A Peek Under the Hood: Explaining the MiniMed™ 780G Algorithm with Meal Detection Technology

Glycemic Control Across the Menstrual Cycle in Women with Type 1 Diabetes Using the MiniMed 780G Advanced Hybrid Closed-Loop System: The 780MENS Prospective Study

Objective: To evaluate whether the MiniMed™ 780G advanced hybrid closed-loop (AHCL) system maintains similar glycemic control across two different phases of the menstrual cycle in women with type 1 diabetes (T1D) and to analyze the system's performance in these situations. Methods: Continuous glucose monitoring (CGM) and insulin delivery metrics from 12 participants with T1D using the MiniMed™ 780G AHCL were analyzed throughout 3 prospectively recorded, consecutive menstrual cycles (36 cycles in total). Mixed models were used to compare the different variables between the early follicular phase and late luteal phase. Results: A higher average glucose was found throughout the late luteal phase compared with the early follicular phase (139.5 [133.5, 145.2] vs. 131.5 [126.8, 140.2] mg/dl, respectively, P = 0.002), together with an increase in total daily insulin dose (37.2 ± 11.9 vs. 33.6 ± 12.2 IU, P < 0.001). However, similar values between phases were observed for most of the remaining CGM metrics, including time in range (83.0 [76.0, 87.5] vs. 85.0 [79.8, 89.0] %, P = 0.101). Conclusion: Our results suggest that differences in glycemic control may be found across the menstrual cycle in women with T1D using the MiniMed™ 780G AHCL. Although higher average glucose levels may be expected in the late luteal phase, the deterioration of glycemic control during this phase may be mild with the MiniMed™ 780G AHCL, given the similarities for most of the CGM metrics with respect to the early follicular phase.

Analysis of "Performance of an Automated Insulin Delivery System in People Living With Type 2 Diabetes and Insulin Resistance: First Real-World Evidence in 26,427 Users"

Automated insulin delivery (AID) is now standard of care for managing type 1 diabetes (T1D), yet its role in type 2 diabetes (T2D) is still emerging. While only one AID system has earned regulatory approval for T2D as of January 2025, real-world studies have demonstrated promising results. The article "Performance of an Automated Insulin Delivery system in people living with type 2 diabetes and insulin resistance: first real-world evidence in 26,427 users" presents a large-scale analysis of the MiniMed 780G system in T2D across 73 countries. By categorizing users into four phenotypically distinct cohorts, the study highlights the system's adaptability, achieving consistent glycemic improvements across groups. Despite limitations in baseline data and clinical parameters, the findings reinforce AID as an effective and scalable therapy for insulin-requiring T2D.

Performance of an Automated Insulin Delivery System in People Living With Type 2 Diabetes and Insulin Resistance: First Real-World Evidence in 26 427 Users

BACKGROUND

Type 2 diabetes (T2D) is a phenotypically heterogeneous disease. The use of insulin is required in a significant portion of people with T2D, despite recent developments in antidiabetic medications. This study analyzes glycemic outcomes in automated insulin delivery (AID) users with T2D with different insulin requirements.

METHODS

This is a retrospective, real-world analysis including MiniMed 780G (MM780G) data uploaded to CareLink Personal (January 2020 to April 2024). Four cohorts were identified based on phenotypes of T2D: (A) users with total daily dose of insulin (TDD) ≥ 100 IU, (B) users with self-reported T2D, (C) users with self-reported T2D and TDD ≥ 100 IU, and (D) users with self-reported T2D and TDD <100 IU. Glycemic outcomes and insulin use were assessed post-AID, pre-AID versus post-AID, and six-month longitudinal post-AID.

RESULTS

A total of 26 427 users were included in this study, of which 18 466 in cohort A, 10 795 in cohort B, 2 834 in cohort C, and 7 961 in cohort D. Mean time in range (TIR) was 71.1% ± 12.2 for cohort A, 75.1% ±14.1 for cohort B, 72.2% ± 15.0 for cohort C, and 76.1% ± 13.6 for cohort D. Mean time below range (TBR) <70 mg/dL was ≤1% in all cohorts. The users in cohort C using the recommended optimal settings (glucose target [GT] of 100 mg/dL and active insulin time [AIT] of two hours) had a greater TIR with 78.7% ± 10.8. All cohorts increased ≥10% post-AID compared with pre-AID.

CONCLUSIONS

The use of this AID is associated with effective therapy outcomes, as indicated by over 70% TIR, and appears to be safe, as demonstrated by a low TBR in a large cohort of real-life users with self-reported T2D and high or low TDD.

Precision medicine in type 1 diabetes: comparing metabolic outcomes of Control-IQ and MiniMed 780G according to patient characteristics

AIMS

This study aimed to compare 12-month metabolic outcomes in patients with type 1 diabetes (T1D) treated with either MiniMed 780G (Guardian 4) or Control-IQ (Dexcom G6) automated insulin delivery (AID) systems and identify interaction with patient characteristics.

MATERIALS AND METHODS

We conducted a single-centre, retrospective study including all patients (aged ≥16) with T1D who were started on either MiniMed 780G or Control-IQ between January 2021 and October 2022 and continued for ≥12 months. We used propensity score matching to compare the average marginal effects between MiniMed 780G and Control-IQ regarding the primary outcome (time in range [TIR]) and secondary outcomes (time below range [TBR], glucose monitoring indicator [GMI] and coefficient of variation [CV]) after 12 months. We tested for interaction effects between baseline characteristics (age, sex, socio-professional background, body mass index, insulin daily dose, carbohydrate counting practice) and treatment effect.

RESULTS

We included 245 patients (58% women): 178 treated with Control-IQ and 67 with MiniMed 780G. The mean ± SD age and haemoglobin A1c were 39 ± 15 years and 8.7 ± 1.8% (72 ± 20 mmol/mol) respectively. In the propensity score-matched sample (n = 221), we observed significant differences in 12-month TIR (MiniMed 780G minus Control-IQ [95% CI]: 6.4 [3.4;9.5]), GMI (-0.42 [-0.59; -0.25]) and CV (-2.12 [-3.68; -0.55]), while TBR showed no significant difference (-0.04 [-0.47; +0.40]). The 12-month TIR difference was consistent across subgroups, including baseline carbohydrate counting characteristics.

CONCLUSION

MiniMed 780G is associated with moderate metabolic superiority compared to Control-IQ, without interaction with patient characteristics. These results suggest that neither model is more appropriate for certain populations, particularly patients without carbohydrate counting practice.

Enhanced Metabolic Control in a Pediatric Population with Type 1 Diabetes Mellitus Using Hybrid Closed-Loop and Predictive Low-Glucose Suspend Insulin Pump Treatments

BACKGROUND

Insulin pumps coupled with continuous glucose monitoring sensors use algorithms to analyze real-time blood glucose levels. This allows for the suspension of insulin administration before hypoglycemic thresholds are reached or for adaptive tuning in hybrid closed-loop systems. This longitudinal retrospective study aims to analyze real-world glycemic outcomes in a pediatric population transitioning to such devices.

METHODS

We evaluated children with type 1 diabetes mellitus (T1D) admitted to the Pediatric Diabetes Department from a major University Hospital in Bucharest, Romania, who transitioned to hybrid closed-loop or predictive low-glucose suspend system from either non-automated insulin pumps or multiple daily injections. The primary outcome was assessing the change in glycated hemoglobin (HbA1c) after initiating these devices. Secondary outcomes analyzed changes in glucose metrics from the 90 days prior to the baseline and follow-up visit.

RESULTS

51 children were included (58.8% girls), the mean age was 10.3 ± 3.7 years, and the mean follow-up duration was 13.2 ± 4.5 months. The analyzed parameters, such as HbA1c (6.9 ± 0.7% vs. 6.7 ± 0.6%, p = 0.023), time in range (69.3 ± 11.2% vs. 76 ± 9.9%, p < 0.001), time in tight range (47.4 ± 10.9% vs. 53.7 ± 10.7%, p < 0.001), time below range (5.6 ± 2.9% vs. 3.5 ± 1.9%, p < 0.001), time above range (25 ± 11.2% vs. 20.4 ± 9.4%, p = 0.001), and coefficient of variation (37.9 ± 4.8% vs. 35.6 ± 4.6%, p = 0.001), showed significant improvements.

CONCLUSIONS

The application of these sensor-integrated insulin pumps can significantly enhance metabolic control in pediatric populations, minimizing glycemic variations to mitigate complications and enrich the quality of life.

The interdependence of targets for continuous glucose monitoring outcomes in type 1 diabetes with automated insulin delivery

AIM

The aim was to determine the interdependence of targets for glucose management indicator (GMI), time within the ranges of 70-180 mg/dL (TIR) and 70-140 mg/dL (time in tight glucose range [TITR]), time above 180 mg/dL (TA180) and 250 mg/dL (TA250) and time below 70 mg/dL (TB70) and 54 mg/dL (TB54) and its implications for setting targets in automated insulin delivery (AID).

MATERIALS AND METHODS

Real-world data from individuals with type 1 diabetes using the 780G system were used to calculate the receiver operating characteristic curves and establish interdependent targets for time in ranges based on several GMI benchmarks. Correlation, regression and principal component analysis were used to determine their association and dimensionality.

RESULTS

In individuals aged >15 years (n = 41 692), a GMI <6.5% required targets of >81%, >58%, <15% and <1.9% for TIR, TITR, TA180 and TA250, respectively, with high sensitivity, specificity and accuracy (>90%), whereas these values were poor for time in hypoglycaemia and GMI, which had a modest correlation (-0.21 to -0.43). Two dimensions emerged: (1) GMI, TIR, TITR, TA180 and TA250, and (2) TB70 and TB54, explaining 95% of total variability. GMI (or TIR) and TB70 explained >81% of the variability in the remaining continuous glucose monitoring (CGM) metrics, providing accurate predictions. Individuals aged ≤15 years (n = 14 459) showed similar results.

CONCLUSION

We developed a methodology to establish interdependent CGM targets for therapies with CGM data outputs. In AID with the 780G system, a GMI <7% requires time in ranges close to consensus targets. Targets for GMI, TIR, TITR, TA180 and TA250 could be reduced to targets for GMI or TIR, whereas targets for time in hypoglycaemia are not inherently tied to GMI/TIR targets.

Automated insulin delivery systems in the treatment of diabetes: Benefits, challenges, and practical considerations in pediatric patients

At present, the majority of patients with type 1 diabetes mellitus do not achieve the recommended glycemic control goals to reduce the risk of acute and chronic complications. Hybrid closed-loop systems or automated insulin infusion systems emerged as an opportunity to improve metabolic control, quality of life and reduce the psychosocial impact of type 1 diabetes. This article analyzes the evidence regarding their effectiveness and safety, the challenges they pose and best practices to optimize results when implemented in clinical practice.

Integrated Strategies to Support Diabetes Technology in Pregnancy

Managing diabetes in pregnancy can be overwhelming, with numerous dramatic physiologic changes taking place that require constant diligence and attention. Advances in diabetes technology have improved glycemic outcomes, well-being, and quality of life for people with type 1 diabetes of all ages. However, regulatory approval and access to diabetes technology in pregnancy has lagged behind these advancements, leaving many pregnant individuals without tools that could dramatically improve diabetes care before, during, and after gestation. Here, we review the benefits of continuous glucose monitors and automated insulin-delivery systems in pregnancy and highlight specific scientific and structural supports to help implement diabetes technology safely, effectively, and equitably in pregnancy.

Novel Protocol for the Use of Advanced Hybrid Closed-Loop System in Adolescents Engaged in Contact Sports

INTRODUCTION

Managing exercise remains challenging for adolescent athletes with type 1 diabetes (T1D), especially in contact sports. Even the use of hybrid closed loops can cause problems due to the need to disconnect the pump during some training or competitions. This study evaluated the efficacy of a novel protocol for the use of an advanced hybrid closed-loop system in adolescent football players with T1D during a sports camp.

METHODS

Eleven boys aged 14.9 years (25-75th percentile: 14-15.5), with a diabetes duration of 5.7 years (5.2-7) and regular training schedules in junior football leagues, participated in the study. They started AHCL (MiniMed780G, Medtronic) therapy a month before a week-long sports camp and were observed during the sports camp and the preceding week. Daily camp activities included two 1.5-h training sessions. Protocol included a 90-min temporary target of 150 mg/dL before and insulin pump disconnection during training. Physical activity was tracked using wGT3X-BT Actigraph monitors.

RESULTS

The camp provided conditions of demanding physical activity (6.6 [6-6.9] h/day of moderate-to-vigorous intensity). After starting AHCL, the average participant time spent in the target glucose range (70-180 mg/dL) was 79.34 ± 8.46%, and no significant change was observed during the camp (mean difference +0.79 ± 8.24%, p = 0.7581). Median glucose levels dropped by 10.91 ± 12.08 mg/dL (p = 0.0134), and time in the tight target range increased by 11.41 ± 11.60% (p = 0.0008) without increasing the time below range (<70 mg/dL) or glycemic variability. During the camp, daily insulin dose and basal/bolus ratio remained comparable with baseline, but the relative amount of automated bolus insulin decreased by 14.24 ± 4.65% (p < 0.0001).

CONCLUSION

The predefined regimen, including a temporary target before and disconnection of AHCL during football training, was safe and may provide satisfactory glucose control in active adolescents with T1D. This protocol could be adapted for use in other intensive contact sports.