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.

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

Background: The aim of this study was to determine the performance of the Dexcom G6 continuous glucose monitoring (CGM) system across three sensor wear sites in pregnant women with diabetes in the second or third trimesters. Methods: Participants with type 1 (T1D), type 2 (T2D), or gestational (GDM) diabetes mellitus were enrolled at 3 sites. Each wore two G6 sensors on the abdomen, upper buttock, and/or posterior upper arm for 10 days and underwent a six-hour clinic session between days 3 and 7 of sensor wear, during which YSI reference blood glucose values were obtained every 30 minutes. No intentional glucose manipulations were performed. Accuracy metrics included the proportion of CGM values that were within ±20% of paired reference values >100 mg/dL or ±20 mg/dL of YSI values ≤100 mg/dL (hereafter referred to as %20/20), as well the analogous %15/15, %30/30 and %40/40. Mean absolute relative difference (MARD) between CGM-YSI pairs was also calculated. Results: Thirty-two participants with T1D (n=20), T2D (n=3), or GDM (n=9) were enrolled; 19 were in the second trimester and 13 were in the third trimester of pregnancy. Compared to the reference, 92.5% of CGM values were within ±20%/20 mg/dL. The overall MARD and that of sensors worn on the abdomen, upper buttock, and posterior upper arm was 10.3%, 11.5%, 11.2%, and 8.7%, respectively. There were no device-related adverse events. Skin reactions at the insertion sites were absent or minor. Conclusions: The Dexcom G6 CGM system is accurate and safe in pregnant women with diabetes.

Assess the efficacy of inControl AP, a mobile closed-loop control (CLC) system. RESEARCH DESIGN AND METHODSThis protocol, NCT02985866, is a 3-month parallel-group, multicenter, randomized unblinded trial designed to compare mobile CLC with sensor-augmented pump (SAP) therapy. Eligibility criteria were type 1 diabetes for at least 1 year, use of insulin pumps for at least 6 months, age ‡14 years, and baseline HbA 1c <10.5% (91 mmol/mol). The study was designed to assess two coprimary outcomes: superiority of CLC over SAP in continuous glucose monitor (CGM)-measured time below 3.9 mmol/L and noninferiority in CGM-measured time above 10 mmol/L. RESULTSBetween November 2017 and May 2018, 127 participants were randomly assigned 1:1 to CLC (n 5 65) versus SAP (n 5 62); 125 participants completed the study. CGM time below 3.9 mmol/L was 5.0% at baseline and 2.4% during follow-up in the CLC group vs. 4.7% and 4.0%, respectively, in the SAP group (mean difference 21.7% [95% CI 22.4, 21.0]; P < 0.0001 for superiority). CGM time above 10 mmol/L was 40% at baseline and 34% during follow-up in the CLC group vs. 43% and 39%, respectively, in the SAP group (mean difference 23.0% [95% CI 26.1, 0.1]; P < 0.0001 for noninferiority). One severe hypoglycemic event occurred in the CLC group, which was unrelated to the study device. CONCLUSIONSIn meeting its coprimary end points, superiority of CLC over SAP in CGM-measured time below 3.9 mmol/L and noninferiority in CGM-measured time above 10 mmol/L, the study has demonstrated that mobile CLC is feasible and could offer certain usability advantages over embedded systems, provided the connectivity between system components is stable.People with type 1 diabetes face a life-long optimization problem: limiting their exposure to hyperglycemia while simultaneously avoiding hypoglycemia (1). Classic studies have shown that many complications from diabetes are predicted by average glycemia, typically assessed by hemoglobin A 1c (HbA 1c ), and can be reduced with intensive insulin therapy (2,3); however, the risk for hypoglycemia remains the primary barrier to optimal glycemic control (1). At present, closed-loop control (CLC), known as the artificial pancreas, offers the best solution to this optimization problem: day-and-night real-time fine-tuning of insulin delivery by an automated system.In the past few years, the volume of CLC clinical trials increased dramatically. In 2018, the National Library of Medicine included 132 publications in the CLC field, and in the first 6 weeks of 2019 alone, 25 new articles were published. Research results are

To evaluate the contemporary prevalence of diabetic peripheral neuropathy (DPN) in participants with type 1 diabetes in the T1D Exchange Clinic Registry throughout the U.S. RESEARCH DESIGN AND METHODSDPN was assessed with the Michigan Neuropathy Screening Instrument Questionnaire (MNSIQ) in adults with ‡5 years of type 1 diabetes duration. A score of ‡4 defined DPN. Associations of demographic, clinical, and laboratory factors with DPN were assessed. RESULTSAmong 5,936 T1D Exchange participants (mean 6 SD age 39 6 18 years, median type 1 diabetes duration 18 years [interquartile range 11, 31], 55% female, 88% non-Hispanic white, mean glycated hemoglobin [HbA 1c ] 8.1 6 1.6% [65.3 6 17.5 mmol/mol]), DPN prevalence was 11%. Compared with those without DPN, DPN participants were older, had higher HbA 1c , had longer duration of diabetes, were more likely to be female, and were less likely to have a college education and private insurance (all P < 0.001). DPN participants also were more likely to have cardiovascular disease (CVD) (P < 0.001), worse CVD risk factors of smoking (P 5 0.008), hypertriglyceridemia (P 5 0.002), higher BMI (P 5 0.009), retinopathy (P 5 0.004), reduced estimated glomerular filtration rate (P 5 0.02), and Charcot neuroarthropathy (P 5 0.002). There were no differences in insulin pump or continuous glucose monitor use, although DPN participants were more likely to have had severe hypoglycemia (P 5 0.04) and/or diabetic ketoacidosis (P < 0.001) in the past 3 months. CONCLUSIONSThe prevalence of DPN in this national cohort with type 1 diabetes is lower than in prior published reports but is reflective of current clinical care practices. These data also highlight that nonglycemic risk factors, such as CVD risk factors, severe hypoglycemia, diabetic ketoacidosis, and lower socioeconomic status, may also play a role in DPN development.Diabetic neuropathy is a prevalent complication in patients with diabetes and a major cause of morbidity and mortality (1). Among the various forms of diabetic neuropathy, distal symmetric polyneuropathy (DPN) and diabetic autonomic neuropathies are by far the most studied (1).