Multisensor Integrated Platform Based on MEMS Charge Variation Sensing Technology for Biopotential Acquisition.

We propose a new methodology for long-term biopotential recording based on an MEMS multisensor integrated platform featuring a commercial electrostatic charge-transfer sensor. This family of sensors was originally intended for presence tracking in the automotive industry, so the existing setup was engineered for the acquisition of electrocardiograms, electroencephalograms, electrooculograms, and electromyography, designing a dedicated front-end and writing proper firmware for the specific application. Systematic tests on controls and nocturnal acquisitions from patients in a domestic environment will be discussed in detail. The excellent results indicate that this technology can provide a low-power, unexplored solution to biopotential acquisition. The technological breakthrough is in that it enables adding this type of functionality to existing MEMS boards at near-zero additional power consumption. For these reasons, it opens up additional possibilities for wearable sensors and strengthens the role of MEMS technology in medical wearables for the long-term synchronous acquisition of a wide range of signals.

Methods for Insulin Bolus Adjustment Based on the Continuous Glucose Monitoring Trend Arrows in Type 1 Diabetes: Performance and Safety Assessment in an In Silico Clinical Trial.

BACKGROUND: Providing real-time magnitude and direction of glucose rate-of-change (ROC) via trend arrows represents one of the major strengths of continuous glucose monitoring (CGM) sensors in managing type 1 diabetes (T1D). Several literature methods were proposed to adjust the standard formula (SF) used for insulin bolus calculation by accounting for glucose ROC, but each of them provides different suggestions, making it difficult to understand which should be applied in practice. This work aims at performing an extensive in-silico assessment of their performance and safety. METHODS: The methods of Buckingham (BU), Scheiner (SC), Pettus/Edelman (PE), Klonoff/Kerr (KL), Aleppo/Laffel (AL), Ziegler (ZI), and Bruttomesso (BR) were evaluated using the UVa/Padova T1D simulator, in single-meal scenarios, where ROC and glucose at mealtime varied between [-2,+2] mg/dL/min and [80,200] mg/dL, respectively. Efficacy of postprandial glucose control was quantitatively assessed by time in, above and below range (TIR, TAR, and TBR, respectively). RESULTS: For negative ROCs, all methods proved to increase TIR and decrease TAR and TBR vs SF, with KL, PE, and BR being the most effective. For positive ROCs, a general worsening of the performances is present, only BR improved the glycemic control when mealtime glucose was close to hypoglycemia, while SC resulted the safest in the other conditions. CONCLUSIONS: Insulin bolus adjustment methods are effective for negative ROCs, but they generally appear to overdose for positive ROCs, calling for safer strategies in such a scenario. These results can be useful in outlining guidelines to identify which adjustment to apply based on the mealtime condition.

Effectiveness of adding alarms to flash glucose monitoring in adults with type 1 diabetes under routine care.

AIM: Whether glucose sensor alarms improve metabolic control and are accepted by individuals with diabetes is unclear. Here, we investigated whether switching from a standard flash glucose monitoring system (FGM1) to a system equipped with hypo- and hyperglycemia alarms (FGM2) improves glycemic control and psychological outcomes in adults with type 1 diabetes (T1D). METHODS: Subjects with T1D and > 4% of time in hypoglycemia or > 40% of time in hyperglycemia were studied while wearing FGM1 (4 weeks) and after switching to FGM2 for 8 weeks. The primary endpoint was the change in time in range (TIR 70-180 mg/dl [3.9-10.0 mmol/L]) after 4 weeks of FGM2 use. Time below range (TBR), time above range (TAR), mean glucose, coefficient of variation (CV), sensor scans, treatment satisfaction, and hypoglycemia fear were secondary outcomes. RESULTS: We included 38 subjects aged 33.7 ± 12.6 year. During 4 weeks of FGM2 use, TIR increased from 52.8 to 57.0% (p = 0.001), TBR decreased from 6.2 to 3.4% (p < 0.0001) as did time < 54 mg/dl (from 1.4 to 0.3%, p < 0.0001) and CV (from 39.6% to 36.1%, p < 0.0001). These changes were confirmed after 8 weeks of FGM2 use. Treatment satisfaction improved and fear of hypoglycemia decreased. Subjects who had > 4% of time in hypoglycemia at baseline showed the greatest improvements in glucose control and treatment satisfaction. CONCLUSION: Switching from FGM1 to FGM2 improved TIR and treatment satisfaction and reduced fear of hypoglycemia. Participants who benefited most from switching from FGM1 to FGM2 were those prone to hypoglycemia.

Switching from predictive low glucose suspend to advanced hybrid closed loop control: Effects on glucose control and patient reported outcomes.

AIMS: Automated insulin delivery improves glucose control. Aim of this study was to compare in real life the effects on glucose control and patient reported outcomes of an advanced hybrid closed loop system (Control-IQ), versus a simpler system with predictive low glucose suspend function (Basal-IQ). METHODS: Thirty-one type 1 diabetic subjects were studied during Basal-IQ and after switching to Control-IQ. Variables analyzed were time spent in range (70-180 mg/dL), in tight range (70-140 mg/dL), above range (>180 mg/dL), below range (<70 mg/dL), mean glucose, coefficient of variation and glycated hemoglobin. Questionnaires were administered regarding therapy satisfaction (Diabetes Treatment Satisfaction Questionnaire in status/change form), fear of hypoglycemia (Hypoglycemia Fear Survey), quality of sleep (Pittsburgh Sleep Quality Index). RESULTS: After 12 weeks of Control-IQ, time in range increased from 62.7 to 74.0%, p < 0.0001, time in tight range increased from 37.1 to 44.6 %, p < 0.001, time above range decreased from 35.6 to 24.4% p < 0.0001. Improvements were observed in mean glucose and glucose variability. Glycated hemoglobin decreased from 7.0% (53 mmol/mol) to 6.6% (49 mmol/mol), p < 0.0001. Subjects using Control-IQ manifested greater satisfaction and less fear of hypoglycemia. CONCLUSION: Compared to Basal-IQ, Control-IQ improves glucose control and therapy satisfaction.

Performance of intermittently scanned continuous glucose monitoring systems in people with type 1 diabetes: A pooled analysis.

AIMS: To conduct a pooled analysis to assess the performance of intermittently scanned continuous glucose monitoring (isCGM) in association with the rate of change in sensor glucose in a cohort of children, adolescents, and adults with type 1 diabetes. MATERIAL AND METHODS: In this pooled analysis, isCGM system accuracy was assessed depending on the rate of change in sensor glucose. Clinical studies that have been investigating isCGM accuracy against blood glucose, accompanied with collection time points were included in this analysis. isCGM performance was assessed by means of median absolute relative difference (MedARD), Parkes error grid (PEG) and Bland-Altman plot analyses. RESULTS: Twelve studies comprising 311 participants were included, with a total of 15 837 paired measurements. The overall MedARD (interquartile range) was 12.7% (5.9-23.5) and MedARD differed significantly based on the rate of change in glucose (P < 0.001). An absolute difference of -22 mg/dL (-1.2 mmol/L) (95% limits of agreement [LoA] 60 mg/dL (3.3 mmol/L), -103 mg/dL (-5.7 mmol/L)) was found when glucose was rapidly increasing (isCGM glucose minus reference blood glucose), while a -32 mg/dL (1.8 mmol/L) (95% LoA 116 mg/dL (6.4 mmol/L), -51 mg/dL (-2.8 mmol/L)) absolute difference was observed in periods of rapidly decreasing glucose. CONCLUSIONS: The performance of isCGM was good when compared to reference blood glucose measurements. The rate of change in glucose for both increasing and decreasing glucose levels diminished isCGM performance, showing lower accuracy during high rates of glucose change.

An Integrated Mobile Platform for Automated Data Collection and Real-Time Patient Monitoring in Diabetes Clinical Trials.

We present a new mobile platform to be used in clinical trials aimed at both collecting data and assessing new technologies and treatments for diabetes care. The main components of the platform are a mobile app, that automatically collects data from continuous glucose monitoring sensors and activity trackers, and also allows users to manually log daily events; a cloud database for safe data storage; a web interface, which allows clinicians to monitor patients' status in real-time. The platform is modular and highly customizable for a multitude of purposes in clinical research. Preliminary tests performed for daily-life data gathering by both clinicians and users are extremely encouraging.

Current treatment options and challenges in patients with Type 1 diabetes: Pharmacological, technical advances and future perspectives.

Type 1 diabetes mellitus imposes a significant burden of complications and mortality, despite important advances in treatment: subjects affected by this disease have also a worse quality of life-related to disease management. To overcome these challenges, different new approaches have been proposed, such as new insulin formulations or innovative devices. The introduction of insulin pumps allows a more physiological insulin administration with a reduction of HbA1c level and hypoglycemic risk. New continuous glucose monitoring systems with better accuracy have allowed, not only better glucose control, but also the improvement of the quality of life. Integration of these devices with control algorithms brought to the creation of the first artificial pancreas, able to independently gain metabolic control without the risk of hypo- and hyperglycemic crisis. This approach has revolutionized the management of diabetes both in terms of quality of life and glucose control. However, complete independence from exogenous insulin will be obtained only by biological approaches that foresee the replacement of functional beta cells obtained from stem cells: this will be a major challenge but the biggest hope for the subjects with type 1 diabetes. In this review, we will outline the current scenario of innovative diabetes management both from a technological and biological point of view, and we will also forecast some cutting-edge approaches to reduce the challenges that hamper the definitive cure of diabetes.

A "Slide Rule" to Adjust Insulin Dose Using Trend Arrows in Adults with Type 1 Diabetes: Test in Silico and in Real Life.

INTRODUCTION: In persons with type 1 diabetes (T1D) insulin dosing can be adjusted based on trend arrows derived from continuous glucose monitoring (CGM). We propose a slide rule with narrower blood glucose intervals and more classes of insulin sensitivity than are available in current models. METHODS: The slide rule was tested in silico, in which a meal was simulated in 100 virtual subjects and the insulin bolus was calculated either in the standard way based on the insulin-to-carbohydrate ratio and the correction factor or according to the slide rule, following which the percentage time spent in range (70-180 mg/dl; %TIR), hypoglycemia (< 70 mg/dl; %THYPO), and hyperglycemia (> 180 mg/dl; %THYPER) was compared between the methods during the 4 h after the meal. Slide rule performance was also tested in real life by analyzing the same variables at during the 4 h postprandial period in 27 individuals with T1D. Only meals starting while the rate of change was at least 1 mg/dl per minute (increasing or decreasing) were considered for analysis. RESULTS: In silico, when the preprandial trend arrow was increasing, our slide rule reduced %THYPER and increased %TIR (p < 0.05), whereas when the preprandial trend arrow was decreasing, it reduced %THYPO and slightly increased %THYPER (p < 0.05). In real life, our slide rule kept subjects on target for 70.8 and 91.6% of postprandial time when preprandial trend arrows were increasing or decreasing, respectively. CONCLUSION: The proposed slide rule performed well both in silico and in real life, suggesting that it could be safely adopted by individuals with T1D to improve glucose control.

Comparing the accuracy of transcutaneous sensor and 90-day implantable glucose sensor.

BACKGROUND AND AIMS: Continuous glucose monitoring improves glycemic control in diabetes. This study compared the accuracy of the Dexcom G5 Mobile (Dexcom, San Diego, CA) transcutaneous sensor (DG5) and the first version of Eversense (Senseonics,Inc., Germantown, MD) implantable sensor (EVS). METHODS AND RESULTS: Subjects with type 1 diabetes (T1D) and using EVS wore simultaneously DG5 for seven days. At day 3, patients were admitted to a clinical research center (CRC) to receive breakfast with delayed and increased insulin bolus to induce glucose excursions. At CRC, venous glucose was monitored every 15 min (or 5 min during hypoglycemia) for 6 h by YSI 2300 STAT PLUS™ glucose and lactate analyzer. At home patients were requested to perform 4 fingerstick glucose measurements per day. Eleven patients (9 males, age 47.4 ± 11.3 years, M±SD) were enrolled. During home-stay the median [25th-75th percentile] absolute relative difference (ARD) over all CGM-fingerstick matched-pairs was 11.64% [5.38-20.65]% for the DG5 and 10.75% [5.15-19.74]% for the EVS (p-value = 0.58). At CRC, considering all the CGM-YSI matched-pairs, the DG5 showed overall smaller median ARD than EVS, 7.91% [4.14-14.30]% vs 11.4% [5.04-18.54]% (p-value<0.001). Considering accuracy during blood glucose swings, DG5 performed better than EVS when glucose rate-of-change was -0.5 to -1.5 mg/dL/min, with median ARD of 7.34% [3.71-12.76]% vs 13.59% [4.53-20.78]% (p-value<0.001), and for rate-of-change < -1.5 mg/dl/min, with median ARD of 5.23% [2.09-15.29]% vs 12.73% [4.14-20.82]% (p-value = 0.02). CONCLUSIONS: DG5 was more accurate than EVS at CRC, especially when glucose decreased. No differences were found at home.

Efficacy of telemedicine for persons with type 1 diabetes during Covid19 lockdown.

BACKGROUND: Starting March 2020 the Italian Government imposed a lockdown to limit the spread of SARS-CoV-2. During lockdown outpatient visits were limited and telemedicine (TM) was encouraged. METHODS: We retrospectively analyzed data from continuous or flash glucose monitoring systems shared through different cloud systems during the lockdown by subjects with type 1 diabetes and compared data obtained 4 weeks before and 4 weeks after structured telephonic visit. Variables considered were mean glucose, time spent in target (70-180 mg/dl), hypoglycemia (<70 mg/dl) and hyperglycemia (>180 mg/dl), coefficient of variation, and length of sensor use. RESULTS: During the 4 weeks following the telephonic visit there was an improvement of glycemic control, with a significant reduction of mean glucose values (161.1 before vs 156.3 mg/dl after, p = 0.001), an increase of the time spent in target (63.6 vs 66.3, p = 0.0009) and a reduction of time spent in hyperglycemia (33.4 vs 30.5, p = 0.002). No changes were observed regarding glucose variability, time spent in hypoglycemia, and length of sensor use. Similar results were observed in subjects treated with multiple daily injections or continuous subcutaneous insulin infusion. CONCLUSIONS: A structured telephonic visit appears to be an effective way to replace or integrate routine visits in particular conditions.

Assessment of the effect of pregnancy planning in women with type 1 diabetes treated by insulin pump.

BACKGROUND: Pregnant women with type 1 diabetes (T1D) have high risk of complications despite improved care based on technology advancements. OBJECTIVE: To assess the effects of pregnancy planning on fetal and maternal outcomes in T1D women treated with continuous subcutaneous insulin infusion (CSII). STUDY DESIGN: We retrospectively assessed maternal and neonatal outcomes in T1D women using CSII who had planned or unplanned pregnancies between 2002 and 2018. The study was done in two European countries with similar sustained programs for pregnancy planning over the study period. RESULTS: Data from 107 pregnancies and newborn babies were collected. Seventy-nine pregnancies (73.8%) had been planned. HbA1c was lower in planned versus unplanned pregnancy before and during all three trimesters of pregnancy (p < 0.0001). Pregnancy planning was associated with a reduction in the occurrence of iatrogenic preterm delivery (RR 0.44, 95% CI 0.23-0.95; p = 0.01). Risk reduction persisted after adjustments for mother's age above 40 years and preeclampsia. High HbA1c before or during pregnancy was associated with an increased risk of iatrogenic preterm delivery (RR 3.05, 95% CI 1.78-5.22, p < 0.0001). Premature newborns needed intensive care more often than those at term (RR 3.10, 95% CI 1.53-4.31; p = 0.002). CONCLUSIONS: Pregnancy planning in T1D women using CSII was associated with better glucose control and decreased risk of iatrogenic preterm delivery. Hence preconception care also improves pregnancy outcome in patients using an advanced mode of insulin delivery. Planned pregnancies could further benefit from the use of new metrics of glucose control.

Practical Considerations for the Management of Cushing's Disease and COVID-19: A Case Report.

Introduction: Italy, since the end of February 2020, is experiencing the corona virus disease 2019 (COVID-19) pandemic that may present as an acute respiratory infection. We report on COVID-19 pneumonia in the context of a complex case of Cushing's disease (CD). Case Report: A 67-year-old man with CD, who was admitted to our hospital, presented with signs and symptoms of adrenal insufficiency with persistent hypotension and glycemia toward the lower limits. We progressively withdrew almost all treatments for diabetes and CD (pasireotide and metyrapone), and i.v. hydrocortisone was necessary. A tendency to hyperkalemia was probably associated to enoxaparin. We summarized the many possible interactions between medications of Cushing's syndrome (CS) and COVID-19. Conclusion: Adrenal insufficiency might be a clinical challenge that needs a prompt treatment also in CS patients during COVID-19 infection. We should consider the possibility to titrate or temporary halt medical therapies of CS in the context of COVID-19 infection. Unexpected hyperkalemia in CS patients under treatment with heparin might be the signal of aldosterone suppression.

Newly-diagnosed diabetes and admission hyperglycemia predict COVID-19 severity by aggravating respiratory deterioration.

AIMS: We investigated whether pre-existing diabetes, newly-diagnosed diabetes, and admission hyperglycemia were associated with COVID-19 severity independently from confounders. METHODS: We retrospectively analyzed data on patients with COVID-19 hospitalized between February and April 2020 in an outbreak hospital in North-East Italy. Pre-existing diabetes was defined by self-reported history, electronic medical records, or ongoing medications. Newly-diagnosed diabetes was defined by HbA1c and fasting glucose. The primary outcome was a composite of ICU admission or death. RESULTS: 413 subjects were included, 107 of whom (25.6%) had diabetes, including 21 newly-diagnosed. Patients with diabetes were older and had greater comorbidity burden. The primary outcome occurred in 37.4% of patients with diabetes compared to 20.3% in those without (RR 1.85; 95%C.I. 1.33-2.57; p < 0.001). The association was stronger for newly-diagnosed compared to pre-existing diabetes (RR 3.06 vs 1.55; p = 0.004). Higher glucose level at admission was associated with COVID-19 severity, with a stronger association among patients without as compared to those with pre-existing diabetes (interaction p < 0.001). Admission glucose was correlated with most clinical severity indexes and its association with adverse outcome was mostly mediated by a worse respiratory function. CONCLUSION: Newly-diagnosed diabetes and admission hyperglycemia are powerful predictors of COVID-19 severity due to rapid respiratory deterioration.

Performance of the Steno type 1 risk engine for cardiovascular disease prediction in Italian patients with type 1 diabetes.

BACKGROUND AND AIMS: Premature cardiovascular disease cause excess mortality in type 1 diabetes (T1D). The Steno T1D Risk Engine was developed and validated in northern European countries but its validity in other populations is unknown. We evaluated the performance of the Steno T1D Risk Engine in Italian patients with T1D. MATERIALS AND METHODS: We included patients with T1D with a baseline visit between July 2013 and April 2014, who were free of cardiovascular disease and had complete information to estimate risk. The estimated cardiovascular risk score was compared with the 5-year rate of cardiovascular events by means of logistic regression. RESULTS: Among 223 patients (mean age 43 ± 13 years, 34.5% male, mean duration of diabetes 22 ± 12 years) the mean estimated cardiovascular risk at 5 years was 5.9% (95% C.I. 5.2-6.5%). At baseline, high estimated risk discriminated the presence of asymptomatic atherosclerosis better than microangiopathy, and was not associated with markers of inflammation or endothelial activation. After a mean follow-up of 4.7 ± 0.5 years, only 3 cardiovascular events were observed and nonetheless the risk score was significantly associated with their incidence (OR 1.22; 95% C.I. 1.08-1.39, p = 0.001). However, the observed event rate was significantly lower than the estimated one (3 vs 13; 95% C.I. 12-14; p < 0.001). CONCLUSION: The Steno T1D Risk Score identified subjects with subclinical atherosclerosis and high cardiovascular risk in an Italian T1D population. However, the absolute risk was significantly overestimated. Further studies in larger population are needed to confirm these results.

Glycaemic Control Among People with Type 1 Diabetes During Lockdown for the SARS-CoV-2 Outbreak in Italy.

INTRODUCTION: In late February 2020, due to the spread of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the Italian Government closed down all educational and sport activities. In March, it introduced further measures to stop the spread of coronavirus disease (COVID-19), placing the country in a state of almost complete lockdown. We report the impact of these restrictions on glucose control among people with type 1 diabetes (T1D). METHODS: Data were collected on 33 individuals with T1D who were monitoring their glucose levels using a flash glucose monitoring device and remotely connected to the diabetes clinic on a cloud platform. We retrieved information on average glucose, standard deviation and percentage time in hypoglycaemia (< 70 mg/dl), glucose range (70-180 mg/dl) and hyperglycaemia (> 180 mg/dl). We compared glycaemic measures collected during lockdown to those collected before the SARS-CoV-2 epidemic and to the periods immediately before lockdown. RESULTS: In 20 patients who had stopped working and were at home as a result of the lockdown, overall glycaemic control improved during the first 7 days of the lockdown as compared to the weeks before the spread of SARS-CoV-2. Average glucose declined from 177 ± 45 mg/dl (week before lockdown) to 160 ± 40 mg/dl (lockdown; p = 0.005) and the standard deviation improved significantly. Time in range increased from 54.4 to 65.2% (p = 0.010), and time in hyperglycaemia decreased from 42.3 to 31.6% (p = 0.016). The number of scans per day remained unchanged. In 13 patients who continued working, none of the measures of glycaemic control changed during lockdown. CONCLUSION: Despite the limited possibility to exercise and the incumbent psychologic stress, glycaemic control improved in patients with T1D who stopped working during the lockdown, suggesting that slowing down routine daily activities can have beneficial effects on T1D management, at least in the short term.

The International Diabetes Closed-Loop Study: Testing Artificial Pancreas Component Interoperability.

BACKGROUND: Use of artificial pancreas (AP) requires seamless interaction of device components, such as continuous glucose monitor (CGM), insulin pump, and control algorithm. Mobile AP configurations also include a smartphone as computational hub and gateway to cloud applications (e.g., remote monitoring and data review and analysis). This International Diabetes Closed-Loop study was designed to demonstrate and evaluate the operation of the inControl AP using different CGMs and pump modalities without changes to the user interface, user experience, and underlying controller. METHODS: Forty-three patients with type 1 diabetes (T1D) were enrolled at 10 clinical centers (7 United States, 3 Europe) and 41 were included in the analyses (39% female, >95% non-Hispanic white, median T1D duration 16 years, median HbA1c 7.4%). Two CGMs and two insulin pumps were tested by different study participants/sites using the same system hub (a smartphone) during 2 weeks of in-home use. RESULTS: The major difference between the system components was the stability of their wireless connections with the smartphone. The two sensors achieved similar rates of connectivity as measured by percentage time in closed loop (75% and 75%); however, the two pumps had markedly different closed-loop adherence (66% vs. 87%). When connected, all system configurations achieved similar glycemic outcomes on AP control (73% [mean] time in range: 70-180 mg/dL, and 1.7% [median] time <70 mg/dL). CONCLUSIONS: CGMs and insulin pumps can be interchangeable in the same Mobile AP system, as long as these devices achieve certain levels of reliability and wireless connection stability.

Effects of Hypoglycemia on Circulating Stem and Progenitor Cells in Diabetic Patients.

Context: Iatrogenic hypoglycemia is the most common acute diabetic complication, and it significantly increases morbidity. In people with diabetes, reduction in the levels of circulating stem and progenitor cells predicts adverse outcomes. Objective: To evaluate whether hypoglycemia in diabetes affects circulating stem cells and endothelial progenitor cells (EPCs). Design: We performed an experimental hypoglycemia study (Study 1) and a case-control study (Study 2). Setting: Tertiary referral inpatient clinic. Patients and Other Participants: Type 1 diabetic patients (Study 1, n = 19); diabetic patients hospitalized for severe iatrogenic hypoglycemia, matched inpatient and outpatient controls (Study 2, n = 22/group). Interventions: Type 1 diabetic patients underwent two in-hospital sessions of glucose monitoring during a breakfast meal with or without induction of hypoglycemia in random order. In Study 2, patients hospitalized for hypoglycemia and matched controls were compared. Main Outcome Measure: Circulating stem cells and EPCs were measured by flow cytometry based on the expression of CD34 and kinase insert domain receptor (KDR). Results: In Study 1, the physiologic decline of CD34+KDR+ EPCs from 8 am to 2 pm was abolished by insulin-induced hypoglycemia in type 1 diabetic patients. In Study 2, diabetic patients hospitalized for severe iatrogenic hypoglycemia had significantly lower levels of CD34+ stem cells and CD34+KDR+ EPCs compared with diabetic inpatients or outpatient controls. Conclusions: In diabetic patients, a single mild hypoglycemic episode can compromise the physiologic EPC fluctuation, whereas severe hypoglycemia is associated with a marked reduction in stem cells and EPCs. These data provide a possible link between hypoglycemia and adverse outcomes of diabetes.

Overnight Closed-Loop Control Improves Glycemic Control in a Multicenter Study of Adults With Type 1 Diabetes.

Context: Closed-loop control (CLC) for the management of type 1 diabetes (T1D) is a novel method for optimizing glucose control, and strategies for individualized implementation are being developed. Objective: To analyze glycemic control in an overnight CLC system designed to "reset" the patient to near-normal glycemic targets every morning. Design: Randomized, crossover, multicenter clinical trial. Participants: Forty-four subjects with T1D requiring insulin pump therapy. Intervention: Sensor-augmented pump therapy (SAP) at home vs 5 nights of CLC (active from 23:00 to 07:00) in a supervised outpatient setting (research house or hotel), with a substudy of 5 nights of CLC subsequently at home. Main Outcome Measure: The percentage of time spent in the target range (70 to 180 mg/dL measured using a continuous glucose monitor). Results: Forty subjects (age, 45.5 ± 9.5 years; hemoglobin A1c, 7.4% ± 0.8%) completed the study. The time in the target range (70 to 180 mg/dL) significantly improved in CLC vs SAP over 24 hours (78.3% vs 71.4%; P = 0.003) and overnight (85.7% vs 67.6%; P < 0.001). The time spent in a hypoglycemic range (<70 mg/dL) decreased significantly in the CLC vs SAP group over 24 hours (2.5% vs 4.3%; P = 0.002) and overnight (0.9% vs 3.2%; P < 0.001). The mean glucose level at 07:00 was lower with CLC than with SAP (123.7 vs 145.3 mg/dL; P < 0.001). The substudy at home, involving 10 T1D subjects, showed similar trends with an increased time in target (70 to 180 mg/dL) overnight (75.2% vs 62.2%; P = 0.07) and decreased time spent in the hypoglycemic range (<70 mg/dL) overnight in CLC vs SAP (0.6% vs 3.7%; P = 0.03). Conclusion: Overnight-only CLC increased the time in the target range over 24 hours and decreased the time in hypoglycemic range over 24 hours in a supervised outpatient setting. A pilot extension study at home showed a similar nonsignificant trend.

Feasibility of Long-Term Closed-Loop Control: A Multicenter 6-Month Trial of 24/7 Automated Insulin Delivery.

BACKGROUND: In the past few years, the artificial pancreas-the commonly accepted term for closed-loop control (CLC) of blood glucose in diabetes-has become a hot topic in research and technology development. In the summer of 2014, we initiated a 6-month trial evaluating the safety of 24/7 CLC during free-living conditions. RESEARCH DESIGN AND METHODS: Following an initial 1-month Phase 1, 14 individuals (10 males/4 females) with type 1 diabetes at three clinical centers in the United States and one in Italy continued with a 5-month Phase 2, which included 24/7 CLC using the wireless portable Diabetes Assistant (DiAs) developed at the University of Virginia Center for Diabetes Technology. Median subject characteristics were age 45 years, duration of diabetes 27 years, total daily insulin 0.53 U/kg/day, and baseline HbA1c 7.2% (55 mmol/mol). RESULTS: Compared with the baseline observation period, the frequency of hypoglycemia below 3.9 mmol/L during the last 3 months of CLC was lower: 4.1% versus 1.3%, P < 0.001. This was accompanied by a downward trend in HbA1c from 7.2% (55 mmol/mol) to 7.0% (53 mmol/mol) at 6 months. HbA1c improvement was correlated with system use (Spearman r = 0.55). The user experience was favorable with identified benefit particularly at night and overall trust in the system. There were no serious adverse events, severe hypoglycemia, or diabetic ketoacidosis. CONCLUSION: We conclude that CLC technology has matured and is safe for prolonged use in patients' natural environment. Based on these promising results, a large randomized trial is warranted to assess long-term CLC efficacy and safety.