Multicenter Trial of a Tubeless, On-Body Automated Insulin Delivery System With Customizable Glycemic Targets in Pediatric and Adult Participants With Type 1 Diabetes

Real-world glycaemic outcomes of automated insulin delivery in type 1 diabetes: A meta-analysis

AIM

To evaluate the real-world effectiveness of automated insulin delivery (AID) systems in patients with type 1 diabetes (T1D).

MATERIALS AND METHODS

PubMed, Embase, the Cochrane Library, and ClinicalTrials.gov were searched for studies published up until 2 March 2024. We included pragmatic randomized controlled trials (RCTs), cohort studies, and before-after studies that compared AID systems with conventional insulin therapy in real-world settings and reported continuous glucose monitoring outcomes. Percent time in range (TIR; 3.9-10 mmol/L), time below range (TBR; <3.9 mmol/L), time above range (TAR; >10 mmol/L), and glycated haemoglobin (HbA1c) level were extracted. Data were summarized as mean differences (MDs) with 95% confidence interval.

RESULTS

A total of 23 before-after studies (101 704 participants) were included in the meta-analysis. AID systems were associated with an increased percentage of TIR (11.61%, 10.47 to 12.76; p < 0.001). The favourable effect of AID systems was consistently observed when used continuously for 6 (11.76%) or 12 months (11.33%), and in both children (12.16%) and adults (11.04%). AID systems also showed favourable effects on TBR (-0.53%, -0.63 to -0.42), TAR (-9.65%, -10.63 to -8.67) and HbA1c level (-0.42%, -0.47 to -0.37) when compared with previous treatments.

CONCLUSIONS

Similar improvements in glycaemic parameters were observed in real-world settings in RCTs using AID systems in T1D. AID systems benefit both children and adults by increasing TIR for both short- and long-term interventions.

Three months use of Hybrid Closed Loop Systems improves glycated hemoglobin levels in adolescents and children with type 1 diabetes: A meta-analysis

BACKGROUND

Longer outpatient studies have demonstrated that hybrid closed loop (HCL) use has led to a concomitant reduction in glycated hemoglobin(HbA1c) by 0.3%-0.7%. However, reports have also indicated that HbA1c levels are not declined in the long-term use of HCL. Therefore, we wonder that 3 months use of HCL could improve glycated hemoglobin levels in adolescents and children with T1D.

METHODS

Relevant studies were searched electronically in the Cochrane Library, PubMed, and Embase utilizing the key words "Pediatrics or Child or Adolescent", "Insulin Infusion Systems" and "Diabetes Mellitus" from inception to 17th March 2024 to evaluate the performance of HCL on HbA1c in adolescents, and children with T1D.

RESULTS

Nine studies involving 927 patients were identified. Three months use of HCL show a beneficial effect on HbA1c management (p <0.001) as compared to standard of care in adolescents and children with T1D, without evidence of heterogeneity between articles (I2 = 40%, p = 0.10). HCL did significantly increase the overall average percentage of hypoglycemic time between 70 and 180 mg/dL (TIR) (p <0.001; I2 = 51%). HCL did not show a beneficial effect on hypoglycemic time <70 mg/dL and <54 mg/dL (p >0.05). The overall percentage of hyperglycemic time was significantly decreased in HCL group compared to the control group when it was defined as >180 mg/dL (p <0.001; I2 = 83%), >250 mg/dL (p = 0.007, I2 = 86%) and >300 mg/dL (p = 0.005; I2 = 76%). The mean glucose level was significantly decreased by HCL (p <0.001; I2 = 58%), however, no significant difference was found in coefficient of variation of sensor glucose (p = 0.82; I2 = 71%) and daily insulin dose (p = 0.94; I2 <0.001) between the HCL group and the control group.

CONCLUSIONS

HCL had a beneficial effect on HbA1c management and TIR without increased hypoglycemic time as compared to standard of care in adolescents and children with T1D when therapy duration of HCL was not less than three months.

TRIAL NUMBER AND REGISTRY URL

CRD42022367493; https://www.crd.york.ac.uk/PROSPERO, Principal investigator: Zhen-feng Zhou, Date of registration: October 30, 2022.

Randomized Trial of Assisted Hybrid Closed-Loop Therapy Versus Sensor-Augmented Pump Therapy in Pregnancy

Objective: Examine gestational safety, glycemic and health outcomes, of a hybrid closed-loop (HCL) system without pregnancy-specific glucose targets. Research Design: This was a pilot feasibility investigator-initiated, two-site, single-blind, randomized controlled trial of sensor-augmented pump therapy (SAPT) versus HCL therapy in type 1 diabetes pregnancies. Participants were enrolled in the first trimester and randomized at 14-18 weeks of gestation and used SAPT or HCL until 4-6 weeks postpartum. We compared continuous glucose monitoring (CGM) metrics, severe hypoglycemia (SH), diabetic ketoacidosis (DKA), adverse skin reactions, and pregnancy outcomes between groups. Results: Baseline characteristics were similar between groups (n = 11 HCL and n = 12 SAPT). There was no SH or DKA episode after randomization. Time spent <54 mg/dL did not differ between groups. Time spent <63 mg/dL decreased in both groups, significantly in the HCL group (3.5% [1.3% standard error] second trimester and 2.8% [1.3%] third trimester vs. 7.9% [1.3%] run-in phase, P < 0.05 for both). Mean sensor glucose was lower with SAPT compared to HCL therapy in the third trimester (119 [4] mg/dL SAPT vs. 132 [4] mg/dL HCL, P < 0.05). Third trimester time-in-range (TIR; 63-140 mg/dL) increased with SAPT (68.2% [3.1%] vs. 64.3% [3.1%] run-in phase, P < 0.05). Gestational health outcomes did not differ between groups. The HCL group used assistive techniques, such as fake carbohydrate boluses and exiting HCL overnight. Conclusions: CGM within group differences were seen for time <63 mg/dL favoring HCL therapy and TIR favoring SAPT (third trimester vs. baseline). Safety and adverse pregnancy outcomes were similar between groups.

Real-World Evidence of Omnipod® 5 Automated Insulin Delivery System Use in 69,902 People with Type 1 Diabetes

Background: The Omnipod® 5 Automated Insulin Delivery System was associated with favorable glycemic outcomes for people with type 1 diabetes (T1D) in two pivotal clinical trials. Real-world evidence is needed to explore effectiveness in nonstudy conditions. Methods: A retrospective analysis of the United States Omnipod 5 System users (aged ≥2 years) with T1D and sufficient data (≥90 days of data; ≥75% of days with ≥220 continuous glucose monitor readings/day) available in Insulet Corporation's device and person-reported datasets as of July 2023 was performed. Target glucose setting usage (i.e., 110-150 mg/dL in 10 mg/dL increments) was summarized and glycemic outcomes were examined. Subgroup analyses of those using the lowest average glucose target (110 mg/dL) and stratification by baseline characteristics (e.g., age, prior therapy, health insurance coverage) were conducted. Results: In total, 69,902 users were included. Multiple and higher glucose targets were more commonly used in younger age groups. Median percentage of time in range (TIR; 70-180 mg/dL) was 68.8%, 61.3%, and 53.6% for users with average glucose targets of 110, 120, and 130-150 mg/dL, respectively, with minimal time <70 mg/dL (all median <1.13%). Among those with an average glucose target of 110 mg/dL (n = 37,640), median TIR was 65.0% in children and adolescents (2-17 years) and 69.9% in adults (≥18 years). Subgroup analyses of users transitioning from Omnipod DASH or multiple daily injections and of Medicaid/Medicare users demonstrated favorable glycemic outcomes among these groups. Conclusion: These glycemic outcomes from a large and diverse sample of nearly 70,000 children and adults demonstrate effective use of the Omnipod 5 System under real-world conditions.

Use of diabetes technology in children

Children with type 1 diabetes and their caregivers face numerous challenges navigating the unpredictability of this complex disease. Although the burden of managing diabetes remains significant, new technology has eased some of the load and allowed children with type 1 diabetes to achieve tighter glycaemic management without fear of excess hypoglycaemia. Continuous glucose monitor use alone improves outcomes and is considered standard of care for paediatric type 1 diabetes management. Similarly, automated insulin delivery (AID) systems have proven to be safe and effective for children as young as 2 years of age. AID use improves not only blood glucose levels but also quality of life for children with type 1 diabetes and their caregivers and should be strongly considered for all youth with type 1 diabetes if available and affordable. Here, we review key data on the use of diabetes technology in the paediatric population and discuss management issues unique to children and adolescents.

Advances in diabetes technology to improve the lives of people with cystic fibrosis

People with cystic fibrosis (CF) are at risk for dysglycaemia caused by progressive beta cell dysfunction and destruction due to pancreatic exocrine disease and fibrosis. CF-related diabetes (CFRD) is a unique form of diabetes that has distinctive features from both type 1 and type 2 diabetes. Recent advances in diabetes technology may be of particular benefit in this population given the complex, multi-system organ involvement and challenging health issues that people with CFRD often face. This review summarises how diabetes technologies, such as continuous glucose monitors (CGMs) and insulin delivery devices: (1) have improved our understanding of CFRD, including how hyperglycaemia affects clinical outcomes in people with CF; (2) may be helpful in the screening and diagnosis of CFRD; and (3) offer promise for improving the management of CFRD and easing the burden that this diagnosis can add to an already medically complicated patient population.

Comparison between a tubeless, on-body automated insulin delivery system and a tubeless, on-body sensor-augmented pump in type 1 diabetes: a multicentre randomised controlled trial

AIMS/HYPOTHESIS

This study compares the efficacy and safety of a tubeless, on-body automated insulin delivery (AID) system with that of a tubeless, on-body sensor-augmented pump (SAP).

METHODS

This multicentre, parallel-group, RCT was conducted at 13 tertiary medical centres in South Korea. Adults aged 19-69 years with type 1 diabetes who had HbA1c levels of <85.8 mmol/mol (<10.0%) were eligible. The participants were assigned at a 1:1 ratio to receive a tubeless, on-body AID system (intervention group) or a tubeless, on-body SAP (control group) for 12 weeks. Stratified block randomisation was conducted by an independent statistician. Blinding was not possible due to the nature of the intervention. The primary outcome was the percentage of time in range (TIR), blood glucose between 3.9 and 10.0 mmol/l, as measured by continuous glucose monitoring. ANCOVAs were conducted with baseline values and study centres as covariates.

RESULTS

A total of 104 participants underwent randomisation, with 53 in the intervention group and 51 in the control group. The mean (±SD) age of the participants was 40±11 years. The mean (±SD) TIR increased from 62.1±17.1% at baseline to 71.5±10.7% over the 12 week trial period in the intervention group and from 64.7±17.0% to 66.9±15.0% in the control group (difference between the adjusted means: 6.5% [95% CI 3.6%, 9.4%], p<0.001). Time below range, time above range, CV and mean glucose levels were also significantly better in the intervention group compared with the control group. HbA1c decreased from 50.9±9.9 mmol/mol (6.8±0.9%) at baseline to 45.9±7.4 mmol/mol (6.4±0.7%) after 12 weeks in the intervention group and from 48.7±9.1 mmol/mol (6.6±0.8%) to 45.7±7.5 mmol/mol (6.3±0.7%) in the control group (difference between the adjusted means: -0.7 mmol/mol [95% CI -2.0, 0.8 mmol/mol] (-0.1% [95% CI -0.2%, 0.1%]), p=0.366). No diabetic ketoacidosis or severe hypoglycaemia events occurred in either group.

CONCLUSIONS/INTERPRETATION

The use of a tubeless, on-body AID system was safe and associated with superior glycaemic profiles, including TIR, time below range, time above range and CV, than the use of a tubeless, on-body SAP.

TRIAL REGISTRATION

Clinical Research Information Service (CRIS) KCT0008398 FUNDING: The study was funded by a grant from the Korea Medical Device Development Fund supported by the Ministry of Science and ICT; the Ministry of Trade, Industry and Energy; the Ministry of Health and Welfare; and the Ministry of Food and Drug Safety (grant number: RS-2020-KD000056).

Analysis of "Hybrid Closed Loop Using a Do-It-Yourself Artificial Pancreas System in Adults With Type 1 Diabetes"

In an article in Journal of Diabetes Science and Technology, Nanayakkara and colleagues assessed the glycemic efficacy and safety of AndroidAPS, an open-source automated delivery (AID) system, in a crossover randomized controlled trial. Although the trial included only 20 participants during a relatively short 4-week intervention period, glycemic outcomes attained were similar to commercial AID systems and there were no safety concerns. Validation of open-source AID systems in studies such as this should help address clinician hesitancy regarding these systems, and affirms the role of patient-centered innovation and self-management in diabetes care.

Increase Access, Reduce Disparities: Recommendations for Modifying Medicaid CGM Coverage Eligibility Criteria

Numerous studies have demonstrated the clinical value of continuous glucose monitoring (CGM) in type 1 diabetes (T1D) and type 2 diabetes (T2D) populations. However, the eligibility criteria for CGM coverage required by the Centers for Medicare & Medicaid Services (CMS) ignore the conclusive evidence that supports CGM use in various diabetes populations that are currently deemed ineligible. In an earlier article, we discussed the limitations and inconsistencies of the agency's CGM eligibility criteria relative to current scientific evidence and proposed practice solutions to address this issue and improve the safety and care of Medicare beneficiaries with diabetes. Although Medicaid is administered through CMS, there is no consistent Medicaid policy for CGM coverage in the United States. This article presents a rationale for modifying and standardizing Medicaid CGM coverage eligibility across the United States.

Glucose Targets Using Continuous Glucose Monitoring Metrics in Older Adults With Diabetes: Are We There Yet?

The older population is increasing worldwide and up to 30% of older adults have diabetes. Older adults with diabetes are at risk of glucose-related acute and chronic complications. Recently, mostly in type 1 diabetes (T1D), continuous glucose monitoring (CGM) devices have proven beneficial in improving time in range (TIR glucose, 70-180 mg/dL or glucose 3.9-10 mmol/L), glycated hemoglobin (HbA1c), and in lowering hypoglycemia (time below range [TBR] glucose <70 mg/dL or glucose <3.9 mmol/L). The international consensus group formulated CGM glycemic targets relating to older adults with diabetes based on very limited data. Their recommendations, based on expert opinion, were aimed at mitigating hypoglycemia in all older adults. However, older adults with diabetes are a heterogeneous group, ranging from healthy to very complex frail individuals based on chronological, biological, and functional aging. Recent clinical trial and real-world data, mostly from healthy older adults with T1D, demonstrated that older adults often achieve CGM targets, including TIR recommended for non-vulnerable groups, but less often meet the recommended TBR <1%. Existing data also support that hypoglycemia avoidance may be more strongly related to minimization of glucose variability (coefficient of variation [CV]) rather than lower TIR. Very limited data are available for glucose goals in older adults adjusted for the complexity of their health status. Herein, we review the bidirectional associations between glucose and health status in older adults with diabetes; use of diabetes technologies, and their impact on glucose control; discuss current guidelines; and propose a new set of CGM targets for older adults with insulin-treated diabetes that are individualized for health and living status.

An automated insulin delivery system from pregestational care to postpartum in women with type 1 diabetes. Preliminary experience with telemedicine in 6 patients

INTRODUCTION

The use of most commercially available automated insulin delivery (AID) systems is off-label in pregnancy. However, an increasing number of women with type 1 diabetes (T1D) use such devices throughout pregnancy and delivery. We analysed the data of six women with T1D from a single centre (Diabetology Outpatient Clinic of District-63/Asl Salerno, Italy) who were able to start and maintain AID therapy with the MiniMed™ 780G (Medtronic, Minneapolis, MN, USA) throughout the pregestational care period, pregnancy, delivery, and postpartum.

METHODS

We retrospectively collected data from six patients with T1D who received training and initiation on use of the MiniMed™ 780G and attended follow-up visits throughout pregnancy (these visits were virtual because of the COVID-19 pandemic). All patients maintained their devices in the closed-loop setting throughout pregnancy and during labour and delivery. We analysed data from the pregestational phase to the first 30 days postpartum.

RESULTS

All patients achieved the recommended metabolic goals before conception [median time in range (TIR) of 88% for 70-180 mg/dL; median pregnancy-specific TIR 63-140 mg/dL (ps-TIR) of 66% and maintained the ps-TIR until delivery (median ps-TIR 83%). All patients had slightly better metrics during the night than during the day, with a very low time below range of < 63 mg/dL. Optimal glycaemic values were also maintained on the day of labour and delivery (median ps-TIR 92.5%) and in the first 30 days postpartum, with no severe hypoglycaemia. The only neonatal complications were jaundice in one child and an interatrial defect in another child.

CONCLUSION

In our well-selected and trained patients, use of the MiniMed™ 780G helped to achieve and maintain ps-metrics from the pregestational period to delivery despite the fact that the algorithm is not set to achieve the ambitious glycaemic values recommended for pregnancy.

Neural-Net Artificial Pancreas: A Randomized Crossover Trial of a First-in-Class Automated Insulin Delivery Algorithm

Background: Automated insulin delivery (AID) is now integral to the clinical practice of type 1 diabetes (T1D). The objective of this pilot-feasibility study was to introduce a new regulatory and clinical paradigm-a Neural-Net Artificial Pancreas (NAP)-an encoding of an AID algorithm into a neural network that approximates its action and assess NAP versus the original AID algorithm. Methods: The University of Virginia Model-Predictive Control (UMPC) algorithm was encoded into a neural network, creating its NAP approximation. Seventeen AID users with T1D were recruited and 15 participated in two consecutive 20-h hotel sessions, receiving in random order either NAP or UMPC. Their demographic characteristics were ages 22-68 years old, duration of diabetes 7-58 years, gender 10/5 female/male, White Non-Hispanic/Black 13/2, and baseline glycated hemoglobin 5.4%-8.1%. Results: The time-in-range (TIR) difference between NAP and UMPC, adjusted for entry glucose level, was 1 percentage point, with absolute TIR values of 86% (NAP) and 87% (UMPC). The two algorithms achieved similar times <70 mg/dL of 2.0% versus 1.8% and coefficients of variation of 29.3% (NAP) versus 29.1 (UMPC)%. Under identical inputs, the average absolute insulin-recommendation difference was 0.031 U/h. There were no serious adverse events on either controller. NAP had sixfold lower computational demands than UMPC. Conclusion: In a randomized crossover study, a neural-network encoding of a complex model-predictive control algorithm demonstrated similar performance, at a fraction of the computational demands. Regulatory and clinical doors are therefore open for contemporary machine-learning methods to enter the AID field. Clinical Trial Registration number: NCT05876273.

Protocol for a prospective, multicenter, parallel-group, open-label randomized controlled trial comparing standard care with Closed lOoP In chiLdren and yOuth with Type 1 diabetes and high-risk glycemic control: the CO-PILOT trial

Purpose

Advanced hybrid closed loop (AHCL) systems have the potential to improve glycemia and reduce burden for people with type 1 diabetes (T1D). Children and youth, who are at particular risk for out-of-target glycemia, may have the most to gain from AHCL. However, no randomized controlled trial (RCT) specifically targeting this age group with very high HbA1c has previously been attempted. Therefore, the CO-PILOT trial (Closed lOoP In chiLdren and yOuth with Type 1 diabetes and high-risk glycemic control) aims to evaluate the efficacy and safety of AHCL in this group.

Methods

A prospective, multicenter, parallel-group, open-label RCT, comparing MiniMed™ 780G AHCL to standard care (multiple daily injections or continuous subcutaneous insulin infusion). Eighty participants aged 7-25 years with T1D, a current HbA1c ≥ 8.5% (69 mmol/mol), and naïve to automated insulin delivery will be randomly allocated to AHCL or control (standard care) for 13 weeks. The primary outcome is change in HbA1c between baseline and 13 weeks. Secondary outcomes include standard continuous glucose monitor glycemic metrics, psychosocial factors, sleep, platform performance, safety, and user experience. This RCT will be followed by a continuation phase where the control arm crosses over to AHCL and all participants use AHCL for a further 39 weeks to assess longer term outcomes.

Conclusion

This study will evaluate the efficacy and safety of AHCL in this population and has the potential to demonstrate that AHCL is the gold standard for children and youth with T1D experiencing out-of-target glucose control and considerable diabetes burden.

Trial registration

This trial was prospectively registered with the Australian New Zealand Clinical Trials Registry on 14 November 2022 (ACTRN12622001454763) and the World Health Organization International Clinical Trials Registry Platform (Universal Trial Number U1111-1284-8452).

Supplementary Information

The online version contains supplementary material available at 10.1007/s40200-024-01397-4.

Digital twins and artificial intelligence in metabolic disease research

Digital twin technology is emerging as a transformative paradigm for personalized medicine in the management of chronic conditions. In this article, we explore the concept and key characteristics of a digital twin and its applications in chronic non-communicable metabolic disease management, with a focus on diabetes case studies. We cover various types of digital twin models, including mechanistic models based on ODEs, data-driven ML algorithms, and hybrid modeling strategies that combine the strengths of both approaches. We present successful case studies demonstrating the potential of digital twins in improving glucose outcomes for individuals with T1D and T2D, and discuss the benefits and challenges of translating digital twin research applications to clinical practice.

The Type of Patient Training Does Not Impact Outcomes in the First 90 Days of Automated Insulin Delivery Use

BACKGROUND

Youth starting Omnipod 5 (OP5) can onboard with a diabetes educator or self-start with support from online, industry-provided educational modules. We compared glycemic control and pump interaction by training type among youth initiating OP5.

METHODS

This retrospective review included 297 youth with type 1 diabetes (T1D) aged <22 years initiating OP5. We analyzed baseline CGM data and pump and CGM data from the first 90 days of OP5 use. Multilevel mixed-effects regression assessed for changes in time in range (TIR) from baseline to 90 days by training type.

RESULTS

Of youth initiating OP5 42.4% trained with a diabetes educator and 57.6% self-started. At baseline self-starters had a longer T1D duration (5.0 (2.6,7.9) vs 2.5 (1.3,5.5) years, p=0.001), more time <54 mg/dL (0.3% (0.1,1) vs 0.15% (0,1), p=0.01), and a higher coefficient of variation (40.2% (37,44.4) vs 38.7% (34.4,42.4), p=0.004). After 90 days of OP5 use, groups did not differ in time in automated mode or boluses per day. In a longitudinal model, after adjusting for baseline TIR and T1D duration, 90-day TIR was 10.5%-points higher (CI 9.2-11.8, p<0.0001), positively associated with baseline TIR (β=0.82, CI 0.78-0.85, p<0.0001), and 1.1%-point greater among self-starters (CI 0.06-2.2; p=0.04).

CONCLUSIONS

After 90 days of OP5 use glycemic control and pump interactions were minimally different between youth who self-started and those who trained with a diabetes educator. For youth at a tertiary care center previously using an Omnipod system, online educational modules offered by industry provides sufficient training for use.

Postprandial glucose-management strategies in type 1 diabetes: Current approaches and prospects with precision medicine and artificial intelligence

Postprandial glucose control can be challenging for individuals with type 1 diabetes, and this can be attributed to many factors, including suboptimal therapy parameters (carbohydrate ratios, correction factors, basal doses) because of physiological changes, meal macronutrients and engagement in postprandial physical activity. This narrative review aims to examine the current postprandial glucose-management strategies tested in clinical trials, including adjusting therapy settings, bolusing for meal macronutrients, adjusting pre-exercise and postexercise meal boluses for postprandial physical activity, and other therapeutic options, for individuals on open-loop and closed-loop therapies. Then we discuss their challenges and future avenues. Despite advancements in insulin delivery devices such as closed-loop systems and decision-support systems, many individuals with type 1 diabetes still struggle to manage their glucose levels. The main challenge is the lack of personalized recommendations, causing suboptimal postprandial glucose control. We suggest that postprandial glucose control can be improved by (i) providing personalized recommendations for meal macronutrients and postprandial activity; (ii) including behavioural recommendations; (iii) using other personalized therapeutic approaches (e.g. glucagon-like peptide-1 receptor agonists, sodium-glucose co-transporter inhibitors, amylin analogues, inhaled insulin) in addition to insulin therapy; and (iv) integrating an interpretability report to explain to individuals about changes in treatment therapy and behavioural recommendations. In addition, we suggest a future avenue to implement precision recommendations for individuals with type 1 diabetes utilizing the potential of deep reinforcement learning and foundation models (such as GPT and BERT), employing different modalities of data including diabetes-related and external background factors (i.e. behavioural, environmental, biological and abnormal events).

Efficacy of the hybrid closedloop insulin delivery system in children and adolescents with type 1 diabetes: a meta-analysis with trial sequential analysis

The aim of this study was to assess the efficacy and safety of hybrid closed-loop (HCL) systems for insulin delivery in children and adolescents with type 1 diabetes (T1D). We searched Embase, PubMed, and Cochrane Library for randomized controlled trials (RCTs) published until March 2023 comparing the HCL therapy with control therapies for children and adolescents with T1D. We computed weighted mean differences (WMDs) for continuous outcomes and risk ratios (RRs) with 95% confidence intervals (CIs) for binary endpoints. Four RCTs and 501 patients were included, of whom 323 were randomized to HCL therapy. Compared with control therapies, HCL significantly improved the period during which glucose level was 70-180 mg/dL (WMD 10.89%, 95% CI 8.22-13.56%) and the number of participants with glycated hemoglobin (HbA1c) level < 7% (RR 2.61, 95% CI 1.29-5.28). Also, HCL significantly reduced the time during which glucoselevel was > 180 mg/dL (WMD-10.46%, 95% CI-13.99 to-6.93%) and the mean levels of glucose (WMD-16.67 mg/dL, 95% CI-22.25 to-11.09 mg/dL) and HbA1c (WMD-0.50%, 95% CI-0.68 to-0.31). There were no significant differences between therapies regarding time during which glucose level was < 70 mg/dL or <54 mg/dL or number of episodes of ketoacidosis, hyperglycemia, and hypoglycemia. In this meta-analysis, HCL compared with control therapies was associated with improved time in range and HbA1c control in children and adolescents with T1D and a similar profile of side effects. These findings support the efficacy of HCL in the treatment of T1D in this population.

Comparative Effectiveness of Hybrid Closed-Loop Automated Insulin Delivery Systems Among Patients with Type 1 Diabetes

BACKGROUND

Clinical trials have demonstrated the efficacy and safety of hybrid closed-loop (HCL) systems, yet few studies have compared outcomes in the real-world setting.

METHOD

This retrospective study analyzed patients from an academic endocrinology practice between January 1, 2018, and November 18, 2022. The inclusion criteria were diagnosis code for type I diabetes (T1D), >18 years of age, new to any HCL system [Medtronic 670G/770G (MT), Tandem Control IQ (CIQ), or Omnipod 5 (OP5)], and availability of a pump download within three months. The outcomes included %time in range (TIR) of 70 to 180 mg/dL, %time below range (TBR) <70 mg/dL at 90 days, and HbA1c for 91 to 180 days.

RESULT

Of the 176 participants, 47 were MT, 74 CIQ, and 55 OP5. Median (25%, 75%) change in HbA1c was -0.1 (-0.8, 0.3), -0.6 (-1.1, -0.15), and -0.55 (-0.98, 0)% for MT, CIQ, and OP5, respectively, (P = .04). TIR was 70 (57, 76), 67 (59, 75), and 68 (60, 76)% (P = .95) at 90 days while TBR was 2 (1, 3), 1 (0, 2), and 1 (0, 1)%, respectively, (P = .002). The %time in automated delivery was associated with TIR and change in HbA1c. After controlling other factors including %time in automated delivery, HCL type was not an independent predictor of change in HbA1c nor TIR but remained a significant predictor of TBR.

CONCLUSION

There were significant reductions in HbA1c in CIQ and OP5. TIR was similar across pumps, but TBR was highest with MT. The %time in automated delivery likely explains differences in change in HbA1c but not TBR between HCL systems.

Disordered Eating Behaviors Among Adolescents and Young Adults with Type 1 Diabetes Treated with Insulin Pumps and Hybrid Closed-Loop Systems

Background and Aims: Disordered eating behaviors (DEB) are more common among individuals with type 1 diabetes (T1D) compared to those without, and for insulin pump users may be associated with higher hemoglobin A1c (HbA1c). We investigated DEB risk factors among insulin pump-treated individuals with T1D and clinical characteristics of hybrid closed-loop (HCL) systems' users by DEB level. Methods: An observational, cross-sectional study of 167 insulin pump-treated individuals with T1D, 13-21 years of age. Data were obtained from patients' medical charts with additional self-reported questionnaires, including assessment of DEB. Results: DEB were found in 71 (42.5%) individuals, and positively associated with female sex (β = 2.98 [standard error (SE) = 1.31], P = 0.025), body mass index (BMI)-Z-score (β = 2.12 [SE = 0.64], P = 0.001), HbA1c (β = 1.40 [SE = 0.45], P = 0.02), and higher rate of pump discontinuation (β = 4.48 [SE = 1.99], P = 0.026). The use of HCL systems compared to insulin pumps was associated with higher BMI-Z-score (odds ratio [OR]: 3.46 [95% confidence interval, CI: 1.52-7.87], P = 0.003) and tendency to lower HbA1c level (OR: 0.44 [95% CI: 0.18-1.09], P = 0.078) among individuals without DEB, and with lower HbA1c level (OR: 0.29 [95% CI: 0.10-0.83], P = 0.022) and higher socioeconomic status (OR: 1.73 [95% CI: 1.09-2.74], P = 0.020) among individuals with DEB. Conclusions: DEB are common among individuals with T1D treated with insulin pumps and are associated with higher HbA1c levels. Among T1D individuals with DEB, HCL system use is associated with lower HbA1c compared to insulin pump treatment. Our findings highlight the importance of regular screening for DEB and its risk factors to improve pump treatment and diabetes management. Moreover, individuals with DEB using HCL systems may benefit from reduced HbA1c levels.

Improved Satisfaction While Maintaining Safety and High Time in Range (TIR) With a Medtronic Investigational Enhanced Advanced Hybrid Closed-Loop (e-AHCL) System

OBJECTIVE

To determine feasibility and compare acceptance of an investigational Medtronic enhanced advanced hybrid closed-loop (e-AHCL) system in adults with type 1 diabetes with earlier iterations.

RESEARCH DESIGN AND METHODS

This nonrandomized three-stage (12 weeks each) exploratory study compared e-AHCL (Bluetooth-enabled MiniMed 780G insulin pump with automatic data upload [780G] incorporating an updated algorithm; calibration-free all-in-one disposable sensor; 7-day infusion set) preceded by a run-in (non-Bluetooth 780G [670G V4.0 insulin pump] requiring manual data upload; Guardian Sensor 3 [GS3] requiring calibration; 3-day infusion set), stage 1 (780G; GS3; 3-day infusion set), and stage 2 (780G; calibration-free Guardian Sensor 4; 3-day infusion set). Treatment satisfaction was assessed by Diabetes Technology Questionnaire (DTQ)-current (primary outcome) and other validated treatment satisfaction tools with glucose outcomes by continuous glucose monitoring metrics.

RESULTS

Twenty-one of 22 (11 women) participants (baseline HbA1c 6.7%/50 mmol/mol) completed the study. DTQ-current scores favored e-AHCL (123.1 [17.8]) versus run-in (101.6 [24.2]) and versus stage 1 (110.6 [20.8]) (both P < 0.001) but did not differ from stage 2 (119.4 [16.0]; P = 0.271). Diabetes Medication System Rating Questionnaire short-form scores for "Convenience and Efficacy" favored e-AHCL over run-in and all stages. Percent time in range 70-180 mg/dL was greater with e-AHCL versus run-in and stage 2 (+2.9% and +3.6%, respectively; both P < 0.001). Percent times of <70 mg/dL for e-AHCL were significantly lower than run-in, stage 1, and stage 2 (-0.9%, -0.6%, and -0.5%, respectively; all P < 0.01).

CONCLUSIONS

e-AHCL was feasible. User satisfaction increased compared with earlier Medtronic HCL iterations without compromising glucose control.

Advances in Automated Insulin Delivery with the Medtronic 780G: The Australian Experience

Aim: To assess the real-world performance of MiniMed™ 780G for Australians with type 1 diabetes (T1D) following advanced hybrid closed loop (AHCL) activation and to evaluate the effect of changing from MiniMed 670/770G to 780G. Methods: We analyzed deidentified Carelink™ continuous glucose monitoring (CGM) data from Australian users from January 2020 to December 2022, including the proportion attaining three major consensus targets: Glucose management indicator (GMI <7.0%), time in range (TIR 70-180 mg/dL >70%), and time below range (TBR 70 mg/dL <4%). Results: Comparing 670/770G users (n = 5676) for mean ± standard deviation 364 ± 244 days with 780G users (n = 3566) for 146 ± 145 days, the latter achieved a higher TIR (72.6% ± 10.6% vs. 67.3% ± 11.4%; P < 0.001), lower time above range (TAR) (25.5% ± 10.9% vs. 30.6% ± 11.7%; P < 0.001), and lower GMI (6.9% ± 0.4% vs. 7.2% ± 0.4%; P < 0.001) without compromising TBR (1.9% ± 1.8% vs. 2.0% ± 1.8%; P = 0.0015). Of 1051 670/770G users transitioning to 780G, TIR increased (70.0% ± 10.7% to 74.0% ± 10.2%; P < 0.001), TAR decreased (28.1% ± 10.9% to 24.0% ± 10.7%; P < 0.001), and TBR was unchanged. The percentage of users attaining all three CGM targets was higher in 780G users (50.1% vs. 29.5%; P < 0.001). CGM metrics were stable at 12 months post-transition. Conclusion: Real-world data from Australia shows that a higher proportion of MiniMed 780G users meet clinical targets for CGM consensus metrics compared to MiniMed 670/770G users and glucose control was sustained over 12 months.

Emerging Technologies and Therapeutics for Type 1 Diabetes

Recent years witnessed advancements in diabetes technologies and therapeutics. People with type 1 diabetes have more options to control their blood glucose, prevent hypoglycemia, and spend more time with their loved ones. Newer diabetes technologies and therapeutics improve the quality of life and boost the confidence of people with type 1 diabetes. In parallel to changes in the diabetes technology field, stem cell research has been evolving. Gene editing and production of β cells from stem cells are ongoing. The current focus of cure studies is how to increase the survival of cells produced with stem cells. New adjunctive therapies are under development.

Real-World Evidence of Automated Insulin Delivery System Use

Objective: Pivotal trials of automated insulin delivery (AID) closed-loop systems have demonstrated a consistent picture of glycemic benefit, supporting approval of multiple systems by the Food and Drug Administration or Conformité Européenne mark receipt. To assess how pivotal trial findings translate to commercial AID use, a systematic review of retrospective real-world studies was conducted. Methods: PubMed and EMBASE were searched for articles published after 2018 with more than five nonpregnant individuals with type 1 diabetes (T1D). Data were screened/extracted in duplicate for sample size, AID system, glycemic outcomes, and time in automation. Results: Of 80 studies identified, 20 met inclusion criteria representing 171,209 individuals. Time in target range 70-180 mg/dL (3.9-10.0 mmol/L) was the primary outcome in 65% of studies, with the majority of reports (71%) demonstrating a >10% change with AID use. Change in hemoglobin A1c (HbA1c) was reported in nine studies (range 0.1%-0.9%), whereas four reported changes in glucose management indicator (GMI) with a 0.1%-0.4% reduction noted. A decrease in HbA1c or GMI of >0.2% was achieved in two-thirds of the studies describing change in HbA1c and 80% of articles where GMI was described. Time below range <70 mg/dL (<3.9 mmol/L) was reported in 16 studies, with all but 1 study showing stable or reduced levels. Most systems had >90% time in automation. Conclusion: With larger and more diverse populations, and follow-up periods of longer duration (∼9 months vs. 3-6 months for pivotal trials), real-world retrospective analyses confirm pivotal trial findings. Given the glycemic benefits demonstrated, AID is rapidly becoming the standard of care for all people living with T1D. Individuals should be informed of these systems and differences between them, have access to and coverage for these technologies, and receive support as they integrate this mode of insulin delivery into their lives.

Feasibility and Preliminary Safety of Smartphone-Based Automated Insulin Delivery in Adolescents and Children With Type 1 Diabetes

BACKGROUND

A smartphone-based automated insulin delivery (AID) controller device can facilitate use of interoperable components and acceptance in adolescents and children.

METHODS

Pediatric participants (N = 20, 8F) with type 1 diabetes were enrolled in three sequential age-based cohorts: adolescents (12-<18 years, n = 8, 5F), school-age (8-<12 years, n = 7, 2F), and young children (2-<8 years, n = 5, 1F). Participants used the interoperable artificial pancreas system (iAPS) and zone model predictive control (MPC) on an unlocked smartphone for 48 hours, consumed unrestricted meals of their choice, and engaged in various unannounced exercises. Primary outcomes and stopping criteria were defined using fingerstick blood glucose (BG) data; secondary outcomes compared continuous glucose monitoring (CGM) data with preceding sensor augmented pump (SAP) therapy.

RESULTS

During AID, there was no more than one BG <50 mg/dL except in one young child participant; no instance of more than two episodes of BG ≥300 mg/dL lasting longer than 2 hours; and no adverse events. Despite large meals (total of 404.9 grams of carbs) and unannounced exercise (total of 182 minutes), overall CGM percent time in range (TIR) of 70 to 180 mg/dL during AID was statistically similar to SAP (63.5% vs 57.3%, respectively, P = .145). Overnight glucose standard deviation was 43 mg/dL (vs SAP 57.9 mg/dL, P = .009) and coefficient of variation was 25.7% (vs SAP 34.9%, P < .001). The percent time in closed-loop mode and connected to the CGM was 92.7% and 99.6%, respectively. Surveys indicated that participants and parents/guardians were satisfied with the system.

CONCLUSIONS

The smartphone-based AID was feasible and safe in sequentially younger cohorts of adolescents and children.

CLINICALTRIALS.GOV

NCT04255381 (https://clinicaltrials.gov/ct2/show/NCT04255381).

Removing Barriers, Bridging the Gap, and the Changing Role of the Health Care Professional with Automated Insulin Delivery Systems

As all people with type 1 diabetes (T1D) and some with type 2 diabetes (T2D) require insulin, there is a need to develop management methods that not only achieve glycemic targets but also reduce the burden of living with diabetes. After insulin pumps and continuous glucose monitors, the next step in the evolution of diabetes technology is automated insulin delivery (AID) systems, which have transformed intensive insulin management over the past decade, as these systems address the shortcomings of previous management options. However, AID use remains fairly limited, and access represents a major barrier to use for many people with diabetes, despite these systems being standard of care. Therefore, the future of AID will necessitate addressing barriers related to social determinants of health, finances, and an expansion of the number and type of health care professionals (HCPs) prescribing AID systems. These crucial steps will be essential to ensure that everyone with intensively managed diabetes can use AID systems. The impact of implementing these changes will create a shift in the future of diabetes care that will result in achievement of more targeted glycemia and psychosocial outcomes for all people with diabetes and an expansion of the role of all HCPs in AID-related diabetes care. Even more importantly, by addressing social determinants of health and clinical inertia related to AID, the field can address disparities in outcomes across countries, race, gender, socioeconomic status, and insurance status. Furthermore, the increased use of AID system will provide more time during appointments for a shift in the discussion away from fine tuning insulin dosing and toward a focus on more topics related to behavior and conversations about general health. This will include psychosocial outcomes, and quality of life. In addition, these changes can hopefully allow for time to discuss more general issues, such as cardiovascular health, obesity prevention, diabetes-related complications, and other health-related concerns.

The Myth of MARD (Mean Absolute Relative Difference): Limitations of MARD in the Clinical Assessment of Continuous Glucose Monitoring Data

The mean absolute relative difference (MARD) is a numerical metric that has been adopted by the diabetes technology community as the main indicator that describes the accuracy of a glucose sensor at a single point in time. The appropriateness of this adoption is questionable because there is limited evidence that MARD has meaningful clinical relevance in the current era of sensor technology. The calculation may be simple, but evaluation of MARD can be very complex because it is substantially impacted by the design of the data collection in an accuracy study. Factors that can influence the overall MARD include participant demographics such as type of diabetes and age, site of sensor wear, and the percentage of collected values in each glycemic range during the study that is, in turn, a function of the study design. MARD is only one of several important statistical metrics such as bias and precision that are relevant to assessing accuracy of a sensor. Furthermore, these analytic metrics convey little information about the safety and effectiveness of sensor use with an automated insulin delivery system or a standalone device. There are no clinical studies in people with diabetes (PWD) proving that MARD can accurately differentiate between a safe and unsafe sensor or between a more and less clinically effective sensor. Moreover, there are alternatives to MARD that can do this in a clinically meaningful way, which include error grid analyses and clinical studies in PWD. This review attempts to demythologize the status of MARD for the diabetes community in an effort to shift the focus from MARD to using clinically relevant assessments.

Efficacy of a Hybrid Closed-Loop Solution in Patients With Excessive Time in Hypoglycaemia: A Post Hoc Analysis of Trials With DBLG1 System

BACKGROUND

Automated insulin delivery is an efficient treatment for patients with type 1 diabetes. Little is known on its impact on patients with excessive time in hypoglycaemia.

METHODS

We performed a post hoc analysis of three randomized control trials that used the DBLG1 (Diabeloop Generation 1) hybrid closed-loop solution. Patients whose time below 70 mg/dL during baseline, open-loop phase exceeded 5% were selected. The outcomes were the differences between the closed-loop and the open-loop phases in time in various ranges and Glycemia Risk Index (GRI).

RESULTS

We identified 45 patients exhibiting ≥5% of time below 70 mg/dL during the open-loop phase. Under closed-loop, the time in hypoglycaemia (54 to <70 mg/dL) dropped from 7.9% (SD 2.4) to 3.2% (SD 1.6) (difference -4.7% [-5.3; -4.1], P < 10-4). The time below 54 mg/dL decreased from 1.9% (SD 1.3) to 0.8% (SD 0.7) (difference -0.9% [-1.4; -0.8], P < 10-4). The time in range (TIR 70-180 mg/dL) improved from 63.3 (SD 9.5) to 68.2% (SD 8.2) (difference 5.1% [2.9; 7.0], P < 10-4). The GRI improved from 51.2 (SD 12.4) to 38.0 (SD 10.9) (difference 13.2 [10.4; 16.0], P < 10-4).

CONCLUSION

DBLG1 decreased time in hypoglycaemia by more than 50% even in patients with excessive time in hypoglycaemia at baseline, while also improving both TIR and GRI, under real-life conditions. The improvement in GRI (13.2%) exceeded that of the improvement in TIR (5.1%) indicating that in this data set, GRI was more sensitive than TIR to the improvement in glycaemia achieved with closed-loop. These results support the safety and efficacy of this treatment.

Hybrid Closed Loop Systems Improve Glycemic Control and Quality of Life in Historically Minoritized Youth with Diabetes

Background: We assessed changes in glycemic control and person-reported outcome measures (PROMs) with t:slim X2 insulin pump with Control-IQ technology use among historically minoritized youth who are least likely to access hybrid closed loop (HCL) technology. Methods: This single-arm, prospective pilot study enrolled 15 publicly insured, insulin pump-naïve, non-Hispanic Black youth ages 6 to <21 years with type 1 diabetes and hemoglobin A1c (HbA1c) ≥10% in a 6-month study of HCL use. The primary outcome was absolute change in time in range (TIR) (70-180 mg/dL). Secondary outcomes included other continuous glucose monitor metrics, PROMs, and diabetic ketoacidosis (DKA) incidence. Results: For 13 youth (median 14.8 years, 53.3% female, HbA1c 11.7%) who completed the study, baseline TIR of 12.3% (6.3-27.1%) increased 23.7%-points (16.9, 30.5%; P < 0.001) or 5.7 h per day. Percent time >250 mg/dL decreased 33.9%-points (-44.8, -23.1%; P < 0.001) or 8.1 h per day from a baseline of 69.4% (51.6, 84.0%). Median time in HCL was 78.3% (59.7, 87.3%). Youth received 10.1 (9.2, 11.9) boluses per day, 71.7% (63.8, 79.3%) of which were HCL-initiated autoboluses. Diabetes-specific quality of life increased among parents (P < 0.001) and youth (P = 0.004), and diabetes distress decreased in both groups (P < 0.001, P = 0.005). Improvements in glycemia did not correlate with any baseline youth or parent PROMs. DKA was high at baseline (67 episodes/100-person years) and did not increase during the intervention (72 episodes/100-person years, P = 0.78). Conclusion: Improvements in glycemic control and quality of life exceeding pivotal trial findings without increased safety risks among historically minoritized youth emphasize the need for equitable access to HCL systems. ClinicalTrials.gov: clinicaltrials.gov ID (NCT04807374).

Remote endpoints for clinical trials in cystic fibrosis: Report from the U.S. CF foundation remote endpoints task force

The COVID-19 pandemic necessitated a rapid shift in clinical research to perform virtual visits and remote endpoint assessments, providing a key opportunity to optimize the use of remote endpoints for clinical trials in cystic fibrosis. The use of remote endpoints could allow more diverse participation in clinical trials while minimizing participant burden but must be robustly evaluated to ensure adequate performance and feasibility. In response, the Cystic Fibrosis Foundation convened the Remote Endpoint Task Force (Supplemental Table 1), a multidisciplinary group of CF researchers with remote endpoint expertise and community members tasked to better understand the current and future use of remote endpoints for clinical research. Here, we describe the current use of remote endpoints in CF clinical research, address key unanswered questions regarding their use and feasibility, and discuss the next steps to determine clinical trial readiness.

Safety and Feasibility Evaluation of Automated User Profile Settings Initialization and Adaptation With Control-IQ Technology

BACKGROUND

Optimization of automated insulin delivery (AID) settings is required to achieve desirable glycemic outcomes. We evaluated safety and efficacy of a computerized system to initialize and adjust insulin delivery settings for the t:slim X2 insulin pump with Control-IQ technology in adults with type 1 diabetes (T1D).

METHODS

After a 2-week continuous glucose monitoring (CGM) run-in period, adults with T1D using multiple daily injections (MDI) (N = 33, mean age 36.1 years, 57.6% female, diabetes duration 19.7 years) were transitioned to 13 weeks of Control-IQ technology usage. A computerized algorithm generated recommendations for initial pump settings (basal rate, insulin-to-carbohydrate ratio, and correction factor) and weekly follow-up settings to optimize glycemic outcomes. Physicians could override the automated settings changes for safety concerns.

RESULTS

Time in range 70 to 180 mg/dL improved from 45.7% during run-in to 69.1% during the last 30 days of Control-IQ use, a median improvement of 18.8% (95% confidence interval [CI]: 13.6-23.9, P < .001). This improvement was evident early in the study and was sustained over 13 weeks. Time <70 mg/dL showed a gradual decreasing trend over time. Percentage of participants achieving HbA1c <7% went from zero at baseline to 55% at study end (P < .001). Only six of the 318 automated settings adaptations (1.9%) were overridden by study investigators.

CONCLUSIONS

Computerized initiation and adaptation of Control-IQ technology settings from baseline MDI therapy was safe in adults with T1D. The use of this simplified system for onboarding and optimizing Control-IQ technology may be useful to increase uptake of AID and reduce staff and patient burden in clinical care.

Open-source Artificial Pancreas Systems Are Safe and Effective When Supported In-clinic: Outcomes in 248 Consecutive Type 1 Diabetes Clients

OBJECTIVE

Our aim in this study was to determine the safety, glycemia, and quality of life (QoL) associated with in-clinic installation and management of supported open-source artificial pancreas systems (SOSAPS) in type 1 diabetes (T1D).

METHODS

This investigation is a retrospective cohort study of consecutive SOSAPS users at a Canadian diabetes centre. SOSAPS were offered to all moderately tech-savvy T1D clients on sensor-augmented multiple daily injection or pump, able to pay for hardware, and willing to sign a consent and waiver document. SOSAPS were installed and maintained by clinic staff at no cost to clients. iPhone users were assigned to either Loop (n=108) or iPhone artificial pancreas systems (iAPS; n=114) and Android users to Android-type APS (n=24). Outcomes included severe hypoglycemia and diabetic ketoacidosis (DKA), time in range (TIR) 4.0 to 10.0 mmol/L, time below range (TBR) <4 mmol/L, glucose management indicator (GMI), mean sensor glucose (MSG), change in glycated hemoglobin (A1C), and QoL.

RESULTS

Two hundred forty-eight subjects (131 males, 117 females), with a mean age of 36 years and diabetes duration of 21 years, experienced 3 episodes of severe hypoglycemia and no DKA over a follow-up of 17 months. TIR rose by 16%, from 64% to 80% (p<0.0001); TBR fell by 1.0%, from 3.5% to 2.5% (p=0.001); MSG fell from 9.0 to 8.1 mmol/L (p<0.001); GMI fell from 7.3% to 6.7% (p<0.001); and A1C fell from 7.2% to 6.7% (p<0.0001). QoL scores were healthy before and improved after SOSAPS.

CONCLUSIONS

Clients with T1D using SOSAPS and supported with no-cost care to the client (software, technology, and physician/physician assistant) safely achieved improved TIR, GMI, A1C, and QoL.

Artificial Intelligence and Machine Learning for Improving Glycemic Control in Diabetes: Best Practices, Pitfalls, and Opportunities

OBJECTIVE

Artificial intelligence and machine learning are transforming many fields including medicine. In diabetes, robust biosensing technologies and automated insulin delivery therapies have created a substantial opportunity to improve health. While the number of manuscripts addressing the topic of applying machine learning to diabetes has grown in recent years, there has been a lack of consistency in the methods, metrics, and data used to train and evaluate these algorithms. This manuscript provides consensus guidelines for machine learning practitioners in the field of diabetes, including best practice recommended approaches and warnings about pitfalls to avoid.

METHODS

Algorithmic approaches are reviewed and benefits of different algorithms are discussed including importance of clinical accuracy, explainability, interpretability, and personalization. We review the most common features used in machine learning applications in diabetes glucose control and provide an open-source library of functions for calculating features, as well as a framework for specifying data sets using data sheets. A review of current data sets available for training algorithms is provided as well as an online repository of data sources.

SIGNIFICANCE

These consensus guidelines are designed to improve performance and translatability of new machine learning algorithms developed in the field of diabetes for engineers and data scientists.

14. Children and Adolescents: Standards of Care in Diabetes-2024

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, an interprofessional expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Two Years with a Tubeless Automated Insulin Delivery System: A Single-Arm Multicenter Trial in Children, Adolescents, and Adults with Type 1 Diabetes

Background: The Omnipod® 5 Automated Insulin Delivery (AID) System was shown to be safe and effective following 3 months of use in people with type 1 diabetes (T1D); however, data on the durability of these results are limited. This study evaluated the long-term safety and effectiveness of Omnipod 5 use in people with T1D during up to 2 years of use. Materials and Methods: After a 3-month single-arm, multicenter, pivotal trial in children (6-13.9 years) and adolescents/adults (14-70 years), participants could continue system use in an extension phase. HbA1c was measured every 3 months for up to 15 months; continuous glucose monitor metrics were collected for up to 2 years. Results: Participants (N = 224) completed median (interquartile range) 22.3 (21.7, 22.7) months of AID. HbA1c was reduced in the pivotal trial from 7.7% ± 0.9% in children and 7.2% ± 0.9% in adolescents/adults to 7.0% ± 0.6% and 6.8% ± 0.7%, respectively, (P < 0.0001), and was maintained at 7.2% ± 0.7% and 6.9% ± 0.6% after 15 months (P < 0.0001 from baseline). Time in target range (70-180 mg/dL) increased from 52.4% ± 15.6% in children and 63.6% ± 16.5% in adolescents/adults at baseline to 67.9% ± 8.0% and 73.8% ± 10.8%, respectively, during the pivotal trial (P < 0.0001) and was maintained at 65.9% ± 8.9% and 72.9% ± 11.3% during the extension (P < 0.0001 from baseline). One episode of diabetic ketoacidosis and seven episodes of severe hypoglycemia occurred during the extension. Children and adolescents/adults spent median 96.1% and 96.3% of time in Automated Mode, respectively. Conclusion: Our study supports that long-term use of the Omnipod 5 AID System can safely maintain improvements in glycemic outcomes for up to 2 years of use in people with T1D. Clinical Trials Registration Number: NCT04196140.

Randomized Trial of the Insulin-Only iLet Bionic Pancreas for the Treatment of Cystic Fibrosis- Related Diabetes

OBJECTIVE

Cystic fibrosis-related diabetes (CFRD) affects up to 50% of adults with cystic fibrosis and adds significant morbidity and treatment burden. We evaluated the safety and efficacy of automated insulin delivery with the iLet bionic pancreas (BP) in adults with CFRD in a single-center, open-label, random-order, crossover trial.

RESEARCH DESIGN AND METHODS

Twenty participants with CFRD were assigned in random order to 14 days each on the BP or their usual care (UC). No restrictions were placed on diet or activity. The primary outcome was the percent time sensor-measured glucose was in target range 70-180 mg/dL (time in range [TIR]) on days 3-14 of each arm, and key secondary outcomes included mean continuous glucose monitoring (CGM) glucose and the percent time sensor-measured glucose was in hypoglycemic range <54 mg/dL.

RESULTS

TIR was significantly higher in the BP arm than the UC arm (75 ± 11% vs. 62 ± 22%, P = 0.001). Mean CGM glucose was lower in the BP arm than in the UC arm (150 ± 19 vs. 171 ± 45 mg/dL, P = 0.007). There was no significant difference in percent time with sensor-measured glucose <54 mg/dL (0.27% vs. 0.36%, P = 1.0), although self-reported symptomatic hypoglycemia episodes were higher during the BP arm than the UC arm (0.7 vs. 0.4 median episodes per day, P = 0.01). No episodes of diabetic ketoacidosis or severe hypoglycemia occurred in either arm.

CONCLUSIONS

Adults with CFRD had improved glucose control without an increase in CGM-measured hypoglycemia with the BP compared with their UC, suggesting that this may be an important therapeutic option for this patient population.

Roadmap to Continuous Glucose Monitoring Adoption and Improved Outcomes in Endocrinology: The 4T (Teamwork, Targets, Technology, and Tight Control) Program

Glucose monitoring is essential for the management of type 1 diabetes and has evolved from urine glucose monitoring in the early 1900s to home blood glucose monitoring in the 1980s to continuous glucose monitoring (CGM) today. Youth with type 1 diabetes struggle to meet A1C goals; however, CGM is associated with improved A1C in these youth and is recommended as a standard of care by diabetes professional organizations. Despite their utility, expanding uptake of CGM systems has been challenging, especially in minoritized communities. The 4T (Teamwork, Targets, Technology, and Tight Control) program was developed using a team-based approach to set consistent glycemic targets and equitably initiate CGM and remote patient monitoring in all youth with new-onset type 1 diabetes. In the pilot 4T study, youth in the 4T cohort had a 0.5% improvement in A1C 12 months after diabetes diagnosis compared with those in the historical cohort. The 4T program can serve as a roadmap for other multidisciplinary pediatric type 1 diabetes clinics to increase CGM adoption and improve glycemic outcomes.

Developing the UVA/Padova Type 1 Diabetes Simulator: Modeling, Validation, Refinements, and Utility

Arguably, diabetes mellitus is one of the best quantified human conditions. In the past 50 years, the metabolic monitoring technologies progressed from occasional assessment of average glycemia via HbA1c, through episodic blood glucose readings, to continuous glucose monitoring (CGM) producing data points every few minutes. The high-temporal resolution of CGM data enabled increasingly intensive treatments, from decision support assisting insulin injection or oral medication, to automated closed-loop control, known as the "artificial pancreas." Throughout this progress, mathematical models and computer simulation of the human metabolic system became indispensable for the technological progress of diabetes treatment, enabling every step, from assessment of insulin sensitivity via the now classic Minimal Model of Glucose Kinetics, to in silico trials replacing animal experiments, to automated insulin delivery algorithms. In this review, we follow these developments, beginning with the Minimal Model, which evolved through the years to become large and comprehensive and trigger a paradigm change in the design of diabetes optimization strategies: in 2007, we introduced a sophisticated model of glucose-insulin dynamics and a computer simulator equipped with a "population" of N = 300 in silico "subjects" with type 1 diabetes. In January 2008, in an unprecedented decision, the Food and Drug Administration (FDA) accepted this simulator as a substitute to animal trials for the pre-clinical testing of insulin treatment strategies. This opened the field for rapid and cost-effective development and pre-clinical testing of new treatment approaches, which continues today. Meanwhile, animal experiments for the purpose of designing new insulin treatment algorithms have been abandoned.

Changes in the glycaemia risk index and its association with other continuous glucose monitoring metrics after initiation of an automated insulin delivery system in adults with type 1 diabetes

AIM

To evaluate the glycaemia risk index (GRI) and its association with other continuous glucose monitoring (CGM) metrics after initiation of an automated insulin delivery (AID) system in patients with type 1 diabetes (T1D).

MATERIALS AND METHODS

Up to 90 days of CGM data before and after initiation of an AID system from 185 CGM users with T1D were collected. GRI and other CGM metrics were calculated using cgmanalysis R software and were analysed for 24 hours, for both night-time and daytime. GRI values were assigned to five GRI zones: zone A (0-20), B (21-40), C (41-60), D (61-80) and E (81-100).

RESULTS

Compared with baseline, GRI and its components decreased significantly after AID initiation (GRI: 48.7 ± 21.8 vs. 29 ± 13; hypoglycaemia component: 2.7 ± 2.8 vs. 1.6 ± 1.7; hyperglycaemia component: 25.3 ± 14.5 vs. 15 ± 8.5; P < .001 for all). The GRI was inversely correlated with time in range before (r = -0.962) and after (r = -0.961) AID initiation (P < .001 for both). GRI was correlated with time above range (before: r = 0.906; after = 0.910; P < .001 for both), but not with time below range (P > .05). All CGM metrics improved after AID initiation during 24 hours, for both daytime and night-time (P < .001 for all). Metrics improved significantly more during night-time than daytime (P < .01).

CONCLUSIONS

GRI was highly correlated with various CGM metrics above, but not below target range, both before and after AID initiation.

Safety and Glycemic Outcomes During the MiniMedTM Advanced Hybrid Closed-Loop System Pivotal Trial in Children and Adolescents with Type 1 Diabetes

Background: During MiniMed™ advanced hybrid closed-loop (AHCL) use by adolescents and adults in the pivotal trial, glycated hemoglobin (A1C) was significantly reduced, time spent in range (TIR) was significantly increased, and there were no episodes of severe hypoglycemia or diabetic ketoacidosis (DKA). The present study investigated the same primary safety and effectiveness endpoints during AHCL use by a younger cohort with type 1 diabetes (T1D). Methods: An intention-to-treat population (N = 160, aged 7-17 years) with T1D was enrolled in a single-arm study at 13 investigational centers. There was a run-in period (∼25 days) using HCL or sensor-augmented pump with/without predictive low-glucose management, followed by a 3-month study period with AHCL activated at two glucose targets (GTs; 100 and 120 mg/dL) for ∼45 days each. The mean ± standard deviation values of A1C, TIR, mean sensor glucose (SG), coefficient of variation (CV) of SG, time at SG ranges, and insulin delivered between run-in and study were analyzed (Wilcoxon signed-rank test or t-test). Results: Compared with baseline, AHCL use was associated with reduced A1C from 7.9 ± 0.9% (N = 160) to 7.4 ± 0.7% (N = 136) (P < 0.001) and overall TIR increased from the run-in 59.4 ± 11.8% to 70.3 ± 6.5% by end of study (P < 0.001), without change in CV, time spent below range (TBR) <70 mg/dL, or TBR <54 mg/dL. Relative to longer active insulin time (AIT) settings (N = 52), an AIT of 2 h (N = 19) with the 100 mg/dL GT increased mean TIR to 73.4%, reduced TBR <70 mg/dL from 3.5% to 2.2%, and reduced time spent above range (TAR) >180 mg/dL from 28.7% to 24.4%. During AHCL use, there was no severe hypoglycemia or DKA. Conclusions: In children and adolescents with T1D, MiniMed AHCL system use was safe, A1C was lower, and TIR was increased. The lowest GT and shortest AIT were associated with the highest TIR and lowest TBR and TAR, all of which met consensus-recommended glycemic targets. ClinicalTrials.gov ID: NCT03959423.

Real-World Glycemic Outcomes with Early Omnipod 5 Use in Youth with Type 1 Diabetes

Background: Pivotal trials of diabetes technologies have demonstrated glycemic improvements; however, these trials include patients of limited diversity and ranges of glycemic control. We assessed changes in glycemic control during the first 90 days of Omnipod 5 use in a real-world cohort of youth with type 1 diabetes (T1D). Methods: Youth 2-21 years with T1D initiating Omnipod 5 at two pediatric academic centers were included. Fourteen days of baseline (BL) continuous glucose monitoring (CGM) data were compared against data from the first 90 days of Omnipod 5 use. Outcome measures included changes in time in range (TIR), hemoglobin A1c (HbA1c), and CGM and insulin pump metrics based on the duration of Omnipod 5 use. Results: Among 195 youth (78.9% non-Hispanic White, 15.4% publicly insured, age 11.7 years, T1D duration 3.3 years) TIR increased 11%-points, from 49% to 61% (P < 0.001), and HbA1c decreased 0.5%-points, from 7.5% to 6.9% (P < 0.001). TIR improved within the first 9 days of Omnipod 5 use (p < 0.001) and did not change significantly thereafter (P = 0.1) despite decreases in user-initiated boluses (5.1 vs. 5.0, P = 0.01) and carbohydrate entries (4.2 vs. 4.1, P = 0.005) from days 1-9 to days 1-90. TIR improved 15%-points among youth with BL TIR <60% compared to a 5%-point increase for youth with BL TIR ≥60% (P < 0.001). Conclusions: Glycemic control improved within 9 days of Omnipod 5 initiation in this real-world cohort, and improvements were sustained over the first 90 days of use despite concomitant decreases in user-initiated boluses. These improvements were comparable to those observed in the pivotal trial.

Benchmarking Diabetes Technology Use Among 21 U.S. Pediatric Diabetes Centers

The American Diabetes Association's Standards of Care in Diabetes recommends the use of diabetes technology such as continuous glucose monitoring systems and insulin pumps for people living with type 1 diabetes. Unfortunately, there are multiple barriers to uptake of these devices, including local diabetes center practices. This study aimed to examine overall change and center-to-center variation in uptake of diabetes technology across 21 pediatric centers in the T1D Exchange Quality Improvement Collaborative. It found an overall increase in diabetes technology use for most centers from 2021 to 2022 with significant variation.

First Generation of a Modular Interoperable Closed-Loop System for Automated Insulin Delivery in Patients With Type 1 Diabetes: Lessons From Trials and Real-Life Data

BACKGROUND

DBLG1 (Diabeloop Generation 1) stands as one of the five commercially available closed-loop solution worldwide for patients with type 1 diabetes as of 2023. Our aim was to provide an overview of all data obtained with this system regarding outcomes and populations, with an emphasis on interoperability.

METHODS

This report includes all available sources of data (three randomized control trials and five surveys on real-life data). Collection ran from March 3, 2017 to April 30, 2022.

RESULTS

We gathered data from 6859 adult patients treated with closed-loop from three to 12 months. Overall, all sources of data showed that time in range (TIR) 70 to 180 mg/dL, starting from 47.4% to 56.6%, improved from 12.2 to 17.3 percentage points. Time in hypoglycemia was reduced by 48% in average (range: 26%-70%) and reached a level of 1.3% in the largest and most recent cohort. In patients with excessive time in hypoglycemia at baseline (≥5%), closed-loop allowed a reduction in time below range (TBR) by 59%. The comparison of days with declared physical activity versus days without physical activity did not show differences in TBR. The improvement in TIR observed with three different pump systems (Vicentra Kaleido, n = 117; Sooil Dana-I, n = 84; and Roche Insight, n = 6684) ranged from 15.4 to 17.3 percentage points.

DISCUSSION

These data obtained in different European countries were consistent throughout all reports, showing that this closed-loop system is efficient (high improvement in TIR), safe (remarkably low level of TBR), and interoperable (three pump settings so far).

Participant Experiences of Low-Dose Empagliflozin Use as Adjunct Therapy to Hybrid Closed Loop: Findings From a Randomized Controlled Trial

BACKGROUND

Very few patient-reported outcomes have been published in regard to opinions of individuals with type 1 diabetes concerning adjunctive therapy. The aim of this subanalysis was to qualitatively and quantitatively assess the thoughts and experiences of participants with type 1 diabetes who have used low doses of empagliflozin as an adjunct to hybrid closed-loop therapy.

METHODS

Semi-structured interviews were performed with adult participants who completed a double-blinded, crossover, randomized controlled trial using low-dose empagliflozin as an adjunct to hybrid closed-loop therapy. Participant experiences were captured through qualitative and quantitative methods. A descriptive analysis was performed using a qualitative approach; attitudes toward relevant topics were extracted from interview transcripts.

RESULTS

Twenty-four participants were interviewed; 15 (63%) perceived differences between interventions despite blinding, due to glycemic control or side effects. Advantages that arose were better glycemic control, in particular postprandially, requiring less insulin, and ease of use. Disadvantages were thought to be adverse effects, increased incidence of hypoglycemia, and increased pill burden. Thirteen (54%) participants were interested in using low-dose empagliflozin beyond the study.

CONCLUSIONS

Many participants had positive experiences with low-dose empagliflozin as an adjunct to the hybrid closed-loop therapy. A dedicated study with unblinding would be beneficial to better characterize patient-reported outcomes.

Experience with burdens of diabetes device use that affect uptake and optimal use in people with type 1 diabetes

Diabetes technology continues to advance, with more individuals with type 1 diabetes (T1D) adopting insulin pumps, continuous glucose monitoring (CGM), and automated insulin delivery (AID) systems that integrate real-time glucose data with an algorithm to assist with insulin dosing decisions. These technologies are linked with benefits to glycemic outcomes (e.g. increased time in target range), diabetes management behaviors, and quality of life. However, current devices and systems are not without barriers and hassles for the user. The intent of this review is to describe the personal challenges and reactions that users experience when interacting with current diabetes technologies, which can affect their acceptance and motivation to engage with their devices. This review will discuss user experiences and strategies to address three main areas: (i) the emotional burden of utilizing a wearable device; (ii) the perceived and experienced negative social consequences of device use; and (iii) the practical challenges of wearing devices.