One Year Real-World Use of the Control-IQ Advanced Hybrid Closed-Loop Technology

Impact of Missed and Late Meal Boluses on Glycemic Outcomes in Automated Insulin Delivery-Treated Children and Adolescents with Type 1 Diabetes: A Two-Center, Population-Based Cohort Study

Objective: To evaluate the impact of missed or late meal boluses (MLBs) on glycemic outcomes in children and adolescents with type 1 diabetes using automated insulin delivery (AID) systems. Research Design and Methods: AID-treated (Tandem Control-IQ or Medtronic MiniMed 780G) children and adolescents (aged 6-21 years) from Stanford Medical Center and Steno Diabetes Center Copenhagen with ≥10 days of data were included in this two-center, binational, population-based, retrospective, 1-month cohort study. The primary outcome was the association between the number of algorithm-detected MLBs and time in target glucose range (TIR; 70-180 mg/dL). Results: The study included 189 children and adolescents (48% females with a mean ± standard deviation age of 13 ± 4 years). Overall, the mean number of MLBs per day in the cohort was 2.2 ± 0.9. For each additional MLB per day, TIR decreased by 9.7% points (95% confidence interval [CI] 11.3; 8.1), and compared with the quartile with fewest MLBs (Q1), the quartile with most (Q4) had 22.9% less TIR (95% CI: 27.2; 18.6). The age-, sex-, and treatment modality-adjusted probability of achieving a TIR of >70% in Q4 was 1.4% compared with 74.8% in Q1 (P < 0.001). Conclusions: MLBs significantly impacted glycemic outcomes in AID-treated children and adolescents. The results emphasize the importance of maintaining a focus on bolus behavior to achieve a higher TIR and support the need for further research in technological or behavioral support tools to handle MLBs.

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.

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.

12-Month Real-Life Efficacy of the MiniMed 780G Advanced Closed-Loop System in Patients Living with Type 1 Diabetes: A French Observational, Retrospective, Multicentric Study

Aim: To evaluate the evolution of glycemic outcomes in patients living with type 1 diabetes (T1D) after 1 year of use of the MiniMed 780G advanced hybrid closed-loop (AHCL) system. Methods: We conducted an observational, retrospective, multicentric study in 20 centers in France. The primary objective was to evaluate the improvement in glycemic control after 1-year use of AHCL. The primary endpoint was the variation of time in range (TIR) between pre-AHCL and after 1-year use of AHCL. Secondary objectives were to analyze the glycemic outcomes after 3, 6, and 12 months of AHCL use, the safety, and the long-term observance of AHCL. Results: Two hundred twenty patients were included, and 200 were analyzed for the primary endpoint. 92.7% of patients continued to use AHCL. After 1 year of use of AHCL, TIR was 72.5% ± 10.6% (+9.1%; 95% confidence interval [CI] [7.6-10.5] compared to pre-AHCL initiation, P < 0.001), HbA1c 7.1% ± 0.7% (-0.5%; 95% CI [-0.6 to -0.4]; P < 0.001), time below range 2.0% [1.0; 3.0] (0.0% [-2.0; 0.0], P < 0.001), and time above range 24.8% ± 10.9% (-7.3%; 95% CI [-8.8 to -5.7]; P < 0.001). More patients achieved the glycemic treatment goals of HbA1c <7.0% (45.1% vs. 18.1%, P < 0.001) and TIR >70% (59.0% vs. 29.5% P < 0.001) when compared with pre-AHCL. Five patients experienced severe hypoglycemia events and two patients experienced ketoacidosis. Conclusion: After 1 year of use of AHCL, people living with T1D safely improved their glucose control and a higher proportion of them achieved optimal glycemic control.

Utility of time in tight range (TITR) in evaluating metabolic control in pediatric and adult patients with type 1 diabetes in treatment with advanced hybrid closed-loop systems

PURPOSE

To analyze the time in tight range (TITR), and its relationship with other glucometric parameters in patients with type 1 diabetes (T1D) treated with advanced hybrid closed-loop (AHCL) systems.

METHODS

A prospective observational study was conducted on pediatric and adult patients with T1D undergoing treatment with AHCL systems for at least 3 months. Clinical variables and glucometric parameters before and after AHCL initiation were collected.

RESULTS

A total of 117 patients were evaluated. Comparison of metabolic control after AHCL initiation showed significant improvements in HbA1c (6.9 ± 0.9 vs. 6.6 ± 0.5%, p < 0.001), time in range (TIR) (68.2 ± 11.5 vs. 82.5 ± 6.9%, p < 0.001), TITR (43.7 ± 10.8 vs. 57.3 ± 9.7%, p < 0.001), glucose management indicator (GMI) (6.9 ± 0.4 vs. 6.6 ± 0.3%, p < 0.001), time below range (TBR) 70-54 mg/dl (4.3 ± 4.5 vs. 2.0 ± 1.4%, p < 0.001), and time above range (TAR) > 180 mg/dl (36.0 ± 7.6 vs. 15.1 ± 6.4%, p < 0.001). Coefficient of variation (CV) also improved (36.3 ± 5.7 vs. 30.6 ± 3.7, p < 0.001), while time between 140-180 mg/dl remained unchanged. In total, 76.3% achieved TITR > 50% (100% pediatric). Correlation analysis between TITR and TIR and GRI showed a strong positive correlation, modified by glycemic variability.

CONCLUSIONS

AHCL systems achieve significant improvements in metabolic control (TIR > 70% in 93.9% patients). The increase in TIR was not related to an increase in TIR 140-180 mg/dl. Despite being closely related to TIR, TITR allows for a more adequate discrimination of the achieved control level, especially in a population with good initial metabolic control. The correlation between TIR and TITR is directly influenced by the degree of glycemic variability.

The role of automated insulin delivery technology in diabetes

The role of automated insulin delivery systems in diabetes is expanding. Hybrid closed-loop systems are being used in routine clinical practice for treating people with type 1 diabetes. Encouragingly, real-world data reflects the performance and usability observed in clinical trials. We review the commercially available hybrid closed-loop systems, their distinctive features and the associated real-world data. We also consider emerging indications for closed-loop systems, including the treatment of type 2 diabetes where variability of day-to-day insulin requirements is high, and other challenging applications for this technology. We discuss issues around access and implementation of closed-loop technology, and consider the limitations of present closed-loop systems, as well as innovative approaches that are being evaluated to improve their performance.

Prevalence, Safety, and Metabolic Control Among Danish Children and Adolescents with Type 1 Diabetes Using Open-Source Automated Insulin Delivery Systems

Background: Treatment of type 1 diabetes mellitus (T1DM) has become increasingly technical with rapid developments in integration of pumps and sensors to regulate insulin dosage, and patient-initiated solutions as open-source automated insulin delivery (OS-AID) systems, have gained popularity in people with diabetes. Studies have shown increased glycemic control and mental wellbeing in users of OS-AID systems. The aim of this study was to estimate the prevalence, the effect on metabolic control, the risk, and the effect on everyday life for users and their parents of OS-AID systems in Danish children and adolescents with T1DM. Methods: This retrospective cohort study recruited participants through pediatric diabetes outpatient clinics and social media. Surveys were distributed and current and retrospective data on glycemic control (HbA1c, time in range [TIR] etc.) were collected. Results: Fifty-six users of OS-AID systems out of 2950 Danish children and adolescents with T1DM were identified from all outpatient clinics in Denmark. Thirty-one responded on contact and were included (55% of the identified), median age 12 [interquartile range: 11-14] years, 51% females, and mean duration of use of OS-AID systems 2.37 ± 0.86 years. Glycemic control increased significantly with TIR increasing from mean 62.29% ± 13.68% to 70.12% ± 10.08%, *P < 0.01, and HbA1c decreasing from mean 50.13 ± 5.76 mmol/mol (6.7% ± 2.7%) to 47.86 ± 6.24 mmol/mol (6.5% ± 2.7%), **P < 0.05. No changes were found in safety parameters. Parents reported better quality of sleep evaluated by Pittsburgh Sleep Quality Index. Conclusion: This study is the first to provide knowledge on pediatric users of OS-AID systems in Denmark and found a prevalence of 1.89% for OS-AID systems, improved TIR, and no increased risk associated with use of OS-AID systems.

Long-term assessment of the NHS hybrid closed-loop real-world study on glycaemic outcomes, time-in-range, and quality of life in children and young people with type 1 diabetes

Hybrid closed-loop (HCL) systems seamlessly interface continuous glucose monitoring (CGM) with insulin pumps, employing specialised algorithms and user-initiated automated insulin delivery. This study aimed to assess the efficacy of HCLs at 12 months post-initiation on glycated haemoglobin (HbA1c), time-in-range (TIR), hypoglycaemia frequency, and quality of life measures among children and young people (CYP) with type 1 diabetes mellitus (T1DM) and their caregivers in a real-world setting. Conducted between August 1, 2021, and December 10, 2022, the prospective recruitment took place in eight paediatric diabetes centres across England under the National Health Service England's (NHSE) HCL pilot real-world study. A cohort of 251 CYP (58% males, mean age 12.3 years) with T1DM participated (89% white, 3% Asian, 4% black, 3% mixed ethnicity, and 1% other). The study utilised three HCL systems: (1) Tandem Control-IQ AP system, which uses the Tandem t:slim X2 insulin pump (Tandem Diabetes Care, San Diego, CA, USA) with the Dexcom G6® CGM (Dexcom, San Diego, CA, USA) sensor; (2) Medtronic MiniMed™ 780G with the Guardian 4 sensor (Medtronic, Northridge, CA, USA); and (3) the CamAPS FX (CamDiab, Cambridge, UK) with the Ypsomed insulin pump (Ypsomed Ltd, Escrick, UK) and Dexcom G6® CGM.All systems were fully funded by the NHS. Results demonstrated significant improvements in HbA1c (average reduction at 12 months 7 mmol/mol; P < 0.001), time-in-range (TIR) (average increase 13.4%; P < 0.001), hypoglycaemia frequency (50% reduction), hypoglycaemia fear, and quality of sleep (P < 0.001) among CYP over a 12-month period of HCL usage. Additionally, parents and carers experienced improvements in hypoglycaemia fear and quality of sleep after 6 and 12 months of use. In addition to the improvements in glycaemic management, these findings underscore the positive impact of HCL systems on both the well-being of CYP with T1DM and the individuals caring for them.

Effects, Safety, and Treatment Experience of Advanced Hybrid Closed-Loop Systems in Clinical Practice Among Adults Living With Type 1 Diabetes

BACKGROUND

There are few studies providing a more comprehensive picture of advanced hybrid closed-loop (AHCL) systems in clinical practice. The aim was to evaluate the effects of the AHCL systems, Tandem® t: slim X2™ with Control IQ™, and MiniMed™ 780G, on glucose control, safety, treatment satisfaction, and practical barriers for individuals with type 1 diabetes.

METHOD

One hundred forty-two randomly selected adults with type 1 diabetes at six diabetes outpatient clinics in Sweden at any time treated with either the Tandem Control IQ (TCIQ) or the MiniMed 780G system were included. Glycated hemoglobin A1c (HbA1c) and glucose metrics were evaluated. Treatment satisfaction and practical barriers were examined via questionnaires.

RESULTS

Mean age was 42 years, median follow-up was 1.7 years, 58 (40.8%) were females, 65% used the TCIQ system. Glycated hemoglobin A1c was reduced by 0.6% (6.8 mmol/mol; 95% confidence interval [CI] = 0.5-0.8% [5.3-8.2 mmol/mol]; P < .001), from 7.3% to 6.7% (57-50 mmol/mol). Time in range (TIR) increased with 14.5% from 57.0% to 71.5% (95% CI = 12.2%-16.9%; P < .001). Time below range (TBR) (<70 mg/dL, <3.9 mmol/L) decreased from 3.8% to 1.6% (P < .001). The standard deviation of glucose values was reduced from 61 to 51 mg/dL (3.4-2.9 mmol/L, P < .001) and the coefficient of variation from 35% to 33% (P < .001). Treatment satisfaction increased, score 14.8 on the Diabetes Treatment Satisfaction Questionnaire (DTSQ) (change version ranging from -18 to 18, P < .001). Four severe hypoglycemia events were detected and no cases of ketoacidosis. Skin problems were experienced by 32.4% of the study population.

CONCLUSIONS

Advanced hybrid closed-loop systems improve glucose control with a reasonable safety profile and high treatment satisfaction. Skin problems are common adverse events.

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.

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.

Glucometrics and device satisfaction in children and adolescents with type 1 diabetes using different treatment modalities: A multicenter real-world observational study

AIMS

To analyze metabolic outcomes, diabetes impact and device satisfaction in children and adolescents with type 1 diabetes in Italy who used different treatment modalities for diabetes care in a real-life context.

METHODS

In this multicenter, nationwide, cross-sectional study, 1464 participants were enrolled at a routine visit. The following treatment modalities were considered MDI + SMBG; MDI + CGM; Sensor Augmented Pump Therapy; predictive management of low glucose; Hybrid Closed Loop (HCL); Advanced Hybrid Closed Loop (AHCL). Health related quality of life was evaluated by the Italian version of the Diabetes Impact and Device Satisfaction Scale (DIDS) questionnaire.

RESULTS

Patients treated with AID systems were more likely to have HbA1c ≤ 6.5 %, higher percentage of time with glucose levels between 70 and 180 mg/dL, lower percentage of time with glucose levels above 180 mg/dL, higher device satisfaction, and reduced impact of diabetes. All the therapeutic modalities with respect to MDI + CGM, except for MDI + SMBG, contributed to increase the device satisfaction. HCL and AHCL respect to MDI + CGM were associated with lower diabetes impact.

CONCLUSION

Real-life use of automated insulin delivery systems is associated with reduced type 1 diabetes impact, increased device satisfaction, and achievement of glycemic goals.

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.

Generative deep learning for the development of a type 1 diabetes simulator

BACKGROUND

Type 1 diabetes (T1D) simulators, crucial for advancing diabetes treatments, often fall short of capturing the entire complexity of the glucose-insulin system due to the imprecise approximation of the physiological models. This study introduces a simulation approach employing a conditional deep generative model. The aim is to overcome the limitations of existing T1D simulators by synthesizing virtual patients that more accurately represent the entire glucose-insulin system physiology.

METHODS

Our methodology utilizes a sequence-to-sequence generative adversarial network to simulate virtual T1D patients causally. Causality is embedded in the model by introducing shifted input-output pairs during training, with a 90-min shift capturing the impact of input insulin and carbohydrates on blood glucose. To validate our approach, we train and evaluate the model using three distinct datasets, each consisting of 27, 12, and 10 T1D patients, respectively. In addition, we subject the trained model to further validation for closed-loop therapy, employing a state-of-the-art controller.

RESULTS

The generated patients display statistical similarity to real patients when evaluated on the time-in-range results for each of the standard blood glucose ranges in T1D management along with means and variability outcomes. When tested for causality, authentic causal links are identified between the insulin, carbohydrates, and blood glucose levels of the virtual patients. The trained generative model demonstrates behaviours that are closer to reality compared to conventional T1D simulators when subjected to closed-loop insulin therapy using a state-of-the-art controller.

CONCLUSIONS

These results highlight our approach's capability to accurately capture physiological dynamics and establish genuine causal relationships, holding promise for enhancing the development and evaluation of therapies in diabetes.

Does minimed 780GTM insulin pump system affect energy and nutrient intake?: long-term follow-up study

OBJECTIVE

We evaluate the energy and nutrient intake of children, adolescents, and young adults with type 1 diabetes (T1D) who started to use automated insulin delivery (AID) systems before the transition and during follow-up for 6 months in a real-world setting.

RESEARCH DESIGN AND METHODS

Twenty-nine people with T1D (PwD) who started to use MiniMed 780GTM participated in the study. Participants' 3-day food diaries and glycemic outcomes were analyzed at baseline and after (the 3rd and 6th month) switching to an advanced hybrid closed-loop system (a-HCL).

RESULTS

Mean carbohydrate, protein, and fat intake (energy %) at baseline were 49.1 ± 4.5, 17.8 ± 2.3, and 33.0 ± 3.9, respectively, and there were no statistically significant differences during the follow-up period. However, low fiber (<14 g/1000 kcal) and high saturated fat (>10 energy %) intake in PwD, both baseline and follow-up period. The median auto-correction bolus ratio was 14.0 (9.5)% at auto mode after 14 days, 18.0 (11.0)% at the 3rd month, and 19.0 (7.5)% at the 6th month (p < 0.05). A negative correlation was present between auto-correction boluses with TIR in both the 3rd (r:-0.747, p < 0.01) and 6th month (r:-0.395, p < 0.05). A negative correlation was present between auto-correction boluses with TIR in both the 3rd (r:-0.747, p < 0.01) and 6th month (r:-0.395, p < 0.05).

CONCLUSIONS

a-HCLS systems offer better glycemic control. Using the Minimed 780 GTM insulin pump system didn't change the energy and nutrient intake of PwD. This real-world follow-up study suggests that children, adolescents, and young adults with T1D consume saturated fat above and fiber intake lower than recommendations independent of the use of a-HCLS.

CLINICAL TRIALS REGISTRATION NUMBER

NCT05666596.

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.

Early Real-World Performance of the MiniMed™ 780G Advanced Hybrid Closed-Loop System and Recommended Settings Use in the United States

Background: The MiniMed™ 780G system (MM780G) with Guardian™ 4 sensor includes a 100 mg/dL glucose target (GT) and automated insulin corrections up to every 5 min and was recently approved for use in the United States. In the present study, early real-world MM780G performance and the use of recommended system settings (100 mg/dL GT with an active insulin time of 2 h), by individuals with type 1 diabetes, were evaluated. Methods: CareLink™ personal data uploaded between the launch of the MM780G to August 22, 2023 were aggregated and underwent retrospective analysis (based on user consent) and if users had ≥10 days of continuous glucose monitoring (CGM) data. The 24-h day CGM metrics, including mean glucose, percentage of time spent in (%TIR), above (%TAR), and below (%TBR) target range (70-180 mg/dL), in addition to delivered insulin and closed-loop (CL) exits, were compared between an overall group (n = 7499) and individuals who used recommended settings (each, for >95% of the time). An analysis of the same metrics for MiniMed™ 770G system (MM770G) users (n = 3851) who upgraded to the MM780G was also conducted (paired t-test or Wilcoxon signed-rank test, P < 0.05 considered statistically significant). Results: For MM780G users, CGM use, and time in CL were >90% and all MM780G CGM metrics exceeded consensus-recommended goals. With recommended settings (22% of all users), mean %TIR and %TITR (70-140 mg/dL) were 81.4% and 56.4%, respectively. For individuals who upgraded from the MM770G, %TIR and %TITR increased from 73.2% to 78.3% and 45.8% to 52.6%, respectively, while %TAR reduced from 25.1% to 20.2% (P < 0.001, for all three). CL exits/week averaged <1, for all MM780G users. Conclusions: Early real-world MM780G use in the United States demonstrated a high percentage of time in range with low time above and below range. These outcomes are similar to those observed for real-world MM780G use in other countries.

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.

Twelve-Month Follow-up from a Randomized Controlled Trial of Simplified Meal Announcement Versus Precise Carbohydrate Counting in Adolescents with Type 1 Diabetes Using the MiniMed™ 780G Advanced Hybrid Closed-Loop System

Background and Aims: Carbohydrate counting is a well-established tool for self-management of type 1 diabetes (T1D) and can improve glycemic control and potentially reduce long-term complication risk. However, it can also be burdensome, error-prone, and complicated for the patient. A randomized controlled trial was conducted to investigate glycemic control with carbohydrate counting ("flex") versus simplified meal announcement ("fix") in adolescents with T1D using the MiniMed™ 780G system. The present study reports follow-up data to 12 months. Methods: Adolescents with T1D were randomly assigned 1:1 to use the MiniMed™ 780G system alongside the flex versus fix approaches. Participants were followed for 12 months with outcomes recorded at 3, 6, 9, and 12 months. The primary endpoint was the difference in time-in-range (TIR), and secondary endpoints included glycated hemoglobin (HbA1c) and other glucose and insulin metrics. Results: At 12 months, TIR (proportion of time with sensor glucose 70-180 mg/dL) was significantly lower in the fix versus flex group (72.9% vs. 80.1%, respectively; P = 0.001). There was no significant difference in HbA1c between the fix (6.8% ± 0.5%) and flex groups (6.5% ± 0.5%) at 12 months (P = 0.092), and mean HbA1c was below 7% at all time points in both arms. Conclusions: Glycemic control with simplified meal announcement was maintained over 12 months. On average, the international consensus targets were met in both arms for all time points. The simplified approach represents a viable alternative to carbohydrate counting, particularly in people who find the latter burdensome; however, carbohydrate counting resulted in superior TIR. This study is registered with ClinicalTrials.gov, number NCT05069727.

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.

Closed-Loop Insulin Delivery Systems for People with Type 1 Diabetes and Chronic Very Poor Metabolic Control: It Works and Is Safe!

To evaluate the percentage of patients with type 1 diabetes (T1D) and very poor metabolic control who would agree to be treated with a hybrid closed-loop (HCL) insulin delivery system, and to assess metabolic improvement and safety. In a single center, we identified all patients aged >18 years with hemoglobin A1c (HbA1c) >11% (97 mmol/mol) before HCL treatment. We collected metabolic control and safety data up to 1 year post-HCL in those who accepted HCL after it was proposed to them. We identified 65 patients eligible for the study, 32 (50%) already used, or accepted to start using HCL. Patients were aged 18-49 years; mean(±standard deviation) baseline HbA1c was 12.5(±1.8)% (113 ± 20 mmol/mol). After 1 year, 25 patients (78%) were still using HCL and their mean HbA1c decreased to 9.4(±1.9)% (79 mmol/mol) (P < 0.001). The rate of acute metabolic events was similar during the year of follow-up to the rate in the 3 years before HCL initiation. HCL systems should be considered in patients with T1D and very poor metabolic control. ClinicalTrials registration no. NCT05282264.

A Multicenter Prospective Evaluation of the Benefits of Two Advanced Hybrid Closed-Loop Systems in Glucose Control and Patient-Reported Outcomes in a Real-world Setting

OBJECTIVE

Advanced hybrid closed-loop systems (AHCL) have been shown to improve glycemic control and patient-reported outcomes in type 1 diabetes. The aim was to analyze the outcomes of two commercially available AHCL in real life.

RESEARCH DESIGN AND METHODS

A prospective study was performed, including adolescents and adults with type 1 diabetes, AHCL naïve, from 14 centers, who initiated the use of MM780G with SmartGuard or Tandem t:slimX2 with Control-IQ. Baseline and 3-month evaluations were performed, assessing HbA1c, time in different glycemic ranges, and patient-reported outcomes. The primary outcome was the between-group time in range 70-180 mg/dL difference from beginning to end of follow-up.

RESULTS

One hundred fifty participants were included, with 75 initiating each system (age: 39.9 ± 11.4 years [16-72]; 64% female; diabetes duration: 21.6 ± 11.9 years). Time in range increased from 61.53 ± 14.01% to 76.17 ± 9.48% (P < 0.001), with no between-group differences (P = 0.591). HbA1c decreased by 0.56% (95% CI 0.44%, 0.68%) (6 mmol/mol, 95% CI 5, 7) (P < 0.001), from 7.43 ± 1.07% to 6.88 ± 0.60% (58 ± 12 to 52 ± 7 mmol/mol) in the MM780G group, and from 7.14 ± 0.70% to 6.56 ± 0.53% (55 ± 8 to 48 ± 6 mmol/mol) in the Control-IQ group (both P < 0.001 to baseline, P = 0.819 between groups). No superiority of one AHCL over the other regarding fear of hypoglycemia or quality of life was found. Improvement in diabetes-related distress was higher in Control-IQ users (P = 0.012). Sleep quality was improved (PSQI: from 6.94 ± 4.06 to 6.06 ± 4.05, P = 0.004), without differences between systems. Experience with AHCL, evaluated by the INSPIRE measures, exceeded the expectations.

CONCLUSIONS

The two AHCL provide significant improvement in glucose control and satisfaction, with no superiority of one AHCL over the other.

Beneficial effects of automated insulin delivery over one-year follow-up in real life for youths and adults with type 1 diabetes irrespective of patient characteristics

AIM

To investigate glycaemic outcomes in youths and adults with type 1 diabetes with either MiniMed™ 780G or Tandem t:slim X2™ control-IQ automated insulin delivery (AID) systems and to evaluate clinical factors that migrate, mitigate the achievement of therapeutic goals.

MATERIALS AND METHODS

This retrospective, real-world, observational study was conducted in a specialized university type 1 diabetes centre with patients observed for 3-12 months post-initiation of an AID system. Primary outcomes were the percentage time in the target glucose range [TIR70-180 mg/dl (3.9-10 mmol/L)] as measured by continuous glucose monitoring, mean glucose management indicator (GMI) and glycated haemoglobin (HbA1c) levels.

RESULTS

Our study cohort consisted of 48 adolescents and 183 adults (55% females) aged 10-77 years. The mean (95% confidence interval) TIR70-180 mg/dl after 30 days was higher than baseline and by 14% points after 360 days with 71.33% (69.4-73.2) (n = 123, p < .001). HbA1c levels decreased by 0.7% and GMI by 0.6% after 360 days. The proportion of time spent <70 mg/dl (3.9 mmol/L) was not significantly different from baseline. During follow-up, 780G users had better continuous glucose monitoring results than control-IQ users but similar HbA1c levels, and an increased risk of weight gain. Age at onset influenced TIR70-180 mg/dl in univariate analysis but there was no significant relationship after adjusting on explanatory variables. Baseline body mass index did not influence the performance of AID systems.

CONCLUSIONS

This analysis showed the beneficial effects of two AID systems for people with type 1 diabetes across a broad spectrum of participant characteristics. Only half of the participants achieved international recommendations for glucose control with TIR70-180 mg/dl >70%, HbA1c levels or GMI <7%, which outlines the need to maintain strong educational and individual strategies.

9. Pharmacologic Approaches to Glycemic Treatment: 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.

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.

The Hybrid Closed-Loop System Tandem t:slim X2™ with Control-IQ Technology: Expert Recommendations for Better Management and Optimization

Technological advances in the management of diabetes, especially type 1 diabetes (T1D), have played a main role in significantly improving glycemic control of these patients in recent years. Undoubtedly, the most important advance has been the commercialization of hybrid closed-loop systems (HCL). Their effectiveness places them in the different guidelines from scientific societies as the gold standard for the treatment of people with T1D. However, obtaining the maximum performance from these systems requires a degree of expertise from the professionals who care for these patients. Specifically, the Tandem X2:slim with Control-IQ technology system, due to its features and configuration options and adjustments, allows T1D patients to better adapt the management of diabetes to multiple circumstances in their day-to-day life. It is necessary, however, to follow a systematic process to start the system and also for the subsequent follow-up, which allows its optimization in the shortest possible time. This expert recommendation reviews the main features of this HCL system, suggesting how to implement it and optimize its use after gaining experience treating many patients.

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.

Advanced Hybrid Closed-Loop System Achieves and Maintains Recommended Time in Range Levels for Up To 2 Years: Predictors of Best Efficacy

Aim: To evaluate the long-term efficacy, up to 2 years, of an advanced hybrid closed-loop (AHCL) system and to assess predictors of best results of the therapy. Methods: We retrospectively evaluated 296 adults with type 1 diabetes mellitus [mean age 42.8 ± 16.5 years, men 42.9%, duration of diabetes 22.5 ± 12.8 years, body mass index 24.9 ± 4.7 kg/m2, baseline glycated hemoglobin (HbA1c) 63.4 ± 12.2 mmol/mol (8.0 ± 1.1%) ] who used the MiniMed™ 780G system. Demographic and clinical data were recorded. Continuous glucose monitoring (CGM)-derived metrics and insulin requirement were analyzed from the 4 weeks before and from every quarter after the switch to the AHCL system. Results: In the first quarter of AHCL treatment, all CGM metrics improved. Time in range (TIR) increased from 58.1 ± 17.5% to 70.3 ± 9.5% (P < 0.0001). The improvement lasted for up to 2 years of observation regardless of previous insulin therapies. Throughout the period of observation, 53.4% of participants achieved mean TIR >70%, 92.6% mean time below range <4%, and 46% mean glucose management indicator <53 mmol/mol (7.0%). At univariable logistic regression older age, lower baseline HbA1c and insulin requirement were associated with mean TIR >70%. At multivariable analysis, lower HbA1c remained independently associated with a better glycemic control. However, mean TIR increased more in participants with a higher baseline HbA1c. Conclusions: Switching to an AHCL leads to a rapid improvement in glycemic control lasting for up to 24 months along with a low risk for hypoglycemia, confirming the safety of the system. Lower baseline HbA1c was the main predictor of better efficacy of therapy, although higher baseline HbA1c was associated with the greatest improvement in mean TIR.

Automated insulin delivery among adults with type 1 diabetes for up to 2 years: a real-world, multicentre study

BACKGROUND AND AIMS

Automated insulin delivery (AID) improves glycaemia among people with type 1 diabetes in clinical trials and overseas real-world studies. Whether improvements are sustained beyond 12 months in the real world, and whether they occur in the Australian context, has not yet been established. We aimed to observe, up to 2 years, the effectiveness of initiating first-generation AID for type 1 diabetes management.

METHODS

Retrospective, real-world, observational study using medical records, conducted across five sites in Australia. Adults with type 1 diabetes, who had AID initiated between February 2019 and December 2021, were observed for 6-24 months after initiation (until June 2022). Outcomes examined included glucose metrics assessed by glycated haemoglobin (HbA1c ) and continuous glucose monitoring (CGM), safety and therapy continuation.

RESULTS

Ninety-four adults were studied (median age 39 years (interquartile range, IQR: 31-51); pre-initiation HbA1c 7.8% (7.2-8.6)). After AID initiation, HbA1c decreased by mean 0.5 percentage points (95% confidence interval (CI): -0.7 to -0.2) at 3 months (P < 0.001); CGM time in range 3.9-10.0 mmol/L increased by 11 percentage points (9-14) at 1 month (P < 0.001); these improvements were maintained up to 24 months (all P < 0.02). Median CGM time below 3.9 mmol/L was <1.5% pre- and post-AID initiation. The subgroup with pre-initiation HbA1c above 8.5% had the greatest HbA1c improvement (-1.4 percentage points (-1.8 to -1.1) at 3 months). Twelve individuals (13%) discontinued AID, predominantly citing difficulties with CGM. During the 150 person-years observed, four diabetes-related emergencies were documented: three severe hypoglycaemic events and one hyperglycaemic event without ketoacidosis.

CONCLUSIONS

Early glucose improvements were observed after real-world AID initiation, sustained up to 2 years, without excess adverse events. The greatest benefits were observed among individuals with highest glycaemia before initiation. Future-generation systems with increased user-friendliness may enhance therapy continuation.

Daytime hypoglycemic episodes during the use of an advanced hybrid closed loop system

AIMS

The use of advanced hybrid closed loop systems is spreading due to the beneficial effects on glycometabolic control obtained in patients with type 1 diabetes. However, hypoglycemic episodes can be sometimes a matter of concern. We aim to compare the hypoglycemic risk of an advanced hybrid closed loop system and a predictive low glucose suspend sensor augmented pump.

METHODS

In this retrospective three months observational study, we included 30 patients using Medtronic Minimed™ 780G advanced hybrid closed loop system and 30 patients using a Medtronic Minimed™ predictive low glucose suspend sensor augmented pump.

RESULTS

The advanced hybrid closed loop system reduced the time spent above 180 mg/dL threshold and increased the time in range as compared to the predictive low glucose suspend. No severe hypoglycemia occurred in both groups and no differences were observed in the percentage of time spent below 70 mg/dl and 54 mg/dl glucose threshold. Nevertheless, more hypoglycemic episodes were recorded during daytime, but not in nighttime, with the use of the advanced hybrid closed loop system.

CONCLUSIONS

Our results confirmed the general improvement of glycemic outcomes obtained with the advanced hybrid closed loop system; however more hypoglycemic episodes during daytime were evident.

Simulation-driven optimization of insulin therapy profiles in a commercial hybrid closed-loop system

BACKGROUND

Automated insulin delivery (AID) has represented a breakthrough in managing type 1 diabetes (T1D), showing safe and effective glucose control extensively across the board. However, metabolic variability still poses a challenge to commercial hybrid closed-loop (HCL) solutions, whose performance depends on customizable insulin therapy profiles. In this work, we propose an Identification-Replay-Optimization (IRO) approach to optimize gradually and safely such profiles for the Control-IQ AID algorithm.

METHODS

Closed-loop data are generated using the full adult cohort of the UVA/Padova T1D simulation platform in diverse glycemic scenarios. For each subject, daily records are processed and used to estimate a personalized model of the underlying insulin-glucose dynamics. Every two weeks, all identified models are integrated into an optimization procedure where daily basal and bolus profiles are adjusted so as to minimize the risks for hypo- and hyperglycemia. The proposed strategy is tested under different scenarios of metabolic and behavioral variability in order to evaluate the efficacy and convergence of the proposed strategy. Finally, glycemic metrics between cycles are compared using paired t-tests with p<0.05 as the significance threshold.

RESULTS

Simulations reveal that the proposed IRO approach was able to improve glucose control over time by safely mitigating the risks for both hypo- and hyperglycemia. Furthermore, smaller changes were recommended at each cycle, indicating convergence when simulation conditions were maintained.

CONCLUSIONS

The use of reliable simulation-driven tools capable of accurately reproducing field-collected data and predicting changes can substantially shorten the process of optimizing insulin therapy, adjusting it to metabolic changes and leading to improved glucose control.

Glucose Monitoring Metrics in Individuals With Type 1 Diabetes Using Different Treatment Modalities: A Real-World Observational Study

OBJECTIVE

This study aimed to investigate the association between continuous glucose monitoring (CGM)-derived glycemic metrics and different insulin treatment modalities using real-world data.

RESEARCH DESIGN AND METHODS

A cross-sectional study at Steno Diabetes Center Copenhagen, Denmark, included individuals with type 1 diabetes using CGM. Data from September 2021 to August 2022 were analyzed if CGM was used for at least 20% of a 4-week period. Individuals were divided into four groups: multiple daily injection (MDI) therapy, insulin pumps with unintegrated CGM (SUP), sensor-augmented pumps with low glucose management (SAP), and automated insulin delivery (AID). The MDI and SUP groups were further subdivided based on CGM alarm features. The primary outcome was percentage of time in range (TIR: 3.9-10.0 mmol/L) for each treatment group. Secondary outcomes included other glucose metrics and HbA1c.

RESULTS

Out of 6,314 attendees, 3,184 CGM users were included in the analysis. Among them, 1,622 used MDI, 504 used SUP, 354 used SAP, and 561 used AID. Median TIR was 54.0% for MDI, 54.9% for SUP, 62,9% for SAP, and 72,1% for AID users. The proportion of individuals achieving all recommended glycemic targets (TIR >70%, time above range <25%, and time below range <4%) was significantly higher in SAP (odds ratio [OR] 2.4 [95% CI 1.6-3.5]) and AID (OR 9.4 [95% CI 6.7-13.0]) compared with MDI without alarm features.

CONCLUSIONS

AID appears superior to other insulin treatment modalities with CGM. Although bias may be present because of indications, AID should be considered the preferred choice for insulin pump therapy.

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.

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).

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.

Are all HCL systems the same? long term outcomes of three HCL systems in children with type 1 diabetes: real-life registry-based study

Objective

To compare parameters of glycemic control among three types of hybrid closed loop (HCL) systems in children with T1D (CwD) using population-wide data from the national pediatric diabetes registry ČENDA.

Methods

CwD aged <19 years treated with Medtronic MiniMed 780G (780G), Tandem t:slim X2 (Control-IQ) or do-it-yourself AndroidAPS (AAPS) systems for >12 months and monitored by CGM >70% of the time were included. HbA1c, times in glycemic ranges, and Glycemia Risk Index (GRI) were used for cross-sectional comparison between the HCL systems.

Results

Data from 512 CwD were analyzed. 780G, Control-IQ and AAPS were used by 217 (42.4%), 211 (41.2%), and 84 (16.4%) CwD, respectively. The lowest HbA1c value was observed in the AAPS group (44 mmol/mol; IQR 8.0, p<0.0001 vs any other group), followed by Control-IQ and 780G groups (48 (IQR 11) and 52 (IQR 10) mmol/mol, respectively). All of the systems met the recommended criteria for time in range (78% in AAPS, 76% in 780G, and 75% in Control-IQ users). CwD using AAPS spent significantly more time in hypoglycemia (5% vs 2% in 780G and 3% in Control-IQ) and scored the highest GRI (32, IQR 17). The lowest GRI (27, IQR 15) was seen in 780G users.

Conclusion

Although all HCL systems proved effective in maintaining recommended long-term glycemic control, we observed differences that illustrate strengths and weaknesses of particular systems. Our findings could help in individualizing the choice of HCL systems.

An mHealth Text Messaging Program Providing Symptom Detection Training and Psychoeducation to Improve Hypoglycemia Self-Management: Intervention Development Study

BACKGROUND

Hypoglycemia remains a challenge for roughly 25% of people with type 1 diabetes (T1D) despite using advanced technologies such as continuous glucose monitors (CGMs) or automated insulin delivery systems. Factors impacting hypoglycemia self-management behaviors (including reduced ability to detect hypoglycemia symptoms and unhelpful hypoglycemia beliefs) can lead to hypoglycemia development in people with T1D who use advanced diabetes technology.

OBJECTIVE

This study aims to develop a scalable, personalized mobile health (mHealth) behavioral intervention program to improve hypoglycemia self-management and ultimately reduce hypoglycemia in people with T1D who use advanced diabetes technology.

METHODS

We (a multidisciplinary team, including clinical and health psychologists, diabetes care and education specialists, endocrinologists, mHealth interventionists and computer engineers, qualitative researchers, and patient partners) jointly developed an mHealth text messaging hypoglycemia behavioral intervention program based on user-centered design principles. The following five iterative steps were taken: (1) conceptualization of hypoglycemia self-management processes and relevant interventions; (2) identification of text message themes and message content development; (3) message revision; (4) patient partner assessments for message readability, language acceptability, and trustworthiness; and (5) message finalization and integration with a CGM data-connected mHealth SMS text message delivery platform. An mHealth web-based SMS text message delivery platform that communicates with a CGM glucose information-sharing platform was also developed.

RESULTS

The mHealth SMS text messaging hypoglycemia behavioral intervention program HypoPals, directed by patients' own CGM data, delivers personalized intervention messages to (1) improve hypoglycemia symptom detection and (2) elicit self-reflection, provide fact-based education, and suggest practical health behaviors to address unhelpful hypoglycemia beliefs and promote hypoglycemia self-management. The program is designed to message patients up to 4 times per day over a 10-week period.

CONCLUSIONS

A rigorous conceptual framework, a multidisciplinary team (including patient partners), and behavior change techniques were incorporated to create a scalable, personalized mHealth SMS text messaging behavioral intervention. This program was systematically developed to improve hypoglycemia self-management in advanced diabetes technology users with T1D. A clinical trial is needed to evaluate the program's efficacy for future clinical implementation.

Glycometabolic outcomes in adult type 1 diabetic patients switching to closed-loop systems

OBJECTIVE

This study aimed to evaluate glycometabolic outcomes in AID technology-naïve T1D patients after switching to Hybrid Closed Loop (HCL) and Advanced Hybrid Closed Loop (AHCL) systems.

RESEARCH DESIGN AND METHODS

This was a 12-month, prospective, observational, two-center study on 54 type 1 diabetes (T1D) patients aged 19-65 years managed with multiple daily injections (MDI) or Continuous Subcutaneous Insulin Infusion (CSII) in open-loop to evaluate the superiority in terms of effectiveness and safety of Automated Insulin Delivery (AID) systems.

RESULTS

HbA1c levels significantly improved at the end of the study. Time spent with glucose levels in target range (TIR70-180 mg/dL, 3.9-10 mmol/L) increased from 50.5 ± 15.6% at baseline to 73.6 ± 8.0% at 12 months (p < 0.001); time spent above range (TAR180-250 mg/dL, 10-13.9 mmol/L and TAR≥250 mg/dL, 13.9 mmol/L) decreased from 30.6 ± 9.0% and 14.2 ± 10.2 at baseline to 19.3 ± 5.3% and 4.8 ± 3.3% at 12 months (p < 0.001 for both), respectively; time spent below range (TBR54-69 mg/dL, 3-3.8 mmol/L and TBR<54 mg/dL, 3.0 mmol/L) decreased from 3.5 ± 2.6% and 1.2 ± 1.4% at baseline to 1.9 ± 1.5% and 0.4 ± 0.7% at the end of the study (p < 0.001 for both); coefficient of variation (CV) decreased from 35.9 ± 7.8% at baseline to 33.0 ± 5.3% (p < 0.05). Satisfaction with the new technology was scored as high.

CONCLUSION

AID-naïve T1D patients switching to HCL/AHCL systems have significantly and safely improved their glycometabolic outcomes with their high satisfaction with the new type of treatment.

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.

Hybrid Closed-Loop Therapy in Adults With Type 1 Diabetes and Above-Target HbA1c: A Real-world Observational Study

OBJECTIVE

We explored longitudinal changes associated with switching to hybrid closed-loop (HCL) insulin delivery systems in adults with type 1 diabetes and elevated HbA1c levels despite the use of intermittently scanned continuous glucose monitoring (isCGM) and insulin pump therapy.

RESEARCH DESIGN AND METHODS

We undertook a pragmatic, preplanned observational study of participants included in the National Health Service England closed-loop pilot. Adults using isCGM and insulin pump across 31 diabetes centers in England with an HbA1c ≥8.5% who were willing to commence HCL therapy were included. Outcomes included change in HbA1c, sensor glucometrics, diabetes distress score, Gold score (hypoglycemia awareness), acute event rates, and user opinion of HCL.

RESULTS

In total, 570 HCL users were included (median age 40 [IQR 29-50] years, 67% female, and 85% White). Mean baseline HbA1c was 9.4 ± 0.9% (78.9 ± 9.1 mmol/mol) with a median follow-up of 5.1 (IQR 3.9-6.6) months. Of 520 users continuing HCL at follow-up, mean adjusted HbA1c reduced by 1.7% (95% CI 1.5, 1.8; P < 0.0001) (18.1 mmol/mol [95% CI 16.6, 19.6]; P < 0.0001). Time in range (70-180 mg/dL) increased from 34.2 to 61.9% (P < 0.001). Individuals with HbA1c of ≤58 mmol/mol rose from 0 to 39.4% (P < 0.0001), and those achieving ≥70% glucose time in range and <4% time below range increased from 0.8 to 28.2% (P < 0.0001). Almost all participants rated HCL therapy as having a positive impact on quality of life (94.7% [540 of 570]).

CONCLUSIONS

Use of HCL is associated with improvements in HbA1c, time in range, hypoglycemia, and diabetes-related distress and quality of life in people with type 1 diabetes in the real world.

The Tandem Control-IQ advanced hybrid system improves glycemic control in children under 18 years of age with type 1 diabetes and night rest in caregivers

OBJECTIVE

To determine the impact of switching from the predictive low glucose suspend (PLGS) system to the advanced hybrid Tandem Control-IQ system on glucometrics and glycosylated haemoglobin (HbA1c) at one year. To assess the impact on the quality of life perceived by parents.

METHOD

Prospective study in 71 patients aged 6-18 years with type 1 diabetes (DM1), in treatment with PLGS, who switched to an advanced hybrid system. Glucometric data were collected before the change, at 4 and 8 weeks, and at one year of use; HbA1c before the change and after one year. The Diabetes Impact and Devices Satisfaction (DIDS) questionnaire was used at weeks 4 and 8.

RESULTS

An increase in time in range (TIR) was observed with a median of 76% (P<.001) at 4 weeks, which was maintained after one year (+8% in the total group). Overall, 73.24% of patients achieved a TIR above 70%. The subgroup with an initial TIR of less than 56% increased it by 14.4%. After one year there was a 0.3% reduction in HbA1c. Level 1 hypoglycaemia, level 1 and level 2 hyperglycaemia, mean glucose (GM) and coefficient of variation (CV) decreased. Auto mode stayed on 97% of the time and no dropouts occurred. Caregivers had a perception of better glycaemic control and less need to monitor blood glucose variations during the night. None of them would switch back to the previous system and they feel safe with the new system.

CONCLUSIONS

The Tandem Control-IQ advanced hybrid system was shown to be effective one year after its implementation with improvement in all glucometric parameters and HbA1c, as well as night-time rest in caregivers.

Glycemic Outcomes During Early Use of the MiniMed™ 780G Advanced Hybrid Closed-Loop System with Guardian™ 4 Sensor

Background: Safety and significant improvement in overall glycated hemoglobin (A1C) and percentage of time spent in (TIR), below (TBR), and above (TAR) glucose range were demonstrated in the pivotal trial of adolescents and adults using the MiniMed™ advanced hybrid closed-loop (AHCL) system with the adjunctive, calibration-required Guardian™ Sensor 3. The present study evaluated early outcomes of continued access study (CAS) participants who transitioned from the pivotal trial investigational system to the approved MiniMed™ 780G system with the non-adjunctive, calibration-free Guardian™ 4 Sensor (MM780G+G4S). Study data were presented alongside those of real-world MM780G+G4S users from Europe, the Middle East, and Africa. Methods: The CAS participants (N = 109, aged 7-17 years and N = 67, aged >17 years) used the MM780G+G4S for 3 months and data of real-world MM780G+G4S system users (N = 10,204 aged ≤15 years and N = 26,099 aged >15 years) were uploaded from September 22, 2021 to December 02, 2022. At least 10 days of real-world continuous glucose monitoring (CGM) data were required for analyses. Glycemic metrics, delivered insulin and system use/interactions underwent descriptive analyses. Results: Time in AHCL and CGM use were >90% for all groups. AHCL exits averaged 0.1/day and there were few blood glucose measurements (BGMs) (0.8/day-1.0/day). Adults in both cohorts met most consensus recommendations for glycemic targets. Pediatric groups met recommendations for %TIR and %TBR, although not those for mean glucose variability and %TAR, possibly due to low use of recommended glucose target (100 mg/dL) and active insulin time (2 h) settings (28.4% in the CAS cohort and 9.4% in the real-world cohort). The CAS pediatric and adult A1C were 7.2% ± 0.7% and 6.8% ± 0.7%, respectively, and there were no serious adverse events. Conclusions: Early clinical use of the MM780G+G4S was safe and involved minimal BGMs and AHCL exits. Consistent with real-world pediatric and adult use, outcomes were associated with achievement of recommended glycemic targets. Clinical Trial Registration number: NCT03959423.

Beneficial Effects of Control-IQ Automated Insulin Delivery in Basal-Bolus and Basal-Only Insulin Users With Type 2 Diabetes

The t:slim X2 insulin pump with Control-IQ technology (Control-IQ) advanced hybrid closed-loop automated insulin delivery system was evaluated in this prospective single-arm trial. Thirty adults with type 2 diabetes using the Control-IQ system showed substantial glycemic improvement with no increase in hypoglycemia. Mean time in range (70-180 mg/dL) improved 15%, representing an increase of 3.6 hours/day, and mean glucose decreased by 22 mg/dL.

The changing landscape of automated insulin delivery in the management of type 1 diabetes

Automated insulin delivery systems, also known as closed-loop or 'artificial pancreas' systems, are transforming the management of type 1 diabetes. These systems consist of an algorithm which responds to real-time glucose sensor levels by automatically modulating insulin delivery through an insulin pump. We review the rapidly changing landscape of automated insulin-delivery systems over recent decades, from initial prototypes to the different hybrid closed-loop systems commercially available today. We discuss the growing body of clinical trials and real-world evidence demonstrating their glycaemic and psychosocial benefits. We also address future directions in automated insulin delivery such as dual-hormone systems and adjunct therapy as well as the challenges around ensuring equitable access to closed-loop technology.