Safety of closed-loop therapy during reduction or omission of meal boluses in adolescents with type 1 diabetes: a randomized clinical trial

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

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

Hybrid Closed Loop Overcomes the Impact of Missed or Suboptimal Meal Boluses on Glucose Control in Children with Type 1 Diabetes Compared to Sensor-Augmented Pump Therapy

Background: It is unclear whether hybrid closed-loop (HCL) therapy attenuates the metabolic impact of missed or suboptimal meal insulin bolus compared with sensor-augmented pump (SAP) therapy in children with type 1 diabetes in free-living conditions. Methods: This is an ancillary study from a multicenter randomized controlled trial that compared 24/7 HCL with evening and night (E/N) HCL for 36 weeks in children between 6 and 12 years old. In the present study, the 60 children from the E/N arm underwent a SAP phase, an E/N HCL for 18 weeks, then a 24/7 phase for 18 weeks, extended for 36 more weeks. The last 28-30 days of each of the four phases were analyzed according to meal bolus management (cumulated 6817 days). The primary endpoint was the percentage of time that the sensor glucose was in the target range (TIR, 70-180 mg/dL) according to the number of missed boluses per day. Findings: TIR was 54% ± 10% with SAP, 63% ± 7% with E/N HCL, and steadily 67% ± 7% with 24/7 HCL. From the SAP phase to 72 weeks of HCL, the percentage of days with at least one missed meal bolus increased from 12% to 22%. Estimated marginal (EM) mean TIR when no bolus was missed was 54% (95% confidence intervals [CI] 53-56) in SAP and it was 13% higher (95% CI 11-15) in the 24/7 HCL phase. EM mean TIR with 1 and ≥2 missed boluses/day was 49.5% (95% CI 46-52) and 45% (95% CI 39-51) in SAP, and it was 15% (95% CI 14-16) and 17% higher (95% CI 6-28), respectively, in the 24/7 HCL phase (P < 0.05 for all comparisons vs. SAP). Interpretation: HCL persistently improves glycemic control compared with SAP, even in case of meal bolus omission. ClinicalTrials.gov (NCT03739099).

First Use of Open-Source Automated Insulin Delivery AndroidAPS in Full Closed-Loop Scenario; Pancreas4ALL Randomized Pilot Study

Objective: We evaluated the safety and feasibility of open-source automated insulin delivery AndroidAPS in adolescents and young adults with type 1 diabetes (T1D) and compared its efficacy in three different scenarios: hybrid closed loop (HCL) with meal boluses, meal announcement only (MA), and full closed loop (FCL). Research Design and Methods: In an open-label, prospective, randomized crossover trial (clinicaltrials.gov NCT04835350), 16 adolescents with T1D (10 females) with mean age of 17 years (range 15-20), glycated hemoglobin 56 mmol/mol (range 43-75), and mean duration of diabetes 5.9 years (9-15) underwent three distinct 3-day periods of camp living, comparing the above-mentioned scenarios of AndroidAPS. We used modified and locked version of AndroidAPS 3.1.03, which was called Pancreas4ALL for study purposes. The order of MA and FCL periods was assigned randomly. The primary endpoints were feasibility and safety of the system represented by percentage of time of glucose control by the system and time in hypoglycemia below 3 mmol/L. Results: The glycemia was controlled by the system 95% time of the study and the proportion of time below 3 mmol/L did not exceed 1% over the whole study period (0.72%). The HCL scenario reached significantly higher percentage of time below 3 mmol/L (HCL 1.05% vs. MA 0.0% vs. FCL 0.0%; P = 0.05) compared to other scenarios. No difference was observed among the scenarios in the percentage of time between 3.9 and 10 mmol/L (HCL 83.3% vs. MA 79.85% vs. FCL 81.03%, P = 0.58) corresponding to mean glycemia (HCL 6.65 mmol/L vs. MA 7.34 mmol/L vs. FCL 7.05 mmol/L, P = 0.28). No difference was observed in the mean daily dose of insulin or in the daily carbohydrate intake. No serious adverse event occurred during the study period. Conclusions: Our pilot study showed that FCL might be a realistic mode of treatment for people with T1D.

Adolescents' and their parents' experiences of using a closed-loop system to manage type 1 diabetes in everyday life: qualitative study

OBJECTIVES

Type 1 diabetes can have life-shattering consequences for adolescents and parents. A closed-loop system is a cutting-edge technology which automatically regulates glucose to reduce the burden of diabetes management. We explored adolescents' and parents' experiences of using this technology to understand how it affects their biographies and everyday lives.

METHODS

In-depth interviews with 18 adolescents newly diagnosed with type 1 diabetes and 21 parents after ≥12 months experience using closed-loop technology. Data were analysed thematically.

RESULTS

Participants reported very few disruptions to their lives when using a closed-loop. Reports of family conflict were minimal as the closed-loop enabled dietary flexibility and glucose levels to be checked effortlessly. Adolescents described doing 'normal' activities without worrying about high/low glucose, and parents reported allowing them to do so unsupervised because the closed-loop would regulate their glucose and keep them safe. Some adolescents expressed concerns about the visibility of components and, to avoid stigma, described curtailing activities such as swimming. Participants described how the closed-loop enabled adolescents to be in control of, or create distance from, diabetes.

DISCUSSION

The closed-loop has life-enhancing consequences for both adolescents and parents and helps to reduce the biographical disruption of type 1 diabetes in this age group.

Internal model control based module for the elimination of meal and exercise announcements in hybrid artificial pancreas systems

BACKGROUND AND OBJECTIVES

Hybrid artificial pancreas systems outperform current insulin pump therapies in blood glucose regulation in type 1 diabetes. However, subjects still have to inform the system about meals intake and exercise to achieve reasonable control. These patient announcements may result in overburden and compromise controller performance if not provided timely and accurately. Here, a hybrid artificial pancreas is extended with an add-on module that releases subjects from meals and exercise announcements.

METHODS

The add-on module consists of an internal-model controller that generates a "virtual" control action to compensate for disturbances. This "virtual" action is converted into insulin delivery, rescue carbohydrates suggestions, or insulin-on-board limitations, depending on a switching logic based on glucose measurements and predictions. The controller parameters are tuned by optimization and then related to standard parameters from the open-loop therapy. This module is implemented in a hybrid artificial pancreas system proposed by our research group for validation. This hybrid system extended with the add-on module is compared with the hybrid controller with carbohydrate counting errors (hybrid) and the hybrid controller with an alternative unannounced meal compensation module based on a meal detection algorithm (meal detector). The validation used the educational version of the UVa/Padova simulator to simulate the three controllers under two scenarios: one with only meals and another with meals and exercise. The exercise was modeled as a temporal increase of the insulin sensitivity resulting in the glucose drop usually related to an aerobic exercise.

RESULTS

For the scenario with only meals, the three controllers achieved similar time in range (proposed: 85.1 [77.9,88.1]%, hybrid: 84.0 [75.9,86.4]%, meal detector: 81.9 [79.3,83.8]%, median [interquartile range]) with low time in moderate hypoglycemia. Under the scenario with meals and exercise, the proposed module reduces 4.61% the time in hypoglycemia achieved with the other controllers, suggesting an acceptable amount of rescues (27.2 [23.7, 31.0] g).

CONCLUSIONS

The proposed add-on module achieved promising results: it outperformed the meal-detector-based controller, even achieving a postprandial performance as good as the hybrid controller (with carbohydrate counting errors). Also, the rescue suggestion feature of the module mitigated exercise-induced hypoglycemia with admissible rescue amounts.

A Meal Detection Algorithm for the Artificial Pancreas: A Randomized Controlled Clinical Trial in Adolescents With Type 1 Diabetes

OBJECTIVE

We developed a meal detection algorithm for the artificial pancreas (AP+MDA) that detects unannounced meals and delivers automatic insulin boluses.

RESEARCH DESIGN AND METHODS

We conducted a randomized crossover trial in 11 adolescents aged 12-18 years with HbA_1c ≥7.5% who missed one or more boluses in the past 6 months. We compared 1) continuous subcutaneous insulin infusion (CSII), 2) artificial pancreas (AP), and 3) AP+MDA. Participants underwent three 9-h interventions involving breakfast with a bolus and lunch without a bolus.

RESULTS

In AP+MDA, the meal detection time was 40.0 (interquartile range 40.0-57.5) min. Compared with CSII, AP+MDA decreased the 4-h postlunch incremental area under the curve (iAUC) from 24.1 ± 9.5 to 15.4 ± 8.0 h ⋅ mmol/L (P = 0.03). iAUC did not differ between AP+MDA and AP (19.6 ± 10.4 h ⋅ mmol/L, P = 0.21) or between AP and CSII (P = 0.33). The AP+MDA reduced time >10 mmol/L (58.0 ± 26.6%) compared with CSII (79.6 ± 27.5%, P = 0.02) and AP (74.2 ± 20.6%, P = 0.047).

CONCLUSIONS

The AP+MDA improved glucose control after an unannounced meal.

Automated Blood Pressure Control

Arterial pressure management is a crucial task in the operating room and intensive care unit. In high-risk surgical and in critically ill patients, sustained hypotension is managed with continuous infusion of vasopressor agents, which most commonly have direct α agonist activity like phenylephrine or norepinephrine. The current standard of care to guide vasopressor infusion is manual titration to an arterial pressure target range. This approach may be improved by using automated systems that titrate vasopressor infusions to maintain a target pressure. In this article, we review the evidence behind blood pressure management in the operating room and intensive care unit and discuss current and potential future applications of automated blood pressure control.

Glucose outcomes of a learning-type artificial pancreas with an unannounced meal in type 1 diabetes

BACKGROUND AND OBJECTIVES

Glycemic control with unannounced meals is the major challenge for artificial pancreas. In this study, we described the performance and safety of learning-type model predictive control (L-MPC) for artificial pancreas challenged by an unannounced meal in type 1 diabetes (T1D).

METHODS

This closed-loop (CL) system was tested in 29 T1D patients at one site in a 4 h inpatient open-label study. Participants used an L-MPC CL system for 6 days after 2-day system identification using open-loop (OL) insulin system. During the CL period, the L-MPC system was started from 8:00 am to noon each day. At 9:00 am, each participant consumed 50 g of carbohydrates with no prandial insulin bolus. At 9:30 am on CL-Day 4 or CL-Day 6, participants rode bicycles for 20 minutes or drank 50 ml of beer, in a random order.

RESULTS

As the primary outcome, TIR on CL-Day 3 was 65.2±23.3%, which was 9.8 points higher (95% CI 1.8 to 17.8; P = 0.019) than that on CL-Day 1. The time of glucose >10 mmol/L was decreased by 11.0% (95% CI -18.7 to 3.3; P = 0.007), and mean glucose level was decreased by 1.1 mmol/L (95% CI -1.1 to 0.5; P = 0.000). The total daily insulin dosage showed no significant difference (-0.1U, 95% CI -1.34 to 1.32; P = 0.982). Compared with OL-Day1 with a postprandial bolus, the TIR was increased by 13.7 points (95% CI 1.4 to 26.0; P = 0.030), the time of glucose >10 mmol/L and the mean glucose level were also decreased. Compared with the exercise day (CL-Day E, 62.0 ± 23.3%; P = 0.347) or alcohol day (CL-Day A, 64.0 ± 23.6%; P = 0.756), there was no statistically significant difference in terms of TIR, time of glucose >10 mmol/L and mean glucose level. No severe hypoglycemic events occurred and hypoglycemic episodes were not increased by using closed-loop insulin system.

CONCLUSION

The L-MPC CL insulin system achieved good glycemic control challenged by an unannounced meal.

What Training, Support, and Resourcing Do Health Professionals Need to Support People Using a Closed-Loop System? A Qualitative Interview Study with Health Professionals Involved in the Closed Loop from Onset in Type 1 Diabetes (CLOuD) Trial

Background: We explored health professionals' views about the training, support, and resourcing needed to support people using closed-loop technology in routine clinical care to help inform the development of formal guidance. Methods: Interviews were conducted with health professionals (n = 22) delivering the Closed Loop from Onset in Type 1 Diabetes (CLOuD) trial after they had ≥6 months' experience of supporting participants using a closed-loop system. Data were analyzed descriptively. Results: Interviewees described how, compared with other insulin regimens, teaching and supporting individuals to use a closed-loop system could be initially more time-consuming. However, they also noted that after an initial adjustment period, users had less need for initiating contact with the clinical team compared with people using pumps or multiple daily injections. Interviewees highlighted how a lessened need for ad hoc clinical input could result in new challenges; specifically, they had fewer opportunities to reinforce users' diabetes knowledge and skills and detect potential psychosocial problems. They also observed heightened anxiety among some parents due to the constant availability of data and unrealistic expectations about the system's capabilities. Interviewees noted that all local diabetes teams should be empowered to deliver closed-loop system care, but stressed that health professionals supporting closed-loop users in routine care will need comprehensive technology training and standardized clinical guidance. Conclusion: These findings constitute an important starting point for the development of formal guidance to support the rollout of closed-loop technology. Our recommendations, if actioned, will help limit the potential additional burden of introducing closed-loop systems in routine clinical care and help inform appropriate user education and support.

Novel Single-Site Device for Conjoined Glucose Sensing and Insulin Infusion: Performance Evaluation in Diabetes Patients During Home-Use

OBJECTIVE

This study evaluated a novel diabetes treatment device that combines commercially available continuous glucose monitoring and insulin infusion technology in such a way as to perform insulin delivery and glucose sensing through a single skin insertion site (single-port device).

METHODS

Ten type 1 diabetes patients used the device for up to six days in their home/work environment for open-loop insulin delivery and glucose sensing. On an additional day, the device was used in combination with an algorithm to perform automated closed-loop glucose control under hospital settings. To assess the performance of the device, capillary blood glucose concentrations were frequently determined and a continuous glucose sensor was additionally worn by the patients.

RESULTS

The average mean absolute relative deviation from blood glucose concentrations obtained for the sensor of the device was low (median, 13.0%; interquartile range, 10.5-16.7%; n = 10) and did not differ from that of the additionally worn glucose sensor (versus 13.9%; 11.9-15.3%; P = 0.922). Furthermore, insulin delivery with the single-port device was reliable and safe during home use and, when performed in combination with the control algorithm, was adequate to achieve and maintain near normoglycemia.

CONCLUSION

Our data show the feasibility of open- and closed-loop glucose control in diabetes patients using a device that combines insulin delivery and glucose sensing at a single tissue site.

SIGNIFICANCE

The reduction in device size and invasiveness achieved by this design may largely increase patient convenience and enhance acceptance of diabetes treatment with continuous glucose monitoring and insulin delivery technology.

The impact of using a closed-loop system on food choices and eating practices among people with Type 1 diabetes: a qualitative study involving adults, teenagers and parents

AIMS

We explored whether, how and why moving onto and using a hybrid day-and-night closed-loop system affected people's food choices and dietary practices to better understand the impact of this technology on everyday life and inform recommendations for training and support given to future users.

METHODS

Twenty-four adults, adolescents and parents were interviewed before commencing use of the closed-loop system and following its 3-month use. Data were analysed thematically and longitudinally.

RESULTS

While participants described preparing and/or eating similar meals to those consumed prior to using a closed-loop, many described feeling more normal and less burdened by diabetes in dietary situations. Individuals also noted how the use of this technology could lead to deskilling (less precise carbohydrate counting) and less healthy eating (increased snacking and portion sizes and consumption of fatty, energy-dense foods) because of the perceived ability of the system to deal with errors in carbohydrate counting and address small rises in blood glucose without a corrective dose needing to be administered.

CONCLUSIONS

While there may be quality-of-life benefits to using a closed-loop, individuals might benefit from additional nutritional and behavioural education to help promote healthy eating. Refresher training in carbohydrate counting may also be necessary to help ensure that users are able to undertake diabetes management in situations where the technology might fail or that they take a break from using it.

Adding wisdom to 'smart' bioelectronic systems: a design framework for physiologic control including practical examples

This perspective provides an overview of how risk can be effectively considered in physiological control loops that strive for semi-to-fully automated operation. The perspective first introduces the motivation, user needs and framework for the design of a physiological closed-loop controller. Then, we discuss specific risk areas and use examples from historical medical devices to illustrate the key concepts. Finally, we provide a design overview of an adaptive bidirectional brain–machine interface, currently undergoing human clinical studies, to synthesize the design principles in an exemplar application.

Participants' Experiences of, and Views About, Daytime Use of a Day-and-Night Hybrid Closed-Loop System in Real Life Settings: Longitudinal Qualitative Study

OBJECTIVE

To explore individuals' experiences of daytime use of a day-and-night hybrid closed-loop system, their information and support needs, and their views about how future systems could be improved.

RESEARCH DESIGN AND METHODS

Twenty-four adults, adolescents, and parents were interviewed before using a hybrid day-and-night closed-loop system and 3 months later, data were analyzed thematically.

RESULTS

Participants praised the closed loop's ability to respond to high and low blood glucose in ways which extended beyond their own capabilities and to act as a safety net and mop up errors, such as when a mealtime bolus was forgotten or unplanned activity was undertaken. Participants also described feeling less burdened by diabetes as a consequence and more able to lead flexible, spontaneous lives. Contrary to their initial expectations, and after trust in the system had been established, most individuals wanted opportunities to collaborate with the closed loop to optimize its effectiveness. Such individuals expressed a need to communicate information, such as when routines changed or to indicate different intensities of physical activity. While individuals valued frequent contact with staff in the initial month of use, most felt that their long-term support needs would be no greater than when using an insulin pump.

CONCLUSIONS

While participants reported substantial benefits to using the closed loop during the day, they also identified ways in which the technology could be refined and education and training tailored to optimize effective use. Our findings suggest that mainstreaming this technology will not necessarily lead to increased demands on clinical staff.

Fully Closed-Loop Multiple Model Probabilistic Predictive Controller Artificial Pancreas Performance in Adolescents and Adults in a Supervised Hotel Setting

BACKGROUND

Initial Food and Drug Administration-approved artificial pancreas (AP) systems will be hybrid closed-loop systems that require prandial meal announcements and will not eliminate the burden of premeal insulin dosing. Multiple model probabilistic predictive control (MMPPC) is a fully closed-loop system that uses probabilistic estimation of meals to allow for automated meal detection. In this study, we describe the safety and performance of the MMPPC system with announced and unannounced meals in a supervised hotel setting.

RESEARCH DESIGN AND METHODS

The Android phone-based AP system with remote monitoring was tested for 72 h in six adults and four adolescents across three clinical sites with daily exercise and meal challenges involving both three announced (manual bolus by patient) and six unannounced (no bolus by patient) meals. Safety criteria were predefined. Controller aggressiveness was adapted daily based on prior hypoglycemic events.

RESULTS

Mean 24-h continuous glucose monitor (CGM) was 157.4 ± 14.4 mg/dL, with 63.6 ± 9.2% of readings between 70 and 180 mg/dL, 2.9 ± 2.3% of readings <70 mg/dL, and 9.0 ± 3.9% of readings >250 mg/dL. Moderate hyperglycemia was relatively common with 24.6 ± 6.2% of readings between 180 and 250 mg/dL, primarily within 3 h after a meal. Overnight mean CGM was 139.6 ± 27.6 mg/dL, with 77.9 ± 16.4% between 70 and 180 mg/dL, 3.0 ± 4.5% <70 mg/dL, 17.1 ± 14.9% between 180 and 250 mg/dL, and 2.0 ± 4.5%> 250 mg/dL. Postprandial hyperglycemia was more common for unannounced meals compared with announced meals (4-h postmeal CGM 197.8 ± 44.1 vs. 140.6 ± 35.0 mg/dL; P < 0.001). No participants met safety stopping criteria.

CONCLUSIONS

MMPPC was safe in a supervised setting despite meal and exercise challenges. Further studies are needed in a less supervised environment.

The challenges of achieving postprandial glucose control using closed-loop systems in patients with type 1 diabetes

For patients with type 1 diabetes, closed-loop delivery systems (CLS) combining an insulin pump, a glucose sensor and a dosing algorithm allowing a dynamic hormonal infusion have been shown to improve glucose control when compared with conventional therapy. Yet, reducing glucose excursion and simplification of prandial insulin doses remain a challenge. The objective of this literature review is to examine current meal-time strategies in the context of automated delivery systems in adults and children with type 1 diabetes. Current challenges and considerations for post-meal glucose control will also be discussed. Despite promising results with meal detection, the fully automated CLS has yet failed to provide comparable glucose control to CLS with carbohydrate-matched bolus in the post-meal period. The latter strategy has been efficient in controlling post-meal glucose using different algorithms and in various settings, but at the cost of a meal carbohydrate counting burden for patients. Further improvements in meal detection algorithms or simplified meal-priming boluses may represent interesting avenues. The greatest challenges remain in regards to the pharmacokinetic and dynamic profiles of available rapid insulins as well as sensor accuracy and lag-time. New and upcoming faster acting insulins could provide important benefits. Multi-hormone CLS (eg, dual-hormone combining insulin with glucagon or pramlintide) and adjunctive therapy (eg, GLP-1 and SGLT2 inhibitors) also represent promising options. Meal glucose control with the artificial pancreas remains an important challenge for which the optimal strategy is still to be determined.

Automated blood glucose control in type 1 diabetes: A review of progress and challenges

Since the 2000s, research teams worldwide have been working to develop closed-loop (CL) systems able to automatically control blood glucose (BG) levels in patients with type 1 diabetes. This emerging technology is known as artificial pancreas (AP), and its first commercial version just arrived in the market. The main objective of this paper is to present an extensive review of the clinical trials conducted since 2011, which tested various implementations of the AP for different durations under varying conditions. A comprehensive table that contains key information from the selected publications is provided, and the main challenges in AP development and the mitigation strategies used are discussed. The development timelines for different AP systems are also included, highlighting the main evolutions over the clinical trials for each system.

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.

Day-and-Night Closed-Loop Glucose Control in Patients With Type 1 Diabetes Under Free-Living Conditions: Results of a Single-Arm 1-Month Experience Compared With a Previously Reported Feasibility Study of Evening and Night at Home

OBJECTIVE

After testing of a wearable artificial pancreas (AP) during evening and night (E/N-AP) under free-living conditions in patients with type 1 diabetes (T1D), we investigated AP during day and night (D/N-AP) for 1 month.

RESEARCH DESIGN AND METHODS

Twenty adult patients with T1D who completed a previous randomized crossover study comparing 2-month E/N-AP versus 2-month sensor augmented pump (SAP) volunteered for 1-month D/N-AP nonrandomized extension. AP was executed by a model predictive control algorithm run by a modified smartphone wirelessly connected to a continuous glucose monitor (CGM) and insulin pump. CGM data were analyzed by intention-to-treat with percentage time-in-target (3.9-10 mmol/L) over 24 h as the primary end point.

RESULTS

Time-in-target (mean ± SD, %) was similar over 24 h with D/N-AP versus E/N-AP: 64.7 ± 7.6 vs. 63.6 ± 9.9 (P = 0.79), and both were higher than with SAP: 59.7 ± 9.6 (P = 0.01 and P = 0.06, respectively). Time below 3.9 mmol/L was similarly and significantly reduced by D/N-AP and E/N-AP versus SAP (both P < 0.001). SD of blood glucose concentration (mmol/L) was lower with D/N-AP versus E/N-AP during whole daytime: 3.2 ± 0.6 vs. 3.4 ± 0.7 (P = 0.003), morning: 2.7 ± 0.5 vs. 3.1 ± 0.5 (P = 0.02), and afternoon: 3.3 ± 0.6 vs. 3.5 ± 0.8 (P = 0.07), and was lower with D/N-AP versus SAP over 24 h: 3.1 ± 0.5 vs. 3.3 ± 0.6 (P = 0.049). Insulin delivery (IU) over 24 h was higher with D/N-AP and SAP than with E/N-AP: 40.6 ± 15.5 and 42.3 ± 15.5 vs. 36.6 ± 11.6 (P = 0.03 and P = 0.0004, respectively).

CONCLUSIONS

D/N-AP and E/N-AP both achieved better glucose control than SAP under free-living conditions. Although time in the different glycemic ranges was similar between D/N-AP and E/N-AP, D/N-AP further reduces glucose variability.

A Review of Safety and Design Requirements of the Artificial Pancreas

As clinical studies with artificial pancreas systems for automated blood glucose control in patients with type 1 diabetes move to unsupervised real-life settings, product development will be a focus of companies over the coming years. Directions or requirements regarding safety in the design of an artificial pancreas are, however, lacking. This review aims to provide an overview and discussion of safety and design requirements of the artificial pancreas. We performed a structured literature search based on three search components—type 1 diabetes, artificial pancreas, and safety or design—and extended the discussion with our own experiences in developing artificial pancreas systems. The main hazards of the artificial pancreas are over- and under-dosing of insulin and, in case of a bi-hormonal system, of glucagon or other hormones. For each component of an artificial pancreas and for the complete system we identified safety issues related to these hazards and proposed control measures. Prerequisites that enable the control algorithms to provide safe closed-loop control are accurate and reliable input of glucose values, assured hormone delivery and an efficient user interface. In addition, the system configuration has important implications for safety, as close cooperation and data exchange between the different components is essential.

The Hypoglycaemia-Hyperglycaemia Minimizer System in the Management of Type 1 Diabetes

Living with type 1 diabetes (T1D) presents many challenges in terms of daily living. Insulin users need to frequently monitor their blood glucose levels and take multiple injections per day and/or multiple boluses through an insulin infusion pump, with the consequences of failing to match the insulin dose to the body's needs resulting in hypoglycaemia and hyperglycaemia. The former can result in seizures, coma and even death; the latter can have both acute and long-term health implications. Many patients with T1D also fail to meet their treatment goals. In order to reduce the burdens of self-administering insulin, and improve efficacy and safety, there is a need to at least partially remove the patient from the loop via a closed-loop 'artificial pancreas’ system. The Hypoglycaemia-Hyperglycaemia Minimizer (HHM) System, comprising a continuous, subcutaneous insulin infusion pump, continuous glucose monitor (CGM) and closed-loop insulin dosing algorithm, is able to predict changes in blood glucose and adjust insulin delivery accordingly to help keep the patient at normal glucose levels. Early clinical data indicate that this system is feasible, effective and safe, and has the potential to dramatically improve the therapeutic outcomes and quality of life for people with T1D.

Use of an artificial pancreas among adolescents for a missed snack bolus and an underestimated meal bolus

OBJECTIVE

The objective of this study was to evaluate the safety and performance of the artificial pancreas (AP) in adolescents with type 1 diabetes (T1D) following insulin omission for food.

RESEARCH DESIGN AND METHODS

In a randomized, cross-over trial, adolescents with T1D aged 13-18 yr were enrolled in a randomized, cross-over trial. On separate days, received either usual care (UC) through their home insulin pump or used an AP system (Diabetes Assistant platform, continuous glucose monitor, and insulin pump). Approximately 1 h after admission, participants in both groups received an unannounced snack of 30 g carbohydrate, and 4 h later they received an 80 g lunch, for which both groups only received 75% of the calculated insulin dose to cover carbohydrates. On the UC day (but not the AP day), they received their full high blood glucose (BG) correction factor at lunch. Each admission lasted approximately 8 h.

RESULTS

A total of 16 participants completed the trial. On the AP day (compared to UC), mean BG was lower (197 ± 10 vs. 235 ± 14 mg/dL) and time in range 70-180 mg/dL was higher (43% ± 7 vs. 19% ± 7) (both p < 0.05) overall; these results held in the time following the snack and meal (also p < 0.05). During the trial, there were no differences between groups in the rate of hypoglycemia <70 mg/dL.

CONCLUSIONS

The AP provided improvements in short-term glycemic control without increases in hypoglycemia following missed insulin for food in adolescents. Thus, the AP partly compensates for missed insulin boluses for food, a common occurrence in adolescent diabetes care. Further testing is needed in longer-term settings.

[New technologies in diabetology. How far are we from a closed loop?]

Today, assistive technologies are highly important in the treatment of diabetes, especially in the therapy of type 1 diabetes. The use of insulin pumps, for example, has become an established form of treatment. Modern insulin pumps offer various functions, such as different basal rate profiles, split delivery of the meal bolus, and integrated bolus calculators. Some pumps are additionally connected to a blood glucose meter or a continuous glucose-monitoring sensor. Several minimally invasive needle-type sensor systems for continuous tissue glucose monitoring are already available. Recent developments aim at increasing the functionality of insulin pumps and the improvements of sensors for continuous glucose monitoring. In addition, many research groups are working on closing the loop between these two components and thus developing an artificial pancreas, which automatically regulates insulin delivery. The first steps have already been taken and bolus calculators or sensor-augmented insulin pumps with suspension of insulin delivery are now available. Many experimental models show promising results. Prior to the implementation of a fully automated system for everyday use, however, partially automated systems that require user input are to be expected. This article aims at giving an overview of the current state of development in the field of diabetes technology.

2 month evening and night closed-loop glucose control in patients with type 1 diabetes under free-living conditions: a randomised crossover trial

BACKGROUND

An artificial pancreas (AP) that can be worn at home from dinner to waking up in the morning might be safe and efficient for first routine use in patients with type 1 diabetes. We assessed the effect on glucose control with use of an AP during the evening and night plus patient-managed sensor-augmented pump therapy (SAP) during the day, versus 24 h use of patient-managed SAP only, in free-living conditions.

METHODS

In a crossover study done in medical centres in France, Italy, and the Netherlands, patients aged 18-69 years with type 1 diabetes who used insulin pumps for continuous subcutaneous insulin infusion were randomly assigned to 2 months of AP use from dinner to waking up plus SAP use during the day versus 2 months of SAP use only under free-living conditions. Randomisation was achieved with a computer-generated allocation sequence with random block sizes of two, four, or six, masked to the investigator. Patients and investigators were not masked to the type of intervention. The AP consisted of a continuous glucose monitor (CGM) and insulin pump connected to a modified smartphone with a model predictive control algorithm. The primary endpoint was the percentage of time spent in the target glucose concentration range (3·9-10·0 mmol/L) from 2000 to 0800 h. CGM data for weeks 3-8 of the interventions were analysed on a modified intention-to-treat basis including patients who completed at least 6 weeks of each intervention period. The 2 month study period also allowed us to asses HbA1c as one of the secondary outcomes. This trial is registered with ClinicalTrials.gov, number NCT02153190.

FINDINGS

During 2000-0800 h, the mean time spent in the target range was higher with AP than with SAP use: 66·7% versus 58·1% (paired difference 8·6% [95% CI 5·8 to 11·4], p<0·0001), through a reduction in both mean time spent in hyperglycaemia (glucose concentration >10·0 mmol/L; 31·6% vs 38·5%; -6·9% [-9·8% to -3·9], p<0·0001) and in hypoglycaemia (glucose concentration <3·9 mmol/L; 1·7% vs 3·0%; -1·6% [-2·3 to -1·0], p<0·0001). Decrease in mean HbA1c during the AP period was significantly greater than during the control period (-0·3% vs -0·2%; paired difference -0·2 [95% CI -0·4 to -0·0], p=0·047), taking a period effect into account (p=0·0034). No serious adverse events occurred during this study, and none of the mild-to-moderate adverse events was related to the study intervention.

INTERPRETATION

Our results support the use of AP at home as a safe and beneficial option for patients with type 1 diabetes. The HbA1c results are encouraging but preliminary.

FUNDING

European Commission.

Artificial Pancreas Project at Cambridge 2013

The development and clinical testing of closed-loop systems (the artificial pancreas) is underpinned by advances in continuous glucose monitoring and benefits from concerted academic and industry collaborative efforts. This review describes the progress of the Artificial Pancreas Project at the University of Cambridge from 2006 to 2014. Initial studies under controlled laboratory conditions, designed to collect representative safety and performance data, were followed by short to medium free-living unsupervised outpatient studies demonstrating the safety and efficacy of closed-loop insulin delivery using a model predictive control algorithm. Accompanying investigations included assessment of the psychosocial impact and key factors affecting glucose control such as insulin kinetics and glucose absorption. Translation to other disease conditions such as critical illness and Type 2 diabetes took place. It is concluded that innovation of iteratively enhanced closed-loop systems will provide tangible means to improve outcomes and quality of life in people with Type 1 diabetes and their families in the next decade.

Closed loop insulin delivery in diabetes

The primary goal of type 1 diabetes treatment is attaining near-normal glucose values. This currently remains out of reach for most people with type 1 diabetes despite intensified insulin treatment in the form of insulin analogues, educational interventions, continuous glucose monitoring, and sensor augmented insulin pump. The main remaining problem is risk of hypoglycaemia, which cannot be sufficiently reduced in all patient groups. Additionally, patients' burn-out often develops with years of tedious day-to-day diabetes management, rendering available diabetes-related technology less efficient. Over the past 40 years, several attempts have been made towards computer-programmed insulin delivery in the form of closed loop, with faster developments especially in the past decade. Automated insulin delivery has reduced human error in glycaemic control and considerably lessened the burden of routine self-management. In this chapter, data from randomized controlled trials with closed-loop insulin delivery that included type 1 diabetes population are summarized, and an evidence-based vision for possible routine utilization of closed loop is provided.