Overnight glucose control with an automated, unified safety system in children and adolescents with type 1 diabetes at diabetes camp

Real-World Use of Hybrid Closed-Loop Systems during Diabetes Camp: A Preliminary Study for Secure Configuration Strategies in Children and Adolescents

The introduction of closed-loop systems in the pediatric population has been a revolution in the management and evolution of diabetes. However, there are not many published studies in situations in which the feeding, schedules, and activities of the children deviate from the routine for which the systems were programmed, as in the case of a summer camp for children and adolescents with diabetes, where the specific programming of this device is not well known. It was a single-center prospective preliminary study. A total of twenty-seven patients (mean age 11.9 ± 1.9 years, 40% male, duration of diabetes 6.44 ± 2.83 years) were included (twenty with Medtronic MiniMed 780G system and seven with Tandem Control-IQ). Glucometric variables and pump functionality were monitored during the 7-day camp and in the following 3 weeks. There was no decrease from the objective TIR 70% at any moment. The worst results in Time Below Range were at 72 h from starting the camp, and the worst results in Time Above Range were in the first 24 h, with a progressive improvement after that. No episodes of level 3 hypoglycemia or ketoacidosis occurred. The use of specific programming in two integrated systems, with complex blood glucose regulation algorithms and not-prepared-for situations with increased levels of physical activity or abrupt changes in feeding routines, did not result in an increased risk of level 3 hypoglycemia and ketoacidosis for our pediatric type 1 diabetes (T1D) patients, regardless of the closed-loop device.

Integration of a Safety Module to Prevent Rebound Hypoglycemia in Closed-Loop Artificial Pancreas Systems

BACKGROUND

With automated insulin delivery (AID) systems becoming widely adopted in the management of type 1 diabetes, we have seen an increase in occurrences of rebound hypoglycemia or generated hypoglycemia induced by the controller's response to rapid glucose rises following rescue carbohydrates. Furthermore, as AID systems aim to enable complete automation of prandial control, algorithms are designed to react even more strongly to glycemic rises. This work introduces a rebound hypoglycemia prevention layer (HypoSafe) that can be easily integrated into any AID system.

METHODS

HypoSafe constrains the maximum permissible insulin delivery dose based on the minimum glucose reading from the previous hour and the current glucose level. To demonstrate its efficacy, we integrated HypoSafe into the latest University of Virginia (UVA) AID system and simulated two scenarios using the 100-adult cohort of the UVA/Padova T1D simulator: a nominal case including three unannounced meals, and another case where hypoglycemia was purposely induced by an overestimated manual bolus.

RESULTS

In both simulation scenarios, rebound hypoglycemia events were reduced with HypoSafe (nominal: from 39 to 0, hypo-induced: from 55 to 7) by attenuating the commanded basal (nominal: 0.27U vs. 0.04U, hypo-induced: 0.27U vs. 0.03U) and bolus (nominal: 1.02U vs. 0.05U, hypo-induced: 0.43U vs. 0.02U) within the 30-minute interval after treating a hypoglycemia event. No clinically significant changes resulted for time in the range of 70 to 180 mg/dL or above 180 mg/dL.

CONCLUSION

HypoSafe was shown to be effective in reducing rebound hypoglycemia events without affecting achieved time in range when combined with an advanced AID system.

The efficacy of automated insulin delivery systems in children and adolescents with Type 1 Diabetes Mellitus: a systematic review and meta-analysis of randomized controlled trials

AIMS

Insulin administration is the treatment of choice for people with type 1 diabetes mellitus (T1D). Technological advances have led to the development of automated insulin delivery (AID) systems, aiming to optimize the quality of life of patients with T1D. We present a systematic review and meta-analysis of the current literature about the efficacy of AID systems in children and adolescents with T1D.

METHODS

We conducted a systematic literature search for randomized controlled trials (RCTs) until August 8^th, 2022, investigating the efficacy of AID systems in the management of patients <21 years of age with T1D. A priori subgroup and sensitivity analyses based on different settings (free-living settings, type of AID system, parallel group or crossover design) were also conducted.

RESULTS

In total, 26 RCTs reporting a total of 915 children and adolescents with T1D were included in the meta-analysis. AID systems revealed statistically significant differences in the main outcomes, such as the proportion of time in the target glucose range (3.9-10 mmol/L) (p<0.00001), in hypoglycemia (<3.9 mmol/L) (p=0.003) and mean proportion of HbA1C (p=0.0007) compared to control group.

CONCLUSIONS

According to the present meta-analysis, AID systems are superior to insulin pump therapy, sensor-augmented pumps and multiple daily insulin injections. Most of the included studies have a high risk of bias because of allocation, blinding of patients and blinding of assessment. Our sensitivity analyses showed that patients <21 years of age with T1D can use AID systems, after proper education, following their daily activities. Further RCTs examining the effect of AID systems on nocturnal hypoglycemia, under free-living settings and studies examining the effect of dual-hormone AID systems are pending.

Trial of Hybrid Closed-Loop Control in Young Children with Type 1 Diabetes

BACKGROUND

Closed-loop control systems of insulin delivery may improve glycemic outcomes in young children with type 1 diabetes. The efficacy and safety of initiating a closed-loop system virtually are unclear.

METHODS

In this 13-week, multicenter trial, we randomly assigned, in a 2:1 ratio, children who were at least 2 years of age but younger than 6 years of age who had type 1 diabetes to receive treatment with a closed-loop system of insulin delivery or standard care that included either an insulin pump or multiple daily injections of insulin plus a continuous glucose monitor. The primary outcome was the percentage of time that the glucose level was in the target range of 70 to 180 mg per deciliter, as measured by continuous glucose monitoring. Secondary outcomes included the percentage of time that the glucose level was above 250 mg per deciliter or below 70 mg per deciliter, the mean glucose level, the glycated hemoglobin level, and safety outcomes.

RESULTS

A total of 102 children underwent randomization (68 to the closed-loop group and 34 to the standard-care group); the glycated hemoglobin levels at baseline ranged from 5.2 to 11.5%. Initiation of the closed-loop system was virtual in 55 patients (81%). The mean (±SD) percentage of time that the glucose level was within the target range increased from 56.7±18.0% at baseline to 69.3±11.1% during the 13-week follow-up period in the closed-loop group and from 54.9±14.7% to 55.9±12.6% in the standard-care group (mean adjusted difference, 12.4 percentage points [equivalent to approximately 3 hours per day]; 95% confidence interval, 9.5 to 15.3; P<0.001). We observed similar treatment effects (favoring the closed-loop system) on the percentage of time that the glucose level was above 250 mg per deciliter, on the mean glucose level, and on the glycated hemoglobin level, with no significant between-group difference in the percentage of time that the glucose level was below 70 mg per deciliter. There were two cases of severe hypoglycemia in the closed-loop group and one case in the standard-care group. One case of diabetic ketoacidosis occurred in the closed-loop group.

CONCLUSIONS

In this trial involving young children with type 1 diabetes, the glucose level was in the target range for a greater percentage of time with a closed-loop system than with standard care. (Funded by the National Institute of Diabetes and Digestive and Kidney Diseases; PEDAP ClinicalTrials.gov number, NCT04796779.).

Automated insulin delivery systems: from early research to routine care of type 1 diabetes

Automated insulin delivery (AID) systems, so-called closed-loop systems or artificial pancreas, are based upon the concept of insulin supply driven by blood glucose levels and their variations according to body glucose needs, glucose intakes and insulin action. They include a continuous glucose monitoring device which provides a signal to a control algorithm tuning insulin delivery from an infusion pump. The control algorithm is the key of the system since it commands insulin administration in order to maintain blood glucose in a predefined target range and close to a near-normal glucose level. The last two decades have shown dramatic advances toward the use in free life of AID systems for routine care of type 1 diabetes through step-by-step demonstrations of feasibility, safety and efficacy in successive hospital, transitional and outpatient trials. Because of the constraints of pharmacokinetics and dynamics of subcutaneous insulin delivery, the currently available AID systems are all 'hybrid' or 'semi-automated' insulin delivery systems with a need of meal and exercise announcements in order to anticipate rapid glucose variations through pre-meal bolus or pre-exercise reduction of infusion rate. Nevertheless, these AID systems significantly improve time spent in a near-normal range with a reduction of the risk of hypoglycemia and the mental load of managing diabetes in everyday life, representing a milestone in insulin therapy. Expected progression toward fully automated, further miniaturized and integrated, possibly implantable on long-term and more physiological closed-loop systems paves the way for a functional cure of type 1 diabetes.

Continuous subcutaneous insulin infusions: Closing the loop

CONTEXT

Continuous subcutaneous insulin infusions (CSIIs) and continuous glucose monitors (CGMs) have revolutionized the management of diabetes mellitus (DM). Over the last two decades the development of advanced, small, and user-friendly technology has progressed substantially, essentially closing the loop in the fasting and post-absorptive state, nearing the promise of an artificial pancreas. The momentum was mostly driven by the diabetes community itself, to improve its health and quality of life.

EVIDENCE ACQUISITION

Literature regarding CSII and CGM was reviewed.

EVIDENCE SYNTHESIS

Management of DM aims to regulate blood glucose to prevent long term micro and macrovascular complications. CSIIs combined with CGMs provide an integrated system to maintain tight glycemic control in a safe and uninterrupted fashion, while minimizing hypoglycemic events. Recent advances have allowed to 'close the loop' by better mimicking endogenous insulin secretion and glucose level regulation. Evidence supports sustained improvement in glycemic control with reduced episodes of hypoglycemia using these systems, while improving quality of life. Ongoing work in delivery algorithms with or without counterregulatory hormones will allow for further layers of regulation of the artificial pancreas.

CONCLUSION

Ongoing efforts to develop an artificial pancreas have created effective tools to improve the management of DM. CSIIs and CGMs are useful in diverse populations ranging from children to the elderly, as well as in various clinical contexts. Individually and more so together, these have had a tremendous impact in the management of DM, while avoiding treatment fatigue. However, cost and accessibility are still a hindrance to its wider application.

Effectiveness and safety of a model predictive control (MPC) algorithm for an artificial pancreas system in outpatients with type 1 diabetes (T1D): systematic review and meta-analysis

BACKGROUND

The purpose of this study was to assess the effectiveness and safety of a model predictive control (MPC) algorithm for an artificial pancreas system in outpatients with type 1 diabetes.

METHODS

We searched PubMed, EMBASE, Cochrane Central, and the Web of Science to December 2021. The eligibility criteria for study selection were randomized controlled trials comparing artificial pancreas systems (MPC, PID, and fuzzy algorithms) with conventional insulin therapy in type 1 diabetes patients. The heterogeneity of the overall results was identified by subgroup analysis of two factors including the intervention duration (overnight and 24 h) and the follow-up periods (< 1 week, 1 week to 1 month, and > 1 month).

RESULTS

The meta-analysis included a total of 41 studies. Considering the effect on the percentage of time maintained in the target range between the MPC-based artificial pancreas and conventional insulin therapy, the results showed a statistically significantly higher percentage of time maintained in the target range in overnight use (10.03%, 95% CI [7.50, 12.56] p < 0.00001). When the follow-up period was considered, in overnight use, the MPC-based algorithm showed a statistically significantly lower percentage of time maintained in the hypoglycemic range (-1.34%, 95% CI [-1.87, -0.81] p < 0.00001) over a long period of use (> 1 month).

CONCLUSIONS

Overnight use of the MPC-based artificial pancreas system statistically significantly improved glucose control while increasing time maintained in the target range for outpatients with type 1 diabetes. Results of subgroup analysis revealed that MPC algorithm-based artificial pancreas system was safe while reducing the time maintained in the hypoglycemic range after an overnight intervention with a long follow-up period (more than 1 month).

Advanced hybrid artificial pancreas system improves on unannounced meal response - In silico comparison to currently available system

BACKGROUND AND OBJECTIVE

Glycemic control, especially meal-related disturbance rejection, has proven to be a major challenge for people with type 1 diabetes. In this manuscript, we introduce a novel, personalized, advanced hybrid insulin infusion system (a.k.a. artificial pancreas) based on the Model Predictive Control (MPC) methodology to adjust insulin infusion while automatically rejecting uninformed meals.

METHODS

The proposed advanced hybrid closed-loop system relies on the integration of three key elements: (i) an adaptive personalized MPC control law that modulates the control strength depending on recent past control actions, glucose measurements, and its derivative, (ii) an automatic Bolus Priming System (BPS) that commands additional insulin injections safely upon the detection of enabling metabolic conditions (e.g., an unacknowledged meal), and (iii) a new hyperglycemia mitigation system to avoid prevailing hyperglycemia. The benefits of the proposed system are demonstrated through simulations and tests using the most up-to-date Type 1 UVA/Padova simulator as preclinical stage prior to in vivo clinical tests. We used a legacy algorithm (USS Virginia), currently used in clinical care, as a benchmark controller.

RESULTS

Overall, the proposed control strategy enhanced by an automatic BPS improves glycemic control when compared with an available system. When a large meal is not announced (80g CHO), the proposed controller outperformed the legacy controller in time-in-target-range TIR (postprandial and overnight) and time-in-tight-range TTR (overall, postprandial, and overnight).

CONCLUSION

The integration of a novel BPS into an advanced control system allowed to automatically reject unannounced meals. Exhaustive simulation studies indicated the safety and feasibility of the proposed controller to be deployed in human clinical trials.

Current Advances of Artificial Pancreas Systems: A Comprehensive Review of the Clinical Evidence

Since Banting and Best isolated insulin in the 1920s, dramatic progress has been made in the treatment of type 1 diabetes mellitus (T1DM). However, dose titration and timely injection to maintain optimal glycemic control are often challenging for T1DM patients and their families because they require frequent blood glucose checks. In recent years, technological advances in insulin pumps and continuous glucose monitoring systems have created paradigm shifts in T1DM care that are being extended to develop artificial pancreas systems (APSs). Numerous studies that demonstrate the superiority of glycemic control offered by APSs over those offered by conventional treatment are still being published, and rapid commercialization and use in actual practice have already begun. Given this rapid development, keeping up with the latest knowledge in an organized way is confusing for both patients and medical staff. Herein, we explore the history, clinical evidence, and current state of APSs, focusing on various development groups and the commercialization status. We also discuss APS development in groups outside the usual T1DM patients and the administration of adjunct agents, such as amylin analogues, in APSs.

Advanced Closed-Loop Control System Improves Postprandial Glycemic Control Compared With a Hybrid Closed-Loop System Following Unannounced Meal

OBJECTIVE

Meals are a major hurdle to glycemic control in type 1 diabetes (T1D). Our objective was to test a fully automated closed-loop control (CLC) system in the absence of announcement of carbohydrate ingestion among adolescents with T1D, who are known to commonly omit meal announcement.

RESEARCH DESIGN AND METHODS

Eighteen adolescents with T1D (age 15.6 ± 1.7 years; HbA1c 7.4 ± 1.5%; 9 females/9 males) participated in a randomized crossover clinical trial comparing our legacy hybrid CLC system (Unified Safety System Virginia [USS]-Virginia) with a novel fully automated CLC system (RocketAP) during two 46-h supervised admissions (each with one announced and one unannounced dinner), following 2 weeks of data collection. Primary outcome was the percentage time-in-range 70-180 mg/dL (TIR) following the unannounced meal, with secondary outcomes related to additional continuous glucose monitoring-based metrics.

RESULTS

Both TIR and time-in-tight-range 70-140 mg/dL (TTR) were significantly higher using RocketAP than using USS-Virginia during the 6 h following the unannounced meal (83% [interquartile range 64-93] vs. 53% [40-71]; P = 0.004 and 49% [41-59] vs. 27% [22-36]; P = 0.002, respectively), primarily driven by reduced time-above-range (TAR >180 mg/dL: 17% [1.3-34] vs. 47% [28-60]), with no increase in time-below-range (TBR <70 mg/dL: 0% median for both). RocketAP also improved control following the announced meal (mean difference TBR: -0.7%, TIR: +7%, TTR: +6%), overall (TIR: +5%, TAR: -5%, TTR: +8%), and overnight (TIR: +7%, TTR: +19%, TAR: -5%). RocketAP delivered less insulin overall (78 ± 23 units vs. 85 ± 20 units, P = 0.01).

CONCLUSIONS

A new fully automated CLC system with automatic prandial dosing was proven to be safe and feasible and outperformed our legacy USS-Virginia in an adolescent population with and without meal announcement.

Initiating hybrid closed loop: A program evaluation of an educator-led Control-IQ follow-up at a large pediatric clinic

BACKGROUND

Control-IQ (Tandem Diabetes) is a hybrid closed-loop (HCL) system that users self-initiate after completing online training. Best practices for clinical follow-up are not known. Our quality improvement objective was to evaluate the usefulness of an educator-led follow-up program for new HCL users in a type 1 diabetes pediatric clinic.

METHODS

We implemented an ''HCLCheck-in'' program, first determining when users started HCL, then having diabetes educators contact them for a follow-up call 2-weeks after start. Educators used a Clinical Tool to inform insulin dose and behavior recommendations, and used four benchmarks to determine need for further follow-up: ≥71% HCL use, ≥71% CGM use, ≥60% Time-in-Range (TIR, 70-180 mg/dL), <5% below 70 mg/dL. Family and educator satisfaction were surveyed.

RESULTS

One-hundred-twenty-three youth [mean age 13.6 ± 3.7 y, 53.7% female, mean HbA1c 7.6 ± 1.4% (60 mmol/mol)] completed an HCLCheck-in call a median (IQR) of 18(15, 21) days post-HCL start. 74 users (60%) surpassed benchmarks with 94% HCL use and 71% TIR. Of the 49 who did not, 16 completed a second call, and improved median TIR 12.5% (p = 0.03). HCL users reported high satisfaction with the program overall [median 10 (9, 10) out of 10]. Educators spent a median of 45 (32,70) minutes per user and rated satisfaction with the program as 8 (7,9.5) and the Tool as 9 (9, 10).

CONCLUSION

Our HCLCheck-in program received high satisfaction ratings and resulted in improved TIR for those initially not meeting benchmarks, suggesting users may benefit from early follow-up. Similar programs may be beneficial for other new technologies.

Closed-loop insulin delivery systems in children and adolescents with type 1 diabetes

Introduction: Optimal glycemic control remains challenging in children and adolescents with type 1 diabetes due to highly variable day-to-day and night-to-night insulin requirements. This hurdle could be addressed by glucose-responsive insulin delivery based on real-time continuous glucose measurements.Areas covered: This review summaries recent advances of closed-loop systems in children and adolescents with type 1 diabetes, using both single- and dual-hormone closed-loop systems. The main outcomes, proportions of time spent in target range 70-180 mg/dl, and time spent in hypoglycemia below 70 mg/dl, are assessed particularly during unsupervised free-living randomized controlled trials.Expert opinion: Noteworthy and clinically meaningful translation of experimental investigations from controlled in-hospital settings to unrestricted home studies have been achieved over the past years, resulting in the regulatory approval of the first hybrid closed-loop system also in the pediatric population and with several other advanced devices in the pipeline. Large multinational and pivotal clinical trials including broad age populations are underway to facilitate the use of closed-loop systems in routine clinical practice.

Safety and Efficacy of Initializing the Control-IQ Artificial Pancreas System Based on Total Daily Insulin in Adolescents with Type 1 Diabetes

Objective: To assess the safety and efficacy of a simplified initialization for the Tandem t:slim X2 Control-IQ hybrid closed-loop system, using parameters based on total daily insulin ("MyTDI") in adolescents with type 1 diabetes under usual activity and during periods of increased exercise. Research Design and Methods: Adolescents with type 1 diabetes 12-18 years of age used Control-IQ for 5 days at home using their usual parameters. Upon arrival at a 60-h ski camp, participants were randomized to either continue Control-IQ using their home settings or to reinitialize Control-IQ with MyTDI parameters. Control-IQ use continued for 5 days following camp. The effect of MyTDI on continuous glucose monitoring outcomes were analyzed using repeated measures analysis of variance (ANOVA): baseline, camp, and at home. Results: Twenty participants were enrolled and completed the study; two participants were excluded from the analysis due to absence from ski camp (1) and illness (1). Time in range was similar between both groups at home and camp. A tendency to higher time <70 mg/dL in the MyTDI group was present but only during camp (median 3.8% vs. 1.4%, P = 0.057). MyTDI users with bolus/TDI ratios >40% tended to show greater time in the euglycemic range improvements between baseline and home than users with ratios <40% (+16.3% vs. -9.0%, P = 0.012). All participants maintained an average of 95% time in closed loop (84.1%-100%). Conclusions: MyTDI is a safe, effective, and easy way to determine insulin parameters for use in the Control-IQ artificial pancreas. Future modifications to account for the influence of carbohydrate intake on MyTDI calculations might further improve time in range.

A Clinical Training Program for Hybrid Closed Loop Therapy in a Pediatric Diabetes Clinic

BACKGROUND

Hybrid closed loop (HCL) therapy is now available in clinical practice for treatment of type 1 diabetes; however, there is limited research on how to educate patients on this new therapy. The purpose of this quality improvement project was to optimize a HCL education program for pediatric patients with type 1 diabetes (T1D).

METHODS

Our multidisciplinary team developed a novel HCL clinical training program for current insulin pump users, using a quality improvement process called the Plan-Do-Study-Act model. Seventy-two patients participated in the HCL training program, which included (1) an in-person group class to reinforce conventional insulin pump and CGM use on the new system, (2) a live video conference class to teach HCL use, and (3) three follow-up phone calls in the first 4 weeks after HCL training to assess system use, make insulin adjustments, and provide targeted reeducation. Diabetes educators collected data during follow-up calls, and patients completed a training satisfaction survey.

RESULTS

The quality improvement process resulted in a training program that emphasized education on HCL exits, CGM use, and optimizing insulin to carbohydrate ratio settings. Patients successfully sustained time in HCL in the initial weeks of use and rated the trainings and follow-up calls highly.

CONCLUSIONS

Ongoing educational support is vital in the early weeks of HCL use. This quality improvement project is the first to examine strategies for implementation of HCL therapy into a large pediatric diabetes center, and may inform best practices for implementation of new diabetes technologies into other diabetes clinics.

Realizing a Closed-Loop (Artificial Pancreas) System for the Treatment of Type 1 Diabetes

Recent, rapid changes in the treatment of type 1 diabetes have allowed for commercialization of an "artificial pancreas" that is better described as a closed-loop controller of insulin delivery. This review presents the current state of closed-loop control systems and expected future developments with a discussion of the human factor issues in allowing automation of glucose control. The goal of these systems is to minimize or prevent both short-term and long-term complications from diabetes and to decrease the daily burden of managing diabetes. The closed-loop systems are generally very effective and safe at night, have allowed for improved sleep, and have decreased the burden of diabetes management overnight. However, there are still significant barriers to achieving excellent daytime glucose control while simultaneously decreasing the burden of daytime diabetes management. These systems use a subcutaneous continuous glucose sensor, an algorithm that accounts for the current glucose and rate of change of the glucose, and the amount of insulin that has already been delivered to safely deliver insulin to control hyperglycemia, while minimizing the risk of hypoglycemia. The future challenge will be to allow for full closed-loop control with minimal burden on the patient during the day, alleviating meal announcements, carbohydrate counting, alerts, and maintenance. The human factors involved with interfacing with a closed-loop system and allowing the system to take control of diabetes management are significant. It is important to find a balance between enthusiasm and realistic expectations and experiences with the closed-loop system.

A Real-Time Continuous Glucose Monitoring-Based Algorithm to Trigger Hypotreatments to Prevent/Mitigate Hypoglycemic Events

Background: The standard treatment for hypoglycemia recommended by the American Diabetes Association (ADA) suggests patients with diabetes to take small amounts of carbohydrates, the so-called hypotreatments (HTs), as soon as blood glucose concentration goes below 70 mg/dL. However, prevention, or at least mitigation, of hypoglycemic events could be achieved by triggering HTs ahead of time thanks to the use of the predictive capabilities of suitable real-time algorithms fed by continuous glucose monitoring (CGM) sensor data. Materials and Methods: The algorithm proposed in this article to trigger HTs for preventing forthcoming hypoglycemic events is based on the computation of the "dynamic risk", there is a nonlinear function combining current glycemia with its rate-of-change, both provided by CGM. A comparison of performance of the proposed algorithm against the ADA guidelines is made, in silico, on datasets of 100 virtual patients undergoing a single-meal experiment, with induced postmeal hypoglycemia, generated by the UVA/Padova type 1 diabetes simulator. Results: On noise-free CGM data, the proposed algorithm reduces the time spent in hypoglycemia, on median [25th-75th percentiles] from 36 [29-43] to 0 [0-11] min (P < 0.0001), with a concomitant decrease of the post-treatment rebound (PTR) in glucose concentration, on median [25th-75th percentiles] from 136 [121-148] to 121 [116-127] mg/dL (P < 0.0001). On noisy CGM data, there is still a reduction of both time spent in hypoglycemia from 41 [28-49] min to 25 [0-41] min (P < 0.0001) and PTR from 174 [146-189] mg/dL to 137 [123-151] mg/dL (P < 0.0001). Conclusions: The potentiality of the new algorithm in generating preventive HTs, which can allow significant reduction of hypoglycemia without concomitant increase of hyperglycemia, suggests its further development and test in silico, for example, simulating both insulin pump and multiple-daily-injection therapies.

Feasibility Studies of an Insulin-Only Bionic Pancreas in a Home-Use Setting

BACKGROUND

We tested the safety and performance of the "insulin-only" configuration of the bionic pancreas (BP) closed-loop blood-glucose control system in a home-use setting to assess glycemic outcomes using different static and dynamic glucose set-points.

METHOD

This is an open-label non-randomized study with three consecutive intervention periods. Participants had consecutive weeks of usual care followed by the insulin-only BP with (1) an individualized static set-point of 115 or 130 mg/dL and (2) a dynamic set-point that automatically varied within 110 to 130 mg/dL, depending on hypoglycemic risk. Human factors (HF) testing was conducted using validated surveys. The last five days of each study arm were used for data analysis.

RESULTS

Thirteen participants were enrolled with a mean age of 28 years, mean A1c of 7.2%, and mean daily insulin dose of 0.6 U/kg (0.4-1.0 U/kg). The usual care arm had an average glucose of 145 ± 20 mg/dL, which increased in the static set-point arm (159 ± 8 mg/dL, P = .004) but not in the dynamic set-point arm (154 ± 10 mg/dL, P = ns). There was no significant difference in time spent in range (70-180 mg/dL) among the three study arms. There was less time <70 mg/dL with both the static (1.8% ± 1.4%, P = .009) and dynamic set-point (2.7±1.5, P = .051) arms compared to the usual-care arm (5.5% ± 4.2%). HF testing demonstrated preliminary user satisfaction and no increased risk of diabetes burden or distress.

CONCLUSIONS

The insulin-only configuration of the BP using either static or dynamic set-points and initialized only with body weight performed similarly to other published insulin-only systems.

Closed loop control in adolescents and children during winter sports: Use of the Tandem Control-IQ AP system

OBJECTIVE

Artificial pancreas (AP) systems have been shown to improve glycemic control throughout the day and night in adults, adolescents, and children. However, AP testing remains limited during intense and prolonged exercise in adolescents and children. We present the performance of the Tandem Control-IQ AP system in adolescents and children during a winter ski camp study, where high altitude, low temperature, prolonged intense activity, and stress challenged glycemic control.

METHODS

In a randomized controlled trial, 24 adolescents (ages 13-18 years) and 24 school-aged children (6-12 years) with Type 1 diabetes (T1D) participated in a 48 hours ski camp (∼5 hours skiing/day) at three sites: Wintergreen, VA; Kirkwood, and Breckenridge, CO. Study participants were randomized 1:1 at each site. The control group used remote monitored sensor-augmented pump (RM-SAP), and the experimental group used the t: slim X2 with Control-IQ Technology AP system. All subjects were remotely monitored 24 hours per day by study staff.

RESULTS

The Control-IQ system improved percent time within range (70-180 mg/dL) over the entire camp duration: 66.4 ± 16.4 vs 53.9 ± 24.8%; P = .01 in both children and adolescents. The AP system was associated with a significantly lower average glucose based on continuous glucose monitor data: 161 ± 29.9 vs 176.8 ± 36.5 mg/dL; P = .023. There were no differences between groups for hypoglycemia exposure or carbohydrate interventions. There were no adverse events.

CONCLUSIONS

The use of the Control-IQ AP improved glycemic control and safely reduced exposure to hyperglycemia relative to RM-SAP in pediatric patients with T1D during prolonged intensive winter sport activities.

Diabetes Technology: Monitoring, Analytics, and Optimal Control

Over the past 50 years, the diabetes technology field progressed remarkably through self-monitoring of blood glucose (SMBG), continuous subcutaneous insulin infusion (CSII), risk and variability analysis, mathematical models and computer simulation of the human metabolic system, real-time continuous glucose monitoring (CGM), and control algorithms driving closed-loop control systems known as the "artificial pancreas" (AP). This review follows these developments, beginning with an overview of the functioning of the human metabolic system in health and in diabetes and of its detailed quantitative network modeling. The review continues with a brief account of the first AP studies that used intravenous glucose monitoring and insulin infusion, and with notes about CSII and CGM-the technologies that made possible the development of contemporary AP systems. In conclusion, engineering lessons learned from AP research, and the clinical need for AP systems to prove their safety and efficacy in large-scale clinical trials, are outlined.

Estimating Dynamic Treatment Regimes in Mobile Health Using V-learning

The vision for precision medicine is to use individual patient characteristics to inform a personalized treatment plan that leads to the best possible health-care for each patient. Mobile technologies have an important role to play in this vision as they offer a means to monitor a patient's health status in real-time and subsequently to deliver interventions if, when, and in the dose that they are needed. Dynamic treatment regimes formalize individualized treatment plans as sequences of decision rules, one per stage of clinical intervention, that map current patient information to a recommended treatment. However, most existing methods for estimating optimal dynamic treatment regimes are designed for a small number of fixed decision points occurring on a coarse time-scale. We propose a new reinforcement learning method for estimating an optimal treatment regime that is applicable to data collected using mobile technologies in an out-patient setting. The proposed method accommodates an indefinite time horizon and minute-by-minute decision making that are common in mobile health applications. We show that the proposed estimators are consistent and asymptotically normal under mild conditions. The proposed methods are applied to estimate an optimal dynamic treatment regime for controlling blood glucose levels in patients with type 1 diabetes.

Successful At-Home Use of the Tandem Control-IQ Artificial Pancreas System in Young Children During a Randomized Controlled Trial

OBJECTIVE

Hybrid closed-loop (HCL) artificial pancreas (AP) systems are now moving from research settings to widespread clinical use. In this study, the inControl algorithm developed by TypeZero Technologies was embedded to a commercial Tandem t:slim X2 insulin pump, now called Control-IQ, paired with a Dexcom G6 continuous glucose monitor and tested for superiority against sensor augmented pump (SAP) therapy. Both groups were physician-monitored throughout the clinical trial.

RESEARCH DESIGN AND METHODS

In a randomized controlled trial, 24 school-aged children (6-12 years) with type 1 diabetes (T1D) participated in a 3-day home-use trial at two sites: Stanford University and the Barbara Davis Center (50% girls, 9.6 ± 1.9 years of age, 4.5 ± 1.9 years of T1D, baseline hemoglobin A1c 7.35% ± 0.68%). Study subjects were randomized 1:1 at each site to either HCL AP therapy with the Control-IQ system or SAP therapy with remote monitoring.

RESULTS

The primary outcome, time in target range 70-180 mg/dL, using Control-IQ significantly improved (71.0% ± 6.6% vs. 52.8% ± 13.5%; P = 0.001) and mean sensor glucose (153.6 ± 13.5 vs. 180.2 ± 23.1 mg/dL; P = 0.003) without increasing hypoglycemia time <70 mg/dL (1.7% [1.3%-2.1%] vs. 0.9% [0.3%-2.7%]; not significant). The HCL system was active for 94.4% of the study period. Subjects reported that use of the system was associated with less time thinking about diabetes, decreased worry about blood sugars, and decreased burden in managing diabetes.

CONCLUSIONS

The use of the Tandem t:slim X2 with Control-IQ HCL AP system significantly improved time in range and mean glycemic control without increasing hypoglycemia in school-aged children with T1D during remote monitored home use.

The International Diabetes Closed-Loop Study: Testing Artificial Pancreas Component Interoperability

BACKGROUND

Use of artificial pancreas (AP) requires seamless interaction of device components, such as continuous glucose monitor (CGM), insulin pump, and control algorithm. Mobile AP configurations also include a smartphone as computational hub and gateway to cloud applications (e.g., remote monitoring and data review and analysis). This International Diabetes Closed-Loop study was designed to demonstrate and evaluate the operation of the inControl AP using different CGMs and pump modalities without changes to the user interface, user experience, and underlying controller.

METHODS

Forty-three patients with type 1 diabetes (T1D) were enrolled at 10 clinical centers (7 United States, 3 Europe) and 41 were included in the analyses (39% female, >95% non-Hispanic white, median T1D duration 16 years, median HbA1c 7.4%). Two CGMs and two insulin pumps were tested by different study participants/sites using the same system hub (a smartphone) during 2 weeks of in-home use.

RESULTS

The major difference between the system components was the stability of their wireless connections with the smartphone. The two sensors achieved similar rates of connectivity as measured by percentage time in closed loop (75% and 75%); however, the two pumps had markedly different closed-loop adherence (66% vs. 87%). When connected, all system configurations achieved similar glycemic outcomes on AP control (73% [mean] time in range: 70-180 mg/dL, and 1.7% [median] time <70 mg/dL).

CONCLUSIONS

CGMs and insulin pumps can be interchangeable in the same Mobile AP system, as long as these devices achieve certain levels of reliability and wireless connection stability.

Effectiveness of artificial pancreas in the non-adult population: A systematic review and network meta-analysis

OBJECTIVE

Artificial pancreas is a technology that minimizes user input by bridging continuous glucose monitoring and insulin pump treatment, and has proven safety in the adult population. The purpose of this systematic review and meta-analysis is to evaluate the efficacy of closed-loop (CL) systems in the glycemic control of non-adult type 1 diabetes patients in both a pairwise and network meta-analysis (NMA) context and investigate various parameters potentially affecting the outcome.

METHODS

Literature was systematically searched using the MEDLINE (1966-2018), Scopus (2004-2018), Cochrane Central Register of Controlled Trials (CENTRAL) (1999-2018), Clinicaltrials.gov (2008-2018) and Google Scholar (2004-2018) databases. Studies comparing the glycemic control in CL (either single- or dual-hormone) with continuous subcutaneous insulin infusion (CSII) in people with diabetes (PWD) aged <18 years old were deemed eligible. The primary outcome analysis was conducted with regard to time spent in the target glycemic range. All outcomes were evaluated in NMA in order to investigate potential between-algorithm differences. Pairwise meta-analysis and meta-regression were performed using the RevMan 5.3 and Open Meta-Analyst software. For NMA, the package pcnetmetain R 3.5.1 was used.

RESULTS

The meta-analysis was based on 25 studies with a total of 504 PWD. The CL group was associated with significantly higher percentage of time spent in the target glycemic range (Mean (SD): 67.59% (SD: 8.07%) in the target range and OL PWD spending 55.77% (SD: 11.73%), MD: -11.97%, 95% CI [-18.40, -5.54%]) and with lower percentages of time in hyperglycemia (MD: 3.01%, 95% CI [1.68, 4.34%]) and hypoglycemia (MD: 0.67%, 95% CI [0.21, 1.13%]. Mean glucose was also decreased in the CL group (MD: 0.75 mmol/L, 95% CI [0.18-1.33]). The NMA arm of the study showed that the bihormonal modality was superior to other algorithms and standard treatment in lowering mean glucose and increasing time spent in the target range. The DiAs platform was superior to PID in controlling hypoglycemia and mean glucose. Time in target range and mean glucose were unaffected by the confounding factors tested.

CONCLUSIONS

The findings of this meta-analysis suggest that artificial pancreas systems are superior to the standard sensor-augmented pump treatment of type 1 diabetes mellitus in non-adult PWD. Between-algorithm differences are also addressed, implying a superiority of the bihormonal treatment modality. Future large-scale studies are needed in the field to verify these outcomes and to determine the optimal algorithm to be used in the clinical setting.

Automated closed-loop control of diabetes: the artificial pancreas

The incidence of Diabetes Mellitus is on the rise worldwide, which exerts enormous health toll on the population and enormous pressure on the healthcare systems. Now, almost hundred years after the discovery of insulin in 1921, the optimization problem of diabetes is well formulated as maintenance of strict glycemic control without increasing the risk for hypoglycemia. External insulin administration is mandatory for people with type 1 diabetes; various medications, as well as basal and prandial insulin, are included in the daily treatment of type 2 diabetes. This review follows the development of the Diabetes Technology field which, since the 1970s, progressed remarkably through continuous subcutaneous insulin infusion (CSII), mathematical models and computer simulation of the human metabolic system, real-time continuous glucose monitoring (CGM), and control algorithms driving closed-loop control systems known as the "artificial pancreas" (AP). All of these developments included significant engineering advances and substantial bioelectronics progress in the sensing of blood glucose levels, insulin delivery, and control design. The key technologies that enabled contemporary AP systems are CSII and CGM, both of which became available and sufficiently portable in the beginning of this century. This powered the quest for wearable home-use AP, which is now under way with prototypes tested in outpatient studies during the past 6 years. Pivotal trials of new AP technologies are ongoing, and the first hybrid closed-loop system has been approved by the FDA for clinical use. Thus, the closed-loop AP is well on its way to become the digital-age treatment of diabetes.

Closing the Loop on Managing Youth With Type 1 Diabetes: Children Are Not Just Small Adults

As hybrid closed-loop (HCL) insulin delivery systems permeate clinical practice, it is critical to ensure all with diabetes are afforded the opportunity to benefit from this technology. Indeed, due to the suboptimal control achieved by the vast majority of youth with type 1 diabetes (T1D), pediatric patients are positioned to see the greatest benefit from automated insulin delivery systems. To ensure these systems are well poised to deliver the promise of more targeted control, it is essential to understand the unique characteristics and factors of childhood. Herein, the developmental and physiological needs of youth with T1D are reviewed and consideration is given to how HCL could address these issues. Studies of HCL technologies in youth are briefly reviewed. As future-generation closed-loop systems are being devised, features that could make this technology more attractive to youth and to their families are discussed. Integration of HCL has the potential to minimize the burden of this chronic medical condition while improving glycemic control and ultimately allowing our pediatric patients to fulfill the primary goal of childhood, to be a kid.

Efficacy and safety of the artificial pancreas in the paediatric population with type 1 diabetes

BACKGROUND

Type 1 diabetes (DM1) is one of the most common chronic diseases in childhood and requires life-long insulin therapy and continuous health care support. An artificial pancreas (AP) or closed-loop system (CLS) have been developed with the aim of improving metabolic control without increasing the risk of hypoglycaemia in patients with DM1. As the impact of APs have been studied mainly in adults, the aim of this review is to evaluate the efficacy and safety of the AP in the paediatric population with DM1.

MAIN BODY

The real advantage of a CLS compared to last-generation sensor-augmented pumps is the gradual modulation of basal insulin infusion in response to glycaemic variations (towards both hyperglycaemia and hypoglycaemia), which has the aim of improving the proportion of time spent in the target glucose range and reducing the mean glucose level without increasing the risk of hypoglycaemia. Some recent studies demonstrated that also in children and adolescents an AP is able to reduce the frequency of hypoglycaemic events, an important limiting factor in reaching good metabolic control, particularly overnight. However, the advantages of the AP in reducing hyperglycaemia, increasing the time spent in the target glycaemic range and thus reducing glycated haemoglobin are less clear and require more clinical trials in the paediatric population, in particular in younger children.

CONCLUSIONS

Although the first results from bi-hormonal CLS are promising, long-term, head-to-head studies will have to prove their superiority over insulin-only approaches. More technological progress, the availability of more fast-acting insulin, further developments of algorithms that could improve glycaemic control after meals and physical activity are the most important challenges in reaching an optimal metabolic control with the use of the AP in children and adolescents.

The Hybrid Closed-Loop System: Evolution and Practical Applications

Achievement of well-controlled blood glucose is essential for preventing complications in patients with type 1 diabetes. Since the inception of continuous subcutaneous insulin infusion, the aim has been to develop an artificial pancreas, with the ability to use an automated algorithm to deliver one or more hormones in response to blood glucose with the intent to keep blood sugar as close to a prespecified target as possible. Development and rapid improvement of continuous glucose sensor technology has recently allowed swift progress toward a fully closed-loop insulin delivery system. In 2017, Medtronic began marketing the 670G insulin pump with Guardian 3 sensor. When in auto mode, this is a hybrid closed-loop insulin delivery system that automatically adjusts basal insulin delivery every 5 min based on sensor glucose to maintain blood glucose levels as close to a specific target as possible. Patients receive prandial insulin by entering carbohydrate amount into the bolus calculator. Early studies show improvement in HbA1c in both adults and adolescents with this technology. Initial safety trials showed no occurrence of diabetic ketoacidosis or hypoglycemia. The utility of this device is limited by blood glucose targets of 120 and 150 mg/dL that are unacceptably high for some patients. Notwithstanding recent advances, we are far from a system that is able to replicate islet function in the form of a fully automated, multihormonal blood glucose control device.

Predictive hyperglycemia and hypoglycemia minimization: In-home double-blind randomized controlled evaluation in children and young adolescents

OBJECTIVE

The primary objective of this trial was to evaluate the feasibility, safety, and efficacy of a predictive hyperglycemia and hypoglycemia minimization (PHHM) system vs predictive low glucose suspension (PLGS) alone in optimizing overnight glucose control in children 6 to 14 years old.

RESEARCH DESIGN AND METHODS

Twenty-eight participants 6 to 14 years old with T1D duration ≥1 year with daily insulin therapy ≥12 months and on insulin pump therapy for ≥6 months were randomized per night into PHHM mode or PLGS-only mode for 42 nights. The primary outcome was percentage of time in sensor-measured range 70 to 180 mg/dL in the overnight period.

RESULTS

The addition of automated insulin delivery with PHHM increased time in target range (70-180 mg/dL) from 66 ± 11% during PLGS nights to 76 ± 9% during PHHM nights (P<.001), without increasing hypoglycemia as measured by time below various thresholds. Average morning blood glucose improved from 176 ± 28 mg/dL following PLGS nights to 154 ± 19 mg/dL following PHHM nights (P<.001).

CONCLUSIONS

The PHHM system was effective in optimizing overnight glycemic control, significantly increasing time in range, lowering mean glucose, and decreasing glycemic variability compared to PLGS alone in children 6 to 14 years old.

Artificial pancreas treatment for outpatients with type 1 diabetes: systematic review and meta-analysis

OBJECTIVE

To evaluate the efficacy and safety of artificial pancreas treatment in non-pregnant outpatients with type 1 diabetes.

DESIGN

Systematic review and meta-analysis of randomised controlled trials.

DATA SOURCES

Medline, Embase, Cochrane Library, and grey literature up to 2 February 2018.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

Randomised controlled trials in non-pregnant outpatients with type 1 diabetes that compared the use of any artificial pancreas system with any type of insulin based treatment. Primary outcome was proportion (%) of time that sensor glucose level was within the near normoglycaemic range (3.9-10 mmol/L). Secondary outcomes included proportion (%) of time that sensor glucose level was above 10 mmol/L or below 3.9 mmol/L, low blood glucose index overnight, mean sensor glucose level, total daily insulin needs, and glycated haemoglobin. The Cochrane Collaboration risk of bias tool was used to assess study quality.

RESULTS

40 studies (1027 participants with data for 44 comparisons) were included in the meta-analysis. 35 comparisons assessed a single hormone artificial pancreas system, whereas nine comparisons assessed a dual hormone system. Only nine studies were at low risk of bias. Proportion of time in the near normoglycaemic range (3.9-10.0 mmol/L) was significantly higher with artificial pancreas use, both overnight (weighted mean difference 15.15%, 95% confidence interval 12.21% to 18.09%) and over a 24 hour period (9.62%, 7.54% to 11.7%). Artificial pancreas systems had a favourable effect on the proportion of time with sensor glucose level above 10 mmol/L (-8.52%, -11.14% to -5.9%) or below 3.9 mmol/L (-1.49%, -1.86% to -1.11%) over 24 hours, compared with control treatment. Robustness of findings for the primary outcome was verified in sensitivity analyses, by including only trials at low risk of bias (11.64%, 9.1% to 14.18%) or trials under unsupervised, normal living conditions (10.42%, 8.63% to 12.2%). Results were consistent in a subgroup analysis both for single hormone and dual hormone artificial pancreas systems.

CONCLUSIONS

Artificial pancreas systems are an efficacious and safe approach for treating outpatients with type 1 diabetes. The main limitations of current research evidence on artificial pancreas systems are related to inconsistency in outcome reporting, small sample size, and short follow-up duration of individual trials.

Motivational profiles, accelerometer-derived physical activity, and acute diabetes-related symptoms in adults with type 2 diabetes

Background

Using self-determination theory, the objective of this study was to examine, over a one-month period, how physical activity (PA) motivation would influence accelerometer-derived PA behavior, and ultimately, acute diabetes-related symptoms burden among adults with type 2 diabetes (T2D adults). Using both a person and variable-centered approach, this objective was attained by means of: 1) investigating the indirect effect of PA participation on the relationship between PA motivation and acute diabetes-related symptom burden and 2) examining whether participants who met PA recommendations (i.e., 150 min of moderate-to-vigorous PA per week) would experience less acute diabetes-related symptom burden over a one-month period.

Methods

A two-wave prospective longitudinal design was used. At time 1, participants completed a questionnaire assessing their PA motivation and were asked to wear an ActiGraph GT3x accelerometer for four consecutive weeks. At time 2, they completed a short questionnaire assessing their acute diabetes-related symptoms (i.e., symptoms related to fatigue, cognitive distress, hyperglycemia, and hypoglycemia). The final sample includes 165 adults (89 or 53.61% women) aged from 26 to 75 years (M = 62.05, SD = 8.75) with T2D, which provided at least 21 valid days of accelerometer-derived data.

Results

First, results of a path analysis demonstrated that over a one-month period, the average number of minutes spent practicing moderate to vigorous PA per week mediated the relationship between intrinsic and external PA motivation and the level of burden associated with the following diabetes-related symptoms: fatigue, cognitive distress, and hyperglycemia. In addition, results of covariance analyses showed that participants meeting PA recommendations also reported significantly less burden associated with these three symptoms over a month period. Then, the existence of four motivational profiles (Self-Determined, High Introjected, Low Motivation, and Non-Self-Determined) was confirmed using a k-means analysis. Results of covariance and chi-square analyses further showed, respectively, that compared to other motivational profiles, the Self-Determined profile was associated with a higher score on weekly PA participation and meeting PA recommendations.

Conclusions

The results highlight the importance of promoting autonomous motives for PA participation among T2D adults. They also suggest that T2D adults meeting PA recommendations experience less acute diabetes-related symptoms burden, which further support the importance of their PA motivation.

Safety and Feasibility of the OmniPod Hybrid Closed-Loop System in Adult, Adolescent, and Pediatric Patients with Type 1 Diabetes Using a Personalized Model Predictive Control Algorithm

BACKGROUND

The safety and feasibility of the OmniPod personalized model predictive control (MPC) algorithm in adult, adolescent, and pediatric patients with type 1 diabetes were investigated.

METHODS

This multicenter, observational trial included a 1-week outpatient sensor-augmented pump open-loop phase and a 36-h inpatient hybrid closed-loop (HCL) phase with announced meals ranging from 30 to 90 g of carbohydrates and limited physical activity. Patients aged 6-65 years with HbA1c between 6.0% and 10.0% were eligible. The investigational system included a modified version of OmniPod, the Dexcom G4 505 Share^® AP System, and the personalized MPC algorithm running on a tablet computer. Primary endpoints included sensor glucose percentage of time in hypoglycemia <70 mg/dL and hyperglycemia >250 mg/dL. Additional glycemic targets were assessed.

RESULTS

The percentage of time <70 mg/dL during the 36-h HCL phase was mean (standard deviation): 0.7 (1.7) in adults receiving 80% meal bolus (n = 24), and 0.7 (1.2) in adults (n = 10), 2.0 (2.4) in adolescents (n = 12), and 2.0 (2.6) in pediatrics (n = 12) receiving 100% meal bolus. The overall hypoglycemia rate was 0.49 events/24 h. The percentage of time >250 mg/dL was 8.0 (7.5), 3.6 (3.7), 4.9 (6.3), and 6.7 (5.6) in the study groups, respectively. Percentage of time in the target range of 70-180 mg/dL was 69.5 (14.4), 73.0 (15.0), 72.6 (15.5), and 70.1 (12.3), respectively.

CONCLUSIONS

The OmniPod personalized MPC algorithm performed well and was safe during day and night use in adult, adolescent, and pediatric patients with type 1 diabetes. Longer term studies will assess the safety and performance of the algorithm under free living conditions with extended use.

Closed-Loop Control During Intense Prolonged Outdoor Exercise in Adolescents With Type 1 Diabetes: The Artificial Pancreas Ski Study

OBJECTIVE

Intense exercise is a major challenge to the management of type 1 diabetes (T1D). Closed-loop control (CLC) systems (artificial pancreas) improve glycemic control during limited intensity and short duration of physical activity (PA). However, CLC has not been tested during extended vigorous outdoor exercise common among adolescents.

RESEARCH DESIGN AND METHODS

Skiing presents unique metabolic challenges: intense prolonged PA, cold, altitude, and stress/fear/excitement. In a randomized controlled trial, 32 adolescents with T1D (ages 10-16 years) participated in a 5-day ski camp (∼5 h skiing/day) at two sites: Wintergreen, VA, and Breckenridge, CO. Participants were randomized to the University of Virginia CLC system or remotely monitored sensor-augmented pump (RM-SAP). The CLC and RM-SAP groups were coarsely paired by age and hemoglobin A_1c (HbA_1c). All subjects were remotely monitored 24 h per day by the study physicians and clinical team.

RESULTS

Compared with physician-monitored open loop, percent time in range (70-180 mg/dL) improved using CLC: 71.3 vs. 64.7% (+6.6% [95% CI 1-12]; P = 0.005), with maximum effect late at night. Hypoglycemia exposure and carbohydrate treatments were improved overall (P = 0.001 and P = 0.007) and during the daytime with strong ski level effects (P = 0.0001 and P = 0.006); ski/snowboard proficiency was balanced between groups but with a very strong site effect: naive in Virginia and experienced in Colorado. There was no adverse event associated with CLC; the participants' feedback was overwhelmingly positive.

CONCLUSIONS

CLC in adolescents with T1D improved glycemic control and reduced exposure to hypoglycemia during prolonged intensive winter sport activities, despite the added challenges of cold and altitude.

Heart rate informed artificial pancreas system enhances glycemic control during exercise in adolescents with T1D

OBJECTIVE

To evaluate the safety and performance of using a heart rate (HR) monitor to inform an artificial pancreas (AP) system during exercise among adolescents with type 1 diabetes (T1D).

MATERIALS AND METHODS

In a randomized, cross-over trial, adolescents with T1D age 13 - 18 years were enrolled to receive on separate days either the unmodified UVa AP (stdAP) or an AP system connected to a portable HR monitor (AP-HR) that triggered an exercise algorithm for blood glucose (BG) control. During admissions participants underwent a structured exercise regimen. Hypoglycemic events and CGM tracings were compared between the two admissions, during exercise and for the full 24-hour period.

RESULTS

Eighteen participants completed the trial. While number of hypoglycemic events during exercise and rest was not different between visits (0.39 AP-HR vs 0.50 stdAP), time below 70 mg dL ^-1 was lower on AP-HR compared to stdAP, 0.5±2.1% vs 7.4±12.5% (P = 0.028). Time with BG within 70-180 mg dL ^-1 was higher for the AP-HR admission vs stdAP during the exercise portion and overall (96% vs 87%, and 77% vs 74%), but these did not reach statistical significance (P = 0.075 and P = 0.366).

CONCLUSIONS

Heart rate signals can safely and efficaciously be integrated in a wireless AP system to inform of physical activity. While exercise contributes to hypoglycemia among adolescents, even when using an AP system, informing the system of exercise via a HR monitor improved time <70 mg dL ^-1 . Nonetheless, it did not significantly reduce the total number of hypoglycemic events, which were low in both groups.

Point-of-Care Endocrine Diagnostics

Endocrinology relies on hormone and metabolite measurement for public health screening, diagnostics, and disease management. Advances in microfluidics, immunoassay technology, electronics, and software are moving in vitro endocrine diagnostics from the laboratory to the point of care. Point-of-care endocrine diagnostics provide results clinically equivalent to those produced by expensive laboratory instrumentation for a fraction of the cost and with a substantially more rapid turnaround time. Similar to the transformation of mainframe computers into laptops, tablets, and smartphones, clinical laboratories are evolving into point-of-care technologies.

Insulin delivery and nocturnal glucose control in children and adolescents with type 1 diabetes

Introduction: Nocturnal glucose control remains challenging in children and adolescents with type 1 diabetes due to highly variable overnight insulin requirements. The issue may be addressed by glucose responsive insulin delivery based on real-time continuous glucose measurements.

Areas covered: This review outlines recent developments of glucose responsive insulin delivery systems from a paediatric perspective. We cover threshold-based suspend application, predictive low glucose suspend, and more advanced single hormone and dual-hormone closed-loop systems. Approaches are evaluated in relation to nocturnal glucose control particularly during outpatient randomised controlled trials.

Expert opinion: Significant progress translating research from controlled clinical centre settings to free-living unsupervised home studies have been achieved over the past decade. Nocturnal glycaemic control can be improved whilst reducing the risk of hypoglycaemia with closed-loop systems. Following the US regulatory approval of the first hybrid closed-loop system in non-paediatric population, large multinational closed-loop clinical trials and pivotal studies including paediatric populations are underway or in preparation to facilitate the use of closed-loop systems in clinical practice.

Effect of artificial pancreas systems on glycaemic control in patients with type 1 diabetes: a systematic review and meta-analysis of outpatient randomised controlled trials

BACKGROUND

Closed-loop artificial pancreas systems have been in development for several years, including assessment in numerous varied outpatient clinical trials. We aimed to summarise the efficacy and safety of artificial pancreas systems in outpatient settings and explore the clinical and technical factors that can affect their performance.

METHODS

We did a systematic review and meta-analysis of randomised controlled trials comparing artificial pancreas systems (insulin only or insulin plus glucagon) with conventional pump therapy (continuous subcutaneous insulin infusion [CSII] with blinded continuous glucose monitoring [CGM] or unblinded sensor-augmented pump [SAP] therapy) in adults and children with type 1 diabetes. We searched Medline, Embase, and the Cochrane Central Register of Controlled Trials for studies published from 1946, to Jan 1, 2017. We excluded studies not published in English, those involving pregnant women or participants who were in hospital, and those testing adjunct medications other than glucagon. The primary outcome was the mean difference in percentage of time blood glucose concentration remained in target range (3·9-10 mmol/L or 3·9-8 mmol/L, depending on the study), assessed by random-effects meta-analysis. This study is registered with PROSPERO, number 2015:CRD42015026854.

FINDINGS

We identified 984 reports; after exclusions, 27 comparisons from 24 studies (23 crossover and one parallel design) including a total of 585 participants (219 in adult studies, 265 in paediatric studies, and 101 in combined studies) were eligible for analysis. Five comparisons assessed dual-hormone (insulin and glucagon), two comparisons assessed both dual-hormone and single-hormone (insulin only), and 20 comparisons assessed single-hormone artificial pancreas systems. Time in target was 12·59% higher with artificial pancreas systems (95% CI 9·02-16·16; p<0·0001), from a weighted mean of 58·21% for conventional pump therapy (I²=84%). Dual-hormone artificial pancreas systems were associated with a greater improvement in time in target range compared with single-hormone systems (19·52% [95% CI 15·12-23·91] vs 11·06% [6·94 to 15·18]; p=0·006), although six of seven comparisons compared dual-hormone systems to CSII with blinded CGM, whereas 21 of 22 single-hormone comparisons had SAP as the comparator. Single-hormone studies had higher heterogeneity than dual-hormone studies (I² 79% vs 66%). Bias assessment characteristics were incompletely reported in 12 of 24 studies, no studies masked participants to the intervention assignment, and masking of outcome assessment was not done in 12 studies and was unclear in 12 studies.

INTERPRETATION

Artificial pancreas systems uniformly improved glucose control in outpatient settings, despite heterogeneous clinical and technical factors.

FUNDING

None.

A review of personalized blood glucose prediction strategies for T1DM patients

This paper presents a methodological review of models for predicting blood glucose (BG) concentration, risks and BG events. The surveyed models are classified into three categories, and they are presented in summary tables containing the most relevant data regarding the experimental setup for fitting and testing each model as well as the input signals and the performance metrics. Each category exhibits trends that are presented and discussed. This document aims to be a compact guide to determine the modeling options that are currently being exploited for personalized BG prediction.

Outpatient 60-hour day-and-night glucose control with dual-hormone artificial pancreas, single-hormone artificial pancreas, or sensor-augmented pump therapy in adults with type 1 diabetes: An open-label, randomised, crossover, controlled trial

AIMS

To assess whether the dual-hormone (insulin and glucagon) artificial pancreas reduces hypoglycaemia compared to the single-hormone (insulin alone) artificial pancreas in outpatient settings during the day and night.

MATERIAL AND METHODS

In a randomized, three-way, crossover trial we compared the dual-hormone artificial pancreas, the single-hormone artificial pancreas and sensor-augmented pump therapy (control) in 23 adults with type 1 diabetes. Each intervention was applied from 8 AM Day 1 to 8 PM Day 3 (60 hours) in outpatient free-living conditions. The primary outcome was time spent with sensor glucose levels below 4.0 mmol/L. A P value of less than .017 was regarded as significant.

RESULTS

The median difference between the dual-hormone system and the single-hormone system was -2.3% (P = .072) for time spent below 4.0 mmol/L, -1.3% (P = .017) for time below 3.5 mmol/L, and -0.7% (P = .031) for time below 3.3 mmol/L. Both systems reduced (P < .017) hypoglycaemia below 4.0, 3.5 and 3.3 mmol/L compared to control therapy, but reductions were larger with the dual-hormone system than with the single-hormone system (medians -4.0% vs -3.4% for 4.0 mmol/L; -2.7% vs -2.2% for 3.5 mmol/L; and -2.2% vs -1.2% for 3.3 mmol/L). There were 34 hypoglycaemic events (<3.0 mmol/L for 20 minutes) with control therapy, 14 with the single-hormone system and 6 with the dual-hormone system. These differences in hypoglycaemia were observed while mean glucose level was low and comparable in all interventions (P = NS).

CONCLUSIONS

The dual-hormone artificial pancreas had the lowest risk of hypoglycaemia, but the differences were not statistically significant. Larger studies are needed.

Performance of an Artificial Pancreas System for Young Children with Type 1 Diabetes

BACKGROUND

Young children 5-8 years old with type 1 diabetes (T1D) exhibit clear needs for improved glycemic control but may be limited in their ability to safely interact with an artificial pancreas system. Our goal was to evaluate the safety and performance of an artificial pancreas (AP) system among young children with T1D.

RESEARCH DESIGN AND METHODS

In a randomized, crossover trial, children with T1D age 5-8 years were enrolled to receive on separate study periods (in random order) either the UVa AP using the DiAs Control Platform software with child-resistant lock-out screens (followed as an out-patient admission) or their usual insulin pump+continuous glucose monitor (CGM) care at home. Hypoglycemic events and CGM tracings were compared between the two 68-h study periods. All analyses were adjusted for level of physical activity as tracked using Fitbit devices.

RESULTS

Twelve participants (median age 7 years, n = 6 males) completed the trial. Compared to home care, the AP admission resulted in increased time with blood glucose (BG) 70-180 mg/dL (73% vs. 47%) and lower mean BG (152 mg/dL vs. 190 mg/dL), both P < 0.001 after adjustment for activity. Occurrence of hypoglycemia was similar between sessions without differences in time <70 mg/dL (AP 1.1% ± 1.1%; home 1.6% ± 1.2%). There were no adverse events during the AP or home study periods.

CONCLUSIONS

Use of an AP in young children was safe and resulted in improved mean BG without increased hypoglycemia. This suggests that AP use in young children is safe and improves overall diabetes control. ClinicalTrials.gov registration number: NCT02750267.

MD-Logic overnight type 1 diabetes control in home settings: A multicentre, multinational, single blind randomized trial

AIMS

To evaluate the safety, efficacy and need for remote monitoring of the MD-Logic closed-loop system during short-term overnight use at home.

METHODS

Seventy-five patients (38 male; aged 10-54 years; average A1c, 7.8% ± 0.7%, 61.8 ± 7.2 mmol/mol) were enrolled from 3 clinical sites. Patients were randomly assigned to participate in 2 overnight crossover periods, each including 4 consecutive nights, 1 under closed-loop control and 1 under sensor-augmented pump (SAP) therapy in the patient's home. Both study arms were supervised using a remote-monitoring system in a blinded manner. Primary endpoints were time spent with glucose levels below 70 mg/dL and percentage of nights in which mean overnight glucose levels were within 90 to 140 mg/dL.

RESULTS

The median [interquartile range] percentage of time spent in hypoglycaemia was significantly lower on nights when MD-Logic was used, compared to SAP therapy (2.07 [0, 4.78] and 2.6 [0, 10.34], respectively; P = .004) and the percentage of individual nights with a mean overnight glucose level in target was significantly greater (75 [42, 75] and 50 [25,75], respectively; P = .008). The time spent in target range was increased by a median of 28% (P = .001), with the same amount of insulin (10.69 [7.28, 13.94] and 10.41[6.9, 14.07], respectively; P = .087). The remote monitoring triggered calls for hypoglycaemia at twice the rate during SAP therapy compared to closed-loop control (62 and 29, respectively; P = .002).

CONCLUSIONS

The MD-Logic system demonstrated a safe and efficient profile during overnight use by children, adolescents and adults with type 1 diabetes and, therefore, provides an effective means of mitigating the risk of nocturnal hypoglycaemia.

Predictive Hyperglycemia and Hypoglycemia Minimization: In-Home Evaluation of Safety, Feasibility, and Efficacy in Overnight Glucose Control in Type 1 Diabetes

OBJECTIVE

The objective of this study was to determine the safety, feasibility, and efficacy of a predictive hyperglycemia and hypoglycemia minimization (PHHM) system compared with predictive low-glucose insulin suspension (PLGS) alone in overnight glucose control.

RESEARCH DESIGN AND METHODS

A 42-night trial was conducted in 30 individuals with type 1 diabetes in the age range 15-45 years. Participants were randomly assigned each night to either PHHM or PLGS and were blinded to the assignment. The system suspended the insulin pump on both the PHHM and PLGS nights for predicted hypoglycemia but delivered correction boluses for predicted hyperglycemia on PHHM nights only. The primary outcome was the percentage of time spent in a sensor glucose range of 70-180 mg/dL during the overnight period.

RESULTS

The addition of automated insulin delivery with PHHM increased the time spent in the target range (70-180 mg/dL) from 71 ± 10% during PLGS nights to 78 ± 10% during PHHM nights (P < 0.001). The average morning blood glucose concentration improved from 163 ± 23 mg/dL after PLGS nights to 142 ± 18 mg/dL after PHHM nights (P < 0.001). Various sensor-measured hypoglycemic outcomes were similar on PLGS and PHHM nights. All participants completed 42 nights with no episodes of severe hypoglycemia, diabetic ketoacidosis, or other study- or device-related adverse events.

CONCLUSIONS

The addition of a predictive hyperglycemia minimization component to our existing PLGS system was shown to be safe, feasible, and effective in overnight glucose control.

Closed-loop for type 1 diabetes - an introduction and appraisal for the generalist

BACKGROUND

Rapid progress over the past decade has been made with the development of the 'Artificial Pancreas', also known as the closed-loop system, which emulates the feedback glucose-responsive functionality of the pancreatic beta cell. The recent FDA approval of the first hybrid closed-loop system makes the Artificial Pancreas a realistic therapeutic option for people with type 1 diabetes. In anticipation of its advent into clinical care, we provide a primer and appraisal of this novel therapeutic approach in type 1 diabetes for healthcare professionals and non-specialists in the field.

DISCUSSION

Randomised clinical studies in outpatient and home settings have shown improved glycaemic outcomes, reduced risk of hypoglycaemia and positive user attitudes. User input and interaction with existing closed-loop systems, however, are still required. Therefore, management of user expectations, as well as training and support by healthcare providers are key to ensure optimal uptake, satisfaction and acceptance of the technology. An overview of closed-loop technology and its clinical implications are discussed, complemented by our extensive hands-on experience with closed-loop system use during free daily living.

CONCLUSIONS

The introduction of the artificial pancreas into clinical practice represents a milestone towards the goal of improving the care of people with type 1 diabetes. There remains a need to understand the impact of user interaction with the technology, and its implication on current diabetes management and care.