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The Tandem Diabetes Care Basal-IQ PLGS system significantly reduced hypoglycemia without rebound hyperglycemia, indicating that the system can benefit adults and youth with type 1 diabetes in improving glycemic control.

Summary Background The safety and effectiveness of a continuous, day-and-night automated glycaemic control system using insulin and glucagon has not been shown in a free-living, home-use setting. We aimed to assess whether bihormonal bionic pancreas initialised only with body mass can safely reduce mean glycaemia and hypoglycaemia in adults with type 1 diabetes who were living at home and participating in their normal daily routines without restrictions on diet or physical activity. Methods We did a random-order crossover study in volunteers at least 18 years old who had type 1 diabetes and lived within a 30 min drive of four sites in the USA. Participants were randomly assigned (1:1) in blocks of two using sequentially numbered sealed envelopes to glycaemic regulation with a bihormonal bionic pancreas or usual care (conventional or sensor-augmented insulin pump therapy) first, followed by the opposite intervention. Both study periods were 11 days in length, during which time participants continued all normal activities, including athletics and driving. The bionic pancreas was initialised with only the participant’s body mass. Autonomously adaptive dosing algorithms used data from a continuous glucose monitor to control subcutaneous delivery of insulin and glucagon. The coprimary outcomes were the mean glucose concentration and time with continuous glucose monitoring (CGM) glucose concentration less than 3·3 mmol/L, analysed over days 2–11 in participants who completed both periods of the study. This trial is registered with ClinicalTrials.gov, number NCT02092220. Findings We randomly assigned 43 participants between May 6, 2014, and July 3, 2015, 39 of whom completed the study: 20 who were assigned to bionic pancreas first and 19 who were assigned to the comparator first. The mean CGM glucose concentration was 7·8 mmol/L (SD 0·6) in the bionic pancreas period versus 9·0 mmol/L (1·6) in the comparator period (difference 1·1 mmol/L, 95% CI 0·7–1·6; p<0·0001), and the mean time with CGM glucose concentration less than 3·3 mmol/L was 0·6% (0·6) in the bionic pancreas period versus 1·9% (1·7) in the comparator period (difference 1·3%, 95% CI 0·8–1·8; p<0·0001). The mean nausea score on the Visual Analogue Scale (score 0–10) was greater during the bionic pancreas period (0·52 [SD 0·83]) than in the comparator period (0·05 [0·17]; difference 0·47, 95% CI 0·21–0·73; p=0·0024). Body mass and laboratory parameters did not differ between periods. There were no serious or unexpected adverse events in the bionic pancreas period of the study. Interpretation Relative to conventional and sensor-augmented insulin pump therapy, the bihormonal bionic pancreas, initialised only with participant weight, was able to achieve superior glycaemic regulation without the need for carbohydrate counting. Larger and longer studies are needed to establish the long-term benefits and risks of automated glycaemic management with a bihormonal bionic pancreas. Funding National Institute of Diabetes and Digestive and Kidney Diseases of the...

Summary Background The safety and efficacy of continuous, multiday, automated glycaemic management has not been tested in outpatient studies of preadolescent children with type 1 diabetes. We aimed to compare the safety and efficacy of a bihormonal bionic pancreas versus conventional insulin pump therapy in this population of patients in an outpatient setting. Methods In this randomised, open-label, crossover study, we enrolled preadolescent children (aged 6–11 years) with type 1 diabetes (diagnosed for ≥1 year) who were on insulin pump therapy, from two diabetes camps in the USA. With the use of sealed envelopes, participants were randomly assigned in blocks of two to either 5 days with the bionic pancreas or conventional insulin pump therapy (control) as the first intervention, followed by a 3 day washout period and then 5 days with the other intervention. Study allocation was not masked. The autonomously adaptive algorithm of the bionic pancreas received data from a continuous glucose monitoring (CGM) device to control subcutaneous delivery of insulin and glucagon. Conventional insulin pump therapy was administered by the camp physicians and other clinical staff in accordance with their established protocols; participants also wore a CGM device during the control period. The coprimary outcomes, analysed by intention to treat, were mean CGM-measured glucose concentration and the proportion of time with a CGM-measured glucose concentration below 3·3 mmol/L, on days 2–5. This study is registered with ClinicalTrials.gov, number NCT02105324. Findings Between July 20, and Aug 19, 2014, 19 children with a mean age of 9·8 years (SD 1·6) participated in and completed the study. The bionic pancreas period was associated with a lower mean CGM-measured glucose concentration on days 2–5 than was the control period (7·6 mmol/L [SD 0·6] vs 9·3 mmol/L [1·7]; p=0·00037) and a lower proportion of time with a CGM-measured glucose concentration below 3·3 mmol/L on days 2–5 (1·2% [SD 1·1] vs 2·8% [1·2]; p<0·0001). The median number of carbohydrate interventions given per participant for hypoglycaemia on days 1–5 (ie, glucose <3·9 mmol/L) was lower during the bionic pancreas period than during the control period (three [range 0–8] vs five [0–14]; p=0·037). No episodes of severe hypoglycaemia were recorded. Medium-to-large concentrations of ketones (range 0·6–3·6 mmol/dL) were reported on seven occasions in five participants during the control period and on no occasion during the bionic pancreas period (p=0·063). Interpretation The improved mean glycaemia and reduced hypoglycaemia with the bionic pancreas relative to insulin pump therapy in preadolescent children with type 1 diabetes in a diabetes camp setting is a promising finding. Studies of a longer duration during which children use the bionic pancreas during their normal routines at home and school should be done to investigate the potential for use of the bionic pancreas in real-world settings. Funding The Leona M and Harry B Helmsley Charitable Trust and the US Nat...

Background: The accuracy of point-of-care blood glucose (BG) meters is important for the detection of dysglycemia, calculation of insulin doses, and the calibration of continuous glucose monitors. The objective of this study was to compare the accuracy of commercially available glucose meters in a challenging laboratory study using samples with a wide range of reference BG and hemoglobin values. Methods:Fresh, discarded blood samples from a hospital STAT laboratory were either used without modification, spiked with a glucose solution, or incubated at 37°C to produce 347 samples with an even distribution across reference BG levels from 20 to 440 mg/dl and hemoglobin values from 9 to 16 g/dl. We measured the BG of each sample with 17 different commercially available glucose meters and the reference method (YSI 2300) at the same time. We determined the mean absolute relative difference (MARD) for each glucose meter, overall and stratified by reference BG and by hemoglobin level. Results:The accuracy of different meters widely, exhibiting a range of MARDs from 5.6% to 20.8%. Accuracy was lower in the hypoglycemic range, but was not consistently lower in samples with anemic blood hemoglobin levels. Conclusions:The accuracy of commercially available glucose meters varies widely. Although the sample mix in this study was much more challenging than those that would be collected under most use conditions, some meters were robust to these challenges and exhibited high accuracy in this setting. These data on relative accuracy and robustness to challenging samples may be useful in informing the choice of a glucose meter.

Objective: Hybrid closed-loop (HCL) artificial pancreas (AP) systems are now moving from research settings to widespread clinical use. In this study, the inControl algorithm developed by TypeZero Technologies was embedded to a commercial Tandem t:slim X2 insulin pump, now called Control-IQ, paired with a Dexcom G6 continuous glucose monitor and tested for superiority against sensor augmented pump (SAP) therapy. Both groups were physician-monitored throughout the clinical trial. Research Design and Methods: In a randomized controlled trial, 24 school-aged children (6-12 years) with type 1 diabetes (T1D) participated in a 3-day home-use trial at two sites: Stanford University and the Barbara Davis Center (50% girls, 9.6 -1.9 years of age, 4.5 -1.9 years of T1D, baseline hemoglobin A1c 7.35% -0.68%). Study subjects were randomized 1:1 at each site to either HCL AP therapy with the Control-IQ system or SAP therapy with remote monitoring. Results: The primary outcome, time in target range 70-180 mg/dL, using Control-IQ significantly improved (71.0% -6.6% vs. 52.8% -13.5%; P = 0.001) and mean sensor glucose (153.6 -13.5 vs. 180.2 -23.1 mg/dL; P = 0.003) without increasing hypoglycemia time <70 mg/dL (1.7% [1.3%-2.1%] vs. 0.9% [0.3%-2.7%]; not significant). The HCL system was active for 94.4% of the study period. Subjects reported that use of the system was associated with less time thinking about diabetes, decreased worry about blood sugars, and decreased burden in managing diabetes. Conclusions: The use of the Tandem t:slim X2 with Control-IQ HCL AP system significantly improved time in range and mean glycemic control without increasing hypoglycemia in school-aged children with T1D during remote monitored home use.

The significant and growing global prevalence of diabetes continues to challenge people with diabetes (PwD), healthcare providers and payers. While maintaining near-normal glucose levels has been shown to prevent or delay the progression of the long-term complications of diabetes, a significant proportion of PwD are not attaining their glycemic goals. During the past six years, we have seen tremendous advances in automated insulin delivery (AID) technologies. Numerous randomized controlled trials and real-world studies have shown that the use of AID systems is safe and effective in helping PwD achieve their long-term glycemic goals while reducing hypoglycemia risk. Thus, AID systems have recently become an integral part of diabetes management. However, recommendations for using AID systems in clinical settings have been lacking. Such guided recommendations are critical for AID success and acceptance. All clinicians working with PwD need to become familiar with the available systems in order to eliminate disparities in diabetes quality of care. This report provides much-needed guidance for clinicians who are interested in utilizing AIDs and presents a comprehensive listing of the evidence payers should consider when determining eligibility criteria for AID insurance coverage.