Day and night home closed-loop insulin delivery in adults with type 1 diabetes: three-center randomized crossover study.

OBJECTIVE: To evaluate the feasibility of day and night closed-loop insulin delivery in adults with type 1 diabetes under free-living conditions. RESEARCH DESIGN AND METHODS: Seventeen adults with type 1 diabetes on insulin pump therapy (means ± SD age 34 ± 9 years, HbA1c 7.6 ± 0.8%, and duration of diabetes 19 ± 9 years) participated in an open-label multinational three-center crossover study. In a random order, participants underwent two 8-day periods (first day at the clinical research facility followed by 7 days at home) of sensor-augmented insulin pump therapy (SAP) or automated closed-loop insulin delivery. The primary end point was the time when sensor glucose was in target range between 3.9 and 10.0 mmol/L during the 7-day home phase. RESULTS: During the home phase, the percentage of time when glucose was in target range was significantly higher during closed-loop compared with SAP (median 75% [interquartile range 61-79] vs. 62% [53-70], P = 0.005). Mean glucose (8.1 vs. 8.8 mmol/L, P = 0.027) and time spent above target (P = 0.013) were lower during closed loop, while time spent below target was comparable (P = 0.339). Increased time in target was observed during both daytime (P = 0.017) and nighttime (P = 0.013). CONCLUSIONS: Compared with SAP, 1 week of closed-loop insulin delivery at home reduces mean glucose and increases time in target without increasing the risk of hypoglycemia in adults with relatively well-controlled type 1 diabetes.

Day and night closed-loop control in adults with type 1 diabetes: a comparison of two closed-loop algorithms driving continuous subcutaneous insulin infusion versus patient self-management.

OBJECTIVE: To compare two validated closed-loop (CL) algorithms versus patient self-control with CSII in terms of glycemic control. RESEARCH DESIGN AND METHODS: This study was a multicenter, randomized, three-way crossover, open-label trial in 48 patients with type 1 diabetes mellitus for at least 6 months, treated with continuous subcutaneous insulin infusion. Blood glucose was controlled for 23 h by the algorithm of the Universities of Pavia and Padova with a Safety Supervision Module developed at the Universities of Virginia and California at Santa Barbara (international artificial pancreas [iAP]), by the algorithm of University of Cambridge (CAM), or by patients themselves in open loop (OL) during three hospital admissions including meals and exercise. The main analysis was on an intention-to-treat basis. Main outcome measures included time spent in target (glucose levels between 3.9 and 8.0 mmol/L or between 3.9 and 10.0 mmol/L after meals). RESULTS: Time spent in the target range was similar in CL and OL: 62.6% for OL, 59.2% for iAP, and 58.3% for CAM. While mean glucose level was significantly lower in OL (7.19, 8.15, and 8.26 mmol/L, respectively) (overall P = 0.001), percentage of time spent in hypoglycemia (<3.9 mmol/L) was almost threefold reduced during CL (6.4%, 2.1%, and 2.0%) (overall P = 0.001) with less time ≤2.8 mmol/L (overall P = 0.038). There were no significant differences in outcomes between algorithms. CONCLUSIONS: Both CAM and iAP algorithms provide safe glycemic control.

Accuracy and reliability of continuous glucose monitoring systems: a head-to-head comparison.

OBJECTIVE: This study assessed the accuracy and reliability of three continuous glucose monitoring (CGM) systems. RESEARCH DESIGN AND METHODS: We studied the Animas® (West Chester, PA) Vibe™ with Dexcom® (San Diego, CA) G4™ version A sensor (G4A), the Abbott Diabetes Care (Alameda, CA) Freestyle® Navigator I (NAV), and the Medtronic (Northridge, CA) Paradigm® with Enlite™ sensor (ENL) in 20 patients with type 1 diabetes mellitus. All systems were investigated both in a clinical research center (CRC) and at home. In the CRC, patients received a meal with a delayed and increased insulin dose to induce a postprandial glucose peak and nadir. Hereafter, randomization determined which two of the three systems would be worn at home until the end of functioning, attempting use beyond manufacturer-specified lifetime. Patients performed at least five reference finger sticks per day. An analysis of variance was performed on all data points ≥15 min apart. RESULTS: Overall average mean absolute relative difference (MARD) (SD) measured at the CRC was 16.5% (14.3%) for NAV and 16.4% (15.6%) for ENL, outperforming G4A at 20.5% (18.2%) (P<0.001). Overall MARD when assessed at home was 14.5% (16.7%) for NAV and 16.5 (18.8%) for G4A, outperforming ENL at 18.9% (23.6%) (P=0.006). Median time until end of functioning was similar: 10.0 (1.0) days for G4A, 8.0 (3.5) days for NAV, and 8.0 (1.5) days for ENL (P=0.119). CONCLUSIONS: In the CRC, G4A was less accurate than NAV and ENL sensors, which seemed comparable. However, at home, ENL was less accurate than NAV and G4A. Moreover, CGM systems often show sufficient accuracy to be used beyond manufacturer-specified lifetime.

Development and validation of a low cost blood filtration element separating plasma from undiluted whole blood.

Clinical point of care testing often needs plasma instead of whole blood. As centrifugation is labor intensive and not always accessible, filtration is a more appropriate separation technique. The complexity of whole blood is such that there is still no commercially available filtration system capable of separating small sample volumes (10-100 µl) at the point of care. The microfluidics research in blood filtration is very active but to date nobody has validated a low cost device that simultaneously filtrates small samples of whole blood and reproducibly recovers clinically relevant biomarkers, and all this in a limited amount of time with undiluted raw samples. In this paper, we show first that plasma filtration from undiluted whole blood is feasible and reproducible in a low-cost microfluidic device. This novel microfluidic blood filtration element (BFE) extracts 12 µl of plasma from 100 µl of whole blood in less than 10 min. Then, we demonstrate that our device is valid for clinical studies by measuring the adsorption of interleukins through our system. This adsorption is reproducible for interleukins IL6, IL8, and IL10 but not for TNFα. Hence, our BFE is valid for clinical diagnostics with simple calibration prior to performing any measurement.

Hospital glucose control: safe and reliable glycemic control using enhanced model predictive control algorithm in medical intensive care unit patients.

BACKGROUND: The aim of this study was to investigate the performance of the enhanced Model Predictive Control (eMPC) algorithm for glycemic control in medical critically ill patients for the whole length of intensive care unit (ICU) stay. METHODS: The trial was designed as a single-center, open, noncontrolled clinical investigation in a nine-bed medical ICU in a tertiary teaching hospital. In 20 patients, blood glucose (BG) was controlled with a laptop-based bedside version of the eMPC. Efficacy was assessed by percentage of time within the target range (4.4-6.1 mM; primary end point), mean BG, and BG sampling interval. Safety was assessed by the number of severe hypoglycemic episodes (<2.2 mM). RESULTS: Twenty patients (69 +/- 11 years old; body mass index, 27.4 +/- 4.5 kg/m(2); APACHE II, 25.5 +/- 5.2) were included for a period of 7.3 days (median; interquartile range, 4.4-10.2 days) in the study. Time within target range was 58.12 +/- 10.05% (mean +/- SD). For all patients with at least 7 days in the ICU, there was no statistically significant difference between the daily mean percentage of times in target range in respect of the averages. Mean arterial BG was 5.8 +/- 0.5 mM, insulin requirement was 101.3 +/- 50.7 IU/day, and mean carbohydrate intake (enteral and parenteral nutrition) was 176.4 +/- 61.9 g/day. Three hypoglycemic episodes occurred in three subjects, corresponding to a rate of 0.02 per treatment day. CONCLUSIONS: In our single-center, noncontrolled study the eMPC algorithm was a safe and reliable method to control BG in critically medical ICU patients for the whole length of ICU stay.