Safety of a Hybrid Closed-Loop Insulin Delivery System in Patients With Type 1 Diabetes

Dual-hormone artificial pancreas for management of type 1 diabetes: Recent progress and future directions

Over the last few years, technological advances have led to tremendous improvement in the management of type 1 diabetes (T1D). Artificial pancreas systems have been shown to improve glucose control compared with conventional insulin pump therapy. However, clinically significant hypoglycemic and hyperglycemic episodes still occur with the artificial pancreas. Postprandial glucose excursions and exercise-induced hypoglycemia represent major hurdles in improving glucose control and glucose variability in many patients with T1D. In this regard, dual-hormone artificial pancreas systems delivering other hormones in addition to insulin (glucagon or amylin) may better reproduce the physiology of the endocrine pancreas and have been suggested as an alternative tool to overcome these limitations in clinical practice. In addition, novel ultra-rapid-acting insulin analogs with a more physiological time-action profile are currently under investigation for use in artificial pancreas devices, aiming to address the unmet need for further improvements in postprandial glucose control. This review article aims to discuss the current progress and future outlook in the development of novel ultra-rapid insulin analogs and dual-hormone closed-loop systems, which offer the next steps to fully closing the loop in the artificial pancreas.

[Individualization of diabetes treatment by automated insulin delivery]

Insulinpumpen und Glucosesensoren haben sich in Registerdaten als effektiv in der Verbesserung der Diabetestherapie und Reduktion akuter Komplikationen gezeigt. In der pädiatrischen Diabetologie ist die Nutzung mindestens eines technischen Geräts Standard. Durch die Kombination beider Systeme ergibt sich Möglichkeit der automatischen Insulinabgabe („automated insulin delivery“, AID).

Viele AID-Systeme sind in klinischen Studien getestet und haben sich als sicher und effektiv erwiesen. Die Versorgungsituation in Deutschland erlaubt es derzeit nur, Mitgliedern der gesetzlichen Krankenversicherungen ein bestimmtes System zu verordnen; dieses ist für Kinder, die jünger als 7 Jahre sind, nicht geeignet. Gründe liegen in gesetzlichen Hürden und mangelnder Zertifizierung durch die Hersteller. Die CE-Zertifikate können Probleme bei der Insulinverordnung mit sich bringen. „Open-source“-Systeme sind Varianten, mit denen bestehende Regularien umgangen werden können. Daraus ergeben sich sowohl für Nutzer wie auch für Verordner Risiken.

Die dauerhafte Nutzung setzt sowohl auf Anwender- als auch auf Behandlerseite die fundierte Kenntnis der Eigenschaften der einzelnen AID-Systeme voraus. Eine vollständige Automatisierung funktioniert noch nicht. Zur Evaluation der AID-Therapie sind die metrischen Daten der Glucosesensoren, die „Zeit im Zielbereich“ und der „Glucose Management Indicator“ anerkannte und geeignete Parameter, da sie eine Beratung auf Basis der reellen Daten aus dem Alltag der Menschen mit Diabetes zulassen.

Da alle Glucosesensoren über Cloud-basierte Software ausgelesen werden oder die Daten automatisch aus einem telefonverbundenen Empfangsgerät beziehen, ist die ideale technische Grundlage für eine telemedizinische Betreuung geschaffen, die noch der Ausgestaltung bedarf.

Activity detection and classification from wristband accelerometer data collected on people with type 1 diabetes in free-living conditions

This paper introduces methods to estimate aspects of physical activity and sedentary behavior from three-axis accelerometer data collected with a wrist-worn device at a sampling rate of 32 [Hz] on adults with type 1 diabetes (T1D) in free-living conditions. In particular, we present two methods able to detect and grade activity based on its intensity and individual fitness as sedentary, mild, moderate or vigorous, and a method that performs activity classification in a supervised learning framework to predict specific user behaviors. Population results for activity level grading show multi-class average accuracy of 99.99%, precision of 98.0 ± 2.2%, recall of 97.9 ± 3.5% and F1 score of 0.9 ± 0.0. As for the specific behavior prediction, our best performing classifier, gave population multi-class average accuracy of 92.43 ± 10.32%, precision of 92.94 ± 9.80%, recall of 92.20 ± 10.16% and F1 score of 92.56 ± 9.94%. Our investigation showed that physical activity and sedentary behavior can be detected, graded and classified with good accuracy and precision from three-axial accelerometer data collected in free-living conditions on people with T1D. This is particularly significant in the context of automated glucose control systems for diabetes, in that the methods we propose have the potential to inform changes in treatment parameters in response to the intensity of physical activity, allowing patients to meet their glycemic targets.

Predictive Low-Glucose Suspend Necessitates Less Carbohydrate Supplementation to Rescue Hypoglycemia: Need to Revisit Current Hypoglycemia Treatment Guidelines

Current guidelines recommend 15-20 g of carbohydrate (CHO) for treatment of mild to moderate hypoglycemia. However, these guidelines do not account for reduced insulin during suspensions with predictive low-glucose suspend (PLGS). We assessed insulin suspensions, hypoglycemic events, and CHO treatment during a 20-h inpatient evaluation of an investigational system with a PLGS feature, including an overnight basal up-titration period to activate the PLGS. Among 10 adults with type 1 diabetes, there were 59 suspensions; 7 suspensions were associated with rescue CHO and 5 with hypoglycemia. Rescue treatment consisted of median 9 g CHO (range: 5-16 g), with no events requiring repeat CHO. No rescue CHO were given during or after insulin suspension for the overnight basal up-titration. To minimize rebound hyperglycemia and needless calorie intake from hypoglycemia overtreatment, updated guidance for PLGS systems should reflect possible need to reduce CHO amounts for hypoglycemia rescue associated with an insulin suspension. The clinical trial was registered with ClinicalTrials.gov (NCT03890003).

Impact of Hybrid Closed Loop Therapy on Hypoglycemia Awareness in Individuals with Type 1 Diabetes and Impaired Hypoglycemia Awareness

Objective: This study evaluated the efficacy of using a hybrid closed loop (HCL) system in restoring hypoglycemia awareness in individuals with impaired awareness of hypoglycemia (IAH). Research Design and Methods: Participants with IAH (Gold score ≥4) were recruited into a randomized crossover pilot study. They participated in two 8-week periods using a HCL system (Medtronic 670G™) (intervention) and standard insulin pump therapy (control). Hyperinsulinemic hypoglycemic clamp studies were undertaken at baseline and at the end of each study period for the evaluation of the counter-regulatory hormonal and symptomatic responses to hypoglycemia. Results: Seventeen participants (mean age [standard deviation] 35.8 years [11.2 years]) were included in the study. Peak epinephrine levels (median, interquartile range [IQR]) in response to hypoglycemia were similar postintervention and control periods; 234.7 pmol/L (109.2; 938.9) versus 188.3 pmol/L (133.7; 402.9), P = 0.233. However, both peak adrenergic and neuroglycopenic symptom scores were higher after intervention; 5.0 (4.5; 9.0) versus 4.0 (4.0; 5.5), P = 0.009, and 8.5 (6.0; 15.0) versus 6.5 (6.0; 7.0) P = 0.014, respectively. Self-reported hypoglycemia awareness improved: median (IQR) Gold score was 4.0 (3.0; 5.5) versus 5.5 (4.5; 6.0); intervention versus control, P = 0.033. Time spent <3.9 and <3.0 mmol/L was lower in the intervention group than in control, P = 0.002. Other patient-reported outcomes (hypoglycemia fear and diabetes treatment satisfaction) did not change. Conclusions: A short-term use of a HCL system failed to demonstrate an improvement in counter-regulatory hormonal responses. However, higher hypoglycemia symptom scores during controlled hypoglycemia, better self-reported hypoglycemia awareness, and less time spent in hypoglycemia suggest the potential benefits of a HCL system in people with IAH. Trial Registration: anzctr.org.au Identifier: ACTRN12616000909426.

Diabetes Technology Meeting 2020

Diabetes Technology Society hosted its annual Diabetes Technology Meeting on November 12 to November 14, 2020. This meeting brought together speakers to cover various perspectives about the field of diabetes technology. The meeting topics included artificial intelligence, digital health, telemedicine, glucose monitoring, regulatory trends, metrics for expressing glycemia, pharmaceuticals, automated insulin delivery systems, novel insulins, metrics for diabetes monitoring, and discriminatory aspects of diabetes technology. A live demonstration was presented.

Predictors of Time-in-Range (70-180 mg/dL) Achieved Using a Closed-Loop Control System

Background: Studies of closed-loop control (CLC) in patients with type 1 diabetes (T1D) consistently demonstrate improvements in glycemic control as measured by increased time-in-range (TIR) 70-180 mg/dL. However, clinical predictors of TIR in users of CLC systems are needed. Materials and Methods: We analyzed data from 100 children aged 6-13 years with T1D using the Tandem Control-IQ CLC system during a randomized trial or subsequent extension phase. Continuous glucose monitor data were collected at baseline and during 12-16 weeks of CLC use. Participants were stratified into quartiles of TIR on CLC to compare clinical characteristics. Results: TIR for those in the first, second, third, and fourth quartiles was 54%, 65%, 71%, and 78%, respectively. Lower baseline TIR was associated with lower TIR on CLC (r = 0.69, P < 0.001). However, lower baseline TIR was also associated with greater improvement in TIR on CLC (r = -0.81, P < 0.001). During CLC, participants in the highest versus lowest TIR-quartile administered more user-initiated boluses daily (8.5 ± 2.8 vs. 5.8 ± 2.6, P < 0.001) and received fewer automated boluses (3.5 ± 1.0 vs. 6.0 ± 1.6, P < 0.001). Participants in the lowest (vs. the highest) TIR-quartile received more insulin per body weight (1.13 ± 0.27 vs. 0.87 ± 0.20 U/kg/d, P = 0.008). However, in a multivariate model adjusting for baseline TIR, user-initiated boluses and insulin-per-body-weight were no longer significant. Conclusions: Higher baseline TIR is the strongest predictor of TIR on CLC in children with T1D. However, lower baseline TIR is associated with the greatest improvement in TIR. As with open-loop systems, user engagement is important for optimal glycemic control.

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

OBJECTIVE

Advances in diabetes technology have transformed the treatment paradigm for type 1 diabetes, yet the burden of disease is significant. We report on a pivotal safety study of the first tubeless, on-body automated insulin delivery system with customizable glycemic targets.

RESEARCH DESIGN AND METHODS

This single-arm, multicenter, prospective study enrolled 112 children (age 6-13.9 years) and 129 adults (age 14-70 years). A 2-week standard therapy phase (usual insulin regimen) was followed by 3 months of automated insulin delivery. Primary safety outcomes were incidence of severe hypoglycemia and diabetic ketoacidosis. Primary effectiveness outcomes were change in HbA_1c and percent time in sensor glucose range 70-180 mg/dL ("time in range").

RESULTS

A total of 235 participants (98% of enrolled, including 111 children and 124 adults) completed the study. HbA_1c was significantly reduced in children by 0.71% (7.8 mmol/mol) (mean ± SD: 7.67 ± 0.95% to 6.99 ± 0.63% [60 ± 10.4 mmol/mol to 53 ± 6.9 mmol/mol], P < 0.0001) and in adults by 0.38% (4.2 mmol/mol) (7.16 ± 0.86% to 6.78 ± 0.68% [55 ± 9.4 mmol/mol to 51 ± 7.4 mmol/mol], P < 0.0001). Time in range was improved from standard therapy by 15.6 ± 11.5% or 3.7 h/day in children and 9.3 ± 11.8% or 2.2 h/day in adults (both P < 0.0001). This was accomplished with a reduction in time in hypoglycemia <70 mg/dL among adults (median [interquartile range]: 2.00% [0.63, 4.06] to 1.09% [0.46, 1.75], P < 0.0001), while this parameter remained the same in children. There were three severe hypoglycemia events not attributable to automated insulin delivery malfunction and one diabetic ketoacidosis event from an infusion site failure.

CONCLUSIONS

This tubeless automated insulin delivery system was safe and allowed participants to significantly improve HbA_1c levels and time in target glucose range with a very low occurrence of hypoglycemia.

AID(„automated insulin delivery“)-Systeme in der Diabetologie

Insulinpumpen und Glukosesensoren können laut Registerdaten die Diabetestherapie verbessern sowie die Rate akuter Komplikationen reduzieren. In der pädiatrischen Diabetologie ist daher die Nutzung mindestens eines dieser technischen Geräte Standard. Deren Kombination macht Systeme zur automatischen Insulinabgabe („automated insulin delivery“ [AID]) möglich. Viele AID-Systeme wurden in klinischen Studien getestet und erwiesen sich als sicher und effektiv. Die Versorgungsituation in Deutschland jedoch lässt derzeit nur ein System als Verordnung bei Versicherten der gesetzlichen Krankenversicherungen zu, und Kinder unter 7 Jahren können damit derzeit nicht versorgt werden. Gründe hierfür sind gesetzliche Hürden und die mangelnde Zertifizierung durch die Hersteller. Die CE-Zertifikate können zudem zu Problemen bei der Insulinverordnung führen. Open-Source-Systeme sind nicht geprüfte Varianten, um bestehende regulatorische Verhältnisse zu umgehen. Deren Anwendung geht mit Risiken sowohl für Nutzer als auch Verordner einher. Für ihren dauerhaften Einsatz müssen sowohl Anwender als auch Behandler über fundierte Kenntnisse der Eigenschaften der einzelnen AID-Systeme verfügen. Zur Evaluation der AID-Therapie sind die metrischen Daten der Glukosesensoren, die „time in range“ und der Glukosemanagementindex die anerkannten und geeigneten Parameter, da sie eine Beratung auf Basis der reellen Werte aus dem Alltag der Menschen mit Diabetes zulassen. Da alle Glukosesensoren über Cloud-basierte Software ausgelesen werden oder die Daten direkt automatisch übermitteln, ist hiermit die ideale technische Grundlage für eine telemedizinische Betreuung geschaffen, die noch der Ausgestaltung bedarf.

Real-world outcomes with different technology modalities in type 1 diabetes

BACKGROUND AND AIMS

Several treatment modalities are available for type 1 diabetes (T1D), including continuous glucose monitoring (CGM) and flash glucose monitoring (FGM) with MDI, sensor-augmented pumps with predictive low-glucose suspend function (SAP-PLGS) and hybrid closed-loop systems (HCL). The aim of the study was to evaluate the real-world benefits obtained with these treatment modalities.

METHODS AND RESULTS

A cross-sectional study was performed, selecting 4 groups of T1D subjects, regarding their treatment modalities, paired by age, sex and diabetes duration. A comparison was performed, concerning time in different glucose ranges in 2-week sensor downloads. Estimated HbA1c, glycaemic variability measures and sensor use were also compared. 302 T1D people were included (age: 39 ± 12 years, 47% male, diabetes duration: 21 ± 10 years, estimated HbA1c: 7.28 ± 0.84% (56 ± 9 mmol/mol), baseline HbA1c: 7.4 ± 1.0% (57 ± 11 mmol/mol), length of use of the device 8 [3-21] months). Group 1 (CGM + MDI) and 2 (FGM + MDI) showed no differences in time in different glucose ranges. Group 4 (HCL) showed a higher time 70-180 mg/dl and a lower time in hypoglycaemia than group 3 (SAP-PLGS). Group 1 and 2 showed lower time 70-180 mg/dl, higher time in hyperglycaemia and higher glycaemic variability measures than group 3. Group 4 was superior to groups 1 and 2 in all the outcomes.

CONCLUSION

Real-life achievements in glycaemic control and glycaemic variability are described. HCL offer the maximum benefit in terms of time in range and hypoglycaemia protection, compared to CGM + MDI, FGM + MDI and SAP-PLGS.

Reducing the need for carbohydrate counting in type 1 diabetes using closed-loop automated insulin delivery (artificial pancreas) and empagliflozin: A randomized, controlled, non-inferiority, crossover pilot trial

AIM

To assess whether adding empagliflozin to closed-loop automated insulin delivery could reduce the need for carbohydrate counting in type 1 diabetes (T1D) without worsening glucose control.

MATERIALS AND METHODS

In an open-label, crossover, non-inferiority trial, 30 adult participants with T1D underwent outpatient automated insulin delivery interventions with three random sequences of prandial insulin strategy days: carbohydrate counting, simple meal announcement (no carbohydrate counting) and no meal announcement. During each sequence of prandial insulin strategies, participants were randomly assigned empagliflozin (25 mg/day) or not, and crossed over to the comparator. Mean glucose for carbohydrate counting without empagliflozin (control) was compared with no meal announcement with empagliflozin (in the primary non-inferiority comparison) and simple meal announcement with empagliflozin (in the conditional primary non-inferiority comparison).

RESULTS

Participants were aged 40 ± 15 years, had 27 ± 15 years diabetes duration and HbA1c of 7.6% ± 0.7% (59 ± 8 mmol/mol). The system with no meal announcement and empagliflozin was not non-inferior (and thus reasonably considered inferior) to the control arm (mean glucose 10.0 ± 1.6 vs. 8.5 ± 1.5 mmol/L; non-inferiority p = .94), while simple meal announcement and empagliflozin was non-inferior (8.5 ± 1.4 mmol/L; non-inferiority p = .003). Use of empagliflozin on the background of automated insulin delivery with carbohydrate counting was associated with lower mean glucose, corresponding to a 14% greater time in the target range. While no ketoacidosis was observed, mean fasting ketones levels were higher on empagliflozin (0.22 ± 0.18 vs. 0.13 ± 0.11 mmol/L; p < .001).

CONCLUSIONS

Empagliflozin added to automated insulin delivery has the potential to eliminate the need for carbohydrate counting and improves glycaemic control in conjunction with carbohydrate counting, but does not allow for the elimination of meal announcement.

First Outpatient Evaluation of a Tubeless Automated Insulin Delivery System with Customizable Glucose Targets in Children and Adults with Type 1 Diabetes

Background: The objective of this study was to assess the safety and effectiveness of the first commercial configuration of a tubeless automated insulin delivery system, Omnipod^® 5, in children (6-13.9 years) and adults (14-70 years) with type 1 diabetes (T1D) in an outpatient setting. Materials and Methods: This was a single-arm, multicenter, prospective clinical study. Data were collected over a 14-day standard therapy (ST) phase followed by a 14-day hybrid closed-loop (HCL) phase, where participants (n = 36) spent 72 h at each of three prespecified glucose targets (130, 140, and 150 mg/dL, 9 days total) then 5 days with free choice of glucose targets (110-150 mg/dL) using the Omnipod 5. Remote safety monitoring alerts were enabled during the HCL phase. Primary endpoints were difference in time in range (TIR) (70-180 mg/dL) between ST and HCL phases and proportion of participants reporting serious device-related adverse events. Results: Mean TIR was significantly higher among children in the free-choice period overall (64.9% ± 12.2%, P < 0.01) and when using a 110 mg/dL target (71.2% ± 10.2%, P < 0.01), a 130 mg/dL target (61.5% ± 7.7%, P < 0.01), and a 140 mg/dL target (64.8% ± 11.6%, P < 0.01), and among adults using a 130 mg/dL target (75.1% ± 11.6%, P < 0.05), compared to the ST phase (children: 51.0% ± 13.3% and adults: 65.6% ± 15.7%). There were no serious device-related adverse events reported during the HCL phase, nor were there episodes of severe hypoglycemia or diabetic ketoacidosis. Conclusion: The Omnipod 5 System was safe and effective when used at glucose targets from 110 to 150 mg/dL for 14 days at home in children and adults with T1D.

A Virtual Training Program for the Tandem t:slim X2 Insulin Pump: Implementation and Outcomes

Insulin pump training has traditionally been performed in-person. The coronavirus disease 2019 (COVID-19) pandemic necessitated vast increases in the number of virtual pump trainings for Tandem t:slim X2 insulin pump starts. A customized structured pump training curriculum specifically tailored to virtual learning was deployed in early 2020, and included (1) preparation for training with use of the t:simulator app, (2) use of the teach-back method during video training, and (3) automating data uploads for follow-up. Retrospective analysis from >23,000 pump training sessions performed from January 1, 2020 to July 28, 2020 showed sensor time-in-range for up to 6 months after training was 72% (60%-81%) for virtual training versus 67% (54%-78%) for in-person training. Higher user satisfaction (4.78 ± 0.52 vs. 4.64 ± 0.68; P < 0.01) and higher user confidence (4.61 ± 0.75 vs. 4.47 ± 0.0.85; P < 0.01) were reported after the virtual sessions. Virtual pump training was well received and proved safe and effective with the new virtual training curriculum.

MiniMedTM780G Insulin pump system with smartphone connectivity for the treatment of type 1 diabetes: overview of its safety and efficacy

Introduction: Despite significant advances in diabetes care over the last three decades, the majority of people living with T1D are not meeting established metabolic goals. Automated insulin delivery can help achieve these metabolic goals (HbA1c and TIR).Areas covered: This review examines the new features and available data regarding safety and efficacy of the MiniMed™ 780 G, a second-generation advanced hybrid closed-loop system. Reported outcomes include time in, above and below range, HbA1c, diabetic ketoacidosis and severe hypoglycemia.Expert opinion: The initial pivotal trials of the MiniMed™ 780 G have demonstrated promising clinical and safety outcomes. Real-world data and longer-term studies are still needed. The success of AID devices moving forward hinges on their ease of use and ability to reduce and relieve the burden of living with T1D.

Outcomes for continuous subcutaneous insulin infusion users in young adults from lower socioeconomic backgrounds

Objective

Diabetes technology is available and its efficacy and safety have been demonstrated; however, there is little evidence as to how this technology is being utilized and its effectiveness in vulnerable populations. This study evaluated differences in outcomes for young adults in the United States (U.S.) from lower socioeconomic (SES) backgrounds with type 1 diabetes (T1D) managed on continuous subcutaneous insulin infusion (CSII) versus multiple daily injections (MDI) or fixed‐dose insulin (FDI).

Research design, methods and participants

Utilizing the Optum® de‐identified Electronic Health Record data set between 2008 and 2018 to perform a retrospective, cohort study, we identified 805 subjects with T1D aged 18–30 years with Medicaid. We evaluated median difference in HbA1c between CSII and MDI/FDI users for 24 months. Predictors of diabetic ketoacidosis (DKA)‐associated hospitalizations by CSII use were evaluated using logistic regression.

Results

CSII users showed statistically significant lower median HbA1c values at 24 months of follow‐up compared to individuals on MDI/FDI. Non‐white individuals were at lower odds of receiving treatment with CSII. Subjects on CSII were not more likely to be hospitalized for DKA compared to subjects treated with MDI/FDI. Older subjects were at lower odds of being hospitalized for DKA. Males and subjects followed by Endocrinologists were at higher odds of being hospitalized for DKA.

Conclusions

Young adults with T1D from lower SES backgrounds show improved glycaemic control when in CSII compared to MDI/FDI without increases in hospitalizations for DKA.

Glucose Prediction under Variable-Length Time-Stamped Daily Events: A Seasonal Stochastic Local Modeling Framework

Accurate glucose prediction along a long-enough time horizon is a key component for technology to improve type 1 diabetes treatment. Subjects with diabetes might benefit from supervision and control systems that accurately predict risks and trigger corrective actions early enough with improved mitigation. However, large intra-patient variability poses big challenges to glucose prediction. In previous works by the authors, clustering and local modeling techniques with seasonal stochastic models proved to be efficient, allowing for good glucose prediction accuracy for long prediction horizons. Continuous glucose monitoring (CGM) data were partitioned into fixed-length postprandial time subseries and clustered with Fuzzy C-Means to collect similar behaviors, enforcing seasonality at each cluster after subseries concatenation. Then, seasonal stochastic models were identified for each cluster and local predictions were integrated into a global prediction. However, free-living conditions do not support the fixed-length partition of CGM data since daily events duration is variable. In this work, a new algorithm is provided to overcome this constraint, allowing better coping with patient's variability under variable-length time-stamped daily events in supervision and control applications. Besides predicted glucose, two real-time indices are additionally provided-a crispness index, indicating good representation of current glucose behavior by a single model, and a normality index, allowing for the detection of an abnormal glucose behavior (unusual according to registered historical data). The framework is tested in a proof-of-concept in silico study with ten patients over four month training data and two independent two month validation datasets, with and without abnormal behaviors, from the distribution version of the UVA/Padova simulator extended with diverse sources of intra-patient variability.

Sleep and diabetes-specific psycho-behavioral outcomes of a new automated insulin delivery system in young children with type 1 diabetes and their parents

BACKGROUND

Data on the use of Control-IQ, the latest FDA-approved automated insulin delivery (AID) system for people with T1D 6 years of age or older is still scarce, particularly regarding nonglycemic outcomes. Children with T1D and their parents are at higher risk for sleep disturbances. This study assesses sleep, psycho-behavioral and glycemic outcomes of AID compared to sensor-augmented pump therapy (SAP) therapy in young children with T1D and their parents.

METHODS

Thirteen parents and their young children (ages 7-10) on insulin pump therapy were enrolled. Children completed an initial 4-week study with SAP using their own pump and a study CGM followed by a 4-week phase of AID. Sleep outcomes for parents and children were evaluated through actigraphy watches. Several questionnaires were administered at baseline and at the end of each study phase. CGM data were used to assess glycemic outcomes.

RESULTS

Actigraphy data did not show any significant change from SAP to AID, except a reduction of number of parental awakenings during the night (p = 0.036). Parents reported statistically significant improvements in Pittsburgh Sleep Quality Index total score (p = 0.009), Hypoglycemia Fear Survey total score (p = 0.011), diabetes-related distress (p = 0.032), and depression (p = 0.023). While on AID, time in range (70-180 mg/dL) significantly increased compared to SAP (p < 0.001), accompanied by a reduction in hyperglycemia (p = 0.001).

CONCLUSIONS

These results suggest that use of AID has a positive impact on glycemic outcomes in young children as well as sleep and diabetes-specific quality of life outcomes in their parents.

Standardized Hybrid Closed-Loop System Reporting

The hybrid closed-loop (HCL) system has been shown to improve glycemic control and reduce hypoglycemia. Optimization of HCL settings requires interpretation of the glucose, insulin, and factors affecting glucose such as food intake and exercise. To the best of our knowledge, there is no published guidance on the standardized reporting of HCL systems. Standardization of HCL reporting would make interpretation of data easy across different systems. We reviewed the literature on patient and provider perspectives on downloading and reporting glucose metric preferences. We also incorporated international consensus on standardized reporting for glucose metrics. We describe a single-page HCL data reporting, referred to here as "artificial pancreas (AP) Dashboard." We propose seven components in the AP Dashboard that can provide detailed information and visualization of glucose, insulin, and HCL-specific metrics. The seven components include (A) glucose metrics, (B) hypoglycemia, (C) insulin, (D) user experience, (E) hyperglycemia, (F) glucose modal-day profile, and (G) insight. A single-page report similar to an electrocardiogram can help providers and patients interpret HCL data easily and take the necessary steps to improve glycemic outcomes. We also describe the optimal sampling duration for HCL data download and color coding for visualization ease. We believe that this is a first step in creating a standardized HCL reporting, which may result in better uptake of the systems. For increased adoption, standardized reporting will require input from providers, patients, diabetes device manufacturers, and regulators.

New closed-loop insulin systems

Advances in diabetes technologies have enabled the development of automated closed-loop insulin delivery systems. Several hybrid closed-loop systems have been commercialised, reflecting rapid transition of this evolving technology from research into clinical practice, where it is gradually transforming the management of type 1 diabetes in children and adults. In this review we consider the supporting evidence in terms of glucose control and quality of life for presently available closed-loop systems and those in development, including dual-hormone closed-loop systems. We also comment on alternative 'do-it-yourself' closed-loop systems. We remark on issues associated with clinical adoption of these approaches, including training provision, and consider limitations of presently available closed-loop systems and areas for future enhancements to further improve outcomes and reduce the burden of diabetes management.

A Real-World Prospective Study of the Safety and Effectiveness of the Loop Open Source Automated Insulin Delivery System

Objective: To evaluate the safety and effectiveness of the Loop Do-It-Yourself automated insulin delivery system. Research Design and Methods: A prospective real-world observational study was conducted, which included 558 adults and children (age range 1-71 years, mean HbA1c 6.8% ± 1.0%) who initiated Loop either on their own or with community-developed resources and provided data for 6 months. Results: Mean time-in-range 70-180 mg/dL (TIR) increased from 67% ± 16% at baseline (before starting Loop) to 73% ± 13% during the 6 months (mean change from baseline 6.6%, 95% confidence interval [CI] 5.9%-7.4%; P < 0.001). TIR increased in both adults and children, across the full range of baseline HbA1c, and in participants with both high- and moderate-income levels. Median time <54 mg/dL was 0.40% at baseline and changed by -0.05% (95% CI -0.09% to -0.03%, P < 0.001). Mean HbA1c was 6.8% ± 1.0% at baseline and decreased to 6.5% ± 0.8% after 6 months (mean difference = -0.33%, 95% CI -0.40% to -0.26%, P < 0.001). The incidence rate of reported severe hypoglycemia events was 18.7 per 100 person-years, a reduction from the incidence rate of 181 per 100 person-years during the 3 months before the study. Among the 481 users providing Loop data at 6 months, median continuous glucose monitoring use was 96% (interquartile range [IQR] 91%-98%) and median time Loop modulating basal insulin was at least 83% (IQR 73%-88%). Conclusions: The Loop open source system can be initiated with community-developed resources and used safely and effectively by adults and children with type 1 diabetes.

New closed-loop insulin systems

Advances in diabetes technologies have enabled the development of automated closed-loop insulin delivery systems. Several hybrid closed-loop systems have been commercialised, reflecting rapid transition of this evolving technology from research into clinical practice, where it is gradually transforming the management of type 1 diabetes in children and adults. In this review we consider the supporting evidence in terms of glucose control and quality of life for presently available closed-loop systems and those in development, including dual-hormone closed-loop systems. We also comment on alternative 'do-it-yourself' closed-loop systems. We remark on issues associated with clinical adoption of these approaches, including training provision, and consider limitations of presently available closed-loop systems and areas for future enhancements to further improve outcomes and reduce the burden of diabetes management.

Insulin and insulin analogs as antidiabetic therapy: A perspective from clinical trials

The discovery of insulin in 1921 and the progress achieved in the ensuing century highlight the promise and challenge of biochemically modifying the molecule to achieve optimization of its delivery and therapeutic efficacy. Normal endogenous insulin secretion consists of a highly orchestrated physiologic loop wherein multiple metabolic signals trigger the pancreatic β cells to secrete the precise amount of insulin into the portal system required to maintain euglycemia. Accordingly, in the treatment of diabetes, attempting to replicate this complex physiology with exogenous insulin therapy given subcutaneously presents a clinical challenge. In this context, recombinant DNA-based technology has enabled the development of insulin analogs that have been specifically designed to confer advantageous pharmacodynamic features that can better mimic endogenous insulin secretion. In this review, we discuss the development of the most widely available insulin preparations and provide evidence-based insight into their use in clinical practice.

Safety and glycemic outcomes of do-it-yourself AndroidAPS hybrid closed-loop system in adults with type 1 diabetes

Background

The aim of the study was to assess the safety and glycemic outcomes with the use of a Do-It-Yourself (DIY) Hybrid Closed-Loop (HCL) system based on the AndroidAPS application in type 1 diabetes (T1D).

Methods

Single-center clinical trial, with 3-week run-in and 12-week study period. DIY HCL system consisted of the Dana Diabecare RS insulin pump, Dexcom G5 continuous glucose monitoring system and AndroidAPS application. Primary outcome was safety: incidences of severe hypoglycemia, diabetic ketoacidosis, time spent in glycemia <54 mg/dl. Secondary endpoints included percentage of time in range (TIR) 70–180 mg/dl, time below 70 mg/dl, HbA1c, insulin requirements, and body weight.

Results

In total 12 subjects (5 men, 7 women) were enrolled, mean age 31.3±6.7, 95%CI(27.7–34.9) years, mean diabetes duration 16.1±5.7, 95%CI(13.0–19.2) years. No episodes of severe hypoglycemia or ketoacidosis were observed. Percentage of time spent in glycemia below 54mg/dl was not increased. Average sensor glycemia was lower in the study period than baseline (141.1 ± 8.4, 95%CI(136.3–145.9) vs. 153.3 ± 17.9, 95%CI(143.2–163.4), mg/dl p<0.001). TIR 70–180 mg/dl was improved by 11.3%, 95%CI(2.8%-19.8%) (from 68.0 ± 12.7 to 79.3 ± 6.4%, p<0.001), without increasing hypoglycemia time. The HbA1c level decreased by -0.5%, 95%CI(-0.9%–-0.1%) (from 6.8 ± 0.5 to 6.3 ± 0.4%, p<0.001). Additionally, in the last 4 weeks of the study period participants significantly improved and showed TIR 70–180 mg/dl 82.1 ± 5.6%, 95%CI(78.9–85.3), time <54 mg/dl 0.30 (0.20–0.55)%, median 95%CI(0.1–0.7) and <70 mg/dl 1.90 (1.10–3.05)%, median 95%CI(0.7–3.2). The insulin requirement and body weight did not change in the study.

Conclusions

The study revealed safety of the Do-It-Yourself HCL system AndroidAPS in adults with T1D, limited to well-controlled, highly selected and closely monitored patients. The use of AndroidAPS significantly improved HbA1c, time in range and average sensor glycemia without increasing hypoglycemia. As both patients and their medical team are gaining experience using the system over time, they improve glycemic control.

Trial registration

German Clinical Trials Register: no. DRKS00015439; https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00015439.

Anticipation of Historical Exercise Patterns by a Novel Artificial Pancreas System Reduces Hypoglycemia During and After Moderate-Intensity Physical Activity in People with Type 1 Diabetes

Objective: Physical activity is a major challenge to glycemic control for people with type 1 diabetes. Moderate-intensity exercise often leads to steep decreases in blood glucose and hypoglycemia that closed-loop control systems have so far failed to protect against, despite improving glycemic control overall. Research Design and Methods: Fifteen adults with type 1 diabetes (42 ± 13.5 years old; hemoglobin A_1c 6.6% ± 1.0%; 10F/5M) participated in a randomized crossover clinical trial comparing two hybrid closed-loop (HCL) systems, a state-of-the-art hybrid model predictive controller and a modified system designed to anticipate and detect unannounced exercise (APEX), during two 32-h supervised admissions with 45 min of planned moderate activity, following 4 weeks of data collection. Primary outcome was the number of hypoglycemic episodes during exercise. Continuous glucose monitor (CGM)-based metrics and hypoglycemia are also reported across the entire admissions. Results: The APEX system reduced hypoglycemic episodes overall (9 vs. 33; P = 0.02), during exercise (5 vs. 13; P = 0.04), and in the 4 h following (2 vs. 11; P = 0.02). Overall CGM median percent time <70 mg/dL decreased as well (0.3% vs. 1.6%; P = 0.004). This protection was obtained with no significant increase in time >180 mg/dL (18.5% vs. 16.6%, P = 0.15). Overnight control was notable for both systems with no hypoglycemia, median percent in time 70-180 mg/dL at 100% and median percent time 70-140 mg/dL at ∼96% for both. Conclusions: A new closed-loop system capable of anticipating and detecting exercise was proven to be safe and feasible and outperformed a state-of-the-art HCL, reducing participants' exposure to hypoglycemia during and after moderate-intensity physical activity. ClinicalTrials.gov NCT03859401.

Feasibility Study of a Hybrid Closed-Loop System with Automated Insulin Correction Boluses

Background: The Medtronic MiniMed™ 670G system adjusts basal insulin delivery in response to continuous glucose monitoring levels and is already in use in clinical practice. We tested the home-based feasibility of the new MiniMed advanced hybrid closed-loop (AHCL) system, which includes several algorithm enhancements and an optional autocorrection bolus mode. Methods: Twelve adolescents and young adults (eight females) with type 1 diabetes [median (interquartile range)] aged 16.6 (15.9, 18.2) years and diabetes duration of 7.1 (4.7, 8.8) years] participated in this single-arm study. The first stage was a 6-day open-loop run-in period, with the predictive low-glucose suspend feature on. This was followed by 6 days/5 nights in a supervised hotel setting, using the AHCL system, including closed-loop challenges (missed meal bolus, late meal bolus, and physical activity); and finally, 3 weeks with unrestricted home use. Glycemic parameters were compared between the open-loop and closed-loop periods. Results: Participants spent 93.3% (4.7) of the time in SmartGuard™ Auto Mode. Hemoglobin A1C levels decreased from median (interquartile range) 7.1% (6.7, 7.9) at baseline to 6.8% (6.6, 7.4) at study end, after 4 weeks (P = 0.0027). Time in range (TIR) (70-180 mg/dL) was 68.4% (10.6) and time below 70 mg/dL was 4% (3.5) during open-loop; and 74% (6.1) and 2.6% (1.9), respectively, during the closed-loop at home phase (P = 0.06, P = 0.27). TIR increased during the nighttime, from 64.6% (17.4) to 80.7% (7.8), P = 0.007, without change in time below 70 mg/dL (P = 0.15). No serious adverse events occurred. Conclusions: The new AHCL system demonstrated safety and effectiveness in controlling day and night glucose levels.

Fast Acting Insulin Aspart Compared with Insulin Aspart in the Medtronic 670G Hybrid Closed Loop System in Type 1 Diabetes: An Open Label Crossover Study

This is a single-center randomized open label active-controlled crossover trial comparing efficacy and safety of fast acting insulin aspart (FA) (FIASP^®) versus insulin aspart (IAsp) (NovoLog^®) when used in the Medtronic 670G system in auto mode in patients with type 1 diabetes. Forty patients were randomized to either IAsp or FA. Each treatment period was 7 weeks and a standardized meal test was administered 6 weeks after the start of each treatment period. The primary endpoint was postprandial glucose (PPG) increment after the meal test at 1 h. Treatment with FA using the MiniMed 670G hybrid closed loop (HCL) led to a greater reduction in 1-h postprandial glucose increase compared with treatment with IAsp during the standardized mixed meal test. Change in glucose: [estimated treatment difference (ETD ± standard deviation [SD]); 95% confidence interval]: 70.27 (±17.36) mg/dL (3.9 ± 1.0 mmol/L) with FA versus 98.42 (±17.36) mg/dL (5.5 ± 1.0 mmol/L) with IAsp (P = 0.008). Patients spent 1.81% (P = 0.016) more time (equivalent to 26 min per day) in the 70-180 mg/dL (3.89-9.99 mmol/L) range with FA than with IAsp. The entire sample spent only 0.5% of time <54 mg/dL (<3.0 mmol/L) range. The increment in the 1 h postmeal test glucose was significantly lower with FA versus IAsp. FA in a HCL setting is safe and effective with patients spending more time in the 70-180 mg/dL (3.89-9.99 mmol/L) target range than with IAsp. Trial registration: Clinicaltrials.gov identifier: NCT03977727.

Real-World Patient Experience of Long-Term Hybrid Closed-Loop Insulin Pump Use

OBJECTIVES

Understanding of patient experiences and adaptations to hybrid closed-loop (HCL) pumps beyond the confines of short-term clinical trials is needed to inform best practices surrounding this emerging technology. We investigated long-term, real-world patient experiences with HCL technology.

METHODS

In semistructured interviews, 21 adults with type 1 diabetes at a single Canadian tertiary diabetes centre discussed their transition to use of Medtronic MiniMed 670G auto-mode. Interviews were audio-recorded, transcribed and analyzed iteratively to identify emerging themes.

RESULTS

Participants' mean age was 50±13 years, 12 of the 21 participants were female, baseline glycated hemoglobin (A1C) was 7.9±1.0% and auto-mode duration was 9.3±4.6 months. Three had discontinued auto-mode. Most participants praised auto-mode for reducing hypoglycemia, stabilizing glucose overnight and improving A1C, while also reporting frustration with frequency of alarms and user input, sensor quality and inadequate response to hyperglycemia. Participants with the highest baseline A1Cs (8.8% to 9.8%) tended to report immense satisfaction and trust in auto-mode, meeting their primary expectations of improved glycemic control. In contrast, participants with controlled diabetes (A1C <7.5%) had hoped to offload active management, but experienced significant cognitive and emotional labour associated with relinquishing control during suboptimal auto-mode performance. Participants were commonly aware of workarounds to "trick" the pump, and almost all participants with A1C <7.5% tried at least 1 workaround.

CONCLUSIONS

In the real-world setting, patients' goals and satisfaction with auto-mode appeared to vary considerably with their baseline diabetes control. Patients with the most suboptimal glycemic control described the greatest benefits and easiest adaptation process, challenging commonly held assumptions for patient selection for pump therapy.

Fully Closed Loop Glucose Control With a Bihormonal Artificial Pancreas in Adults With Type 1 Diabetes: An Outpatient, Randomized, Crossover Trial

OBJECTIVE

To demonstrate the performance and safety of a bihormonal (insulin and glucagon) artificial pancreas (AP) in adults with type 1 diabetes.

RESEARCH DESIGN AND METHODS

In this outpatient, randomized, crossover trial, 2-week fully closed loop glucose control (AP therapy) was compared with 2-week open loop control (patient's normal insulin pump therapy with a glucose sensor if they had one).

RESULTS

A total of 23 patients were included in the analysis. Time in range (70-180 mg/dL [3.9-10 mmol/L]) was significantly higher during closed loop (median 86.6% of time [interquartile range 84.9-88.5]) compared with open loop (53.9% [49.7-67.2]; P < 0.0001).

CONCLUSIONS

Compared with insulin pump therapy, the bihormonal AP provided superior glucose control, without meal or exercise announcements, and was safe in adults with type 1 diabetes.

Hybrid closed-loop therapy: Where are we in 2021?

Hybrid closed-loop systems are characterized by the coexistence of algorithm-driven automated insulin delivery combined with manual mealtime boluses. Used correctly, these insulin delivery systems offer better glucose control and reduced risk of hypoglycaemia and represent the most advanced form of insulin delivery available for people with type 1 diabetes. The aim of this paper was to compare the currently available commercial hybrid closed-loop systems in the UK: the Medtronic 670G/780G, Tandem t:slim X2 Control IQ and CamAPS FX systems. The Medtronic 670G/780G systems use Guardian 3 sensor (7-day use, two to four calibrations per day), while Tandem and CamAPS systems use the calibration-free Dexcom G6 sensor (10 days). The CamAPS system is available as an android app, whereas the other two systems have the algorithm embedded in the insulin pump. During pivotal studies, depending on the study population and baseline glycated haemoglobin level, these systems achieve a time spent in the target range 3.9 to 10 mmol/L (70 to 180 mg/dL) of 65% to 76% with low burden of hypoglycaemia. All three systems allow a higher glucose target for announced exercise, while the Tandem system offers an additional night-time tighter target. The CamAPS system offers fully customizable glucose targets and is the only system licensed for use during pregnancy. Additional education is required for both users and healthcare professionals to harness the best performance from these systems as well as to troubleshoot when "automode exits" occur. We provide consensus recommendations to develop pragmatic pathways to guide patients, clinicians and commissioners in making informed decisions on the appropriate use of the diabetes technology.

Comparison Between Closed-Loop Insulin Delivery System (the Artificial Pancreas) and Sensor-Augmented Pump Therapy: A Randomized-Controlled Crossover Trial

Objective: Several studies have shown that closed-loop automated insulin delivery (the artificial pancreas) improves glucose control compared with sensor-augmented pump therapy. We aimed to confirm these findings using our automated insulin delivery system based on the iPancreas platform. Research Design and Methods: We conducted a two-center, randomized crossover trial comparing automated insulin delivery with sensor-augmented pump therapy in 36 adults with type 1 diabetes. Each intervention lasted 12 days in outpatient free-living conditions with no remote monitoring. The automated insulin delivery system used a model predictive control algorithm that was a less aggressive version of our earlier dosing algorithm to emphasize safety. The primary outcome was time in the range 3.9-10.0 mmol/L. Results: The automated insulin delivery system was operational 90.2% of the time. Compared with the sensor-augmented pump therapy, automated insulin delivery increased time in range (3.9-10.0 mmol/L) from 61% (interquartile range 53-74) to 69% (60-73; P = 0.006) and increased time in tight target range (3.9-7.8 mmol/L) from 37% (30-49) to 45% (35-51; P = 0.011). Automated insulin delivery also reduced time spent below 3.9 and 3.3 mmol/L from 3.5% (0.8-5.4) to 1.6% (1.1-2.7; P = 0.0021) and from 0.9% (0.2-2.1) to 0.5% (0.2-1.1; P = 0.0122), respectively. Time spent below 2.8 mmol/L was 0.2% (0.0-0.6) with sensor-augmented pump therapy and 0.1% (0.0-0.4; P = 0.155) with automated insulin delivery. Conclusions: Our study confirms findings that automated insulin delivery improves glucose control compared with sensor-augmented pump therapy. ClinicalTrials.gov no. NCT02846831.

Perceptions and expectations of adults with type 1 diabetes for the use of artificial pancreas systems with and without glucagon addition: Results of an online survey

BACKGROUND AND AIMS

The first hybrid artificial pancreas (AP) systems with insulin only (mono-hormonal) have recently reached the market while next generations systems are under development including those with glucagon addition (bi-hormonal). Understanding the expectations and impressions of future potential users about AP systems is important for optimal use of this clinically effective emerging technology.

METHODS AND RESULTS

An online survey about AP systems which consisted of 50 questions was addressed to people with type 1 diabetes in the province of Quebec, Canada. Surveys were completed by 123 respondents with type 1 diabetes (54% women, mean (SD) age 40.2 (14.4) y.o., diabetes duration 23.7 (14.1) years, 58% insulin pump users and 43% glucose sensor users). Of the respondents, 91% understood how AP systems work, 79% trusted them with correct insulin dosing, 73% were willing to replace their current treatment with AP and 80% expected improvement in quality of life. Anxiety about letting an algorithm control their glucose levels was expressed by 18% while the option of ignoring or modifying AP instructions was favoured by 88%. As for bi-hormonal AP systems, 83% of respondents thought they would be useful to further reduce hypoglycemic risks.

CONCLUSIONS

Overall, respondents expressed positive views about AP systems use and high expectations for a better quality of life, glycemic control and hypoglycemia reduction. Data from this survey could be useful to health care professionals and developers of AP systems.

Toward a Fully Automated Artificial Pancreas System Using a Bioinspired Reinforcement Learning Design: In Silico Validation

OBJECTIVE

The automation of insulin treatment is the most challenge aspect of glucose management for type 1 diabetes owing to unexpected exogenous events (e.g., meal intake). In this article, we propose a novel reinforcement learning (RL) based artificial intelligence (AI) algorithm for a fully automated artificial pancreas (AP) system.

METHODS

A bioinspired RL designing method was developed for automated insulin infusion. This method has reward functions that imply the temporal homeostatic objective and discount factors that reflect an individual specific pharmacological characteristic. The proposed method was applied to a training method using an RL algorithm and was evaluated in virtual patients from the FDA approved UVA/Padova simulator with unannounced meal intakes.

RESULTS

For a single-meal experiment with preprandial fasting, the trained policy demonstrated fully automated regulation in both the basal and postprandial phases. In the in silico trial with a variation of insulin sensitivity and dawn phenomenon, the policy achieved a mean glucose of 124.72 mg/dL and percentage time in the normal range of 89.56%. The layer-wise relevance propagation provides interpretable information on AI-driven decision for robustness to sensor noise, automated postprandial regulation, and insulin stacking avoidance.

CONCLUSION

The AP algorithm based on the bioinspired RL approach enables fully automated blood glucose control with unannounced meal intake.

SIGNIFICANCE

The proposed framework can be extended to other drug-based treatments for systems with significant uncertainties.

The Digital/Virtual Diabetes Clinic: The Future Is Now-Recommendations from an International Panel on Diabetes Digital Technologies Introduction

The increasing prevalence of diabetes, combined with a growing global shortage of health care professionals (HCP), necessitates the need to develop new approaches to diabetes care delivery to expand access to care, lessen the burden on people with diabetes, improve efficiencies, and reduce the unsustainable financial liability on health systems and payers. Use of digital diabetes technologies and telehealth protocols within a digital/virtual diabetes clinic has the potential to address these challenges. However, several issues must be resolved to move forward. In February 2020, organizers of the Advanced Technologies & Treatments for Diabetes Annual Conference convened an international panel of HCP, researchers, patient advocates, and industry representatives to review the status of digital diabetes technologies, characterize deficits in current technologies, and identify issues for consideration. Since that meeting, the importance of using telehealth and digital diabetes technologies has been demonstrated amid the global coronavirus disease (COVID-19) pandemic. This article summarizes the panel's discussion of the opportunities, obstacles, and requisites for advancing the use of these technologies as a standard of care for the management of diabetes.

One-year experience of hybrid closed-loop system in children and adolescents with type 1 diabetes previously treated with multiple daily injections: drivers to successful outcomes

OBJECTIVE

To evaluate the effect of a 1-year hybrid closed-loop (HCL) system on glycemic control in children and adolescents with type 1 diabetes (T1D) previously treated with multiple daily injections (MDI).

METHODS

This was a 1-year observational study, as a continuation of the previous 3 months prospective study of pediatric patients with T1D conducted at Sidra Medicine in Qatar. The study enrolled individuals aged 7-18 years with T1D > 1 year, on MDI with self-monitoring of blood glucose or continuous glucose monitoring, with no prior pump experience, and with an HbA1c level < 12.5% (< 113 mmol/mol). After the first 3 months of HCL use, patients were followed at 6, 9 and 12 months, where HbA1c was obtained and pump data were collected.

RESULTS

All 30 participants (age 10.24 ± 2.6 years) who initiated HCL completed 12 months of HCL system use in Auto Mode. The participants used the sensor 88.4 ± 6.5% of the time with Auto Mode usage 85.6 ± 7.4% during 12 months of HCL system use. HbA1c decreased from 8.2 ± 1.4% (66 ± 15.3 mmol/mol) at baseline, to 6.7 ± 0.5% (50 ± 5.5 mmol/mol) at 3 months (p = 0.02) and remained stable to 7.1 ± 0.6 (54 ± 6.6 mmol/mol) at 12 months (p = 0.02). TIR (70-180 mg/dL) increased from 46.9% at baseline to 71.9% at 1 month and remained above 70% during the 12 months of HCL use.

CONCLUSION

HCL system (MiniMed 670G) in children and adolescents previously treated with MDI significantly improves glycemic outcomes (HbA1c and Time in Ranges) immediately during the first month. This improved glycemic control was maintained over the 1 year following Auto Mode initiation.

A comparison of two hybrid closed-loop systems in adolescents and young adults with type 1 diabetes (FLAIR): a multicentre, randomised, crossover trial

BACKGROUND

Management of type 1 diabetes is challenging. We compared outcomes using a commercially available hybrid closed-loop system versus a new investigational system with features potentially useful for adolescents and young adults with type 1 diabetes.

METHODS

In this multinational, randomised, crossover trial (Fuzzy Logic Automated Insulin Regulation [FLAIR]), individuals aged 14-29 years old, with a clinical diagnosis of type 1 diabetes with a duration of at least 1 year, using either an insulin pump or multiple daily insulin injections, and glycated haemoglobin (HbA_1c) levels of 7·0-11·0% (53-97 mmol/mol) were recruited from seven academic-based endocrinology practices, four in the USA, and one each in Germany, Israel, and Slovenia. After a run-in period to teach participants how to use the study pump and continuous glucose monitor, participants were randomly assigned (1:1) using a computer-generated sequence, with a permuted block design (block sizes of two and four), stratified by baseline HbA_1c and use of a personal MiniMed 670G system (Medtronic) at enrolment, to either use of a MiniMed 670G hybrid closed-loop system (670G) or the investigational advanced hybrid closed-loop system (Medtronic) for the first 12-week period, and then participants were crossed over with no washout period, to the other group for use for another 12 weeks. Masking was not possible due to the nature of the systems used. The coprimary outcomes, measured with continuous glucose monitoring, were proportion of time that glucose levels were above 180 mg/dL (>10·0 mmol/L) during 0600 h to 2359 h (ie, daytime), tested for superiority, and proportion of time that glucose levels were below 54 mg/dL (<3·0 mmol/L) calculated over a full 24-h period, tested for non-inferiority (non-inferiority margin 2%). Analysis was by intention to treat. Safety was assessed in all participants randomly assigned to treatment. This trial is registered with ClinicalTrials.gov, NCT03040414, and is now complete.

FINDINGS

Between June 3 and Aug 22, 2019, 113 individuals were enrolled into the trial. Mean age was 19 years (SD 4) and 70 (62%) of 113 participants were female. Mean proportion of time with daytime glucose levels above 180 mg/dL (>10·0 mmol/L) was 42% (SD 13) at baseline, 37% (9) during use of the 670G system, and 34% (9) during use of the advanced hybrid closed-loop system (mean difference [advanced hybrid closed-loop system minus 670G system] -3·00% [95% CI -3·97 to -2·04]; p<0·0001). Mean 24-h proportion of time with glucose levels below 54 mg/dL (<3·0 mmol/L) was 0·46% (SD 0·42) at baseline, 0·50% (0·35) during use of the 670G system, and 0·46% (0·33) during use of the advanced hybrid closed-loop system (mean difference [advanced hybrid closed-loop system minus 670G system] -0·06% [95% CI -0·11 to -0·02]; p<0·0001 for non-inferiority). One severe hypoglycaemic event occurred in the advanced hybrid closed-loop system group, determined to be unrelated to study treatment, and none occurred in the 670G group.

INTERPRETATION

Hyperglycaemia was reduced without increasing hypoglycaemia in adolescents and young adults with type 1 diabetes using the investigational advanced hybrid closed-loop system compared with the commercially available MiniMed 670G system. Testing an advanced hybrid closed-loop system in populations that are underserved due to socioeconomic factors and testing during pregnancy and in individuals with impaired awareness of hypoglycaemia would advance the effective use of this technology FUNDING: National Institute of Diabetes and Digestive and Kidney Diseases.

9. Pharmacologic Approaches to Glycemic Treatment: Standards of Medical Care in Diabetes-2021

The American Diabetes Association (ADA) "Standards of Medical 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, a multidisciplinary expert committee (https://doi.org/10.2337/dc21-SPPC), 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, please refer to the Standards of Care Introduction (https://doi.org/10.2337/dc21-SINT). Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

A Decade of Disparities in Diabetes Technology Use and HbA1c in Pediatric Type 1 Diabetes: A Transatlantic Comparison

OBJECTIVE

As diabetes technology use in youth increases worldwide, inequalities in access may exacerbate disparities in hemoglobin A1c (HbA1c). We hypothesized that an increasing gap in diabetes technology use by socioeconomic status (SES) would be associated with increased HbA1c disparities.

RESEARCH DESIGN AND METHODS

Participants aged <18 years with diabetes duration ≥1 year in the Type 1 Diabetes Exchange (T1DX, U.S., n = 16,457) and Diabetes Prospective Follow-up (DPV, Germany, n = 39,836) registries were categorized into lowest (Q1) to highest (Q5) SES quintiles. Multiple regression analyses compared the relationship of SES quintiles with diabetes technology use and HbA1c from 2010-2012 to 2016-2018.

RESULTS

HbA1c was higher in participants with lower SES (in 2010-2012 and 2016-2018, respectively: 8.0% and 7.8% in Q1 and 7.6% and 7.5% in Q5 for DPV; 9.0% and 9.3% in Q1 and 7.8% and 8.0% in Q5 for T1DX). For DPV, the association between SES and HbA1c did not change between the two time periods, whereas for T1DX, disparities in HbA1c by SES increased significantly (P < 0.001). After adjusting for technology use, results for DPV did not change, whereas the increase in T1DX was no longer significant.

CONCLUSIONS

Although causal conclusions cannot be drawn, diabetes technology use is lowest and HbA1c is highest in those of the lowest SES quintile in the T1DX, and this difference for HbA1c broadened in the past decade. Associations of SES with technology use and HbA1c were weaker in the DPV registry.

13. Children and Adolescents: Standards of Medical Care in Diabetes-2021

The American Diabetes Association (ADA) "Standards of Medical 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, a multidisciplinary expert committee (https://doi.org/10.2337/dc21-SPPC), 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, please refer to the Standards of Care Introduction (https://doi.org/10.2337/dc21-SINT). Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Six-Month Effectiveness of Advanced vs. Standard Hybrid Closed-Loop System in Children and Adolescents With Type 1 Diabetes Mellitus

INTRODUCTION

The purpose of this study was to assess the effectiveness of advanced- (a-HCL) vs. standard-hybrid closed-loop (s-HCL) systems use up to 6 months of treatment in a real-world setting of children and adolescents with T1DM.

METHODS

We retrospectively evaluated all T1DM pediatric users of MiniMed™ 670G system (s-HCL) and 780G system (a-HCL). HbA1c and BMI were collected at baseline and three and six months after HCL start. Data on glycemic control were extracted from reports generated with CareLink™ Personal Software in Manual Mode, at HCL start, after one, three, and six months after HCL beginning.

RESULTS

The study included 44 individuals with a median age of 13.3 years (range 2- 21 years), 20 on s-HCL, and 24 on a-HCL. a-HCL users had a significantly lower HbA1c compared to s-HCL after six months of HCL use (7.1 vs. 7.7%). Significant differences in HbA1c between a-HCL and s-HCL users were found in children aged 7-14 years (7.1 vs. 7.7% after six months) and in those with a worse (HbA1c >8%) glycemic control at the beginning (7.1 vs. 8.1% after six months). No significant changes in HbA1c were found in a-HCL users that previously used a s-HCL system. Nevertheless, only the use of a-HCL significantly predicted a lower HbA1c after six months. All sensor-specific measures of glycemic control improved from Manual to Auto mode, in both s-HCL and a-HCL, without increasing time spent in hypoglycemia. However, the percentage of individuals with TIR>70% increased significantly in a-HCL users, who attained this target earlier and more stably: younger age, a higher rate of auto-correction, and a lower amount of CHO inserted predicted a TIR>70%. BMI SDS did not significantly change throughout the study period.

CONCLUSION

This real-world study suggests that effectiveness might be greater in a-HCL than in s-HCL, with significant changes in HbA1c, and reaching earlier and more stably the target of TIR >70%, without increasing hypoglycemia or BMI. At the same time, previous users of s-HCL systems did not show any further improvement with a-HCL. Children under the age of 14 years of age, not represented in previous studies, seem to benefit the most from a-HCL pumps as well as individuals with the worst glycemic control.

Developing Insulin Delivery Devices with Glucose Responsiveness

Individuals with type 1 and advanced type 2 diabetes require daily insulin therapy to maintain blood glucose levels in normoglycemic ranges to prevent associated morbidity and mortality. Optimal insulin delivery should offer both precise dosing in response to real-time blood glucose levels as well as a feasible and low-burden administration route to promote long-term adherence. A series of glucose-responsive insulin delivery mechanisms and devices have been reported to increase patient compliance while mitigating the risk of hypoglycemia. This review discusses currently available insulin delivery devices, overviews recent developments towards the generation of glucose-responsive delivery systems, and provides commentary on the opportunities and barriers ahead regarding the integration and translation of current glucose-responsive insulin delivery designs.

Characterizing Glycemic Control and Sleep in Adults with Long-Standing Type 1 Diabetes and Hypoglycemia Unawareness Initiating Hybrid Closed Loop Insulin Delivery

Nocturnal hypoglycemia is life threatening for individuals with type 1 diabetes (T1D) due to loss of hypoglycemia symptom recognition (hypoglycemia unawareness) and impaired glucose counter regulation. These individuals also show disturbed sleep, which may result from glycemic dysregulation. Whether use of a hybrid closed loop (HCL) insulin delivery system with integrated continuous glucose monitoring (CGM) designed for improving glycemic control, relates to better sleep across time in this population remains unknown. The purpose of this study was to describe long-term changes in glycemic control and objective sleep after initiating hybrid closed loop (HCL) insulin delivery in adults with type 1 diabetes and hypoglycemia unawareness. To accomplish this, six adults (median age = 58 y) participated in an 18-month ongoing trial assessing HCL effectiveness. Glycemic control and sleep were measured using continuous glucose monitoring and wrist accelerometers every 3 months. Paired sample t-tests and Cohen's d effect sizes modeled glycemic and sleep changes and the magnitude of these changes from baseline to 9 months. Reduced hypoglycemia (d = 0.47-0.79), reduced basal insulin requirements (d = 0.48), and a smaller glucose coefficient of variation (d = 0.47) occurred with medium-large effect sizes from baseline to 9 months. Hypoglycemia awareness improved from baseline to 6 months with medium-large effect sizes (Clarke score (d = 0.60), lability index (d = 0.50), HYPO score (d = 1.06)). Shorter sleep onset latency (d = 1.53; p < 0.01), shorter sleep duration (d = 0.79), fewer total activity counts (d = 1.32), shorter average awakening length (d = 0.46), and delays in sleep onset (d = 1.06) and sleep midpoint (d = 0.72) occurred with medium-large effect sizes from baseline to 9 months. HCL led to clinically significant reductions in hypoglycemia and improved hypoglycemia awareness. Sleep showed a delayed onset, reduced awakening length and onset latency, and maintenance of high sleep efficiency after initiating HCL. Our findings add to the limited evidence on the relationships between diabetes therapeutic technologies and sleep health. This trial is registered with ClinicalTrials.gov (NCT03215914).

Cost-effectiveness of a novel hybrid closed-loop system compared with continuous subcutaneous insulin infusion in people with type 1 diabetes in the UK

AIMS

The MiniMed 670 G insulin pump system is the first commercially available hybrid closed-loop (HCL) insulin delivery system and clinical studies have shown that this device is associated with incremental benefits in glycemic control relative to continuous subcutaneous insulin infusion (CSII) with or without continuous glucose monitoring (CGM). The aim was to evaluate the long-term cost-effectiveness of the MiniMed 670 G system versus CSII alone in people with type 1 diabetes (T1D) in the UK.

MATERIALS AND METHODS

Cost-effectiveness analysis was performed using the IQVIA CORE Diabetes Model. Clinical input data were sourced from a clinical trial of the MiniMed 670 G system in 124 adults and adolescents with T1D. The analysis was performed over a lifetime time horizon and both future costs and clinical outcomes were discounted at 3.5% per annum. The analysis was performed from a healthcare payer perspective.

RESULTS

The use of the MiniMed 670 G system led to an improvement in quality-adjusted life expectancy of 1.73 quality-adjusted life years (QALYs), relative to CSII. Total lifetime direct costs were GBP 35,425 higher with the MiniMed 670 G system than with CSII resulting in an incremental cost-effectiveness ratio (ICER) of GBP 20,421 per QALY gained. Sensitivity analyses revealed that the ICER was sensitive to assumptions around glycemic control and assumptions relating to the quality-of-life benefit associated with a reduction in fear of hypoglycemia.

LIMITATIONS

Long-term projections from short-term data are inherently associated with uncertainty but represent arguably the best available evidence in lieu of long-term clinical trials.

CONCLUSIONS

In the UK, over patient lifetimes, the incremental clinical benefits associated with the use of MiniMed 670 G system means that it is likely to be cost-effective relative to the continued use of CSII in people with T1D, particularly for those with a fear of hypoglycemia or poor baseline glycemic control.

Review of the Long-Term Implantable Senseonics Continuous Glucose Monitoring System and Other Continuous Glucose Monitoring Systems

The article published by Kevin Cowart in this issue of the Journal of Diabetes Science and Technology (JDST) is a detailed overview of the clinical trial data and analysis used to demonstrate the safety and effectiveness of the Eversense continuous glucose monitoring (CGM) System for regulatory approval and clinical acceptance. The article describes the published study results for safety, accuracy, reliability, ease of insertion/removal, adverse events, and ease of diabetes patient-use for controlling their glucose levels short and long term. The author nicely compares Eversense CGM System safety and performance with the short-term subcutaneous tissue CGM systems being commercialized by Dexcom, Medtronic Diabetes, and Abbott Diabetes. This comparison may help the clinician define which type of patient with diabetes might benefit the most from the long-term implantable CGM system. The majority of studied patients describe a positive experience managing their diabetes with the Eversense CGM System and request implantation of a new sensor 90 or 180 days later.

7. Diabetes Technology: Standards of Medical Care in Diabetes-2021

The American Diabetes Association (ADA) "Standards of Medical 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, a multidisciplinary expert committee (https://doi.org/10.2337/dc21-SPPC), 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, please refer to the Standards of Care Introduction (https://doi.org/10.2337/dc21-SINT). Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

A Comparison of Two Hybrid Closed-Loop Systems in Italian Children and Adults With Type 1 Diabetes

Tandem Control-IQ and Minimed 780G represent the most Advanced Hybrid Closed Loop (AHCL) systems currently available in pediatric and adult subjects with Type 1 Diabetes (T1D). We retrospectively compared clinical and continuous glucose monitoring data from 51 patients who upgraded to Minimed 780G system and have completed 1-month observation period with data from 39 patients who upgraded to Tandem Control-IQ. Inverse probability weighting was used to minimize the basal characteristics imbalances. Both AHCL systems showed a significant improvement in glycemic parameters. Minimed 780G group achieved higher TIR increase (p= 0.004) and greater reduction of blood glucose average (p= 0.001). Tandem Control-IQ system significantly reduced the occurrence of TBR (p= 0.010) and the Coefficient of Variation of glucose levels (p= 0.005). The use of ACHL systems led to a significant improvement of glycemic control substantially reaching the International recommended glycemic targets. Minimed 780G appears to be more effective in managing hyperglycemia, while Tandem Control-IQ seems to be more effective in reducing time in hypoglycemia.

Time in Range from Continuous Glucose Monitoring: A Novel Metric for Glycemic Control

Glycosylated hemoglobin (HbA1c) has been the sole surrogate marker for assessing diabetic complications. However, consistently reported limitations of HbA1c are that it lacks detailed information on short-term glycemic control and can be easily interfered with by various clinical conditions such as anemia, pregnancy, or liver disease. Thus, HbA1c alone may not represent the real glycemic status of a patient. The advancement of continuous glucose monitoring (CGM) has enabled both patients and healthcare providers to monitor glucose trends for a whole single day, which is not possible with HbA1c. This has allowed for the development of core metrics such as time spent in time in range (TIR), hyperglycemia, or hypoglycemia, and glycemic variability. Among the 10 core metrics, TIR is reported to represent overall glycemic control better than HbA1c alone. Moreover, various evidence supports TIR as a predictive marker of diabetes complications as well as HbA1c, as the inverse relationship between HbA1c and TIR reveals. However, there are more complex relationships between HbA1c, TIR, and other CGM metrics. This article provides information about 10 core metrics with particular focus on TIR and the relationships between the CGM metrics for comprehensive understanding of glycemic status using CGM.

Continuous glucose monitoring: The achievement of 100 years of innovation in diabetes technology

Monitoring of glucose levels is essential to effective diabetes management. Over the past 100 years, there have been numerous innovations in glucose monitoring methods. The most recent advances have centered on continuous glucose monitoring (CGM) technologies. Numerous studies have demonstrated that use of continuous glucose monitoring confers significant glycemic benefits on individuals with type 1 diabetes (T1DM) and type 2 diabetes (T2DM). Ongoing improvements in accuracy and convenience of CGM devices have prompted increasing adoption of this technology. The development of standardized metrics for assessing CGM data has greatly improved and streamlined analysis and interpretation, enabling clinicians and patients to make more informed therapy modifications. However, many clinicians many be unfamiliar with current CGM and how use of these devices may help individuals with T1DM and T2DM achieve their glycemic targets. The purpose of this review is to present an overview of current CGM systems and provide guidance to clinicians for initiating and utilizing CGM in their practice settings.