Night glucose control with MD-Logic artificial pancreas in home setting: a single blind, randomized crossover trial-interim analysis

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.

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).

Safety and Glycemic Outcomes During the MiniMed™ Advanced Hybrid Closed-Loop System Pivotal Trial in Adolescents and Adults with Type 1 Diabetes

Introduction: This trial assessed safety and effectiveness of an advanced hybrid closed-loop (AHCL) system with automated basal (Auto Basal) and automated bolus correction (Auto Correction) in adolescents and adults with type 1 diabetes (T1D). Materials and Methods: This multicenter single-arm study involved an intent-to-treat population of 157 individuals (39 adolescents aged 14-21 years and 118 adults aged ≥22-75 years) with T1D. Study participants used the MiniMed™ AHCL system during a baseline run-in period in which sensor-augmented pump +/- predictive low glucose management or Auto Basal was enabled for ∼14 days. Thereafter, Auto Basal and Auto Correction were enabled for a study phase (∼90 days), with glucose target set to 100 or 120 mg/dL for ∼45 days, followed by the other target for ∼45 days. Study endpoints included safety events and change in mean A1C, time in range (TIR, 70-180 mg/dL) and time below range (TBR, <70 mg/dL). Run-in and study phase values were compared using Wilcoxon signed-rank test or paired t-test. Results: Overall group time spent in closed loop averaged 94.9% ± 5.4% and involved only 1.2 ± 0.8 exits per week. Compared with run-in, AHCL reduced A1C from 7.5% ± 0.8% to 7.0% ± 0.5% (<0.001, Wilcoxon signed-rank test, n = 155), TIR increased from 68.8% ± 10.5% to 74.5% ± 6.9% (<0.001, Wilcoxon signed-rank test), and TBR reduced from 3.3% ± 2.9% to 2.3% ± 1.7% (<0.001, Wilcoxon signed-rank test). Similar benefits to glycemia were observed for each age group and were more pronounced for the nighttime (12 AM-6 AM). The 100 mg/dL target increased TIR to 75.4% (n = 155), which was further optimized at a lower active insulin time (AIT) setting (i.e., 2 h), without increasing TBR. There were no severe hypoglycemic or diabetic ketoacidosis events during the study phase. Conclusions: These findings show that the MiniMed AHCL system is safe and allows for achievement of recommended glycemic targets in adolescents and adults with T1D. Adjustments in target and AIT settings may further optimize glycemia and improve user experience. Clinical Trial Registration number: NCT03959423.

Efficacy, safety, and user experience of DIY or open-source artificial pancreas systems: a systematic review

The do-it-yourself artificial pancreas system (DIYAPS) is a patient-driven initiative with the potential to revolutionise diabetes management, automating insulin delivery with existing pumps and CGM combined with open-source algorithms. Given the considerable interest in this topic within the diabetes community, we have conducted a systematic review of DIYAPS efficacy, safety, and user experience. Following recognised procedures and reporting standards, we identified 10 eligible publications of 730 participants within the peer-reviewed literature. Overall, studies reported improvements in time in range, HbA1c (glycated haemoglobin), reduced hypoglycaemia, and improved quality of life with DIYAPS use. While results were positive, the identified studies were small, and the majority were observational and at high risk of bias. Further research including well-designed randomised trials comparing DIYAPS with appropriate comparators is recommended.

Intelligent automated drug administration and therapy: future of healthcare

In the twenty-first century, the collaboration of control engineering and the healthcare sector has matured to some extent; however, the future will have promising opportunities, vast applications, and some challenges. Due to advancements in processing speed, the closed-loop administration of drugs has gained popularity for critically ill patients in intensive care units and routine life such as personalized drug delivery or implantable therapeutic devices. For developing a closed-loop drug delivery system, the control system works with a group of technologies like sensors, micromachining, wireless technologies, and pharmaceuticals. Recently, the integration of artificial intelligence techniques such as fuzzy logic, neural network, and reinforcement learning with the closed-loop drug delivery systems has brought their applications closer to fully intelligent automatic healthcare systems. This review's main objectives are to discuss the current developments, possibilities, and future visions in closed-loop drug delivery systems, for providing treatment to patients suffering from chronic diseases. It summarizes the present insight of closed-loop drug delivery/therapy for diabetes, gastrointestinal tract disease, cancer, anesthesia administration, cardiac ailments, and neurological disorders, from a perspective to show the research in the area of control theory.

Assessing the effect of closed-loop insulin delivery from onset of type 1 diabetes in youth on residual beta-cell function compared to standard insulin therapy (CLOuD study): a randomised parallel study protocol

INTRODUCTION

Management of newly diagnosed type 1 diabetes (T1D) in children and adolescents is challenging for patients, families and healthcare professionals. The objective of this study is to determine whether continued intensive metabolic control using hybrid closed-loop (CL) insulin delivery following diagnosis of T1D can preserve C-peptide secretion, a marker of residual beta-cell function, compared with standard multiple daily injections (MDI) therapy.

METHODS AND ANALYSIS

The study adopts an open-label, multicentre, randomised, parallel design, and aims to randomise 96 participants aged 10-16.9 years, recruited within 21 days of diagnosis with T1D. Following a baseline mixed meal tolerance test (MMTT), participants will be randomised to receive 24 months treatment with conventional MDI therapy or with CL insulin delivery. A further 24-month optional extension phase will be offered to all participants to continue with the allocated treatment. The primary outcome is the between group difference in area under the stimulated C-peptide curve (AUC) of the MMTT at 12 months post diagnosis. Analyses will be conducted on an intention-to-treat basis. Key secondary outcomes are between group differences in time spent in target glucose range (3.9-10 mmol/L), glycated haemoglobin (HbA1c) and time spent in hypoglycaemia (<3.9 mmol/L) at 12 months. Secondary efficacy outcomes include between group differences in stimulated C-peptide AUC at 24 months, time spent in target glucose range, glucose variability, hypoglycaemia and hyperglycaemia as recorded by periodically applied masked continuous glucose monitoring devices, total, basal and bolus insulin dose, and change in body weight. Cognitive, emotional and behavioural characteristics of participants and parents will be evaluated, and a cost-utility analysis performed to support adoption of CL as a standard treatment modality following diagnosis of T1D.

ETHICS AND DISSEMINATION

Ethics approval has been obtained from Cambridge East Research Ethics Committee. The results will be disseminated by peer-reviewed publications and conference presentations.

TRIAL REGISTRATION NUMBER

NCT02871089; Pre-results.

Automated Insulin Delivery in Adults

Hybrid closed-loop (artificial pancreas) systems have recently been introduced into clinical practice for adults with type 1 diabetes. This reflects successful translation from research studies in highly supervised settings to evaluation of the technology in free-living home settings. We review the different closed-loop approaches and the key clinical evidence supporting adoption of hybrid closed-loop systems for adults with type 1 diabetes. We also discuss the growing evidence for automated insulin delivery in pregnant women and in hospitalized patients with hyperglycemia. We consider the psychosocial impact of closed-loop systems and the challenges and potential future advancements for automated insulin delivery.

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.

Automated Insulin Delivery Algorithms

IN BRIEF Automated insulin delivery (AID; also known as artificial pancreas) has improved the regulation of blood glucose concentrations, reduced the frequency of hyperglycemic and hypoglycemic episodes, and improved the quality of life of people with diabetes and their families. Three different types of algorithms-proportional-integral-derivative control, model predictive control, and fuzzy-logic knowledge-based systems-have been used in AID control systems. This article will highlight the foundations of these algorithms and discuss their strengths and limitations. Multivariable artificial pancreas and dual-hormone (insulin and glucagon) systems will be introduced.

Assessing the efficacy, safety and utility of 6-month day-and-night automated closed-loop insulin delivery under free-living conditions compared with insulin pump therapy in children and adolescents with type 1 diabetes: an open-label, multicentre, multinational, single-period, randomised, parallel group study protocol

INTRODUCTION

Closed-loop systems titrate insulin based on sensor glucose levels, providing novel means to reduce the risk of hypoglycaemia while improving glycaemic control. We will assess effectiveness of 6-month day-and-night closed-loop insulin delivery compared with usual care (conventional or sensor-augmented pump therapy) in children and adolescents with type 1 diabetes.

METHODS AND ANALYSIS

The trial adopts an open-label, multicentre, multinational (UK and USA), randomised, single-period, parallel design. Participants (n=130) are children and adolescents (aged ≥6 and <19 years) with type 1 diabetes for at least 1 year, and insulin pump use for at least 3 months with suboptimal glycaemic control (glycated haemoglobin ≥58 mmol/mol (7.5%) and ≤86 mmol/mol (10%)). After a 2-3 week run-in period, participants will be randomised to 6-month use of hybrid closed-loop insulin delivery, or to usual care. Analyses will be conducted on an intention-to-treat basis. The primary outcome is glycated haemoglobin at 6 months. Other key endpoints include time in the target glucose range (3.9-10 mmol/L, 70-180 mg/dL), mean sensor glucose and time spent above and below target. Secondary outcomes include SD and coefficient of variation of sensor glucose levels, time with sensor glucose levels <3.5 mmol/L (63 mg/dL) and <3.0 mmol/L (54 mg/dL), area under the curve of glucose <3.5 mmol/L (63 mg/dL), time with glucose levels >16.7 mmol/L (300 mg/dL), area under the curve of glucose >10.0 mmol/L (180 mg/dL), total, basal and bolus insulin dose, body mass index z-score and blood pressure. Cognitive, emotional and behavioural characteristics of participants and caregivers and their responses to the closed-loop and clinical trial will be assessed. An incremental cost-effectiveness ratio for closed-loop will be estimated.

ETHICS AND DISSEMINATION

Cambridge South Research Ethics Committee and Jaeb Center for Health Research Institutional Review Office approved the study. The findings will be disseminated by peer-review publications and conference presentations.

TRIAL REGISTRATION NUMBER

NCT02925299; Pre-results.

DREAM5: An open-label, randomized, cross-over study to evaluate the safety and efficacy of day and night closed-loop control by comparing the MD-Logic automated insulin delivery system to sensor augmented pump therapy in patients with type 1 diabetes at home

AIMS

Previous DREAM studies demonstrated the safety and efficacy of the CE marked MD-Logic closed-loop system (DreaMed GlucoSitter) in different settings for overnight glycaemic control. The present study aimed to evaluate the system for day and night use for 60 hours during the weekend at home compared to sensor-augmented pump (SAP) therapy in participants with type 1 diabetes.

METHODS

This was a prospective, multicentre, crossover, controlled study (clinicaltrials.gov NCT01238406). All participants were connected in randomized order for one weekend to SAP therapy or the MD-Logic System. In the intervention arm only, the amount of carbohydrate was entered into the bolus calculator; the rest of insulin delivery was automated and wireless via a tablet computer. The primary endpoint was percentage of glucose values between 70 and 180 mg/dL.

RESULTS

The ITT population comprised 48 (19 males, 29 females) adolescents and adults experienced in sensor use: (median, [IQR]): age, 16.1years [13.2-18.5]; diabetes duration, 9.4 years [5.0-12.7]; pump use, 5.4 years [3.1-9.4]; HbA1c, 7.6% [7.0-8.1]. A significant increase in the percentage of time within target range (70-180 mg/dL) (66.6% vs 59.9%, P = 0.002) was observed with the closed-loop system vs control weekends with unchanged percentage of time below 70 mg/dL (2.3% vs 1.5%, P = 0.369). Mean weekend glucose level per participant was significantly lower (153 [142-175] vs 164 [150-186] mg/dL, P = 0.003). No safety signals were observed.

CONCLUSIONS

The MD-Logic system was safe and associated with better glycaemic control than SAP therapy for day and night use. The absence of remote monitoring did not lead to safety signals in adapting basal rates nor in administration of automated bolus corrections.

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.

Artificial Intelligence for Diabetes Management and Decision Support: Literature Review

Background

Artificial intelligence methods in combination with the latest technologies, including medical devices, mobile computing, and sensor technologies, have the potential to enable the creation and delivery of better management services to deal with chronic diseases. One of the most lethal and prevalent chronic diseases is diabetes mellitus, which is characterized by dysfunction of glucose homeostasis.

Objective

The objective of this paper is to review recent efforts to use artificial intelligence techniques to assist in the management of diabetes, along with the associated challenges.

Methods

A review of the literature was conducted using PubMed and related bibliographic resources. Analyses of the literature from 2010 to 2018 yielded 1849 pertinent articles, of which we selected 141 for detailed review.

Results

We propose a functional taxonomy for diabetes management and artificial intelligence. Additionally, a detailed analysis of each subject category was performed using related key outcomes. This approach revealed that the experiments and studies reviewed yielded encouraging results.

Conclusions

We obtained evidence of an acceleration of research activity aimed at developing artificial intelligence-powered tools for prediction and prevention of complications associated with diabetes. Our results indicate that artificial intelligence methods are being progressively established as suitable for use in clinical daily practice, as well as for the self-management of diabetes. Consequently, these methods provide powerful tools for improving patients’ quality of life.

Glucose-responsive insulin delivery for type 1 diabetes: The artificial pancreas story

Insulin replacement therapy is integral to the management of type 1 diabetes, which is characterised by absolute insulin deficiency. Optimal glycaemic control, as assessed by glycated haemoglobin, and avoidance of hyper- and hypoglycaemic excursions have been shown to prevent diabetes-related complications. Insulin pump use has increased considerably over the past decade with beneficial effects on glycaemic control, quality of life and treatment satisfaction. The advent and progress of ambulatory glucose sensor technology has enabled continuous glucose monitoring based on real-time glucose levels to be integrated with insulin therapy. Low glucose and predictive low glucose suspend systems are currently used in clinical practice to mitigate against hypoglycaemia, and provide the first step towards feedback glucose control. The more advanced technology approach, an artificial pancreas or a closed-loop system, gradually increases and decreases insulin delivery in a glucose-responsive fashion to mitigate against hyper- and hypoglycaemia. Randomised outpatient clinical trials over the past 5 years have demonstrated the feasibility, safety and efficacy of the approach, and the recent FDA approval of the first single hormone closed-loop system establishes a new standard of care for people with type 1 diabetes.

Twelve-Week 24/7 Ambulatory Artificial Pancreas With Weekly Adaptation of Insulin Delivery Settings: Effect on Hemoglobin A1c and Hypoglycemia

OBJECTIVE

Artificial pancreas (AP) systems are best positioned for optimal treatment of type 1 diabetes (T1D) and are currently being tested in outpatient clinical trials. Our consortium developed and tested a novel adaptive AP in an outpatient, single-arm, uncontrolled multicenter clinical trial lasting 12 weeks.

RESEARCH DESIGN AND METHODS

Thirty adults with T1D completed a continuous glucose monitor (CGM)-augmented 1-week sensor-augmented pump (SAP) period. After the AP was started, basal insulin delivery settings used by the AP for initialization were adapted weekly, and carbohydrate ratios were adapted every 4 weeks by an algorithm running on a cloud-based server, with automatic data upload from devices. Adaptations were reviewed by expert study clinicians and patients. The primary end point was change in hemoglobin A_1c (HbA_1c). Outcomes are reported adhering to consensus recommendations on reporting of AP trials.

RESULTS

Twenty-nine patients completed the trial. HbA_1c, 7.0 ± 0.8% at the start of AP use, improved to 6.7 ± 0.6% after 12 weeks (-0.3, 95% CI -0.5 to -0.2, P < 0.001). Compared with the SAP run-in, CGM time spent in the hypoglycemic range improved during the day from 5.0 to 1.9% (-3.1, 95% CI -4.1 to -2.1, P < 0.001) and overnight from 4.1 to 1.1% (-3.1, 95% CI -4.2 to -1.9, P < 0.001). Whereas carbohydrate ratios were adapted to a larger extent initially with minimal changes thereafter, basal insulin was adapted throughout. Approximately 10% of adaptation recommendations were manually overridden. There were no protocol-related serious adverse events.

CONCLUSIONS

Use of our novel adaptive AP yielded significant reductions in HbA_1c and hypoglycemia.

Closed-loop glucose control in young people with type 1 diabetes during and after unannounced physical activity: a randomised controlled crossover trial

AIMS/HYPOTHESIS

Hypoglycaemia during and after exercise remains a challenge. The present study evaluated the safety and efficacy of closed-loop insulin delivery during unannounced (to the closed-loop algorithm) afternoon physical activity and during the following night in young people with type 1 diabetes.

METHODS

A randomised, two-arm, open-label, in-hospital, crossover clinical trial was performed at a single site in Slovenia. The order was randomly determined using an automated web-based programme with randomly permuted blocks of four. Allocation assignment was not masked. Children and adolescents with type 1 diabetes who were experienced insulin pump users were eligible for the trial. During four separate in-hospital visits, the participants performed two unannounced exercise protocols: moderate intensity (55% of [Formula: see text]) and moderate intensity with integrated high-intensity sprints (55/80% of [Formula: see text]), using the same study device either for closed-loop or open-loop insulin delivery. We investigated glycaemic control during the exercise period and the following night. The closed-loop insulin delivery was applied from 15:00 h on the day of the exercise to 13:00 h on the following day.

RESULTS

Between 20 January and 16 June 2016, 20 eligible participants (9 female, mean age 14.2 ± 2.0 years, HbA_1c 7.7 ± 0.6% [60.0 ± 6.6 mmol/mol]) were included in the trial and performed all trial-mandated activities. The median proportion of time spent in hypoglycaemia below 3.3 mmol/l was 0.00% for both treatment modalities (p = 0.7910). Use of the closed-loop insulin delivery system increased the proportion of time spent within the target glucose range of 3.9-10 mmol/l when compared with open-loop delivery: 84.1% (interquartile range 70.0-85.5) vs 68.7% (59.0-77.7), respectively (p = 0.0057), over the entire study period. This was achieved with significantly less insulin delivered via the closed-loop (p = 0.0123).

CONCLUSIONS/INTERPRETATION

Closed-loop insulin delivery was safe both during and after unannounced exercise protocols in the in-hospital environment, maintaining glucose values mostly within the target range without an increased risk of hypoglycaemia.

TRIAL REGISTRATION

Clinicaltrials.gov NCT02657083 FUNDING: University Medical Centre Ljubljana, Slovenian National Research Agency, and ISPAD Research Fellowship.

Closed-Loop Control Without Meal Announcement in Type 1 Diabetes

OBJECTIVE

A fully closed-loop insulin-only system was developed to provide glucose control in patients with type 1 diabetes without requiring announcement of meals or activity. Our goal was to assess initial safety and efficacy of this system.

RESEARCH DESIGN AND METHODS

The multiple model probabilistic controller (MMPPC) anticipates meals when the patient is awake. The controller used the subject's basal rates and total daily insulin dose for initialization. The system was tested at two sites on 10 patients in a 30-h inpatient study, followed by 15 subjects at three sites in a 54-h supervised hotel study, where the controller was challenged by exercise and unannounced meals. The system was implemented on the UVA DiAs system using a Roche Spirit Combo Insulin Pump and a Dexcom G4 Continuous Glucose Monitor.

RESULTS

The mean overall (24-h basis) and nighttime (11 PM-7 AM) continuous glucose monitoring (CGM) values were 142 and 125 mg/dL during the inpatient study. The hotel study used a different daytime tuning and manual announcement, instead of automatic detection, of sleep and wake periods. This resulted in mean overall (24-h basis) and nighttime CGM values of 152 and 139 mg/dL for the hotel study and there was also a reduction in hypoglycemia events from 1.6 to 0.91 events/patient/day.

CONCLUSIONS

The MMPPC system achieved a mean glucose that would be particularly helpful for people with an elevated A1c as a result of frequent missed meal boluses. Current full closed loop has a higher risk for hypoglycemia when compared with algorithms using meal announcement.

Manual Closed-Loop Insulin Delivery Using a Saddle Point Model Predictive Control Algorithm: Results of a Crossover Randomized Overnight Study

BACKGROUND

The purpose was to assess the efficacy of a new closed-loop algorithm (Saddle Point Model Predictive Control, SP-MPC) in achieving nocturnal normoglycemia while reducing the risk of hypoglycemia in patients with type 1 diabetes.

METHOD

In this randomized crossover study, 10 adult patients (mean hemoglobin A1c 7.35 ± 1.04%) were assigned to be treated overnight by open loop using sensor-augmented pump therapy (open-loop SAP) or manual closed-loop delivery. During closed loop, insulin doses were calculated using the SP-MPC algorithm and administered as manual boluses every 15 minutes from 9:00 pm to 8:00 am. Patients consumed a self-selected meal (65-125 g of carbohydrates) at 7:00 pm accompanied by their usual prandial bolus. Blood glucose was measured every 30 minutes. The primary endpoints were the time spent in target (70-145 mg/dl) and time spent below 70 mg/dl from 11:00 pm to 8:00 am.

RESULTS

Time spent in target did not differ between closed-loop and open-loop SAP. The number of hypoglycemic events (<70 mg/dl) was reduced 2.8-fold in closed loop (n = 5, median = 0/patient/hour; interquartile range: 0-0.11) as compared to open-loop SAP (n = 14, median = 0.22/patient/hour, 0.02-0.22) ( P = .02). The area under the curve for sensor glucose values >145 mg/dl was significantly lower during closed-loop than during open-loop SAP ( P = .03) as well as HBGI ( P = .02).

CONCLUSIONS

This pilot study suggests that the use of the SP-MPC algorithm may improve mean overnight glucose control and reduce the number of hypoglycemic events as compared to SAP therapy.

Multivariable Adaptive Artificial Pancreas System in Type 1 Diabetes

PURPOSE OF REVIEW

The review summarizes the current state of the artificial pancreas (AP) systems and introduces various new modules that should be included in future AP systems.

RECENT FINDINGS

A fully automated AP must be able to detect and mitigate the effects of meals, exercise, stress and sleep on blood glucose concentrations. This can only be achieved by using a multivariable approach that leverages information from wearable devices that provide real-time streaming data about various physiological variables that indicate imminent changes in blood glucose concentrations caused by meals, exercise, stress and sleep. The development of a fully automated AP will necessitate the design of multivariable and adaptive systems that use information from wearable devices in addition to glucose sensors and modify the models used in their model-predictive alarm and control systems to adapt to the changes in the metabolic state of the user. These AP systems will also integrate modules for controller performance assessment, fault detection and diagnosis, machine learning and classification to interpret various signals and achieve fault-tolerant control. Advances in wearable devices, computational power, and safe and secure communications are enabling the development of fully automated multivariable AP systems.

In-home nighttime predictive low glucose suspend experience in children and adults with type 1 diabetes

Overnight predictive low glucose suspend (PLGS) reduces hypoglycemia across all ages; however, there are no reports on behavior or experience differences across age groups, especially in pediatrics. As run-in for a subsequent randomized clinical trial (RCT), 127 subjects (50% male) ages 4-45 yr utilized the experimental PLGS system nightly for 5-10 nights (PLGS active phase). We analyzed the number of blood glucose (BG) checks and boluses given per age group. During the subsequent 42 night RCT phase, we analyzed sensor use, skin reactions, errors, and reasons why the experimental system was not used. In 821 nights of active PLGS, subjects ages 4-6 yr (and their parents) tested BG levels 75% of nights compared with 65% of nights (7-10 yr), 53% of nights (11-14 yr), 33% of nights (15-25 yr), and 28% of nights (26-45 yr), respectively (p < 0.001). Likewise, youngest subjects (and parents) administered insulin boluses 56% of nights during active PLGS use compared with 48%, 33%, 20%, and 25%, respectively (p < 0.001). This was unrelated to study requirements. During the RCT phase, subjects 4-6 yr experienced more frequent and severe skin reactions (p = 0.02), while adult subjects (26-45 yr) wore individual sensors a median of 26 h longer than the youngest subjects (p < 0.001). Technical problems with the sensor (errors, miscalibrations, etc.), traveling, and BG levels >270 at bedtime (study requirement) were primary contributors to non-system use. Understanding the different use patterns and challenges in pediatrics and adolescence is needed to direct patient education to optimize use of PLGS and future artificial pancreas systems.

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.

Sensor Life and Overnight Closed Loop: A Randomized Clinical Trial

BACKGROUND

Closed-loop (CL) systems direct insulin delivery based on continuous glucose monitor (CGM) sensor values. CGM accuracy varies with sensor life, being least accurate on day 1 of sensor insertion. We evaluated the effect of sensor life (enhanced Enlite, Medtronic MiniMed, Northridge, CA) on overnight CL.

METHODS

In an open-label, randomized, 2-period, inpatient crossover pilot study, 12 adolescents on insulin pump (age 16.7 ± 1.9 years; HbA1c 66 ± 10 mmol/mol) attended a clinical research facility on 2 overnight occasions. In random order, participants received CL on day 1 or on day 3-4 after sensor insertion. During both periods, glucose was automatically controlled by a model predictive control algorithm informed by sensor glucose. Plasma glucose was measured every 30 to 60 min.

RESULTS

During overnight CL (22:30 to 07:30), the proportion of time with plasma glucose readings in the target range (3.9-8.0 mmol/l, primary endpoint) when initiated on day 1 of sensor insertion vs day 3-4 were comparable (58 ± 32% day 1 vs 56 ± 36% day 3-4; P = .34), and there were no significant differences between interventions in terms of mean plasma glucose ( P = .26), percentage time above 8.0 mmol/l ( P = .49), and time spent below 3.9 mmol/l ( P = .93). Sensor accuracy varied with sensor life (mean absolute relative difference 19.8 ± 15.0% on day 1 and 13.7 ± 10.2% on day 3 to 4). Sensor glucose tended to under-read plasma glucose inflating benefits of CL on glucose control.

CONCLUSIONS

In spite of differences in sensor accuracy, overnight CL glucose control informed by sensor glucose on day 1 or day 3-4 after sensor insertion was comparable. The model predictive controller appears to mitigate against sensor inaccuracies.

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.

Glucose Outcomes with the In-Home Use of a Hybrid Closed-Loop Insulin Delivery System in Adolescents and Adults with Type 1 Diabetes

BACKGROUND

The safety and effectiveness of the in-home use of a hybrid closed-loop (HCL) system that automatically increases, decreases, and suspends insulin delivery in response to continuous glucose monitoring were investigated.

METHODS

Adolescents (n = 30, ages 14-21 years) and adults (n = 94, ages 22-75 years) with type 1 diabetes participated in a multicenter (nine sites in the United States, one site in Israel) pivotal trial. The Medtronic MiniMed^® 670G system was used during a 2-week run-in phase without HCL control, or Auto Mode, enabled (Manual Mode) and, thereafter, with Auto Mode enabled during a 3-month study phase. A supervised hotel stay (6 days/5 nights) that included a 24-h frequent blood sample testing with a reference measurement (i-STAT) occurred during the study phase.

RESULTS

Adolescents (mean ± standard deviation [SD] 16.5 ± 2.29 years of age and 7.7 ± 4.15 years of diabetes) used the system for a median 75.8% (interquartile range [IQR] 68.0%-88.4%) of the time (2977 patient-days). Adults (mean ± SD 44.6 ± 12.79 years of age and 26.4 ± 12.43 years of diabetes) used the system for a median 88.0% (IQR 77.6%-92.7%) of the time (9412 patient-days). From baseline run-in to the end of study phase, adolescent and adult HbA_1c levels decreased from 7.7% ± 0.8% to 7.1% ± 0.6% (P < 0.001) and from 7.3% ± 0.9% to 6.8% ± 0.6% (P < 0.001, Wilcoxon signed-rank test), respectively. The proportion of overall in-target (71-180 mg/dL) sensor glucose (SG) values increased from 60.4% ± 10.9% to 67.2% ± 8.2% (P < 0.001) in adolescents and from 68.8% ± 11.9% to 73.8% ± 8.4% (P < 0.001) in adults. During the hotel stay, the proportion of in-target i-STAT^® blood glucose values was 67.4% ± 27.7% compared to SG values of 72.0% ± 11.6% for adolescents and 74.2% ± 17.5% compared to 76.9% ± 8.3% for adults. There were no severe hypoglycemic or diabetic ketoacidosis events in either cohort.

CONCLUSIONS

HCL therapy was safe during in-home use by adolescents and adults and the study phase demonstrated increased time in target, and reductions in HbA_1c, hyperglycemia and hypoglycemia, compared to baseline.

TRIAL REGISTRATION

Clinicaltrials.gov identifier: NCT02463097.

Home Use of Day-and-Night Hybrid Closed-Loop Insulin Delivery in Suboptimally Controlled Adolescents With Type 1 Diabetes: A 3-Week, Free-Living, Randomized Crossover Trial

OBJECTIVE

This study evaluated the feasibility, safety, and efficacy of day-and-night hybrid closed-loop insulin delivery in adolescents with type 1 diabetes under free-living conditions.

RESEARCH DESIGN AND METHODS

In an open-label randomized crossover study, 12 suboptimally controlled adolescents on insulin pump therapy (mean ± SD age 14.6 ± 3.1 years; HbA_1c 69 ± 8 mmol/mol [8.5 ± 0.7%]; duration of diabetes 7.8 ± 3.5 years) underwent two 21-day periods in which hybrid closed-loop insulin delivery was compared with sensor-augmented insulin pump therapy in random order. During the closed-loop intervention, a model predictive algorithm automatically directed insulin delivery between meals and overnight. Participants used a bolus calculator to administer prandial boluses.

RESULTS

The proportion of time that sensor glucose was in the target range (3.9-10 mmol/L; primary end point) was increased during the closed-loop intervention compared with sensor-augmented insulin pump therapy by 18.8 ± 9.8 percentage points (mean ± SD; P < 0.001), the mean sensor glucose level was reduced by 1.8 ± 1.3 mmol/L (P = 0.001), and the time spent above target was reduced by 19.3 ± 11.3 percentage points (P < 0.001). The time spent with sensor glucose levels below 3.9 mmol/L was low and comparable between interventions (median difference 0.4 [interquartile range -2.2 to 1.3] percentage points; P = 0.33). Improved glucose control during closed-loop was associated with increased variability of basal insulin delivery (P < 0.001) and an increase in the total daily insulin dose (53.5 [39.5-72.1] vs. 51.5 [37.6-64.3] units/day; P = 0.006). Participants expressed positive attitudes and experience with the closed-loop system.

CONCLUSIONS

Free-living home use of day-and-night closed-loop in suboptimally controlled adolescents with type 1 diabetes is safe, feasible, and improves glucose control without increasing the risk of hypoglycemia. Larger and longer studies are warranted.

Model-Free Machine Learning in Biomedicine: Feasibility Study in Type 1 Diabetes

Although reinforcement learning (RL) is suitable for highly uncertain systems, the applicability of this class of algorithms to medical treatment may be limited by the patient variability which dictates individualised tuning for their usually multiple algorithmic parameters. This study explores the feasibility of RL in the framework of artificial pancreas development for type 1 diabetes (T1D). In this approach, an Actor-Critic (AC) learning algorithm is designed and developed for the optimisation of insulin infusion for personalised glucose regulation. AC optimises the daily basal insulin rate and insulin:carbohydrate ratio for each patient, on the basis of his/her measured glucose profile. Automatic, personalised tuning of AC is based on the estimation of information transfer (IT) from insulin to glucose signals. Insulin-to-glucose IT is linked to patient-specific characteristics related to total daily insulin needs and insulin sensitivity (SI). The AC algorithm is evaluated using an FDA-accepted T1D simulator on a large patient database under a complex meal protocol, meal uncertainty and diurnal SI variation. The results showed that 95.66% of time was spent in normoglycaemia in the presence of meal uncertainty and 93.02% when meal uncertainty and SI variation were simultaneously considered. The time spent in hypoglycaemia was 0.27% in both cases. The novel tuning method reduced the risk of severe hypoglycaemia, especially in patients with low SI.

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.

Artificial Pancreas Device Systems for the Closed-Loop Control of Type 1 Diabetes: What Systems Are in Development?

BACKGROUND

Closed-loop artificial pancreas device (APD) systems are externally worn medical devices that are being developed to enable people with type 1 diabetes to regulate their blood glucose levels in a more automated way. The innovative concept of this emerging technology is that hands-free, continuous, glycemic control can be achieved by using digital communication technology and advanced computer algorithms.

METHODS

A horizon scanning review of this field was conducted using online sources of intelligence to identify systems in development. The systems were classified into subtypes according to their level of automation, the hormonal and glycemic control approaches used, and their research setting.

RESULTS

Eighteen closed-loop APD systems were identified. All were being tested in clinical trials prior to potential commercialization. Six were being studied in the home setting, 5 in outpatient settings, and 7 in inpatient settings. It is estimated that 2 systems may become commercially available in the EU by the end of 2016, 1 during 2017, and 2 more in 2018.

CONCLUSIONS

There are around 18 closed-loop APD systems progressing through early stages of clinical development. Only a few of these are currently in phase 3 trials and in settings that replicate real life.

Real-Time Model-Based Fault Detection of Continuous Glucose Sensor Measurements

OBJECTIVE

Faults in subcutaneous glucose concentration readings with a continuous glucose monitoring (CGM) may affect the computation of insulin infusion rates that can lead to hypoglycemia or hyperglycemia in artificial pancreas control systems for patients with type 1 diabetes (T1D).

METHODS

Multivariable statistical monitoring methods are proposed for detection of faults in glucose concentration values reported by a subcutaneous glucose sensor. A nonlinear first principle glucose/insulin/meal dynamic model is developed. An unscented Kalman filter is used for state and parameter estimation of the nonlinear model. Principal component analysis models are developed and used for detection of dynamic changes. K-nearest neighbor classification algorithm is used for diagnosis of faults. Data from 51 subjects are used to assess the performance of the algorithm.

RESULTS

The results indicate that the proposed algorithm works successfully with 84.2% sensitivity. Overall, 155 (out of 184) of the CGM failures are detected with a 2.8-min average detection time.

CONCLUSION

A novel algorithm that integrates data-driven and model-based methods is developed. The proposed method is able to detect CGM failures with a high rate of success.

SIGNIFICANCE

The proposed fault detection algorithm can decrease the effects of faults on insulin infusion rates and reduce the potential for hypo- or hyperglycemia for patients with T1D.

Continuous Glucose Monitoring, Future Products, and Update on Worldwide Artificial Pancreas Projects

The development of accurate and easy-to-use continuous glucose monitoring (CGM) improved diabetes treatment by providing additional temporal information on glycemia and glucose trends to patient and physician. Although CGM enables users to lower their average glucose level without an increased incidence of hypoglycemia, this comes at the price of additional patient effort. Automation of insulin administration, also known as closed-loop (CL) or artificial pancreas treatment, has the promise to reduce patient effort and improve glycemic control. CGM data serve as the conditional input for insulin automation devices. The first commercial product for partial automation of insulin administration used insulin delivery shutoff at a predefined glucose level. These systems showed a reduction in hypoglycemia. Insulin-only CL devices show increased time spent in euglycemia and a reduction of hypo- and hyperglycemia. Improved glycemic control, coinciding with a minor decrease in hemoglobin A1c level, was confirmed in recent long-term home studies investigating these devices, paving the way for pivotal studies for commercialization of the artificial pancreas. Although the first results from dual-hormone CL systems are promising, because of increased cost of consumables of these systems, long-term head-to-head studies will have to prove superiority over insulin-only approaches. Now CL glucose control for daily use might finally become reality. Improved continuous glucose sensing technology, miniaturization of electrical devices, and development of algorithms were key in making this possible. Clinical adoption challenges, including device usability and reimbursement, need to be addressed. Time will tell for which patient groups CL systems will be reimbursed and whether these devices can deliver the promise that they hold.

A new horizon for glucose monitoring

Regular self-monitoring of blood glucose is crucial for proper insulin dosing and gives a reliable foundation for reasonable glycaemic control. According to recent data, recommended values for glycated haemoglobin A1c as set by the professional associations remain out of the reach for a large proportion of the paediatric population. In the last decades, the treatment of type 1 diabetes has changed significantly as new devices gain a role in routine clinical care. Real-time glucose levels can be monitored with continuous glucose monitoring (CGM), which provides a broad spectrum of information on glucose trends on a moment-to-moment basis. This information can be useful for patients' decision making and clinicians' understanding of patients' conduct. However, several barriers, including the current price, impede a broader use of CGM in most regions of the world. This review summarizes data from randomized, controlled trials that included a paediatric population, and it provides some evidence-based visions for the possible broader utilization of CGM, also for incorporation into insulin delivery devices that enable a closed-loop insulin delivery.

Continuous subcutaneous insulin infusion in diabetes: patient populations, safety, efficacy, and pharmacoeconomics

The level of glycaemic control necessary to achieve optimal short-term and long-term outcomes in subjects with type 1 diabetes mellitus (T1DM) typically requires intensified insulin therapy using multiple daily injections or continuous subcutaneous insulin infusion. For continuous subcutaneous insulin infusion, the insulins of choice are the rapid-acting insulin analogues, insulin aspart, insulin lispro and insulin glulisine. The advantages of continuous subcutaneous insulin infusion over multiple daily injections in adult and paediatric populations with T1DM include superior glycaemic control, lower insulin requirements and better health-related quality of life/patient satisfaction. An association between continuous subcutaneous insulin infusion and reduced hypoglycaemic risk is more consistent in children/adolescents than in adults. The use of continuous subcutaneous insulin infusion is widely recommended in both adult and paediatric T1DM populations but is limited in pregnant patients and those with type 2 diabetes mellitus. All available rapid-acting insulin analogues are approved for use in adult, paediatric and pregnant populations. However, minimum patient age varies (insulin lispro: no minimum; insulin aspart: ≥2 years; insulin glulisine: ≥6 years) and experience in pregnancy ranges from extensive (insulin aspart, insulin lispro) to limited (insulin glulisine). Although more expensive than multiple daily injections, continuous subcutaneous insulin infusion is cost-effective in selected patient groups. This comprehensive review focuses on the European situation and summarises evidence for the efficacy and safety of continuous subcutaneous insulin infusion, particularly when used with rapid-acting insulin analogues, in adult, paediatric and pregnant populations. The review also discusses relevant European guidelines; reviews issues that surround use of this technology; summarises the effects of continuous subcutaneous insulin infusion on patients' health-related quality of life; reviews relevant pharmacoeconomic data; and discusses recent advances in pump technology, including the development of closed-loop 'artificial pancreas' systems. © 2015 The Authors. Diabetes/Metabolism Research and Reviews Published by John Wiley & Sons Ltd.

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.

Identification of Main Factors Explaining Glucose Dynamics During and Immediately After Moderate Exercise in Patients With Type 1 Diabetes

BACKGROUND

Physical activity is recommended for patients with type 1 diabetes (T1D). However, without proper management, it can lead to higher risk for hypoglycemia and impaired glycemic control. In this work, we identify the main factors explaining the blood glucose dynamics during exercise in T1D. We then propose a prediction model to quantify the glycemic drop induced by a mild to moderate physical activity.

METHODS

A meta-data analysis was conducted over 59 T1D patients from 4 different studies in the United States and France (37 men and 22 women; 47 adults; weight, 71.4 ± 10.6 kg; age, 42 ± 10 years; 12 adolescents: weight, 60.7 ± 12.5 kg; age, 14.0 ± 1.4 years). All participants had physical activity between 3 and 5 pm at a mild to moderate intensity for approximately 30 to 45 min. A multiple linear regression analysis was applied to the data to identify the main parameters explaining the glucose dynamics during such physical activity.

RESULTS

The blood glucose at the beginning of exercise ([Formula: see text]), the ratio of insulin on board over total daily insulin ([Formula: see text]) and the age as a categorical variable (1 for adult, 0 for adolescents) were significant factors involved in glucose evolution at exercise (all P < .05). The multiple linear regression model has an R-squared of .6.

CONCLUSIONS

The main factors explaining glucose dynamics in the presence of mild-to-moderate exercise in T1D have been identified. The clinical parameters are formally quantified using real data collected during clinical trials. The multiple linear regression model used to predict blood glucose during exercise can be applied in closed-loop control algorithms developed for artificial pancreas.

Adjustment of Open-Loop Settings to Improve Closed-Loop Results in Type 1 Diabetes: A Multicenter Randomized Trial

CONTEXT

Closed-loop control (CLC) relies on an individual's open-loop insulin pump settings to initialize the system. Optimizing open-loop settings before using CLC usually requires significant time and effort.

OBJECTIVE

The objective was to investigate the effects of a one-time algorithmic adjustment of basal rate and insulin to carbohydrate ratio open-loop settings on the performance of CLC.

DESIGN

This study reports a multicenter, outpatient, randomized, crossover clinical trial.

PATIENTS

Thirty-seven adults with type 1 diabetes were enrolled at three clinical sites.

INTERVENTIONS

Each subject's insulin pump settings were subject to a one-time algorithmic adjustment based on 1 week of open-loop (i.e., home care) data collection. Subjects then underwent two 27-hour periods of CLC in random order with either unchanged (control) or algorithmic adjusted basal rate and carbohydrate ratio settings (adjusted) used to initialize the zone-model predictive control artificial pancreas controller. Subject's followed their usual meal-plan and had an unannounced exercise session.

MAIN OUTCOMES AND MEASURES

Time in the glucose range was 80-140 mg/dL, compared between both arms.

RESULTS

Thirty-two subjects completed the protocol. Median time in CLC was 25.3 hours. The median time in the 80-140 mg/dl range was similar in both groups (39.7% control, 44.2% adjusted). Subjects in both arms of CLC showed minimal time spent less than 70 mg/dl (median 1.34% and 1.37%, respectively). There were no significant differences more than 140 mg/dL.

CONCLUSIONS

A one-time algorithmic adjustment of open-loop settings did not alter glucose control in a relatively short duration outpatient closed-loop study. The CLC system proved very robust and adaptable, with minimal (<2%) time spent in the hypoglycemic range in either arm.

Outpatient overnight glucose control with dual-hormone artificial pancreas, single-hormone artificial pancreas, or conventional insulin pump therapy in children and adolescents with type 1 diabetes: an open-label, randomised controlled trial

BACKGROUND

Additional benefits of the dual-hormone (insulin and glucagon) artificial pancreas compared with the single-hormone (insulin alone) artificial pancreas have not been assessed in young people in outpatient unrestricted conditions. We evaluated the efficacy of three systems for nocturnal glucose control in children and adolescents with type 1 diabetes.

METHODS

We did a randomised, three-way, crossover trial in children aged 9-17 years with type 1 diabetes attending a diabetes camp in Canada. With use of sealed envelopes, children were randomly assigned in a 1:1:1:1:1:1 ratio with blocks of six to different sequences of the three interventions (single-hormone artificial pancreas, dual-hormone artificial pancreas, and conventional continuous subcutaneous insulin pump therapy). Each intervention was applied for 3 consecutive nights. Participants, study staff, and endpoint assessors were not masked. The primary outcome was the percentage of time spent with glucose concentrations lower than 4·0 mmol/L from 2300 h to 0700 h. Analysis was by intention to treat. A p value of less than 0·0167 was regarded as significant. This study is registered with ClinicalTrials.gov, number NCT02189694.

FINDINGS

Between June 30, 2014, and Aug 9, 2014, we enrolled 33 children of mean age 13·3 years (SD 2·3; range 9-17). The time spent at a glucose concentration lower than 4·0 mmol/L was median 0% (IQR 0·0-2·4) during nights with the dual-hormone artificial pancreas, 3·1% (0·0-6·9) during nights with the single-hormone artificial pancreas (p=0·032), and 3·4% (0-11·0) during nights with conventional pump therapy (p=0·0048 compared with dual-hormone artificial pancreas and p=0·32 compared with single-hormone artificial pancreas). 15 hypoglycaemic events (<3·1 mmol/L for 20 min measured by sensor then confirmed with capillary glucose <4·0 mmol/L) were noted during nights with conventional pump therapy compared with four events with the single-hormone system and no events with the dual-hormone system. None of the assessed outcomes varied with the order in which children and young adults were assigned interventions.

INTERPRETATION

The dual-hormone artificial pancreas could improve nocturnal glucose control in children and adolescents with type 1 diabetes. Longer and larger outpatient studies are now needed.

FUNDING

Canadian Diabetes Association, Fondation J A De Sève.

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.

Multicenter outpatient dinner/overnight reduction of hypoglycemia and increased time of glucose in target with a wearable artificial pancreas using modular model predictive control in adults with type 1 diabetes

AIMS

To test in an outpatient setting the safety and efficacy of continuous subcutaneous insulin infusion (CSII) driven by a modular model predictive control (MMPC) algorithm informed by continuous glucose monitoring (CGM) measurement.

METHODS

13 patients affected by type 1 diabetes participated to a non-randomized outpatient 42-h experiment that included two evening meals and overnight periods (in short, dinner & night periods). CSII was patient-driven during dinner & night period 1 and MMPC-driven during dinner&night period 2. The study was conducted in hotels, where patients could move around freely. A CGM system (G4 Platinum; Dexcom Inc., San Diego, CA, USA) and insulin pump (AccuChek Combo; Roche Diagnostics, Mannheim, Germany) were connected wirelessly to a smartphone-based platform (DiAs, Diabetes Assistant; University of Virginia, Charlottesville, VA, USA) during both periods.

RESULTS

A significantly lower percentage of time spent with glucose levels <3.9 mmol/l was achieved in period 2 compared with period 1: 1.96 ± 4.56% vs 12.76 ± 15.84% (mean ± standard deviation, p < 0.01), together with a greater percentage of time spent in the 3.9-10 mmol/l target range: 83.56 ± 14.02% vs 62.43 ± 29.03% (p = 0.04). In addition, restricting the analysis to the overnight phases, a lower percentage of time spent with glucose levels <3.9 mmol/l (1.92 ± 4.89% vs 12.7 ± 19.75%; p = 0.03) was combined with a greater percentage of time spent in 3.9-10 mmol/l target range in period 2 compared with period 1 (92.16 ± 8.03% vs 63.97 ± 2.73%; p = 0.01). Average glucose levels were similar during both periods.

CONCLUSIONS

The results suggest that MMPC managed by a wearable system is safe and effective during evening meal and overnight. Its sustained use during this period is currently being tested in an ongoing randomized 2-month study.

Psychosocial aspects of closed- and open-loop insulin delivery: closing the loop in adults with Type 1 diabetes in the home setting

AIMS

To explore the psychosocial experiences of closed-loop technology and to compare ratings of closed- and open-loop technology for adults with Type 1 diabetes taking part in a randomized crossover study.

METHODS

Adults (aged > 18 years) on insulin pump therapy were recruited to receive a first phase of either real-time continuous glucose monitoring with overnight closed-loop or real-time continuous glucose monitoring alone (open-loop) followed by a second phase of the alternative treatment in random order, at home for 4 weeks, unsupervised. Participants were invited to share their views in semi-structured interviews. The impact of the closed-loop technology, positive and negative aspects of living with the device overnight, along with the hopes and anxieties of the participants, were explored.

RESULTS

The participants in the trial were 24 adults with a mean (sd) age of 43 (12) years, of whom 54% were men. The mean (range) interview duration was 26 (12-46) min. Content and thematic analysis showed the following key positive themes: improved blood glucose control (n = 16); reassurance/reduced worry (n = 16); improved overnight control leading to improved daily functioning and diabetes control (n = 16); and improved sleep (n = 8). The key negative themes were: technical difficulties (n = 24); intrusiveness of alarms (n = 13); and size of equipment (n = 7). Of the 24 participant, 20 would recommend the closed-loop technology.

CONCLUSIONS

Closed-loop therapy has positive effects when it works in freeing participants from the demands of self-management. The downside was technical difficulties, particularly concerning the pump and 'connectivity', which it is hoped will improve. Future research should continue to explore the acceptability of the closed-loop system as a realistic therapy option, taking account of user concerns as new systems are designed. Failure to do this may reduce the eventual utility of new systems.

Physical activity and type 1 diabetes: time for a rewire?

While being physically active bestows many health benefits on individuals with type 1 diabetes, their overall blood glucose control is not enhanced without an effective balance of insulin dosing and food intake to maintain euglycemia before, during, and after exercise of all types. At present, a number of technological advances are already available to insulin users who desire to be physically active with optimal blood glucose control, although a number of limitations to those devices remain. In addition to continued improvements to existing technologies and introduction of new ones, finding ways to integrate all of the available data to optimize blood glucose control and performance during and following exercise will likely involve development of "smart" calculators, enhanced closed-loop systems that are able to use additional inputs and learn, and social aspects that allow devices to meet the needs of the users.

Unsupervised home use of an overnight closed-loop system over 3-4 weeks: a pooled analysis of randomized controlled studies in adults and adolescents with type 1 diabetes

AIMS

To compare overnight closed-loop and sensor-augmented pump therapy in patients with type 1 diabetes by combining data collected during free-living unsupervised randomized crossover home studies.

METHODS

A total of 40 participants with type 1 diabetes, of whom 24 were adults [mean ± standard deviation (s.d.) age 43 ± 12 years and glycated haemoglobin (HbA1c) 8.0 ± 0.9%] and 16 were adolescents (mean ± s.d. age 15.6 ± 3.6 years and HbA1c 8.1 ± 0.8%), underwent two periods of sensor-augmented pump therapy in the home setting, in combination with or without an overnight closed-loop insulin delivery system that uses a model predictive control algorithm to direct insulin delivery. The order of the two interventions was random; each period lasted 4 weeks in adults and 3 weeks in adolescents. The primary outcome was time during which sensor glucose readings were in the target range of 3.9-8.0 mmol/l.

RESULTS

The proportion of time when sensor glucose was in the target range (3.9-8.0 mmol/l) overnight (between 24:00 and 08:00 hours) was 18.5% greater during closed-loop insulin delivery than during sensor-augmented therapy (p < 0.001). Closed-loop therapy significantly reduced mean overnight glucose levels by 0.9 mmol/l (p < 0.001), with no difference in glycaemic variability, as measured by the standard deviation of sensor glucose. Time spent above the target range was reduced (p = 0.001), as was time spent in hypoglycaemia (<3.9 mmol/l; p = 0.014) during closed-loop therapy. Lower mean overnight glucose levels during closed-loop therapy were brought about by increased overnight insulin delivery (p < 0.001) without changes to the total daily delivery (p = 0.84).

CONCLUSION

Overnight closed-loop insulin therapy at home in adults and adolescents with type 1 diabetes is feasible, showing improvements in glucose control and reducing the risk of nocturnal hypoglycaemia.

Progress of artificial pancreas devices towards clinical use: the first outpatient studies

PURPOSE OF REVIEW

This article describes recent progress in the automated control of glycemia in type 1 diabetes with artificial pancreas devices that combine continuous glucose monitoring with automated decision-making and insulin delivery.

RECENT FINDINGS

After a gestation period of closely supervised feasibility studies in research centers, the last 2 years have seen publication of studies testing these devices in outpatient environments, and many more such studies are ongoing. The most basic form of automation, suspension of insulin delivery for actual or predicted hypoglycemia, has been shown to be effective and well tolerated, and a first-generation device has actually reached the market. Artificial pancreas devices that actively dose insulin fall into two categories, those that dose insulin alone and those that also use glucagon to prevent and treat hypoglycemia (bihormonal artificial pancreas). Initial outpatient clinical trials have shown that both strategies can improve glycemic management in comparison with patient-controlled insulin pump therapy, but only the bihormonal strategy has been tested without restrictions on exercise.

SUMMARY

Artificial pancreas technology has the potential to reduce acute and chronic complications of diabetes and mitigate the burden of diabetes self-management. Successful outpatient studies bring these technologies one step closer to availability for patients.

Psychosocial assessment of artificial pancreas (AP): commentary and review of existing measures and their applicability in AP research

AIM

This study aimed to systematically review the evidence base for the use of existing psychological and psychosocial measures suitable for use in artificial pancreas (AP) research.

MATERIALS AND METHODS

This systematic review of published literature, gray literature, previous systematic reviews, and qualitative and economic studies was conducted using terms and abbreviations synonymous with diabetes, AP, and quality of life (QoL).

RESULTS

Two hundred ninety-two abstracts were identified that reported psychosocial assessment of diabetes-related technologies. Of these, nine met the inclusion criteria and were included. Only four of 103 ongoing trials evaluated psychosocial aspects as an outcome in the trial. Of these, treatment satisfaction, acceptance and use intention of AP, fear of hypoglycemia episodes, satisfaction with AP, and an unspecified QoL measure were used.

CONCLUSIONS

A better understanding of the psychosocial side of AP systems and the extent to which human factors play a role in the uptake and efficient use of these systems will ultimately lead to the most benefit for people with diabetes.