The Official Journal of ATTD Advanced Technologies & Treatments for Diabetes Conference 22‐25 February 2023 I Berlin & Online

ATTD 2021 Invited Speaker Abstracts.

Real-World Diabetes Technology: Overcoming Barriers and Disparities.

How can we reach the target of glucose control in type 1 diabetes?

Abstracts from ATTD 2016 9th International Conference on Advanced Technologies & Treatments for Diabetes Milan, Italy-February 3-6, 2016.

The Official Journal of ATTD Advanced Technologies &amp; Treatments for Diabetes Conference <i>Berlin, Germany—February 20–23, 2019</i>

T he past year saw marked advances in research in pediatric diabetes with numerous studies investigating the use of closed-loop systems in the pediatric population. While such technologies are on the horizon for clinical use in pediatrics, other studies in the past year have highlighted the challenges with clinical implementation of insulin pump therapy, a technology that has been available for decades. The hope for an automatedor initially a semiautomated or hybrid closed-loop system requiring the user to give premeal boluses of insulinis well deserved. These systems aim to improve glucose control and lower the burden of care for children with type 1 diabetes (T1D) and their families. However, initial systems will continue to require significant user involvement as well as experienced and informed pediatric diabetes teams for successful adoption of these diabetes technologies. In addition, advances were seen in the use of a novel intranasal formulation of glucagon to treat hypoglycemia that simplifies the current injectable version of this potentially lifesaving medication. A randomized trial on the benefits of metformin in overweight adolescents with T1D found no benefit on HbA1c, but other potential metabolic improvements. Technology was also studied using telehealth to improve diabetes outcomes by delivering care to rural populations and in pediatric patients struggling to achieve treatment goals. Research in diabetes technology in pediatrics has accelerated in the past few years and with the advent of clinical availability of closed-loop technology promises to remain a rich field of investigation for years to come. Pediatric patients and their families should begin to reap the benefits of decades of work on these diabetes technologies to improve glucose control and lower the burden of care for diabetes. We conducted a Medline search for articles on the following topics: diabetes technology, insulin pump therapy (continuous subcutaneous insulin infusion [CSII]), continuous glucose monitoring (CGM), closed-loop systems, and new therapies in T1D relating to the pediatric age group (0-18 years). This article focuses on key articles that were published between July 1, 2015 and June 30, 2016. Use of insulin pump therapy in children and adolescents with type 1 diabetes and its impact on metabolic control: comparison of results from three large, transatlantic paediatric registries

Objective: While it is recognized that there is a strong relationship between the amount of time glucose levels are <70 mg/dL (T<70) and the amount of time <54 mg/dL (T<54), the association has not been well quantified. Methods: Datasets with Dexcom continuous glucose monitoring (CGM) data from nine type 1 diabetes randomized trials were pooled to evaluate the relationship between CGM-measured T<70 and T<54. Penalized B-spline regression lines were fitted to assess the relationship between T<70 and T<54 for blinded CGM use, unblinded CGM use without an automated insulin delivery (AID) system, and unblinded CGM use with an AID system. Results: For blinded data, the T<54 : T<70 ratio varied from 19% when the amount of T<70 was <1% to 44% when the amount of T<70 was ≥7% whereas for unblinded data the ratio varied from 15% to 42%, respectively. When T<70 was 4%, the predicted T<54 was 1.18%, 0.94%, and 0.91% for the blinded, unblinded, and AID data, respectively (P<0.001 comparing blinded versus unblinded and AID). Conclusions: The T<54 : T<70 ratio increases with greater T<70, and the ratio generally is higher with blinded than unblinded CGM data, with the latter appearing to be similar to AID system data. The finding of greater T<54 for a given T<70 with blinded CGM data is presumed to be due to an action being taken by the unblinded CGM user and/or by the AID system to minimize hypoglycemia which will have the effect of reducing the amount of T<54.

While automated insulin delivery (AID) systems have multiple well-established benefits outside of pregnancy and are widely used in non-pregnant individuals with type 1 diabetes (T1D), none of the commercially available AID systems in North America are approved for use during pregnancy. Use of commercially available AID systems off-label in pregnancy is currently limited by: (1) glucose targets higher than the fasting glucose target range recommended during pregnancy and (2) algorithms which were not designed for the dynamic changes in insulin resistance which occur across gestation. However, as AID use in the general population expands, many individuals will opt to continue using these systems off-label during pregnancy, and thus, guidance for providers regarding AID use and optimization during pregnancy is of the utmost importance. A cornerstone to the effective use of AID systems is the systematic and accurate interpretation of continuous glucose monitoring (CGM) data. One obstacle to the use of both CGM and AID systems by obstetric providers is the lack of comfort with CGM interpretation. We therefore present here: (1) a systematic approach to CGM interpretation during pregnancy and (2) practical guidance regarding AID use during pregnancy for individuals who opt to use commercially available AID systems off-label during pregnancy after consideration of individualized risks and benefits.

Optimal inpatient glycemic management targets a blood glucose (BG) of 140-180 mg/dL and is an important safety measure for hospitalized patients with hyperglycemia. Traditional barriers to appropriate insulin administration include incorrect timing of prandial insulin administration, failure to administer basal insulin to persons with insulin deficiency/type 1 diabetes mellitus (DM), and inaccurate insulin dosing or timing resulting in hypoglycemia. Given the ongoing rapid assimilation of technology to manage our patients with DM, we investigated the use of continuous glucose monitoring (CGM) in the inpatient setting as a potential solution to traditional barriers to optimal hyperglycemia management for inpatient care. In this study, we evaluated the efficacy of use of inpatient CGM for insulin dosing in comparison with current standard of care and whether CGM could aid in minimizing hypoglycemic events. This study evaluated the use of Abbott professional (blinded) Freestyle Libre CGMs in participants treated with basal bolus insulin administered with subcutaneous insulin (basal bolus therapy [BBT]: n = 20) or on intravenous insulin (IVI) infusions (n =16) compared with standard point of care (POC) BG measurements. All participants on IVI were admitted with a diagnosis of diabetic ketoacidosis (DKA). The CGM data was not available in real time. Sensors were removed at the time of discharge and data uploaded to Libre View. Continuous BG data were aggregated for each subject and matched to POC BG or lab chemistry values within five minutes. The POC BG results were assessed for comparability (CGM vs standard BG testing). Data were further analyzed for clinical decision-making for correction insulin. The overall mean absolute relative difference including both IVI and BBT groups was 22.3% (SD, 9.0), with a median of 20.0%. By group, the IVI arm mean was 19.6% (SD, 9.4), with a median of 16.0%; for BBT, the arm mean was 24.6% (SD, 8.1), with a median 23.4%. Using the Wilcoxon two-sample test, the means were not different (P = .10), whereas the medians were (P = .015). The CGM consistently reported lower glucose values than POC BG in the majority of paired values (BBT arm mean difference = 44.8 mg/dL, IVI mean difference = 19.7 mg/dL). Glucose results were in agreement for the group 83% of the time with Bland-Altman Plot of Difference versus the mean of all glucometric data. Analysis of correction dose insulin using either CGM or POC BG values resulted in a negligible difference in calculated insulin dose recommended in those receiving subcutaneous insulin. Corrective doses were based on weight and insulin sensitivity (type 1 vs type 2 DM). Participants initially on IVI were included in a data set of BBT once IVI therapy ceased and basal bolus insulin regimen was started. The data of all basal bolus therapy participants with 1142 paired values of CGM versus POC glucose were used. The dosing difference was less for CGM than POC BG in the majority of paired values, and there was an absolute difference in dose of insulin of only 1.34 units. In the IVI group with 300 paired values of CGM versus POC glucose, there was an absolute difference in dose of insulin of only 0.74 units. About a third of the patients studied in the BBT arm experienced a hypoglycemic event with POC BG <70 mg/dL. If used in real time, CGM would have identified a hypoglycemic event for our patients on average 3 hours and 34 minutes before it was detected by standard POC BG. Two participants incurred severe nocturnal hypoglycemia during the study with POC BG <54 mg/dL with hypoglycemia detected on CGM up to 3 hours and 42 minutes before POC testing. These results suggest that the use of inpatient CGM arrives at similar correction insulin dosing. The routine use of CGM for inpatients would consistently underestimate the BG compared with POC BG and could aid in minimizing and predicting hypoglycemia in the hospital setting. Our data support that the model of adoption of real-time inpatient CGM technology is anticipated to have significant impact in the clinical setting in efforts to maintain adequate glycemic control targeting BG 140-180 mg/dL while minimizing the frequency of hypoglycemic events.

The primary goal of managing type1 diabetes mellitus (T1D) is to achieve glycemic control and prevent both acute and chronic complications. In recent years, automated insulin delivery (AID) systems, such as the 780G AID system, have significantly improved glycemic control and patient safety. Despite being the most advanced treatment option, AID initiation is often delayed until the honeymoon stage (partial remission phase). This study evaluated the impact of initiating MiniMed™ 780G at diagnosis on metabolic control and glycemic metrics in children newly diagnosed with T1D. It compares early AID initiation with continuous glucose monitoring (CGM) and multiple daily injection (MDI) therapy over a 1-year follow-up period. This retrospective study included children and adolescents (age range 0.87-17.72years) newly diagnosed with T1D between January 2023 and August 2024. Ten patients who were initiated on AID therapy at diagnosis were included, with eight patients completing a 1-year follow-up. Data from these eight patients and seven patients on CGM + MDI therapy were analyzed at baseline and at 3, 6, and 12months. The mean age at diagnosis was 6.98 ± 3.22years (0.87-9.82) for the AID group and 9.77 ± 4.89years (3.70-17.72) for the CGM + MDI group (p = 0.14). The AID system was initiated at an average of 3.33 ± 7.73days (2-23) after diagnosis, while sensor use in the CGM + MDI group began an average of 17.37 ± 8.86days (1-29) after diagnosis. At 12months, mean hemoglobin A1c (HbA1c) was 6.10% (43 mmol/mol) in the AID group compared with 7.73% (61 mmol/mol) in the CGM + MDI group. Time in range (TIR) was 79.0% vs. 50.7%, and time above range (TAR) was 13.4% vs. 30.7%, based on 2-week CGM data prior to the 12-month visit (p = 0.02, p = 0.009, p = 0.02). No case of diabetic ketoacidosis or severe hypoglycemia was reported during the follow-up period. This study highlights the potential benefits of initiating AID therapy at the time of diagnosis, offering novel insights into its safety and efficacy in the early management of T1D. These findings suggest that early initiation of AID therapy at the time of diagnosis is feasible and may improve glycemic outcomes.

Abstracts from ATTD 20158th International Conference on Advanced Technologies &amp; Treatments for DiabetesParis, France—February 18–21, 2015

State of Type 1 Diabetes Care in the United States in 2016-2018 from T1D Exchange Registry Data.

We investigated the potential benefits of automated insulin delivery (AID) among individuals with type 1 diabetes (T1D) in sub-populations of baseline device use determined by continuous glucose monitor (CGM) use status and insulin delivery via multiple daily injections (MDI) or insulin pump. In a six-month randomized, multicenter trial, 168 individuals were assigned to closed-loop control (CLC, Control-IQ, Tandem Diabetes Care), or sensor-augmented pump (SAP) therapy. The trial included a two- to eight-week run-in phase to train participants on study devices. The participants were stratified into four subgroups: insulin pump and CGM (pump+CGM), pump-only, MDI and CGM (MDI+CGM), and MDI users without CGM (MDI-only) users. We compared glycemic outcomes among four subgroups. At baseline, 61% were pump+CGM users, 18% pump-only users, 10% MDI+CGM users, and 11% MDI-only users. Mean time in range 70-180 mg/dL (TIR) improved from baseline in the four subgroups using CLC: pump+CGM, 62% to 73%; pump-only, 61% to 70%; MDI+CGM, 54% to 68%; and MDI-only, 61% to 69%. The reduction in time below 70 mg/dL from baseline was comparable among the four subgroups. No interaction effect was detected with baseline device use for TIR (P = .67) or time below (P = .77). On the System Usability Questionnaire, scores were high at 26 weeks for all subgroups: pump+CGM: 87.2 ± 12.1, pump-only: 89.4 ± 8.2, MDI+CGM 87.2 ± 9.3, MDI: 78.1 ± 15. There was a consistent benefit in patients with T1D when using CLC, regardless of baseline insulin delivery modality or CGM use. These data suggest that this CLC system can be considered across a wide range of patients.

The use of continuous glucose monitors (CGM) and insulin pumps has revolutionized the care of patients with type 1 diabetes (T1D). Few data are available regarding the use of diabetes technology use in the pregnant T1D population. This study was conducted to evaluate temporal trends of diabetes technology use and predictors of use among pregnant individuals with TID in the United States from 2009 to 2020.MarketScan Research Databases from 2009 to 2020 were used to identify pregnant individuals with T1D who were and were not using CGM and/or insulin pumps. Joinpoint regression analysis was used to estimate the average annual percent change (AAPC) in diabetes technology use over time. Unadjusted and adjusted log-linear Poisson regression models were developed to assess the associations between the outcomes of CGM and insulin pump use and demographic and clinical predictors. Associations were reported as adjusted risk ratios (ARR) with 95% confidence intervals (CI).Among 9,201 pregnancies with T1D, CGM use increased from 2.3% in 2009 to 13.7% in 2020 (AAPC: 13.9%; 95% CI: 11.7-17.1), while insulin pump use remained unchanged from 10.9% in 2009 to 11.8% in 2020 (AAPC: -2.4%; 95% CI: -4.4 to 0.4). Medicaid insurance and obesity were associated with a lower likelihood of CGM use and insulin pump use, while a high obstetric comorbidity index score was associated with a higher likelihood of insulin pump use (ARR: 1.26; 95% CI: 1.05-1.51).From 2009 to 2020, CGM use among pregnant individuals with T1D increased, while insulin pump use remained unchanged. Use varied by patient demographic and clinical factors, most notable for lower likelihood of CGM use and insulin pump use with Medicaid insurance. Although CGM use increased over time, overall CGM use remained lower than expected despite the known benefits of CGM use in improving neonatal outcomes in pregnancies complicated by T1D. · CGM use in pregnant individuals with T1D increased from 2.3 to 13.7%, but pump use was stable.. · Medicaid and obesity were associated with lower CGM and pump use in pregnant individuals with T1D.. · Low CGM use in pregnant T1D individuals highlights barriers and the need for equitable access..

Continuous glucose monitor (CGM) use improves type 1 diabetes (T1D) outcomes, yet children from diverse backgrounds and on public insurance have worse outcomes and lower CGM utilization. Using novel CGM data acquisition and analysis of two T1D cohorts, we test the hypothesis that T1D youth from different backgrounds experience disparities in meaningful CGM use following both T1D diagnosis and CGM uptake. Cohorts drawn from a pediatric T1D program were followed for one year beginning at diagnosis (n = 815, 2016-2020) or CGM uptake (n = 1392, 2015-2020). Using chart and CGM data, CGM start and meaningful use outcomes between racial/ethnic and insurance groups were compared using median days, one-year proportions, and survival analysis. Publicly compared with privately insured were slower to start CGM (233, 151 days, P < .01), had fewer use-days in the year following uptake (232, 324, P < .001), and had faster first discontinuation rates (hazard ratio [HR] = 1.61, P < .001). Disparities were more pronounced among Hispanic and black compared with white subjects for CGM start time (312, 289, 149, P = .0013) and discontinuation rates (Hispanic HR = 2.17, P < .001; black HR = 1.45, P = .038), and remained even among privately insured (Hispanic/black HR = 1.44, P = .0286). Given the impact of insurance and race/ethnicity on CGM initiation and use, it is imperative that we target interventions to support universal access and sustained CGM use to mitigate the potential impact of provider biases and systemic disadvantage and racism. By enabling more equitable and meaningful T1D technology use, such interventions will begin to alleviate outcome disparities between youth with T1D from different backgrounds.