Outpatient glycemic control with a bionic pancreas in type 1 diabetes

Safety, efficacy and glucose turnover of reduced prandial boluses during closed-loop therapy in adolescents with type 1 diabetes: a randomized clinical trial

AIMS

To evaluate safety, efficacy and glucose turnover during closed-loop with meal announcement using reduced prandial insulin boluses in adolescents with type 1 diabetes (T1D).

METHODS

We conducted a randomized crossover study comparing closed-loop therapy with standard prandial insulin boluses versus closed-loop therapy with prandial boluses reduced by 25%. Eight adolescents with T1D [3 males; mean (standard deviation) age 15.9 (1.5) years, glycated haemoglobin 74 (17) mmol/mol; median (interquartile range) total daily dose 0.9 (0.7, 1.1) IU/kg/day] were studied on two 36-h-long visits. In random order, subjects received closed-loop therapy with either standard or reduced insulin boluses administered with main meals (50-80 g carbohydrates) but not with snacks (15-30 g carbohydrates). Stable-label tracer dilution methodology measured total glucose appearance (Ra_total) and glucose disposal (Rd).

RESULTS

The median (interquartile range) time spent in target (3.9-10 mmol/l) was similar between the two interventions [74 (66, 84)% vs 80 (65, 96)%; p = 0.87] as was time spent above 10 mmol/l [21.8 (16.3, 33.5)% vs 18.0 (4.1, 34.2)%; p = 0.87] and below 3.9 mmol/l [0 (0, 1.5)% vs 0 (0, 1.8)%; p = 0.88]. Mean plasma glucose was identical during the two interventions [8.4 (0.9) mmol/l; p = 0.98]. Hypoglycaemia occurred once 1.5 h post-meal during closed-loop therapy with standard bolus. Overall insulin delivery was lower with reduced prandial boluses [61.9 (55.2, 75.0) vs 72.5 (63.6, 80.3) IU; p = 0.01] and resulted in lower mean plasma insulin concentration [186 (171, 260) vs 252 (198, 336) pmol/l; p = 0.002]. Lower plasma insulin was also documented overnight [160 (136, 192) vs 191 (133, 252) pmol/l; p = 0.01, pooled nights]. Ra_total was similar [26.3 (21.9, 28.0) vs 25.4 (21.0, 29.2) µmol/kg/min; p = 0.19] during the two interventions as was Rd [25.8 (21.0, 26.9) vs 25.2 (21.2, 28.8) µmol/kg/min; p = 0.46].

CONCLUSIONS

A 25% reduction in prandial boluses during closed-loop therapy maintains similar glucose control in adolescents with T1D whilst lowering overall plasma insulin levels. It remains unclear whether closed-loop therapy with a 25% reduction in prandial boluses would prevent postprandial hypoglycaemia.

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.

Home Use of an Artificial Beta Cell in Type 1 Diabetes

BACKGROUND

The feasibility, safety, and efficacy of prolonged use of an artificial beta cell (closed-loop insulin-delivery system) in the home setting have not been established.

METHODS

In two multicenter, crossover, randomized, controlled studies conducted under free-living home conditions, we compared closed-loop insulin delivery with sensor-augmented pump therapy in 58 patients with type 1 diabetes. The closed-loop system was used day and night by 33 adults and overnight by 25 children and adolescents. Participants used the closed-loop system for a 12-week period and sensor-augmented pump therapy (control) for a similar period. The primary end point was the proportion of time that the glucose level was between 70 mg and 180 mg per deciliter for adults and between 70 mg and 145 mg per deciliter for children and adolescents.

RESULTS

Among adults, the proportion of time that the glucose level was in the target range was 11.0 percentage points (95% confidence interval [CI], 8.1 to 13.8) greater with the use of the closed-loop system day and night than with control therapy (P<0.001). The mean glucose level was lower during the closed-loop phase than during the control phase (difference, -11 mg per deciliter; 95% CI, -17 to -6; P<0.001), as were the area under the curve for the period when the glucose level was less than 63 mg per deciliter (39% lower; 95% CI, 24 to 51; P<0.001) and the mean glycated hemoglobin level (difference, -0.3%; 95% CI, -0.5 to -0.1; P=0.002). Among children and adolescents, the proportion of time with the nighttime glucose level in the target range was higher during the closed-loop phase than during the control phase (by 24.7 percentage points; 95% CI, 20.6 to 28.7; P<0.001), and the mean nighttime glucose level was lower (difference, -29 mg per deciliter; 95% CI, -39 to -20; P<0.001). The area under the curve for the period in which the day-and-night glucose levels were less than 63 mg per deciliter was lower by 42% (95% CI, 4 to 65; P=0.03). Three severe hypoglycemic episodes occurred during the closed-loop phase when the closed-loop system was not in use.

CONCLUSIONS

Among patients with type 1 diabetes, 12-week use of a closed-loop system, as compared with sensor-augmented pump therapy, improved glucose control, reduced hypoglycemia, and, in adults, resulted in a lower glycated hemoglobin level. (Funded by the JDRF and others; AP@home04 and APCam08 ClinicalTrials.gov numbers, NCT01961622 and NCT01778348.).

Metabolic Control With the Bio-inspired Artificial Pancreas in Adults With Type 1 Diabetes: A 24-Hour Randomized Controlled Crossover Study

BACKGROUND

The Bio-inspired Artificial Pancreas (BiAP) is a closed-loop insulin delivery system based on a mathematical model of beta-cell physiology and implemented in a microchip within a low-powered handheld device. We aimed to evaluate the safety and efficacy of the BiAP over 24 hours, followed by a substudy assessing the safety of the algorithm without and with partial meal announcement. Changes in lactate and 3-hydroxybutyrate concentrations were investigated for the first time during closed-loop.

METHODS

This is a prospective randomized controlled open-label crossover study. Participants were randomly assigned to attend either a 24-hour closed-loop visit connected to the BiAP system or a 24-hour open-loop visit (standard insulin pump therapy). The primary outcome was percentage time spent in target range (3.9-10 mmol/l) measured by sensor glucose. Secondary outcomes included percentage time in hypoglycemia (<3.9 mmol/l) and hyperglycemia (>10 mmol/l). Participants were invited to attend for an additional visit to assess the BiAP without and with partial meal announcements.

RESULTS

A total of 12 adults with type 1 diabetes completed the study (58% female, mean [SD] age 45 [10] years, BMI 25 [4] kg/m(2), duration of diabetes 22 [12] years and HbA1c 7.4 [0.7]% [58 (8) mmol/mol]). The median (IQR) percentage time in target did not differ between closed-loop and open-loop (71% vs 66.9%, P = .9). Closed-loop reduced time spent in hypoglycemia from 17.9% to 3.0% (P < .01), but increased time was spent in hyperglycemia (10% vs 28.9%, P = .01). The percentage time in target was higher when all meals were announced during closed-loop compared to no or partial meal announcement (65.7% [53.6-80.5] vs 45.5% [38.2-68.3], P = .12).

CONCLUSIONS

The BiAP is safe and achieved equivalent time in target as measured by sensor glucose, with improvement in hypoglycemia, when compared to standard pump therapy.

Effect of Repeated Glucagon Doses on Hepatic Glycogen in Type 1 Diabetes: Implications for a Bihormonal Closed-Loop System

OBJECTIVE

To evaluate subjects with type 1 diabetes for hepatic glycogen depletion after repeated doses of glucagon, simulating delivery in a bihormonal closed-loop system.

RESEARCH DESIGN AND METHODS

Eleven adult subjects with type 1 diabetes participated. Subjects underwent estimation of hepatic glycogen using (13)C MRS. MRS was performed at the following four time points: fasting and after a meal at baseline, and fasting and after a meal after eight doses of subcutaneously administered glucagon at a dose of 2 µg/kg, for a total mean dose of 1,126 µg over 16 h. The primary and secondary end points were, respectively, estimated hepatic glycogen by MRS and incremental area under the glucose curve for a 90-min interval after glucagon administration.

RESULTS

In the eight subjects with complete data sets, estimated glycogen stores were similar at baseline and after repeated glucagon doses. In the fasting state, glycogen averaged 21 ± 3 g/L before glucagon administration and 25 ± 4 g/L after glucagon administration (mean ± SEM) (P = NS). In the fed state, glycogen averaged 40 ± 2 g/L before glucagon administration and 34 ± 4 g/L after glucagon administration (P = NS). With the use of an insulin action model, the rise in glucose after the last dose of glucagon was comparable to the rise after the first dose, as measured by the 90-min incremental area under the glucose curve.

CONCLUSIONS

In adult subjects with well-controlled type 1 diabetes (mean A1C 7.2%), glycogen stores and the hyperglycemic response to glucagon administration are maintained even after receiving multiple doses of glucagon. This finding supports the safety of repeated glucagon delivery in the setting of a bihormonal closed-loop system.

Endocrinology research-reflecting on the past decade and looking to the next

The inaugural issue of this journal, published in November 2005, included articles on thyroid cancer, type 2 diabetes mellitus, the metabolic syndrome, pituitary adenomas and obesity. 10 years later, we are still publishing articles on these topics (and many others). Although a great deal of progress has been made in our understanding of the pathogenesis, diagnosis and treatment of diseases of the endocrine system over the past 10 years, many challenges still remain. For this Viewpoint, we have asked five of our Advisory Board Members to comment on the progress and challenges from the past 10 years. They were also asked to offer their thoughts on where money should be spent going forward, and their predictions for what advances might be achieved in the next 10 years.

The relationship between carbohydrate and the mealtime insulin dose in type 1 diabetes

A primary focus of the nutritional management of type 1 diabetes has been on matching prandial insulin therapy with carbohydrate amount consumed. Different methods exist to quantify carbohydrate including counting in one gram increments, 10g portions or 15g exchanges. Clinicians have assumed that counting in one gram increments is necessary to precisely dose insulin and optimize postprandial control. Carbohydrate estimations in portions or exchanges have been thought of as inadequate because they may result in less precise matching of insulin dose to carbohydrate amount. However, studies examining the impact of errors in carbohydrate quantification on postprandial glycemia challenge this commonly held view. In addition it has been found that a single mealtime bolus of insulin can cover a range of carbohydrate intake without deterioration in postprandial control. Furthermore, limitations exist in the accuracy of the nutrition information panel on a food label. This article reviews the relationship between carbohydrate quantity and insulin dose, highlighting limitations in the evidence for a linear association. These insights have significant implications for patient education and mealtime insulin dose calculations.

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.

Current management of diabetes mellitus and future directions in care

The last 90 years have seen considerable advances in the management of type 1 and type 2 diabetes. Prof MacLean of Guy's Hospital wrote in the Postgraduate Medical Journal in 1926 about the numerous challenges that faced patients and their healthcare professionals in delivering safe and effective diabetes care at that time. The discovery of insulin in 1922 heralded a new age in enabling long-term glycaemic control, which reduced morbidity and mortality. Thirty years later, the first oral agents for diabetes, the biguanides and sulfonylureas, appeared and freed type 2 patients from having to inject insulin following diagnosis. Improvements in insulin formulations over the decades, including rapid-acting and long-acting insulin analogues that more closely mimic physiological insulin secretion, have increased the flexibility and efficacy of type 1 diabetes management. The last two decades have seen major advances in technology, which has manifested in more accurate glucose monitoring systems and insulin delivery devices ('insulin pump'). Increased understanding of the pathophysiological deficits underlying type 2 diabetes has led to the development of targeted therapeutic approaches such as on the small intestine (glucagon-like peptide-1 receptor analogues and dipeptidyl-peptidase IV inhibitors) and kidneys (sodium-glucose cotransporter-2 inhibitors). A patient-centred approach delivered by a multidisciplinary team is now advocated. Glycaemic targets are set according to individual circumstances, taking into account factors such as weight, hypoglycaemia risk and patient preference. Stepwise treatment guidelines devised by international diabetes organisations standardise and rationalise management. Structured education programmes and psychological support are now well-established as essential for improving patient motivation and self-empowerment. Large multicentre randomised trials have confirmed the effectiveness of intensive glycaemic control on microvascular outcomes, but macrovascular outcomes and cardiovascular safety remain controversial with several glucose-lowering agents. Future directions in diabetes care include strategies such as the 'bionic pancreas', stem cell therapy and targeting the intestinal microbiome. All of these treatments are still being refined, and it may be several decades before they are clinically useful. Prevention and cure of diabetes is the Holy Grail but remain elusive due to lack of detailed understanding of the metabolic, genetic and immunological causes that underpin diabetes. Much progress has been made since the time of Prof MacLean 90 years ago, but there are still great strides to be taken before the life of the patient with diabetes improves even more significantly.

Classification of Physical Activity: Information to Artificial Pancreas Control Systems in Real Time

Physical activity has a wide range of effects on glucose concentrations in type 1 diabetes (T1D) depending on the type (ie, aerobic, anaerobic, mixed) and duration of activity performed. This variability in glucose responses to physical activity makes the development of artificial pancreas (AP) systems challenging. Automatic detection of exercise type and intensity, and its classification as aerobic or anaerobic would provide valuable information to AP control algorithms. This can be achieved by using a multivariable AP approach where biometric variables are measured and reported to the AP at high frequency. We developed a classification system that identifies, in real time, the exercise intensity and its reliance on aerobic or anaerobic metabolism and tested this approach using clinical data collected from 5 persons with T1D and 3 individuals without T1D in a controlled laboratory setting using a variety of common types of physical activity. The classifier had an average sensitivity of 98.7% for physiological data collected over a range of exercise modalities and intensities in these subjects. The classifier will be added as a new module to the integrated multivariable adaptive AP system to enable the detection of aerobic and anaerobic exercise for enhancing the accuracy of insulin infusion strategies during and after exercise.

Switched LPV Glucose Control in Type 1 Diabetes

OBJECTIVE

The purpose of this paper is to regulate the blood glucose level in Type 1 Diabetes Mellitus patients with a practical and flexible procedure that can switch among a finite number of distinct controllers, depending on the user's choice.

METHODS

A switched linear parameter-varying controller with multiple switching regions, related to hypo-, hyper-, and euglycemia situations, is designed. The key feature is to arrange the controller into a framework that provides stability and performance guaranty.

RESULTS

The closed-loop performance is tested on the complete in silico adult cohort of the UVA/Padova metabolic simulator, which has been accepted by the U.S. Food and Drug Administration in lieu of animal trials. The outcome produces comparable or improved results with respect to previous works.

CONCLUSION

The strategy is practical because it is based on a model tuned only with a priori patient information in order to cover the interpatient uncertainty. Results confirm that this control structure yields tangible improvements in minimizing risks of hyper- and hypoglycemia in scenarios with unannounced meals.

SIGNIFICANCE

This flexible procedure opens the possibility of taking into account, at the design stage, unannounced meals and/or patients' physical exercise.

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.

Dual-hormone treatment with insulin and glucagon in patients with type 1 diabetes

Intensive insulin treatment in type 1 diabetes reduces the incidence and slows the progression of microvascular and macrovascular complications; however, it is associated with an increased risk of hypoglycaemia and weight gain. In this review, we propose dual-hormone treatment with insulin and glucagon as a method for achieving near normalization of blood glucose levels without increasing hypoglycaemia frequency and weight gain. We briefly summarize glucagon pathophysiology in type 1 diabetes as well as the current applications of glucagon for the treatment of hypoglycaemia. Until now, the use of glucagon has been limited by the need for reconstitution immediately before use, because of instability of the available compounds; however, stabile compounds are soon to be launched and will render long-term intensive dual-hormone treatment in type 1 diabetes possible.

Stress Testing of an Artificial Pancreas System With Pizza and Exercise Leads to Improvements in the System's Fuzzy Logic Controller

BACKGROUND

Under controlled conditions, the Dose Safety artificial pancreas (AP) system controller, which utilizes "fuzzy logic" (FL) methodology to calculate and deliver appropriate insulin dosages based on changes in blood glucose, successfully managed glycemic excursions. The aim of this study was to show whether stressing the system with pizza (high carbohydrate/high fat) meals and exercise would reveal deficits in the performance of the Dose Safety FL controller (FLC) and lead to improvements in the dosing matrix.

METHODS

Ten subjects with type 1 diabetes (T1D) were enrolled and participated in 30 studies (17 meal, 13 exercise) using 2 versions of the FLC. After conducting 13 studies with the first version (FLC v2.0), interim results were evaluated and the FLC insulin-dosing matrix was modified to create a new controller version (FLC v2.1) that was validated through regression testing using v2.0 CGM datasets prior to its use in clinical studies. The subsequent 17 studies were performed using FLC v2.1.

RESULTS

Use of FLC v2.1 vs FLC v2.0 in the pizza meal tests showed improvements in mean blood glucose (205 mg/dL vs 232 mg/dL, P = .04). FLC v2.1 versus FLC v2.0 in exercise tests showed improvements in mean blood glucose (146 mg/dL vs 201 mg/dL, P = .004), percentage time spent >180 mg/dL (19.3% vs 46.7%, P = .001), and percentage time spent 70-180 mg/dL (80.0% vs 53.3%, P = .002).

CONCLUSION

Stress testing the AP system revealed deficits in the FLC performance, which led to adjustments to the dosing matrix followed by improved FLC performance when retested.

Combining glucose monitoring and insulin delivery into a single device: current progress and ongoing challenges of the artificial pancreas

Despite the widespread availability of insulin pumps, continuous glucose sensors, and insulin analogs with rapid-acting pharmacokinetic profiles, most people with type 1 diabetes fail to meet recommended glycemic targets, rates of severe hypoglycemia remain unacceptably high, and the burden of care on patients and loved ones exacts an enormous psychosocial toll. The combination of continuous glucose monitoring with insulin delivery into an integrated automated system promises to improve diabetes control while at the same time reduce the burden of care. A wide variety of automated insulin delivery systems, ranging in scope from simple pump suspension to reduce hypoglycemia, to complex multiple hormone systems under separate regulation and delivery, have been studied in both controlled inpatient settings and more free-ranging outpatient environments. Preliminary findings have been positive, with most studies demonstrating reduction in overall glucose levels, increased time-in-target range, and reductions in exposure to hypoglycemia. As these systems move closer to commercialization, the focus of ongoing efforts will need to address the continuing challenges of sensor accuracy and reliability, connectivity issues, and human factors considerations.

A case study in open source innovation: developing the Tidepool Platform for interoperability in type 1 diabetes management

Objective Develop a device-agnostic cloud platform to host diabetes device data and catalyze an ecosystem of software innovation for type 1 diabetes (T1D) management.

Materials and Methods An interdisciplinary team decided to establish a nonprofit company, Tidepool, and build open-source software.

Results Through a user-centered design process, the authors created a software platform, the Tidepool Platform, to upload and host T1D device data in an integrated, device-agnostic fashion, as well as an application (“app”), Blip, to visualize the data. Tidepool’s software utilizes the principles of modular components, modern web design including REST APIs and JavaScript, cloud computing, agile development methodology, and robust privacy and security.

Discussion By consolidating the currently scattered and siloed T1D device data ecosystem into one open platform, Tidepool can improve access to the data and enable new possibilities and efficiencies in T1D clinical care and research. The Tidepool Platform decouples diabetes apps from diabetes devices, allowing software developers to build innovative apps without requiring them to design a unique back-end (e.g., database and security) or unique ways of ingesting device data. It allows people with T1D to choose to use any preferred app regardless of which device(s) they use.

Conclusion The authors believe that the Tidepool Platform can solve two current problems in the T1D device landscape: 1) limited access to T1D device data and 2) poor interoperability of data from different devices. If proven effective, Tidepool’s open source, cloud model for health data interoperability is applicable to other healthcare use cases.

Glucagon sensitivity and clearance in type 1 diabetes: insights from in vivo and in silico experiments

Glucagon use in artificial pancreas for type 1 diabetes (T1D) is being explored for prevention and rescue from hypoglycemia. However, the relationship between glucagon stimulation of endogenous glucose production (EGP) viz., hepatic glucagon sensitivity, and prevailing glucose concentrations has not been examined. To test the hypothesis that glucagon sensitivity is increased at hypoglycemia vs. euglycemia, we studied 29 subjects with T1D randomized to a hypoglycemia or euglycemia clamp. Each subject was studied at three glucagon doses at euglycemia or hypoglycemia, with EGP measured by isotope dilution technique. The peak EGP increments and the integrated EGP response increased with increasing glucagon dose during euglycemia and hypoglycemia. However, the difference in dose response based on glycemia was not significant despite higher catecholamine concentrations in the hypoglycemia group. Knowledge of glucagon's effects on EGP was used to develop an in silico glucagon action model. The model-derived output fitted the obtained data at both euglycemia and hypoglycemia for all glucagon doses tested. Glucagon clearance did not differ between glucagon doses studied in both groups. Therefore, the glucagon controller of a dual hormone control system may not need to adjust glucagon sensitivity, and hence glucagon dosing, based on glucose concentrations during euglycemia and hypoglycemia.

Clinical implementation of islet transplantation: A current assessment

Beta-cell replacement is the only physiologically relevant alternative to insulin injections in patients with type 1 diabetes (T1D). Pancreas and islet transplantation from deceased organ donors can provide a new beta-cell pool to produce insulin, help blood glucose management, and delay secondary diabetes complications. For children and adolescents with T1D, whole pancreas transplantation is not a viable option because of surgical complications, whereas islet transplantation, even if it is procedurally simpler, must still overcome the burden of immunosuppression to become a routine therapy for children in the future.

Ethical considerations in tissue engineering research: Case studies in translation

Tissue engineering research is a complex process that requires investigators to focus on the relationship between their research and anticipated gains in both knowledge and treatment improvements. The ethical considerations arising from tissue engineering research are similarly complex when addressing the translational progression from bench to bedside, and investigators in the field of tissue engineering act as moral agents at each step of their research along the translational pathway, from early benchwork and preclinical studies to clinical research. This review highlights the ethical considerations and challenges at each stage of research, by comparing issues surrounding two translational tissue engineering technologies: the bioartificial pancreas and a tissue engineered skeletal muscle construct. We present relevant ethical issues and questions to consider at each step along the translational pathway, from the basic science bench to preclinical research to first-in-human clinical trials. Topics at the bench level include maintaining data integrity, appropriate reporting and dissemination of results, and ensuring that studies are designed to yield results suitable for advancing research. Topics in preclinical research include the principle of "modest translational distance" and appropriate animal models. Topics in clinical research include key issues that arise in early-stage clinical trials, including selection of patient-subjects, disclosure of uncertainty, and defining success. The comparison of these two technologies and their ethical issues brings to light many challenges for translational tissue engineering research and provides guidance for investigators engaged in development of any tissue engineering technology.

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.

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.

Performance of an Electronic Diary System for Intensive Insulin Management in Global Diabetes Clinical Trials

BACKGROUND

This report describes the performance of a wireless electronic diary (e-diary) system for data collection and enhanced patient-investigator interactions during intensive insulin management in diabetes clinical trials.

MATERIALS AND METHODS

We implemented a customized electronic communication system featuring an e-diary and a Web portal in three global, randomized, controlled Phase 3 clinical trials testing basal insulin peglispro compared with insulin glargine, both combined with prandial insulin lispro, in patients with type 1 or type 2 diabetes mellitus (T1DM and T2DM, respectively). We collected data during 28 weeks of study e-diary use for the report.

RESULTS

Patients (n=2,938) in 31 countries used e-diaries to transmit 2,439,087 blood glucose (BG) values, 96% of which were associated by the patient with a protocol time point during the 72-h response window. Of 208,192 hypoglycemia events captured, 96% had a BG value, and 95% had treatments and outcomes entered by patients within the 72-h window. Patients recorded administration of 1,964,477 insulin doses; 93% of basal insulin doses were adherent with the investigator prescription. Investigators adjusted 13 basal and 92 bolus insulin prescriptions per patient-year using the e-diary system. After 26 weeks of treatment and e-diary use in the combined study arms, hemoglobin A1c values decreased by 0.6% or 1.6% and fasting BG decreased by 7.8 or 28 mg/dL in patients with T1DM or T2DM, respectively.

CONCLUSIONS

The e-diary system enabled comprehensive data collection and facilitated communication between investigators and patients for intensive insulin management in three global clinical trials testing basal insulins.

Medications for type 2 diabetes: how will we be treating patients in 50 years?

The past 50 years have seen the development of many new options for treating and preventing type 2 diabetes. Despite this success, the individual and societal burden of the disease continues unabated. Thus, the next 50 years will be critical if we are going to quell the major non-communicable disease of our time. The knowledge we will gain in the next few years from clinical studies will inform treatment guidelines with regard to which agents to use in whom and whether more aggressive approaches can slow the development of hyperglycaemia in those at high risk. Beyond that, we anticipate identification of novel targets and techniques for therapeutic intervention. These advances will lead to more personalised approaches to treatment. Most importantly, we will need to focus our political and economic efforts on enhancing and implementing public health approaches aimed at prevention of diabetes and its co-morbidities. This is one of a series of commentaries under the banner '50 years forward', giving personal opinions on future perspectives in diabetes, to celebrate the 50th anniversary of Diabetologia (1965-2015).

The Impact of Technology on Current Diabetes Management

Technological innovations have revolutionized the treatment of type 1 diabetes. Although technological advances can potentially improve diabetes outcomes, maintenance of target glycemic control, at the present time, remains largely dependent on patient and family motivation, competence, and adherence to daily diabetes care requirements. Trials of closed loop or "artificial pancreas" technology show great promise to automate insulin delivery and achieve near normal glucose control and reduced hypoglycemia with minimal patient intervention.

Minimizing Hypoglycemia in Diabetes

Hypoglycemia caused by treatment with a sulfonylurea, a glinide, or insulin coupled with compromised defenses against the resulting falling plasma glucose concentrations is a problem for many people with diabetes. It is often recurrent, causes significant morbidity and occasional mortality, limits maintenance of euglycemia, and impairs physiological and behavioral defenses against subsequent hypoglycemia. Minimizing hypoglycemia includes acknowledging the problem; considering each risk factor; and applying the principles of intensive glycemic therapy, including drug selection and selective application of diabetes treatment technologies. For diabetes health-care providers treating most people with diabetes who are at risk for or are suffering from iatrogenic hypoglycemia, these principles include selecting appropriate individualized glycemic goals and providing structured patient education to reduce the incidence of hypoglycemia. This is typically combined with short-term scrupulous avoidance of hypoglycemia, which often will reverse impaired awareness of hypoglycemia. Clearly, the risk of hypoglycemia is modifiable.

Impact of new technologies on diabetes care

Technologies for diabetes management, such as continuous subcutaneous insulin infusion (CSII) and continuous glucose monitoring (CGM) systems, have improved remarkably over the last decades. These developments are impacting the capacity to achieve recommended hemoglobin A1c levels and assisting in preventing the development and progression of micro- and macro vascular complications. While improvements in metabolic control and decreases in risk of severe and moderate hypoglycemia have been described with use of these technologies, large epidemiological international studies show that many patients are still unable to meet their glycemic goals, even when these technologies are used. This editorial will review the impact of technology on glycemic control, hypoglycemia and quality of life in children and youth with type 1 diabetes. Technologies reviewed include CSII, CGM systems and sensor-augmented insulin pumps. In addition, the usefulness of advanced functions such as bolus profiles, bolus calculators and threshold-suspend features will be also discussed. Moreover, the current editorial will explore the challenges of using these technologies. Indeed, despite the evidence currently available of the potential benefits of using advanced technologies in diabetes management, many patients still report barriers to using them. Finally this article will highlight the importance of future studies tailored toward overcome these barriers to optimizing glycemic control and avoiding severe hypoglycemia.

Chronic Pancreatitis and Diabetes Mellitus

OPINION STATEMENT

Patients with chronic pancreatitis should be screening at least annually for diabetes. Lifestyle modifications remain to be an important part of treatment for diabetic control. Unless contraindicated or not tolerated, metformin can be initiated and continued concurrently with other anti-diabetic agents or insulin. All anti-diabetic agents should be used based on their physiology and adverse effect profiles, along with the metabolic status of patients. Insulin therapy should be initiated without delay for any of the following: symptomatic or overt hyperglycemia, catabolic state secondary to uncontrolled diabetes, history of diabetic ketoacidosis, hospitalization or acute exacerbation of pancreatitis, or hyperglycemia that cannot be otherwise controlled. Dose adjustment should be done conservatively as these patients are more likely to be insulin sensitive and have loss of counter regulatory hormones. Insulin pump and continuous glucose monitoring should be considered early during therapy in selected patients. For patients undergoing total pancreatectomy or extensive partial pancreatectomy, evaluations to determine the eligibilities for islet cell autotransplantation should be considered.

Engineering Synthetically Modified Insulin for Glucose-Responsive Diabetes Therapy

Though a suite of different insulin variants have been used clinically to provide greater control over pharmacokinetics, no clinically used insulin can tune its potency and/or bioavailability in a glucose-dependent manner. In order to improve therapy for diabetic patients, a vision has been the development of autonomous closed-loop approaches. Toward this goal, insulin has been synthetically modified with glucose-sensing groups or groups that can compete with free glucose for binding to glucose-binding proteins and evaluated in pre-clinical models. Specifically, it was demonstrated that site-specific modification of insulin with phenylboronic acid can result in glucose-responsive activity, leading to faster recovery in diabetic mice following a glucose challenge but with less observed hypoglycemia in healthy mice. This strategy, along with several others being pursued, holds promise to improve the fidelity in glycemic control with routine insulin therapy.

Explaining the increased mortality in type 1 diabetes

Despite large improvements in the management of glucose levels and in the treatment of cardiovascular risk factors, the mortality rate in individuals with type 1 diabetes (T1D) is still high. Recently, Lind et al found that T1D individuals with glycated hemoglobin levels of 6.9% or lower had a risk of death from any cause or from cardiovascular causes that is twice as high as the risk for matched controls. T1D is a chronic disease with an early onset (e.g., pediatric age) and thus in order to establish a clear correlation between death rate and the glycometabolic control, the whole history of glycemic control should be considered; particularly in the early years of diabetes. The switch from a normo- to hyperglycemic milieu in an individual with T1D in the pediatric age, represents a stressful event that may impact outcomes and death rate many years later. In this paper we will discuss the aforementioned issues, and offer our view on these findings, paying a particular attention to the several alterations occurring in the earliest phases of T1D and to the many factors that may be associated with the chronic history of T1D. This may help us to better understand the recently published death rate data and to develop future innovative and effective preventive strategies.

Development of an encapsulated stem cell-based therapy for diabetes

INTRODUCTION

Islet transplantation can treat the most severe cases of type 1 diabetes but it currently requires deceased donor pancreata as an islet source and chronic immunosuppression to prevent rejection and recurrence of autoimmunity. Stem cell-derived insulin-producing cells may address the shortage of organ donors, whereas cell encapsulation may reduce or eliminate the requirement for immunosuppression, minimizing the risks associated with the islet transplantation procedure, and potentially prolonging graft survival.

AREAS COVERED

This review focuses on the design principles for immunoisolation devices and on stem cell differentiation into insulin-producing cell products. The reader will gain understanding of the different types of immunoisolation devices and the key parameters that affect the outcome of the encapsulated graft. Progresses in stem cell differentiation towards mature endocrine islet cells, including the most recent clinical trials and the challenges associated with the application of immunoisolation devices designed for primary islets to stem-cell products, are also discussed.

EXPERT OPINION

Recent advancements in the field of stem cell-derived islet cell products and immunoisolation strategies hold great promise for type 1 diabetes. However, a combination product including both cells and an immunoisolation strategy still needs to be optimized and tested for safety and efficacy.

Day and Night Closed-Loop Control Using the Integrated Medtronic Hybrid Closed-Loop System in Type 1 Diabetes at Diabetes Camp

OBJECTIVE

To evaluate the feasibility and efficacy of a fully integrated hybrid closed-loop (HCL) system (Medtronic MiniMed Inc., Northridge, CA), in day and night closed-loop control in subjects with type 1 diabetes, both in an inpatient setting and during 6 days at diabetes camp.

RESEARCH DESIGN AND METHODS

The Medtronic MiniMed HCL system consists of a fourth generation (4S) glucose sensor, a sensor transmitter, and an insulin pump using a modified proportional-integral-derivative (PID) insulin feedback algorithm with safety constraints. Eight subjects were studied over 48 h in an inpatient setting. This was followed by a study of 21 subjects for 6 days at diabetes camp, randomized to either the closed-loop control group using the HCL system or to the group using the Medtronic MiniMed 530G with threshold suspend (control group).

RESULTS

The overall mean sensor glucose percent time in range 70-180 mg/dL was similar between the groups (73.1% vs. 69.9%, control vs. HCL, respectively) (P = 0.580). Meter glucose values between 70 and 180 mg/dL were also similar between the groups (73.6% vs. 63.2%, control vs. HCL, respectively) (P = 0.086). The mean absolute relative difference of the 4S sensor was 10.8 ± 10.2%, when compared with plasma glucose values in the inpatient setting, and 12.6 ± 11.0% compared with capillary Bayer CONTOUR NEXT LINK glucose meter values during 6 days at camp.

CONCLUSIONS

In the first clinical study of this fully integrated system using an investigational PID algorithm, the system did not demonstrate improved glucose control compared with sensor-augmented pump therapy alone. The system demonstrated good connectivity and improved sensor performance.

Predictive Low-Glucose Insulin Suspension Reduces Duration of Nocturnal Hypoglycemia in Children Without Increasing Ketosis

OBJECTIVE

Nocturnal hypoglycemia can cause seizures and is a major impediment to tight glycemic control, especially in young children with type 1 diabetes. We conducted an in-home randomized trial to assess the efficacy and safety of a continuous glucose monitor-based overnight predictive low-glucose suspend (PLGS) system.

RESEARCH DESIGN AND METHODS

In two age-groups of children with type 1 diabetes (11-14 and 4-10 years of age), a 42-night trial for each child was conducted wherein each night was assigned randomly to either having the PLGS system active (intervention night) or inactive (control night). The primary outcome was percent time <70 mg/dL overnight.

RESULTS

Median time at <70 mg/dL was reduced by 54% from 10.1% on control nights to 4.6% on intervention nights (P < 0.001) in 11-14-year-olds (n = 45) and by 50% from 6.2% to 3.1% (P < 0.001) in 4-10-year-olds (n = 36). Mean overnight glucose was lower on control versus intervention nights in both age-groups (144 ± 18 vs. 152 ± 19 mg/dL [P < 0.001] and 153 ± 14 vs. 160 ± 16 mg/dL [P = 0.004], respectively). Mean morning blood glucose was 159 ± 29 vs. 176 ± 28 mg/dL (P < 0.001) in the 11-14-year-olds and 154 ± 25 vs. 158 ± 22 mg/dL (P = 0.11) in the 4-10-year-olds, respectively. No differences were found between intervention and control in either age-group in morning blood ketosis.

CONCLUSIONS

In 4-14-year-olds, use of a nocturnal PLGS system can substantially reduce overnight hypoglycemia without an increase in morning ketosis, although overnight mean glucose is slightly higher.

Technology to Reduce Hypoglycemia

Hypoglycemia is a major barrier toward achieving glycemic targets and is associated with significant morbidity (both psychological and physical) and mortality. This article reviews technological strategies, from simple to more advanced technologies, which may help prevent or mitigate exposure to hypoglycemia. More efficient insulin delivery systems, bolus advisor calculators, data downloads providing information on glucose trends, continuous glucose monitoring with alarms warning of hypoglycemia, predictive algorithms, and finally closed loop insulin delivery systems are reviewed. The building blocks to correct use and interpretation of this range of available technology require patient education and appropriate patient selection.

Glucagon - the new 'insulin' in the pathophysiology of diabetes

PURPOSE OF REVIEW

Autoimmune destruction of the β cells is considered the key abnormality in type 1 diabetes mellitus and insulin replacement the primary therapeutic strategy. However, a lack of insulin is accompanied by disturbances in glucagon release, which is excessive postprandially, but insufficient during hypoglycaemia. In addition, replacing insulin alone appears insufficient for adequate glucose control. This review focuses on the growing body of evidence that glucagon abnormalities contribute significantly to the pathophysiology of diabetes and on recent efforts to target the glucagon axis as adjunctive therapy to insulin replacement.

RECENT FINDINGS

This review discusses recent (since 2013) advances in abnormalities of glucagon regulation and their link to the pathophysiology of diabetes; new mechanisms of glucagon action and regulation; manipulation of glucagon in diabetes treatment; and analytical and systems biology tools to study glucagon regulation.

SUMMARY

Recent efforts 'resurrected' glucagon as a key hormone in the pathophysiology of diabetes. New studies target its abnormal regulation and action that is key for improving diabetes treatment. The progress is promising, but major questions remain, including unravelling the mechanism of loss of glucagon counterregulation in type 1 diabetes mellitus and how best to manipulate glucagon to achieve more efficient and safer glycaemic control.

Sensitivity of the Predictive Hypoglycemia Minimizer System to the Algorithm Aggressiveness Factor

BACKGROUND

The Predictive Hypoglycemia Minimizer System ("Hypo Minimizer"), consisting of a zone model predictive controller (the "controller") and a safety supervision module (the "safety module"), aims to mitigate hypoglycemia by preemptively modulating insulin delivery based on continuous glucose monitor (CGM) measurements. The "aggressiveness factor," a pivotal variable in the system, governs the speed and magnitude of the controller's insulin dosing characteristics in response to changes in CGM levels.

METHODS

Twelve adults with type 1 diabetes were studied in closed-loop in a clinical research center for approximately 24 hours. This analysis focused primarily on the effect of the aggressiveness factor on the automated insulin-delivery characteristics of the controller, and secondarily on the glucose control results.

RESULTS

As aggressiveness increased from "conservative" to "medium" to "aggressive," the controller recommended less insulin (-3.3% vs -14.4% vs -19.5% relative to basal) with a higher frequency (5.3% vs 14.4% vs 20.3%) during the critical times when the CGM was reading 90-120 mg/dl and decreasing. Blood glucose analyses indicated that the most aggressive setting resulted in the most desirable combination of the least time spent <70 mg/dl and the most time spent 70-180 mg/dl, particularly in the overnight period. Hyperglycemia, diabetic ketoacidosis, or severe hypoglycemia did not occur with any of the aggressiveness values.

CONCLUSION

The Hypo Minimizer's controller took preemptive action to prevent hypoglycemia based on predicted changes in CGM glucose levels. The most aggressive setting was quickest to take action to reduce insulin delivery below basal and achieved the best glucose metrics.

Meal Detection in Patients With Type 1 Diabetes: A New Module for the Multivariable Adaptive Artificial Pancreas Control System

A novel meal-detection algorithm is developed based on continuous glucose measurements. Bergman's minimal model is modified and used in an unscented Kalman filter for state estimations. The estimated rate of appearance of glucose is used for meal detection. Data from nine subjects are used to assess the performance of the algorithm. The results indicate that the proposed algorithm works successfully with high accuracy. The average change in glucose levels between the meals and the detection points is 16(±9.42) [mg/dl] for 61 successfully detected meals and snacks. The algorithm is developed as a new module of an integrated multivariable adaptive artificial pancreas control system. Meal detection with the proposed method is used to administer insulin boluses and prevent most of postprandial hyperglycemia without any manual meal announcements. A novel meal bolus calculation method is proposed and tested with the UVA/Padova simulator. The results indicate significant reduction in hyperglycemia.

Efficacy of dual-hormone artificial pancreas to alleviate the carbohydrate-counting burden of type 1 diabetes: A randomized crossover trial

AIM

Carbohydrate-counting is a complex task for many patients with type 1 diabetes. This study examined whether an artificial pancreas, delivering insulin and glucagon based on glucose sensor readings, could alleviate the burden of carbohydrate-counting without degrading glucose control.

METHODS

Twelve adults were recruited into a randomized, three-way, crossover trial (ClinicalTrials.gov identifier No. NCT01930097). Participants were admitted on three occasions from 7AM to 9PM and consumed a low-carbohydrate breakfast (women: 30g; men: 50g), a medium-carbohydrate dinner (women: 50g; men: 70g) and a high-carbohydrate lunch (women: 90g; men: 120g). At each visit, glucose levels were randomly regulated by: (1) conventional pump therapy; (2) an artificial pancreas (AP) accompanied by prandial boluses, matching the meal's carbohydrate content based on insulin-to-carbohydrate ratios (AP with carbohydrate-counting); or (3) an AP accompanied by prandial boluses based on qualitative categorization (regular or large) of meal size (AP without carbohydrate-counting).

RESULTS

The AP without carbohydrate-counting achieved similar incremental AUC values compared with carbohydrate-counting after the low- (P=0.54) and medium- (P=0.38) carbohydrate meals, but yielded higher post-meal excursions after the high-carbohydrate meal (P=0.004). The AP with and without carbohydrate-counting yielded similar mean glucose levels (8.2±2.1mmol/L vs. 8.4±1.7mmol/L; P=0.52), and both strategies resulted in lower mean glucose compared with conventional pump therapy (9.6±2.0mmol/L; P=0.02 and P=0.03, respectively).

CONCLUSION

The AP with qualitative categorization of meal size could alleviate the burden of carbohydrate-counting without compromising glucose control, although more categories of meal sizes are probably needed to effectively control higher-carbohydrate meals.

Design and Evaluation of a Robust PID Controller for a Fully Implantable Artificial Pancreas

Treatment of type 1 diabetes mellitus could be greatly improved by applying a closed-loop control strategy to insulin delivery, also known as an artificial pancreas (AP). In this work, we outline the design of a fully implantable AP using intraperitoneal (IP) insulin delivery and glucose sensing. The design process utilizes the rapid glucose sensing and insulin action offered by the IP space to tune a PID controller with insulin feedback to provide safe and effective insulin delivery. The controller was tuned to meet robust performance and stability specifications. An anti-reset windup strategy was introduced to prevent dangerous undershoot toward hypoglycemia after a large meal disturbance. The final controller design achieved 78% of time within the tight glycemic range of 80-140 mg/dL, with no time spent in hypoglycemia. The next step is to test this controller design in an animal model to evaluate the in vivo performance.

Evidence-informed clinical practice recommendations for treatment of type 1 diabetes complicated by problematic hypoglycemia

Problematic hypoglycemia, defined as two or more episodes per year of severe hypoglycemia or as one episode associated with impaired awareness of hypoglycemia, extreme glycemic lability, or major fear and maladaptive behavior, is a challenge, especially for patients with long-standing type 1 diabetes. Individualized therapy for such patients should include a composite target: optimal glucose control without problematic hypoglycemia. Therefore, we propose a tiered, four-stage algorithm based on evidence of efficacy given the limitations of educational, technological, and transplant interventions. All patients with problematic hypoglycemia should undergo structured or hypoglycemia-specific education programs (stage 1). Glycemic and hypoglycemia treatment targets should be individualized and reassessed every 3-6 months. If targets are not met, one diabetes technology-continuous subcutaneous insulin infusion or continuous glucose monitoring-should be added (stage 2). For patients with continued problematic hypoglycemia despite education (stage 1) and one diabetes technology (stage 2), sensor-augmented insulin pumps preferably with an automated low-glucose suspend feature and/or very frequent contact with a specialized hypoglycemia service can reduce hypoglycemia (stage 3). For patients whose problematic hypoglycemia persists, islet or pancreas transplant should be considered (stage 4). This algorithm provides an evidence-informed approach to resolving problematic hypoglycemia; it should be used as a guide, with individual patient circumstances directing suitability and acceptability to ensure the prudent use of technology and scarce transplant resources. Standardized reporting of hypoglycemia outcomes and inclusion of patients with problematic hypoglycemia in studies of new interventions may help to guide future therapeutic strategies.

Pathway to artificial pancreas systems revisited: moving downstream

Artificial pancreas (AP) systems, a long-sought quest to replicate mechanically islet physiology that is lost in diabetes, are reaching the clinic, and the potential of automating insulin delivery is about to be realized. Significant progress has been made, and the safety and feasibility of AP systems have been demonstrated in the clinical research center and more recently in outpatient "real-world" environments. An iterative road map to AP system development has guided AP research since 2009, but progress in the field indicates that it needs updating. While it is now clear that AP systems are technically feasible, it remains much less certain that they will be widely adopted by clinicians and patients. Ultimately, the true success of AP systems will be defined by successful integration into the diabetes health care system and by the ultimate metric: improved diabetes outcomes.

Islet α cells and glucagon--critical regulators of energy homeostasis

Glucagon is secreted from islet α cells and controls blood levels of glucose in the fasting state. Impaired glucagon secretion predisposes some patients with type 1 diabetes mellitus (T1DM) to hypoglycaemia; whereas hyperglycaemia in patients with T1DM or type 2 diabetes mellitus (T2DM) is often associated with hyperglucagonaemia. Hence, therapeutic strategies to safely achieve euglycaemia in patients with diabetes mellitus now encompass bihormonal approaches to simultaneously deliver insulin and glucagon (in patients with T1DM) or reduce excess glucagon action (in patients with T1DM or T2DM). Glucagon also reduces food intake and increases energy expenditure through central and peripheral mechanisms, which suggests that activation of signalling through the glucagon receptor might be useful for controlling body weight. Here, we review new data that is relevant to understanding α-cell biology and glucagon action in the brain, liver, adipose tissue and heart, with attention to normal physiology, as well as conditions associated with dysregulated glucagon action. The feasibility and safety of current and emerging glucagon-based therapies that encompass both gain-of-function and loss-of-function approaches for the treatment of T1DM, T2DM and obesity is discussed in addition to developments, challenges and critical gaps in our knowledge that require additional investigation.

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.

Care of diabetes in children and adolescents: controversies, changes, and consensus

Diabetes is one of the most common chronic medical disorders in children. The management of diabetes remains a substantial burden on children with diabetes and their families, despite improvements in treatment and rates of morbidity and mortality. Although most children with diabetes have type 1 diabetes, the increasing recognition of type 2 diabetes and genetic forms of diabetes in the paediatric population has important treatment implications. Diabetes therapy focuses strongly on targets for good metabolic control to reduce the risk of long-term complications. A parallel goal is to minimise short-term complications of hypoglycaemia and diabetic ketoacidosis. Technology offers opportunity for improvement in care, but has not yet fully lived up to its potential. New insights into the pathogenesis of diabetes and the development of new therapies have led to clinical trials aimed at the prevention of diabetes.