other (0.95 to 0.99).
  • On measures of glycemic variability, Dr. Beck recommended using coefficient of variation (CV) over standard deviation (SD) and mean amplitude of glucose excursions (MAGE). Because SD and MAGE are positively correlated with mean glucose (r=0.82 and 0.76, respectively), patients and providers can be misled into thinking their variability is being reduced when only their mean glucose is changing. In contrast, CV is not correlated with mean glucose. Perhaps unintuitively, CV is also not correlated with hyperglycemia, though it was significantly correlated with hypoglycemia (r=0.68). Thus, by reducing time spent in hypoglycemia, patients are likely to improve their glycemic variability.
  • Referencing his 2018 paper in Diabetes Care, Dr. Beck showed graphs demonstrating the relationship between decreased TIR and increased rates of complications using data from DCCT. TIR was calculated using the quarterly seven fingersticks/day data that was collected in DCCT. For every 10% decrease in TIR, hazard ratios for retinopathy and microalbuminuria increased by 64% and 40%, respectively. With actual CGM data (up to 288 measurements/day), the association between TIR and complication rates could be even stronger.

Selected Question and Answer

Q: If you had to design a trial, would you go for the seven fingersticks/day (from the DCCT trial), A1c, or CGM? How much time would you need for the CGM to be used?

A: CGM is easier and now, you get more than seven points a day – I’d rather have 288 points/day. We’ve shown you need about 10-14 days during a pretty stable time to get a good estimate of glucose metrics, so in studies, we try to get two weeks of data, either with real-time CGM or blinded, and then we gather data in 10-14 day intervals … In some closed loop studies, like this week’s NEJM paper about Control-IQ that the NIH-funded, they use CGM metrics as the primary outcomes. The FDA is not willing to accept that yet as part of an effectiveness claim, so there’s a lot of work going on to get the FDA to come along. One challenge with CGM, compared to A1c, is that you have to actually wear it. It becomes a challenge if it’s going to be a metric to make sure you get a high level of adherence.

5. Hotel Study of Omnipod Horizon Algorithm in Children Ages 2-6 (n=14): One Severe Hypoglycemia Event (Unrelated to System), Time-in-Range Improved From 55% to 73% (+4 Hours/Day)

In yet another demonstration of his brilliance and poise, Dr. Bruce Buckingham (Stanford University) powered through a presentation of positive results (+4 hours/day time-in-range) from Omnipod Horizon in young children, even as the presenter’s laptop malfunctioned making his slides disappear (“Photography is permitted at this presentation,” he quipped.). While Dr. Buckingham first read out the study (n=14) at ADA 2019, he shared information about an adverse event, which was deemed to be unrelated to the system itself, for the first time. The study evaluated the safety and efficacy of Omnipod’s Horizon automated insulin delivery (AID) algorithm in young children, ages 2-6. The study involved seven days of standard therapy baseline data collection followed by 48-72 hours in a supervised hotel setting (a fun-looking “hotel” we’d note – see below). Without the algorithm integrated on the pump, participants had to carry a tablet with MATLAB that held the algorithm and handled communication between the CGM (Dexcom G4 or G5) and Omnipod. The participants, mean age 4.8, had fairly tight glycemic control at baseline with an A1c of 7.4% and mean glucose “around 174 mg/dl.” Notably, the study included both MDI and CSII participants, with MDI participants going straight to the closed loop system. The kids were allowed to “free-range” their meals and averaged exercise time of ~1 hour/day (e.g., trampoline, laser tag, etc.).

  • During the study period, time-in-range (70-180 mg/dl) was 73%, compared to 56% in standard therapy (p=0.0002) – a remarkable four additional hours in range! Both time in hyperglycemia and hypoglycemia were reduced, though the time in hypoglycemia difference was not statistically due to small sample size. Participants spent 3.6 fewer hours/day above 180 mg/dl (40% vs. 25%; p=0.005) and even 2.6 fewer hours/day above 250 mg/dl (17% vs. 6%; p=0.002). During overnight hours (11 PM – 7 AM), time-in-range was 85%, compared to 58% during baseline, a massive difference. Lastly, coefficient of variation during the closed-loop period was 36%, compared to 40% under standard therapy (p=0.02).


With Horizon (2-3 days)

Standard Therapy (7 days)


Mean glucose

148 mg/dl

172 mg/dl


Time-in-range (70-180 mg/dl)




Time >180 mg/dl




Time >250 mg/dl




Time <70 mg/dl




Omnipod Horizon is scheduled for a pivotal trial starting 4Q19, with US launch coming as soon as 2H20. Insulet is committed to “breakthrough ease of use,” smartphone control, and launching with a pediatric indication. Moving forward, the young children’s study will be done in a fully free-range setting, which will likely require the algorithm to become integrated into the Omnipod itself.

6. Quotable Quotes from Kelly Close: Looking Back at How Far the Field Has Progressed and Looking Forward at CGMs, Beyond A1c, and Diabetes Apps

In a sweeping presentation, our own Kelly Close reflected on her diabetes journey, how much the field has changed since her diagnosis, and looked ahead at technologies driving changes in diabetes management. At times, the mood was somber, with Ms. Close sharing her regret at not having expressed her gratitude towards her parents and family for helping manage her diabetes (“I was so busy just being diabetic.” Other times, the mood was jovial, with Ms. Close’s stories causing the audience to burst into laughter. In a moment where she shared how CGM and time in range are tools similar to microscopes and telescopes, she shared a story with her daughter related to her 14-year old: “I keep saying to my 14-year old, ‘Coco, how are you taller than me now?’ She says, shrugging, ‘Cell division.’” The audience nodded multiple times as Ms. Close talked about how for providers, there may be more work at the beginning with apps related to CGM or food, but that ultimately, as apps become easier, engagement will grow, and patients will become more engrossed. The heterogeneity of patients means this won’t be everyone, but our team has been astounded by the improvement in both technology and apps, and particularly automated insulin delivery, which many in the audience clearly had extensive experience. And, there’s still a long way to go – while virtually everyone had patients using CGM, we estimate about 50%-75% of patients on CGM are using apps, despite the fact that there was so much enthusiasm on apps including those for Clarity, LibreLink, Senseonics, and Medtronic.

On Her Gratitude and How Far the Field Has Progressed

  • “I’ve had diabetes for 35 years. In 1986, I was diagnosed on the way to an English class, when I just couldn’t walk. I learned about diabetes from an amazing doctor, Dr. Ingeborg van Pelt and “through inter-library loans”. That’s what we used to do, pre-Internet. So much of the work that all of you are doing is helping the families of people with diabetes so much. I always talk about my husband, who does so much for me – generally in our field, we don’t thank partners very much and we don’t thank children or parents. My parents passed away when they were very young, and I never said thank you to them for helping me with my diabetes, just because I was so busy having diabetes. Never, before I was working in diabetes full-time, did I say thank you to the doctors, the nurses, to the coordinators and manager, to the researchers – thank you for what you do. You have chosen the hardest field, and I know in many cases, it’s chosen you!”

  • “I started my own organization, Close Concerns, back in 2002. Ever since then, I’ve been able to go to multiple scientific, regulatory, and advocacy meetings every single year. That first year, in 2003, there were eight meetings – ISPAD was one of them. There were not that many scientific meetings that we could even go to, however. Looking at where the field was then, it’s amazing where you have taken it and where you have made so many changes today.”

  • “Until really recently, my identity as somebody with diabetes was ‘this is really complicated, and there are so many pieces of it that are unfair.’ I’m someone who is lucky, because I have access to so many great providers and a great family. Even when patients have this, there are things that we present that show our vulnerabilities. But, since I’ve gone on automated insulin delivery, I don’t even have hypoglycemia anymore, not much at all, or not in the same way. I now have soft landings, or I can tell that the hypoglcyemia is coming through the app, and I manage it, and have it for so much less time. The apps work so well that [when I go low] that it prevents me from having over-corrections since I don’t need to make any corrections! And then, all of the hyperglycemia that I experience comes as something I can identify as not the best food choices. The apps are making us smarter as patients and helping us see what we want to avoid.”

On CGMs and Time-in-Range

  • “Do you know what’s special about this date? 1993? [murmers in the crowd] Yes, it was DCCT! There are some amazing stories about DCCT. ADA was in Las Vegas in [1993] and I guess that ADA has never been asked back to Vegas again … Dr. Jerry Share shared with me what happened in Las Vegas: there were standing ovations at ADA, with DCCT and it’s validation of A1c and the knowledge that tighter management and lower A1cs were so positive. If you had control that was tighter, would really reduce your long-term complications. We are in a similar movement now, with time-in-range, and getting beyond A1c. It’s not about replacing A1c, but supplementing it! Today, through so much new work leveraging CGM and Time in Range, we know so much more about how A1c is not the end-all, be-all, and about how Time in Range shows us so much more and helps contextualize A1c.”

  • “And, there’s still so much amazing research to do! What do we know about Time in Range and the long-term outcomes from various patterns?” [Knowing nods.]

  • “Adam Brown compares CGM to other amazing historical tools like the microscope and telescope. In biology, the microscope taught us so much about how cells work. (My 14-year old, Coco, by the way, whenever I ask how she can possibly be taller than me, always responds ‘cell division!’) We got new understanding the component parts of different plants and animals from microscopes. Telescopes, similarly, allowed us to look at the planets and stars and understand our place in the universe. Similarly, in diabetes, CGM IS that tool for understanding what’s working and what’s not working, how food drives it glucose and out of range. These two incredible tools have amazing value. In a similar way, I think that’s where CGM is. This is an amazing tool that has helped us think about time-in-range and how we can get [better].”

  • “Not everyone gets pumps. Not everyone gets CGMs, and a lot of what I’m talking about today relates with [that tech]. Obviously, we need to get to a point where everyone who wants one, gets one. Not everyone wants one. But if they do, we need to make that possible, and then, we need to make these things as easy as possible to use. Things like replacing CGM receivers with cell phones are gamechangers, especially for teenagers.”

  • “With the discretion of seeing [your CGM data] on your phone, you can get a big increase on the number of people using these technologies.”

On Diabetes Apps and More

  • “Apps are not only very heterogenous, and they’ve really improved. When you think of how you used apps, back in the day, you might have been frustrated or your patients might have been frustrated. Now, they are improving all the time.”

  • “Seventy-eight percent of people in [dQ&A’s] panel who are using CGM use an app. That is up from closer to 50% a couple of years ago.”

  • “Not everybody has CGM, but everyone can have a connected meter. Only about 10% of people who use BGMs in [dQ&A’s] panel are actually using the connected part of those meters. We really encourage use of Glooko or Tidepool [to record data] as well as using the apps to analyze it daily or hourly.”

  • “Do you guys know ‘FNIR’? Flat, narrow, in-range. It’s so aspirational. I’m pretty much never flat or narrow, but I’m getting better at in-range. That term comes from the International Diabetes Center in Minneapolis and Dr. Rich Bergenstal and his group.”

  • “The magic of automated insulin deliveries is the soft-landings that come. You don’t have much hypoglycemia at all. So, you don’t have over-corrections ….”

  • “What happens when many more people are at 70% time-in-range? What’s the difference between people who are at 179 mg/dl and are FNIR vs. people who are at 80 mg/dl and are FNIR? What’s the difference when there’s a lot of variability? There are going to be so many interesting things as we try to tackle this massive public health problem and work to reduce long term complications leveraging technology.”

7. Physicians View DreaMed’s Advisor Pro as “Safe,” “Reliable,” and “Useful”

Following an introduction from Dr. Lori Laffel (Joslin Diabetes Center) on the need for diabetes decision support systems, DreaMed’s Dr. Revital Nimri presented some strong early physicians’ satisfaction results from the Advice4U study. DreaMed’s Advisor Pro decision support software is CE-Marked and FDA cleared to provide insulin pump adjustment recommendations using BGM or CGM data. The Advice4U study is a seven-center, Helmsley-funded study, designed to compare glycemic outcomes using insulin pump adjustments based on CGM readings using Advisor Pro vs. experienced physicians. The six-month study, which randomized 122 patients (ages 10-21) to an Advisor Pro arm and physician arm, will read out ATTD 2020, with time-in-range and time spent below 54 mg/dl as primary outcomes. Physicians using Advisor Pro (n=13) also filled out a 50-item questionnaire on their satisfaction at 12- and 24-weeks. On a five-point Likert scale (1=”strongly disagree” and 5=”strongly agree”), physicians gave Advisor Pro a 4.8 for “intuitive and simple,” 4.5 for “reliable,” and 4.5 for “useful,” after 24-weeks. Notably, the physicians rated Advisor Pro 4.2 as “sufficiently dynamic to provide accurate advice in different situations,” even though they only gave the system a 3.5 rating for “similar to therapy adjustments I would have done.” Perhaps most telling, eleven of the thirteen physicians responded that they would want to keep Advisor Pro in clinical practice. In September, we heard that Advisor Pro has been used to delivery advice to more than 100 patients, with launch coming in Israel next.

  • Dr. Gregory Forlenza (Barbara Davis Center), one of the physicians in the study, walked through the way Advisor Pro analyzes CGM data. Both Advisor Pro and a clinician normally begin by analyzing areas in which the patient is doing well, i.e., times when the patient is consistently in-range. Then, the system analyzes periods with hypoglycemia and hyperglycemia. Then, it can analyze insulin dosing data to help identify causes. Dr. Forlenza noted that he would typically spend about one-third of his time in visits answering these types of questions, which takes away from the time left for face-to-face interaction. By using Advisor Pro, there is more time left over in a clinic visit to address concerns that the patient or their families want to talk about.

8. Laurel Messer: Even As Technology Improves, Basic Diabetes Management Education and Training Must be Maintained

The highly-regarded Ms. Laurel Messer (Barbara Davis Center) shared some practical tips for successfully implementing automated insulin delivery systems, emphasizing the need for training around delivering boluses and treating hypoglycemia, even as technology handles more of those tasks automatically. In fact, Ms. Messer called bolusing the “most important part of any technology in the next five years.” When new automated insulin delivery (AID) systems come to market, the tendency is to say to patients, “You don’t have to perform X activity anymore.” According to Ms. Messer, this is probably an overpromise; while diabetes technology certainly does have the ability to greatly reduce certain behaviors (e.g., no-calibration, non-adjunctive CGMs have significantly reduced the need for fingersticks), underplaying behavior X too early can easily result in poorer glycemic control. In the cases of bolus delivery and treating hypoglycemia, “we are not in any space to let up” on education. In line with her point on managing expectations for new AID systems, Ms. Messer recommended that these systems be turned off and to use temporary basal rates when users were sick, on steroids, etc. Lastly, she emphasized the fact that all commercial systems will only be designed to work when people aren’t trying to “fight against the system”; in other words, patients who want more control over the system’s behavior and parameters may prefer different options. As we heard from Dr. Rich Bergenstal back at ENDO 2017, the best way to use MiniMed 670G is to “let it work, let it work, let it work.”

  • To make her point, Ms. Messer shared a humorous, but telling, story about MiniMed 670G. One school nurse called her and told her that there was an emergency because one child’s 670G had gone out of Auto Mode – the nurse thought that exiting Auto Mode meant the device had completely stopped insulin delivery. To combat this type of misperception, Ms. Messer recommended that people view AID systems as the next iteration of pumps, “Pump 2.0.”

  • Ms. Messer showed results gathered from Stanford and the University of Colorado, identifying the top barriers to diabetes tech use in adolescents: hassle of wearing devices all of the time (38%), dislike having devices on the body (33%), dislike how devices look on the body (29%), nervousness that the device won’t work (25%), and not wanting to spend more time managing diabetes (20%). Similarly, a recent article in DT&T showed identified similar barriers to CGM use, though that study seemed to underscore the heterogeneity of responses to diabetes devices.

    • We heard some helpful tips for helping address barriers to device adoption utilized at Barbara Davis Center.
      • Hassle. Alerts should be minimized by always assessing glycemia goals (e.g., avoid hypoglycemia, but not hyperglycemia) and personal tolerance for alerts. Alerts should also be customized by time of day and users should consider taking occasional breaks from device use.
      • On-body discomfort. Providers should help patients choose the proper devices based on size, location of wear, waterproofing, etc. Additionally, patients should be encouraged to wear the device in a place that is convenient (“a CGM on the forearm is better than not having data”).
      • Nervousness. AID systems can be demystified by emphasizing that they are just pumps + sensors. Education around basic diabetes management, such as hypoglycemia and ketone protocols (e.g., STICH) cannot be lost.

  • As the AID landscape becomes populated with more commercial systems, Ms. Messer shared her CARES (Calculates, Adjusts, Reverts, Education, Sensor/Share) paradigm for thinking about AID systems. The framework, used to evaluate MiniMed 670G and Control-IQ in the table below, can be used by both patients and providers who do not have time to learn the ins and outs of every available AID system.

9. Sanofi Symposium Focuses on Managing Type 1, the Importance of Language, and the Advent of TIR

Sanofi’s star-studded symposium provided a broad sweep of the state of type 1 diabetes, from diagnosis to management with up and coming technologies. Dr. Lori Laffel gave the opening address, emphasizing that over 40% of teens and young adults with type 1 diabetes had A1cs of 9 or higher in developed countries. High A1c can be especially problematic when it is persistent and turns into complications many years down the line. Dr. Thomas Danne led a discussion on the progression of type 1 diabetes from disease onset to adulthood and centered his discussion on the early prevention of CVD complications. He believes that digitization can lead to improved outcomes, but only along with increased education, CGM, and related technologies to more tightly manage glucose levels. However, we must not forget that language matters just as much as biology. Dr. Barbara Anderson stressed that it is important to consider cultural factors and avoid judgmental language when treating children (or anyone!) with diabetes. Especially in pediatric populations, Motivational Interviewing should be used to when speaking with patients and families following OARS (Open questions, Affirm, Reflect, Summarize) in order to help families understand the condition’s complexities and options. Though she maintains that face-to-face interactions are the gold standard for behavior change, virtual consultations and training programs with relational agents can also help education and guide patients when clinics are harder to access. Dr. Tadej Battelino wrapped up the symposium with a talk on the importance of time in range (TIR) to manage type 1 diabetes. As A1c doesn’t account for individual glucose variation, using CGM to find TIR is another option for gathering reliable data to advise diabetes care and improve quality of life. With this, the accumulation of data that CGM allows can significantly impact disease burden and cost savings when analyzed in exploratory studies to create novel, effective interventions.

New Type 1 Therapies

1. SGLT-2 Inhibitors for Youth and Adolescents? KOLs Debate the Drug Class’s Benefits and Risks

In a near-packed symposium in the conference’s largest room, Drs. Bruce Perkins, Chantal Mathieu, and Simeon Taylor discussed SGLT inhibitors’ potential use in pediatrics diabetes management. The drug class has been picking up steam for its cardiometabolic promise in adult populations. Examples include Farxiga’s (dapagliflozin) first-in-class indication for hospitalization for heart failure (driven by stunning DAPA-HF results), the FDA’s fast track designation to Lilly/BI’s Jardiance (empagliflozin) for chronic heart failure, and even ESC’s 2019 guidelines that promote SGLT-2 inhibitors as first-line therapy for patients at high risk for/with established CVD. Knowledge of the drug class is nowhere near sparse, with many more large scale CVOTs expected to be complete by 2021.

  • Dr. Bruce Perkins began the session with an overview of the drug class’s mechanism and potential in both type 1 and type 2 populations. He sang the class’s praises in both glycemic and cardiometabolic control. While data from the remogliflozin single-dose study and ATIRMA (on empagliflozin) validate SGLT-2s’ ability to lower A1c, data from CREDENCE supports the drug’s ability to lower risk of adverse renal outcomes. SGLT inhibitors’ ability to confer cardiorenal protection is further supported by DAPA-HF and ATTEMPT. While Dr. Perkins focused on mechanisms for glycemic, natriuretic, and cardio-renal protection, we found his discussion of DKA to be particularly enlightening. SGLT-2s have, of course, been linked to DKA, primarily because of metabolic shifts and decreased insulin doses leading to lipolysis and ketogenesis. Many opponents of extending SGLTs to youth and adolescents also argue that young patients can better manage their diabetes through automated insulin delivery, hybrid closed loop, and CGM to get the same effects as very low dose SGLT treatment. Dr. Perkins emphasizes that DKA can be overcome clinically, and patients should be able to choose from a panel of therapy and technology options to help manage diabetes.    

  • Dr. Chantal Mathieu continued with the effects of SGLT treatment in people with type 1. Current unmet needs in type 1 populations include glycemic control, high risk of hypoglycemia, weight gain, glucose variability, daily diabetes management burden, suboptimal CV risk factor control, and high CVD morbidity and mortality. The DEPICT, inTandem, and EASE studies all show drops in A1c, increased TIR, and decreases in weight and hypoglycemia, but also show side effects like DKA and genital infections. Dr. Mathieu stated that SGLT inhibitors are promising adjunct therapies for type 1 given their ability to reduce hypoglycemia, weight, and glucose variability while improving quality of life – but the right dose must be found to balance the benefits against the risks. Currently, only sotagliflozin and dapagliflozin are approved by the EMA at low doses (5 mg) to treat adult patients with BMI over 27 kg/m2. Dr. Mathieu closed her talk with her own opinions on prescribing SGLT inhibitors, stating that she’d need to know her patient’s entire medical history and only prescribe the drug to patients with A1c below 9 and 10 and BMI over 27 kg/m2. She added that education, for both the patient and entire medical team, is integral to successful SGLT use and mitigating and managing DKA.

  • Calling himself “devil’s advocate,” Dr. Simeon Taylor wrapped the session with a discussion on the potential pitfalls of SGLT inhibitor use, specifically focusing on side effects’ proliferation from early SGLT use. While the drug class has shown an attractive clinical profile in patients with type 2 diabetes, Dr. Taylor cautions that these benefits may not fully extend to patients with type 1. SGLT2 inhibitors have only shown modest decreases in A1c and weight - this, coupled with a 5.8-fold increase in DKA and subsequent risk of death, should make practitioners wary on their benefit in younger populations. SGLT2 use even showed waning glycemic efficacy patients with type 2 in CANVAS, burgeoning the question if the drug could control blood glucose beyond five years if therapy were to start in childhood. Individual variation in response to SGLT2s has also not been studied sufficiently. This combined with genital infections, DKA, accelerated loss of bone mineral density, and increased risk of bone fracture and amputations may not be worth somewhat increased blood glucose control. Dr. Taylor went so far as to call the SGLT2 inhibitor sotagliflozin ten times riskier than troglitazone, an agent taken off the market for its association to liver failure. He concluded his talk with a list of unanswered questions that should be answered before use of this drug class is considered in pediatric diabetes.

2. Could Early Treatment with ACE Inhibitors and Statins Prevent Vascular Complications in Youth with Type 1? Updates from the AdDIT Study

Dr. Loredana Marcovecchio presented findings from the Adolescent Type 1 Diabetes Cardiorenal (AdDIT) study, which sought to determine if early initiation of ACE inhibitors or statins could prevent the onset of kidney, eye, and cardiovascular complications. This update focused on whether treatment with ACE inhibitors and statins prevented CVD onset via urinary albumin excretion as a link between renal health and CVD. Higher albumin-to-creatinine (ACR) ratio, even within normal limits, was associated with progression to worse CV profiles. Thus, Dr. Marcovecchio believes that early screening for ACR may be valuable to identify teens at high risk for vascular complications. The next phase of AdDIT sought to do just so and focused on a group of patients with high ACRs. Treatment with statins reduced lipid levels, but didn’t impact more direct measures of CVD, while treatment with ACE inhibitors reduced progression to microalbuminuria. Both therapies were well tolerated with high adherence rates, and longer-term studies are needed with stricter CVD endpoints to determine the usefulness of these therapies in this younger population. The AdDIT Follow Up study plans to track risk for vascular complications from adolescence to adulthood, and completion is expected in 2021. The hope is that full results from the follow up study can lead to better risk assessment protocols based on the link between the cardiovascular and renal systems, as well as identify new targets for interventions to prevent complications.

  • Even if ACE inhibitors and statins receive approval for use in pediatric populations, the challenge of clinical inertia cannot be forgotten. Dr. Michelle Katz focused on this issue in her presentation during this session, emphasizing that pharmacotherapy can be a viable treatment option for patients that do not have the full support required for lifestyle change or who do not feel confident in their ability to facilitate one. She stated that other challenges include too short of patient visits, insufficient patient education materials, and limited provider training on facilitating lifestyle interventions for patients. While lifestyle change remains the most recommended and viable option for populations as resilient and transitory as youth, we understand that more patient options in treatment options will help many. We believe in particular that options of therapy can help supplement and even encourage lifestyle changes.

3. Results from EDITION JUNIOR: Toujeo Meets Non-Inferiority in A1c Reduction, Adverse Events in Youth Age 6-17 with Type 1 Diabetes

A Sanofi poster highlighted results from the EDITION JUNIOR trial in which treatment with Toujeo (insulin glargine U300) showed non-inferiority in A1c reduction and fewer severe hypoglycemic events compared to Lantus (insulin glargine U100). The EDITION JUNIOR trial (n=463) found similar reductions in A1c (RR: 0.99; 95% CI: 0.88 – 1.02) in patients age 6 to 17 years old with a baseline A1c of 7.5-11% taking Toujeo versus U100, confirming the study’s primary outcome. The secondary outcome of adverse effects was also comparable between both agents, with the number of patients experiencing severe hypoglycemia (6% of participants on Toujeo versus 9% on U100) and hyperglycemia with DKA (8% on Toujeo versus 11% on U100) lower in the Toujeo-treated group. This is the first RCT comparing Toujeo with U100 in a pediatric population, and six-month follow up data will be presented later. The EMA’s CHMP has given Toujeo a positive opinion and recommendation for expanding Toujeo’s label in the EU for the treatment of diabetes in children ages six and older. The EMA is expected to make a decision in the upcoming months. We’re thrilled to see further treatment options being investigated in this important population.

Prevention and Pathophysiology

1. Intermediate Care (2-3 Fingersticks/Day, Human Insulin MDI, Diabetes Education) Is Cost-Effective and Can Increase Survival Rates by Five Times in Low-Resource Countries

Australia’s Dr. Graham Ogle (Life for a Child) shared powerful data showing that moving the state of diabetes care in low-resource countries from “minimal” (fingerstick testing only at clinic, human premixed insulin only, minimal education) to “intermediate” (2-3 fingersticks/day, human insulin MDI, diabetes education) could greatly improve A1c, reduce complications, and mortality. While, ideally, all people with diabetes would receive “comprehensive” care (i.e., the standards of care in ISPAD guidelines), Dr. Ogle performed an analysis examined the effectiveness of intermediate care in six countries: Azerbaijan, Bolivia, Mali, Pakistan, Sri Lanka, and Tanzania. By reducing A1c from 12.5% to 9%, the rate of blindness as a diabetes-related complication dropped from ~50% to ~10%. More drastically, rates of end-stage renal disease fell from ~70% to ~5%. The 30-year survival rate was most dramatically increased in Mali, from 8% to 50%. Azerbaijan, which saw the least improvement, would see a 30-year survival rate jump from 62% to 89% by raising its level of care to “intermediate.” A study of 20 children from Mali in 1999 found that all but two had died after three years. As of 2007, Mali had more than 550 people with type 1 diabetes older than 30. While prevalence of diabetes in Mali is “screaming up,” this is largely due to improved diagnosis. Impressively, Dr. Graham also pointed at countries like Bolivia and Mexico, which have been able to achieve mean A1cs around 8%-9.5% with intermediate care – “just as good as the T1D Exchange data.”

Table 1. 30-Year Survival Rates Under Minimal and Intermediate Care


Minimal Care

Intermediate Care










Sri Lanka









  • Importantly, Dr. Ogle also recently published a cost-analysis, finding that intermediate care was “extremely cost-effective.” Unsurprisingly, providing intermediate care was more expensive than minimal care, though Dr. Ogle noted this was primarily because “providing healthcare for a dead child doesn’t cost anything.” By indexing cost against a country’s GDP per capita, Dr. Ogle called intermediate care “extremely cost-effective” in four Azerbaijan, Bolivia, Pakistan, and Sri Lanka) of the six countries analyzed with the cost of a healthy-life year generated much lower than the GDP per capita. In the other two countries (Mali and Tanzania), intermediate care was still fairly cost-effective.

Questions and Answers

Q: This would be very persuasive if you show it to ministers of health in different countries. Is that the plan?

A: That is the intention. We are planning to combine this with other advocacy materials. Countries are already incrementally improving care. People from Ecuador at this meeting have reported the government is about to start providing analogs. More importantly, to me, they will provide more test strips to their [type 1] children. We’re all working with the governments and this will help us to have more results.

Q (Dr. Thomas Danne): We need data to show what is really effective in improving those outcomes: is it analogs, test strips, pumps?

A: We have increasing data from Bolivia and Mexico. I think they’re blood glucose monitoring and diabetes education. I think analogs are nice, but no one has ever shown that analogs, in a full analysis, improve A1c. They do reduce hypoglycemia. I think the key things are blood glucose monitoring and diabetes education. My dream is that flash glucose monitoring will become cheaper and cheaper, and we can directly jump from no glucose monitoring.

In a multi-disciplinary session spanning epidemiology, genetics, immunology, and the environment, speakers discussed novel links to type 1 and 2 diabetes. Some of the most interesting were due to environmental factors, both in a physical and sociological sense. See below for our summaries of some of the most intriguing, forward-looking presentations of the session.

  • Presenting data from a Swedish national case control study, Dr. Nina Lindell posited the association between size for gestational age and type 1 diabetes. Results found that large size for gestational age increases a child’s risk of developing type 1, while small size for gestational age decreases the risk. After controlling for maternal BMI and diabetes, being born at a large size for gestational age was determined to be an independent risk factor for type 1 diabetes. These findings derived from data from the SWEDIABKIDS registry and the Swedish Medical Birth Register emphasize the importance of prevention to reduce risk factors, like maternal weight and diabetes status, associated with large size for gestational age. Specifically, children born to mothers who were either overweight or obese during pregnancy were at an increased risk for developing type 1 (OR: 1.07, 95% CI: 1.00 – 1.14; OR: 1.22, 95% CI: 1.11 – 1.34). Maternal diabetes status was the strongest risk factor for children developing type 1 diabetes (OR: 3.34, 95% CI: 2.77 – 4.03).

  • Moving to the effects of the outdoor environment, Dr. Kate Miller presented data that link low 25-hydroxyvitamin D to increased risk of type 1 diabetes, younger age of onset and more severe presentation. The study population showcased an average 34% deficiency in 25-hydroxyvitamin D. This deficiency was associated with a significantly increased risk of developing type 1 diabetes (OR: 6.4, p<0.001). When results were stratified by sex, boys showed a linear pattern with age of type 1 diabetes onset: onset was delayed ~two years for every doubling of vitamin D level. Overall, vitamin D deficiency was associated with a mean 5.4 years earlier diabetes onset and being 4 times more likely to present with DKA. In Q&A, one audience member brought up the relevance of measuring vitamin D binding protein levels instead of free vitamin D alone to paint a more accurate picture of metabolic processes. In response, Dr. Miller mentioned that the next iteration of this study will focus on polymorphisms and genetic influences to attempt to target binding proteins.

  • To look into the lives of children with diabetes, Dr. Niels Skipper presented data on the association of prodromal type 1 diabetes with school absenteeism. The mean age of onset of the Danish sample was at 10.9 years old. While peers without type 1 averaged 1 absence a month, children with diabetes began being increasingly absent from school ~four months before diagnosis onward. Specifically, children with diabetes were absent 20% more often than their counterparts without diabetes four months before diagnosis. Peak in absences occurred right at diagnosis (50% more absent), which Dr. Skipper attributed to likely hospitalization associated with diabetes diagnosis. After onset of diabetes, children with less glycemic control were significantly 40-50% more absent than 6-12 months before onset. There was no difference in school attendance in children who had DKA, other than in the month of diagnosis. Though these trends are just correlational at this point, it’s possible that school absenteeism may be a marker for increased intervention in supporting diabetes management.

3. Education Alone May Not be the Best Intervention: The Role of Community Health Workers in Improving Type 1 Outcomes

Dr. Colin Hawkes discussed the unique problem solving required to treat high-risk children with type 1, highlighting the promise of a family-directed, social determinants of health focused community health worker (CHW) intervention. The intervention involved six months of intensive support then six months of reduced support from a CHW to help families with any and all issues that go beyond diabetes care. In the first six months, mean A1c fell 0.5% and appointment attendance improved. These results are impressive given the currently small sample size and the sample’s demographics: 11.3% mean A1c, $31,0000 median household income, and self-reported food insecurity and difficulties paying household bills. Due to the formally analyzed data set being so small, Dr. Hawkes shared a story of one family who received the intervention and greatly benefitted. For a single parent household struggling with food insecurity, bill and loan payments, and reading hospital materials, a CHW helped ensure utilities remained on, helped with loan refinancing, helped with reading hospital documents, and even enrolled the single parent in secondary education. These efforts helped the family’s teenager reduce his A1c to 7.6% from a baseline of 12.3% while improving quality of life and self-efficacy. Dr. Hawkes went so far to say that some families do not need more diabetes education to make improvements, meaning that social determinants can make optimal diabetes control unattainable despite knowledge of how to manage the condition. While early results are preliminary and anecdotal evidence is most impressive, quality improvement and a longitudinal study need to be performed to both enhance the program and determine if the CHW’s impact is sustained overtime.

4. Key Findings on the Relationship Between Behavioral Health, Young Adulthood, and Type 1 Diabetes Care

This multidisciplinary section focused on the different aspects of behavioral health that could affect diabetes care in young adulthood, a period of time defined by the transition from parental to self-diabetes management. See below for some of the biggest takeaways from the session:

  • Dr. Regitze Pals discussed the challenges of adolescence in diabetes care and how interventions in pre-adolescence could help. The most effective programs are mixed method ones that take from different frameworks of interventions rather than programs that focus on self-care or psychosocial aspects alone. However, most studies on theoretical frameworks do not specify how each theory was used to tailor an intervention. Thus, few interventions have targeted pre-teens with type 1 specifically because of their primary basis on adult-centric, individual level psychological theories. Dr. Pals recommends co-producing interventions with the target group in order to increase their efficacy.
  • Dr. Angela Galler talked about the connections between metabolic outcomes and psychological care in teens with type 1 in real world settings. Youth with type 1 diabetes are at higher risk for developing psychological problems than their peers, and psychological problems have been associated with poor glycemic control and higher rates of DKA. While interventions in controlled environments have improved glycemic control and reduced DKA and hospital admissions, data on the efficacy of these interventions in real world settings is sparse. Using data from the German DPV study, Dr. Galler found that 40% of youth received psychological care, and a third of these youth also received continued care. After analyzing the data set, her group found that psychological care was preferentially given to children and teens with worse glycemic outcomes and higher rates of DKA. Glycemic control stabilized after receiving psychological care. Results offer preliminary evidence that more youth with type 1 should seek psychological care in order to better manage their diabetes and complications. 
  • Though receiving supplementary psychological care to help manage type 1 diabetes may be beneficial, it is expensive, and many emerging adults cannot afford it. Dr. Julia Blanchette focused on emerging adults (ages 18 to 25/30) in her presentation. As emergent adults are usually not working full time, financial stressors linked to insulin rationing and hospitalization costs cause 85% to not meet their glycemic goals. A survey given to emergent adults found that most have transitioned to adult health providers, half used CGM, 2/3 used pumps, and 2/3 were on private health insurance while 17% were uninsured (which is higher than figures reported in other studies). Mean reported A1c was 8.1%, and they reported low financial independence – which Dr. Blanchette speculates means that those with type 1 may not meet financial adulthood milestones because of the costs associated with living with diabetes. Overall, this age group has limited knowledge of healthcare finances, so future studies should look at the impact of personal finances on self-management outcomes. Dr. Blanchette urged providers to advocate for policies that support accessible care, assess financial stress in clinics, and deliver developmentally accurate diabetes education and care to emerging adults.
    • Mindfulness and self-acceptance may be low-cost options for treating depression, diabetes distress, and diabetes-related outcomes in teens with type 1. Dr. Hiba Abujaradeh shared that mindfulness focused on enhanced awareness of the present and attitudes of non-judgmental acceptance have been associated with lower levels of depression and diabetes distress and higher levels of self-management behaviors. With this, Dr. Eveline Goethals presented data that shows that increased mean levels of illness acceptance may lead to better diabetes management. She concluded with the point that understanding and recognizing how illness impacts daily life may help clinicians better target diabetes guidance and triage adolescents for psychological care if needed.

5. Children with Diabetes’ Jeff Hitchcock Shares Powerful, Personal Stories on Severe Hypoglycemia

At a Lilly-sponsored symposium on Baqsimi (nasal glucagon), Mr. Jeff Hitchcock (Children with Diabetes) shared multiple personal stories about his experiences with severe hypoglycemia. The stories were powerful and moving, and all of them emphasized how important it is for people with diabetes and their caretakers to be prepared to treat severe hypoglycemia. Baqsimi, launched just a few months ago, has already seen strong uptake in the US, holding one-third of all new brand prescriptions. Given the challenges with using traditional glucagon, we’re surprised this number is not even higher although we know drug adoption for anything new can be slow. We hope to see more investment in marketing.

  • “It was 1989, my daughter was 2 years old and she would beg us for water – we didn’t realize at that time that those were classic symptoms of type 1 diabetes. We had taken her to the pediatrician, where she was diagnosed with oral thrush, later diagnosed with type 1 diabetes, and taken to Washington DC Children’s Hospital. We met with a pediatric endocrinologist, and he basically said ‘don’t worry, everything’s going to be okay.’ In the end it turns out that he was correct – this year, my daughter celebrates her 33rd birthday living with type 1 diabetes. But, as we all know, living with type 1 diabetes on a daily basis has some challenges. One of those challenges is matching food to insulin for a toddler and young child. This is a picture of my daughter at the age of six, recovering from the lowest blood sugar she ever experienced, it was 17 mg/dl. At the time, the best instrument for measuring blood glucose took 120 seconds. We began feeding her cake frosting frantically until we got enough in her for her blood sugar to rise. At the time, glucose tablets were orange and chalky, and she would only take cake frosting – a little bit of advice, don’t use red because when they throw up, it stains everything. Had we had [glucagon] with us, we would have definitely used it. She was fortunate enough to have never needed to use a glucagon rescue, she was always able to rescue herself with oral carbohydrates, but we have been fortunate.”

  • “I just dropped my daughter and wife off at the airport and I got this on my phone: ‘Dad, don’t panic. My blood sugar is 33 [mg/dl]. If you don’t hear from me in five minutes, please call.’ Nothing good starts with ‘Dad, don’t panic.’ I’m sitting in my car, outside, on the free-way near the airport and I thought, what is her address? How do I call emergency services in Tampa? Can they get to her before she loses consciousness? I called her back, told her to sit down, put her phone on the ground, and put it on speaker – ‘we’re just going to talk.’ Her sensor had caught the lowering blood sugar, and she had treated it, but it was still going down and she was scared. A friend of mine said I should be very proud that at 23 she felt confident enough to call me, and I am, but it was terrifying. She had called her boyfriend, now husband, but phone service did not work in the hospital. We were talking, she was starting to feel better, and I’m also thinking, well, if she had a glucagon kit and had tried to flag someone down, would they have known how to use it? Probably not. It took about 40 minutes for her blood sugar to finally get up to 70 [mg/dL], and she said she felt good enough to go to work. It took me a little bit longer before I could drive home.”

  • “[It] was breakfast on Thursday night, this young man with type 1 diabetes had bolused for his breakfast. A friend came by and asked him for help to carry some fun stuff in his room back. He got up, started walking across this resort, he’s a thousand feet away from this giant swimming pool and his blood sugar crashes. He ends up falling to the ground. The people around him that worked for a diabetes care company had no idea what to do. By chance, a mom attending the conference had a glucagon emergency kit in the back of her child’s stroller. Also, a CDE with type 1 diabetes was running by on his morning jog. He stopped, got the glucagon kit, mixed it up, injected it, and rescued him. That’s a lot of things that had to happen all at once to save that young man.”

  • “Later that afternoon, there was a young teenager who had gotten the stomach virus. We watched that teenager’s blood sugar slowly decline. They couldn’t eat anything. We had time to take a glucagon kit, mix it up, inject glucagon, and prevent severe hypoglycemia. The teenager was taken by their parents to a local hospital for an IV and emergency room visit for the stomach virus.”

--by Ursula Biba, Albert Cai, and Kelly Close