Analysis of "Multicenter Evaluation Study Comparing a New Factory-Calibrated Real-Time Continuous Glucose Monitoring System to Existing Flash Glucose Monitoring System".

In an article in the Journal of Diabetes Science and Technology, Ji et al. report on the accuracy of a new factory calibrated continuous glucose monitoring system, the AiDEX CGM (Microtech Medical Company, Ltd., Hangzhou, China). This is the first report from a new manufacturer of a highly accurate factory calibrated CGM. The authors report that the accuracy of the AiDEX CGM is comparable to previous results from Abbott Diabetes Care and Dexcom. However, the study protocol was significantly different from previous studies. This study is the first of numerous studies likely from other manufacturers of CGM technology. It raises the question of how to evaluate sensor performance in the coming era of mass adoption of CGM and increased use of automated insulin delivery systems.

Safety and Performance of the Omnipod Hybrid Closed-Loop System in Adults, Adolescents, and Children with Type 1 Diabetes Over 5 Days Under Free-Living Conditions.

Background: The objective of this study was to assess the safety and performance of the Omnipod® personalized model predictive control (MPC) algorithm in adults, adolescents, and children aged ≥6 years with type 1 diabetes (T1D) under free-living conditions using an investigational device. Materials and Methods: A 96-h hybrid closed-loop (HCL) study was conducted in a supervised hotel/rental home setting following a 7-day outpatient standard therapy (ST) phase. Eligible participants were aged 6-65 years with A1C <10.0% using insulin pump therapy or multiple daily injections. Meals during HCL were unrestricted, with boluses administered per usual routine. There was daily physical activity. The primary endpoints were percentage of time with sensor glucose <70 and ≥250 mg/dL. Results: Participants were 11 adults, 10 adolescents, and 15 children aged (mean ± standard deviation) 28.8 ± 7.9, 14.3 ± 1.3, and 9.9 ± 1.0 years, respectively. Percentage time ≥250 mg/dL during HCL was 4.5% ± 4.2%, 3.5% ± 5.0%, and 8.6% ± 8.8% per respective age group, a 1.6-, 3.4-, and 2.0-fold reduction compared to ST (P = 0.1, P = 0.02, and P = 0.03). Percentage time <70 mg/dL during HCL was 1.9% ± 1.3%, 2.5% ± 2.0%, and 2.2% ± 1.9%, a statistically significant decrease in adults when compared to ST (P = 0.005, P = 0.3, and P = 0.3). Percentage time 70-180 mg/dL increased during HCL compared to ST, reaching significance for adolescents and children: HCL 73.7% ± 7.5% vs. ST 68.0% ± 15.6% for adults (P = 0.08), HCL 79.0% ± 12.6% vs. ST 60.6% ± 13.4% for adolescents (P = 0.01), and HCL 69.2% ± 13.5% vs. ST 54.9% ± 12.9% for children (P = 0.003). Conclusions: The Omnipod personalized MPC algorithm was safe and performed well over 5 days and 4 nights of use by a cohort of participants ranging from youth aged ≥6 years to adults with T1D under supervised free-living conditions with challenges, including daily physical activity and unrestricted meals.

Performance of Omnipod Personalized Model Predictive Control Algorithm with Moderate Intensity Exercise in Adults with Type 1 Diabetes.

Background: The objective of this study was to assess the safety and performance of the Omnipod® personalized model predictive control (MPC) algorithm with variable glucose setpoints and moderate intensity exercise using an investigational device in adults with type 1 diabetes (T1D). Materials and Methods: A supervised 54-h hybrid closed-loop (HCL) study was conducted in a hotel setting after a 7-day outpatient standard treatment phase. Adults aged 18-65 years with T1D and HbA1c between 6.0% and 10.0% were eligible. Subjects completed two moderate intensity exercise sessions of >30 min duration on consecutive days: the first with the glucose set point increased from 130 to 150 mg/dL and the second with a temporary basal rate of 50%, both started 90 min pre-exercise. Primary endpoints were percentage time in hypoglycemia <70 mg/dL and hyperglycemia ≥250 mg/dL. Results: Twelve subjects participated in the study, with (mean ± standard deviation) age 36.5 ± 14.4 years, diabetes duration 21.7 ± 15.7 years, HbA1c 7.6% ± 1.1%, and total daily dose 0.60 ± 0.22 U/kg. Outcomes for the 54-h HCL period were mean glucose: 136 ± 14 mg/dL, percentage time <70 mg/dL: 1.4% ± 1.3%, 70-180 mg/dL: 85.1% ± 9.3%, and ≥250 mg/dL: 1.8% ± 2.4%. In the 12-h period after exercise start, percentage time <70 mg/dL was 1.4% ± 2.7% with the raised glucose set point and 1.6% ± 3.0% with reduced basal rate. The percentage time <70 mg/dL overnight was 0% ± 0% on both study nights. Conclusions: The Omnipod personalized MPC algorithm performed well and was safe during day and night use in response to variable glucose set points and with temporarily raised glucose set point or reduced basal rate 90 min in advance of moderate intensity exercise in adults with T1D.

Performance of the Omnipod Personalized Model Predictive Control Algorithm with Meal Bolus Challenges in Adults with Type 1 Diabetes.

BACKGROUND: This study assessed the safety and performance of the Omnipod® personalized model predictive control (MPC) algorithm using an investigational device in adults with type 1 diabetes in response to overestimated and missed meal boluses and extended boluses for high-fat meals. MATERIALS AND METHODS: A supervised 54-h hybrid closed-loop (HCL) study was conducted in a hotel setting after a 7-day outpatient open-loop run-in phase. Adults aged 18-65 years with type 1 diabetes and HbA1c 6.0%-10.0% were eligible. Primary endpoints were percentage time in hypoglycemia <70 mg/dL and hyperglycemia ≥250 mg/dL. Glycemic responses for 4 h to a 130% overestimated bolus and a missed meal bolus were compared with a 100% bolus for identical meals, respectively. The 12-h postprandial responses to a high-fat meal were compared using either a standard or extended bolus. RESULTS: Twelve subjects participated in the study, with (mean ± standard deviation): age 35.4 ± 14.1 years, diabetes duration 16.5 ± 9.3 years, HbA1c 7.7 ± 0.9%, and total daily dose 0.58 ± 0.19 U/kg. Outcomes for the 54-h HCL period were mean glucose 153 ± 15 mg/dL, percentage time <70 mg/dL [median (interquartile range)]: 0.0% (0.0-1.2%), 70-180 mg/dL: 76.1% ± 8.0%, and ≥250 mg/dL: 4.5% ± 3.6%. After both the 100% and 130% boluses, postprandial percentage time <70 mg/dL was 0.0% (0.0-0.0%) (P = 0.50). After the 100% and missed boluses, postprandial percentage time ≥250 mg/dL was 0.2% ± 0.6% and 10.3% ± 16.5%, respectively (P = 0.06). Postprandial percentages time ≥250 mg/dL and <70 mg/dL were similar with standard or extended boluses for a high-fat meal. CONCLUSIONS: The Omnipod personalized MPC algorithm performed well and was safe during day and night use in response to overestimated, missed, and extended meal boluses in adults with type 1 diabetes.

Safety and Feasibility of the OmniPod Hybrid Closed-Loop System in Adult, Adolescent, and Pediatric Patients with Type 1 Diabetes Using a Personalized Model Predictive Control Algorithm.

BACKGROUND: The safety and feasibility of the OmniPod personalized model predictive control (MPC) algorithm in adult, adolescent, and pediatric patients with type 1 diabetes were investigated. METHODS: This multicenter, observational trial included a 1-week outpatient sensor-augmented pump open-loop phase and a 36-h inpatient hybrid closed-loop (HCL) phase with announced meals ranging from 30 to 90 g of carbohydrates and limited physical activity. Patients aged 6-65 years with HbA1c between 6.0% and 10.0% were eligible. The investigational system included a modified version of OmniPod, the Dexcom G4 505 Share® AP System, and the personalized MPC algorithm running on a tablet computer. Primary endpoints included sensor glucose percentage of time in hypoglycemia <70 mg/dL and hyperglycemia >250 mg/dL. Additional glycemic targets were assessed. RESULTS: The percentage of time <70 mg/dL during the 36-h HCL phase was mean (standard deviation): 0.7 (1.7) in adults receiving 80% meal bolus (n = 24), and 0.7 (1.2) in adults (n = 10), 2.0 (2.4) in adolescents (n = 12), and 2.0 (2.6) in pediatrics (n = 12) receiving 100% meal bolus. The overall hypoglycemia rate was 0.49 events/24 h. The percentage of time >250 mg/dL was 8.0 (7.5), 3.6 (3.7), 4.9 (6.3), and 6.7 (5.6) in the study groups, respectively. Percentage of time in the target range of 70-180 mg/dL was 69.5 (14.4), 73.0 (15.0), 72.6 (15.5), and 70.1 (12.3), respectively. CONCLUSIONS: The OmniPod personalized MPC algorithm performed well and was safe during day and night use in adult, adolescent, and pediatric patients with type 1 diabetes. Longer term studies will assess the safety and performance of the algorithm under free living conditions with extended use.

Glycemic Variability Percentage: A Novel Method for Assessing Glycemic Variability from Continuous Glucose Monitor Data.

BACKGROUND: High levels of glycemic variability are still observed in most patients with diabetes with severe insulin deficiency. Glycemic variability may be an important risk factor for acute and chronic complications. Despite its clinical importance, there is no consensus on the optimum method for characterizing glycemic variability. METHOD: We developed a simple new metric, the glycemic variability percentage (GVP), to assess glycemic variability by analyzing the length of the continuous glucose monitoring (CGM) temporal trace normalized to the duration under evaluation. The GVP is similar to other recently proposed glycemic variability metrics, the distance traveled, and the mean absolute glucose (MAG) change. We compared results from distance traveled, MAG, GVP, standard deviation (SD), and coefficient of variation (CV) applied to simulated CGM traces accentuating the difference between amplitude and frequency of oscillations. The GVP metric was also applied to data from clinical studies for the Dexcom G4 Platinum CGM in subjects without diabetes, with type 2 diabetes, and with type 1 diabetes (adults, adolescents, and children). RESULTS: In contrast to other metrics, such as CV and SD, the distance traveled, MAG, and GVP all captured both the amplitude and frequency of glucose oscillations. The GVP metric was also able to differentiate between diabetic and nondiabetic subjects and between subjects with diabetes with low, moderate, and high glycemic variability based on interquartile analysis. CONCLUSION: A new metric for the assessment of glycemic variability has been shown to capture glycemic variability due to fluctuations in both the amplitude and frequency of glucose given by CGM data.

Application of Glycemic Variability Percentage: Implications for Continuous Glucose Monitor Utilization and Analysis of Artificial Pancreas Data.

BACKGROUND: The problem of glycemic variability has been widely acknowledged in patients with diabetes with severe insulin deficiency. In a companion article, we proposed a novel metric, the glycemic variability percentage (GVP), for assessing glycemic variability that accounts for both the amplitude and frequency of glycemic fluctuations. METHOD: We applied the new metric, the GVP, to a previously reported case of a subject using an earlier generation continuous glucose monitoring (CGM) device, in which successive periods of use were associated with an apparent decrease in glycemic variability. Results were compared with histogram distributions for the rate of change of glucose as well. The GVP was also applied to data from a published study of a bihormonal artificial pancreas system comparing results from open loop and closed loop in adolescents and in adults. RESULTS: The GVP was able to quantify the changes in glycemic variability during successive periods of CGM use. Application of the GVP to a published study of a bihormonal artificial pancreas found an increase in glycemic variability compared with other accepted metrics which suggested a decrease in glycemic variability. CONCLUSION: The GVP may be a clinically useful tool in characterizing the change in glycemic variability in subjects using CGM devices. Compared with metrics, such as the standard deviation, that focus solely on the amplitude of oscillations, the GVP, which measures both frequency and amplitude, may also be a more useful tool in assessing the true level of glycemic variability in artificial pancreas studies.

A Simple Composite Metric for the Assessment of Glycemic Status from Continuous Glucose Monitoring Data: Implications for Clinical Practice and the Artificial Pancreas.

BACKGROUND: The potential clinical benefits of continuous glucose monitoring (CGM) have been recognized for many years, but CGM is used by a small fraction of patients with diabetes. One obstacle to greater use of the technology is the lack of simplified tools for assessing glycemic control from CGM data without complicated visual displays of data. METHODS: We developed a simple new metric, the personal glycemic state (PGS), to assess glycemic control solely from continuous glucose monitoring data. PGS is a composite index that assesses four domains of glycemic control: mean glucose, glycemic variability, time in range and frequency and severity of hypoglycemia. The metric was applied to data from six clinical studies for the G4 Platinum continuous glucose monitoring system (Dexcom, San Diego, CA). The PGS was also applied to data from a study of artificial pancreas comparing results from open loop and closed loop in adolescents and in adults. RESULTS: The new metric for glycemic control, PGS, was able to characterize the quality of glycemic control in a wide range of study subjects with various mean glucose, minimal, moderate, and excessive glycemic variability and subjects on open loop versus closed loop control. CONCLUSION: A new composite metric for the assessment of glycemic control based on CGM data has been defined for use in assessing glycemic control in clinical practice and research settings. The new metric may help rapidly identify problems in glycemic control and may assist with optimizing diabetes therapy during time-constrained physician office visits.

Continuous Glucose Monitor Interference With Commonly Prescribed Medications: A Pilot Study.

BACKGROUND: Reliability of continuous glucose monitors (CGM) is a prerequisite for therapeutic dosing of insulin without the need for confirmatory blood glucose meter measurements. Interference of CGMs with commonly prescribed substances has not been extensively evaluated. METHODS: We sought to undertake a novel pilot study to determine the susceptibility of FDA-approved CGM systems (Medtronic Guardian Sof-Sensor, Dexcom G4 Platinum) to erroneous readings in the presence of common medications. CGMs were placed on the abdomen of healthy subjects 48 hours prior to study. Subjects were admitted to the Clinical Research Trials Unit (CRTU) on the evening before study and fed a standard supper. The following morning, an oral medication was administered in the fasted state and blood was sampled for 9 hours. CGM values were compared to ambient glucose (measured with YSI) to observe variations in CGM readings. Microdialysis catheters were also placed in the abdomen to sample interstitial fluid (ISF) for drug concentrations. RESULTS: Nineteen healthy drug-naïve subjects without diabetes participated in the study. A drug/substance was tested up to a maximum of nine times on separate occasions. Comparison of CGM glucose patterns to actual plasma glucose concentrations show several drugs, including lisinopril, albuterol, and acetaminophen, appear to interfere with commonly used CGM devices. Wine also interfered with CGM readings. CONCLUSIONS: We conclude there is some evidence of CGM interference with lisinopril, albuterol, acetaminophen, atenolol, and red wine. Future studies are required to address interference with newer sensors being approved or in the process of approval.

Direct Evidence of Acetaminophen Interference with Subcutaneous Glucose Sensing in Humans: A Pilot Study.

BACKGROUND: Recent advances in accuracy and reliability of continuous glucose monitoring (CGM) devices have focused renewed interest on the use of such technology for therapeutic dosing of insulin without the need for independent confirmatory blood glucose meter measurements. An important issue that remains is the susceptibility of CGM devices to erroneous readings in the presence of common pharmacologic interferences. We report on a new method of assessing CGM sensor error to pharmacologic interferences using the example of oral administration of acetaminophen. MATERIALS AND METHODS: We examined the responses of several different Food and Drug Administration-approved and commercially available CGM systems (Dexcom [San Diego, CA] Seven(®) Plus™, Medtronic Diabetes [Northridge, CA] Guardian(®), and Dexcom G4(®) Platinum) to oral acetaminophen in 10 healthy volunteers without diabetes. Microdialysis catheters were placed in the abdominal subcutaneous tissue. Blood and microdialysate samples were collected periodically and analyzed for glucose and acetaminophen concentrations before and after oral ingestion of 1 g of acetaminophen. We compared the response of CGM sensors with the measured acetaminophen concentrations in the blood and interstitial fluid. RESULTS: Although plasma glucose concentrations remained constant at approximately 90 mg/dL (approximately 5 mM) throughout the study, CGM glucose measurements varied between approximately 85 to 400 mg/dL (from approximately 5 to 22 mM) due to interference from the acetaminophen. The temporal profile of CGM interference followed acetaminophen concentrations measured in interstitial fluid (ISF). CONCLUSIONS: This is the first direct measurement of ISF concentrations of putative CGM interferences with simultaneous measurements of CGM performance in the presence of the interferences. The observed interference with glucose measurements in the tested CGM devices coincided temporally with appearance of acetaminophen in the ISF. The method applied here can be used to determine the susceptibility of current and future CGM systems to interference from acetaminophen or other exogenous pharmacologic agents.

Are Systematic Reviews and Meta-Analyses Appropriate Tools for Assessing Evolving Medical Device Technologies?

Systematic reviews and meta-analyses (SRMAs) provide unique insights into comparative effectiveness of diabetes treatments. However, use of these analyses may be inappropriate for assessing the value and utility of technologies that involve significant behavioral interventions and encompass rapidly evolving technologies such as real-time continuous glucose monitoring (RT-CGM). The rapid evolution of RT-CGM, compared with the time required for publication of clinical studies used in SRMAs, may preclude differentiation between past and current generations of devices. In addition, the effect of performance and usability differences between the various commercial devices on possible clinical outcomes associated with the devices are often not clearly discussed, and many of the RT-CGM studies assessed in SRMAs do not provide adequate information regarding whether and/or to what degree study subjects and clinicians were trained to use the RT-CGM and utilize the data to adjust therapy. Although numerous clinical studies have shown that the glycemic benefit of RT-CGM is related to the frequency and duration of use, a disproportionate number of RT-CGM studies included in recent SRMAs are based on the results of the intention-to-treat analyses and do not consider this fundamental behavioral component in their conclusions. Given these limitations, the generalizability of SRMA conclusions may be limited, and findings from these reports may significantly underestimate the potential glycemic benefit of current and future devices, posing challenges for coverage and reimbursement. We reviewed the potential limitations of the recent Cochrane Collaboration report on CGM, focusing on the 12 studies that assessed RT-CGM use in adults, children/adolescents or both.

Modeling Plasma-to-Interstitium Glucose Kinetics from Multitracer Plasma and Microdialysis Data.

BACKGROUND: Quantitative assessment of the dynamic relationship between plasma and interstitial fluid (ISF) glucose and the estimation of the plasma-to-ISF delay are of major importance to determine the accuracy of subcutaneous glucose sensors, an essential component of open- and closed-loop therapeutic systems for type 1 diabetes mellitus (T1DM). The goal of this work is to develop a model of plasma-to-ISF glucose kinetics from multitracer plasma and interstitium data, obtained by microdialysis, in healthy and T1DM subjects, under fasting conditions. MATERIALS AND METHODS: A specific experimental design, combining administration of multiple tracers with the microdialysis technique, was used to simultaneously frequently collect plasma and ISF data. Linear time-invariant compartmental modeling was used to describe glucose kinetics from the tracer data because the system is in steady state. RESULTS: A two-compartment model was shown accurate and was identified from both plasma and ISF data. An "equilibration time" between plasma and ISF of 9.1 and 11.0 min (median) in healthy and T1DM subjects, respectively, was calculated. CONCLUSIONS: We have demonstrated that, in steady-state condition, the glucose plasma-to-ISF kinetics can be modeled with a linear two-compartment model and that the "equilibration time" between the two compartments can be estimated with precision. Future studies will assess plasma-to-interstitium glucose kinetics during glucose and insulin perturbations in both healthy and T1DM subjects.

Hypoglycemic Accuracy and Improved Low Glucose Alerts of the Latest Dexcom G4 Platinum Continuous Glucose Monitoring System.

OBJECTIVE: Accuracy of continuous glucose monitoring (CGM) devices in hypoglycemia has been a widely reported shortcoming of this technology. We report the accuracy in hypoglycemia of a new version of the Dexcom (San Diego, CA) G4 Platinum CGM system (software 505) and present results regarding the optimum setting of CGM hypoglycemic alerts. MATERIALS AND METHODS: CGM values were compared with YSI analyzer (YSI Life Sciences, Yellow Springs, OH) measurements every 15 min. We reviewed the accuracy of the CGM system in the hypoglycemic range using standard metrics. We analyzed the time required for the CGM system to detect biochemical hypoglycemia (70 mg/dL) compared with the YSI with alert settings at 70 mg/dL and 80 mg/dL. We also analyzed the time between the YSI value crossing 55 mg/dL, defined as the threshold for cognitive impairment due to hypoglycemia, and when the CGM system alerted for hypoglycemia. RESULTS: The mean absolute difference for a glucose level of less than 70 mg/dL was 6 mg/dL. Ninety-six percent of CGM values were within 20 mg/dL of the YSI values between 40 and 80 mg/dL. When the CGM hypoglycemic alert was set at 80 mg/dL, the device provided an alert for biochemical hypoglycemia within 10 min in 95% of instances and at least a 10-min advance warning before the cognitive impairment threshold in 91% of instances in the study. CONCLUSIONS: Use of an 80 mg/dL threshold setting for hypoglycemic alerts on the G4 Platinum (software 505) may provide patients with timely warning of hypoglycemia before the onset of cognitive impairment, enabling them to treat themselves for hypoglycemia with fast-acting carbohydrates and prevent neuroglycopenia associated with very low glucose levels.

Time lag of glucose from intravascular to interstitial compartment in type 1 diabetes.

The premise of effective closed-loop insulin therapy for type 1 diabetes (T1D) relies on the accuracy of continuous interstitial fluid glucose sensing that represents the crucial afferent arm of such a system. An important determinant of sensor accuracy is the physiological time lag of glucose transport from the vascular to the interstitial space. The purpose of current studies was to determine the physiological time lag of glucose transport from the vascular to the abdominal subcutaneous interstitial space in T1D. Four microdialysis catheters were inserted into the abdominal subcutaneous space in 6 T1D subjects under overnight fasted conditions. Plasma glucose was maintained at 113.7 ± 6.3 mg/dl using a continuous intravenous insulin infusion. After sequential intravenous bolus administrations of glucose isotopes, timed plasma and interstitial fluid samples were collected chronologically and analyzed for tracer enrichments. We observed a median (range) time lag of tracer appearance (time to detection) into the interstitial space after intravenous bolus of 6.8 (4.8-9.8) minutes, with all participants having detectable values by 9.8 minutes. We conclude that in the overnight fasted state in T1D adults, the delay of glucose appearance from the vascular to the interstitial space is less than 10 minutes, thereby implying that this minimal physiological time lag should not be a major impediment to the development of an effective closed-loop control system for T1D.

The artificial pancreas: current status and future prospects in the management of diabetes.

Recent advances in insulins, insulin pumps, continuous glucose-monitoring systems, and control algorithms have resulted in an acceleration of progress in the development of artificial pancreas devices. This review discusses progress in the development of external systems that are based on subcutaneous drug delivery and subcutaneous continuous glucose monitoring. There are two major system-level approaches to achieving closed-loop control of blood glucose in diabetic individuals. The unihormonal approach uses insulin to reduce blood glucose and relies on complex safety mitigation algorithms to reduce the risk of hypoglycemia. The bihormonal approach uses both insulin to lower blood glucose and glucagon to raise blood glucose, and also relies on complex algorithms to provide for safety of the user. There are several major strategies for the design of control algorithms and supervision control for application to the artificial pancreas: proportional-integral-derivative, model predictive control, fuzzy logic, and safety supervision designs. Advances in artificial pancreas research in the first decade of this century were based on the ongoing computer revolution and miniaturization of electronic technology. The advent of modern smartphones has created the ability to utilize smartphone technology as the engineering centerpiece of an artificial pancreas. With these advances, an artificial or bionic pancreas is within reach.

Remote glucose monitoring in camp setting reduces the risk of prolonged nocturnal hypoglycemia.

OBJECTIVE: This study tested the feasibility and effectiveness of remote continuous glucose monitoring (CGM) in a diabetes camp setting. SUBJECTS AND METHODS: Twenty campers (7-21 years old) with type 1 diabetes were enrolled at each of three camp sessions lasting 5-6 days. On alternating nights, 10 campers were randomized to usual wear of a Dexcom (San Diego, CA) G4™ PLATINUM CGM system, and 10 were randomized to remote monitoring with the Dexcom G4 PLATINUM communicating with the Diabetes Assistant, a cell phone platform, to allow wireless transmission of CGM values. Up to 15 individual graphs and sensor values could be displayed on a single remote monitor or portable tablet. An alarm was triggered for values <70 mg/dL, and treatment was given for meter-confirmed hypoglycemia. The primary end point was to decrease the duration of hypoglycemic episodes <50 mg/dL. RESULTS: There were 320 nights of CGM data and 197 hypoglycemic events. Of the remote monitoring alarms, 79% were true (meter reading of <70 mg/dL). With remote monitoring, 100% of alarms were responded to, whereas without remote monitoring only 54% of alarms were responded to. The median duration of hypoglycemic events <70 mg/dL was 35 min without remote monitoring and 30 min with remote monitoring (P=0.078). Remote monitoring significantly decreased prolonged hypoglycemic events, eliminating all events <50 mg/dL lasting longer than 30 min as well as all events <70 mg/dL lasting more than 2 h. CONCLUSIONS: Remote monitoring is feasible at diabetes camps and effective in reducing the risk of prolonged nocturnal hypoglycemia. This technology will facilitate forthcoming studies to evaluate the efficacy of automated closed-loop systems in the camp setting.

Dexcom G4AP: an advanced continuous glucose monitor for the artificial pancreas.

Input from continuous glucose monitors (CGMs) is a critical component of artificial pancreas (AP) systems, but CGM performance issues continue to limit progress in AP research. While G4 PLATINUM has been integrated into AP systems around the world and used in many successful AP controller feasibility studies, this system was designed to address the needs of ambulatory CGM users as an adjunctive use system. Dexcom and the University of Padova have developed an advanced CGM, called G4AP, to specifically address the heightened performance requirements for future AP studies. The G4AP employs the same sensor and transmitter as the G4 PLATINUM but contains updated denoising and calibration algorithms for improved accuracy and reliability. These algorithms were applied to raw data from an existing G4 PLATINUM clinical study using a simulated prospective procedure. The results show that mean absolute relative difference (MARD) compared with venous plasma glucose was improved from 13.2% with the G4 PLATINUM to 11.7% with the G4AP. Accuracy improvements were seen over all days of sensor wear and across the plasma glucose range (40-400 mg/dl). The greatest improvements occurred in the low glucose range (40-80 mg/dl), in euglycemia (80-120 mg/dl), and on the first day of sensor use. The percentage of sensors with a MARD <15% increased from 69% to 80%. Metrics proposed by the AP research community for addressing specific AP requirements were also computed. The G4AP consistently exhibited improved sensor performance compared with the G4 PLATINUM. These improvements are expected to enable further advances in AP research.

Time lag of glucose from intravascular to interstitial compartment in humans.

The accuracy of continuous interstitial fluid (ISF) glucose sensing is an essential component of current and emerging open- and closed-loop systems for type 1 diabetes. An important determinant of sensor accuracy is the physiological time lag of glucose transport from the vascular to the interstitial space. We performed the first direct measurement of this phenomenon to our knowledge in eight healthy subjects under an overnight fasted condition. Microdialysis catheters were inserted into the abdominal subcutaneous space. After intravenous bolus administrations of glucose tracers, timed samples of plasma and ISF were collected sequentially and analyzed for tracer enrichments. After accounting for catheter dead space and assay noise, the mean time lag of tracer appearance in the interstitial space was 5.3-6.2 min. We conclude that in the overnight fasted state in healthy adults, the physiological delay of glucose transport from the vascular to the interstitial space is 5-6 min. Physiological delay between blood glucose and ISF glucose, therefore, should not be an obstacle to sensor accuracy in overnight or fasting-state closed-loop systems of insulin delivery or open-loop therapy assessment for type 1 diabetes.

A new-generation continuous glucose monitoring system: improved accuracy and reliability compared with a previous-generation system.

BACKGROUND: Use of continuous glucose monitoring (CGM) systems can improve glycemic control, but widespread adoption of CGM utilization has been limited, in part because of real and perceived problems with accuracy and reliability. This study compared accuracy and performance metrics for a new-generation CGM system with those of a previous-generation device. SUBJECTS AND METHODS: Subjects were enrolled in a 7-day, open-label, multicenter pivotal study. Sensor readings were compared with venous YSI measurements (blood glucose analyzer from YSI Inc., Yellow Springs, OH) every 15 min (±5 min) during in-clinic visits. The aggregate and individual sensor accuracy and reliability of a new CGM system, the Dexcom(®) (San Diego, CA) G4™ PLATINUM (DG4P), were compared with those of the previous CGM system, the Dexcom SEVEN(®) PLUS (DSP). RESULTS: Both study design and subject characteristics were similar. The aggregate mean absolute relative difference (MARD) for DG4P was 13% compared with 16% for DSP (P<0.0001), and 82% of DG4P readings were within ± 20 mg/dL (for YSI ≤ 80 mg/dL) or 20% of YSI values (for YSI >80 mg/dL) compared with 76% for DSP (P<0.001). Ninety percent of the DG4P sensors had an individual MARD ≤ 20% compared with only 76% of DSP sensors (P=0.015). Half of DG4P sensors had a MARD less than 12.5% compared with 14% for the DSP sensors (P=0.028). The mean absolute difference for biochemical hypoglycemia (YSI <70 mg/dL) for DG4P was 11 mg/dL compared with 16 mg/dL for DSP (P<0.001). CONCLUSIONS: The performance of DG4P was significantly improved compared with that of DSP, which may increase routine clinical use of CGM and improve patient outcomes.

Use of a novel fluorescent glucose sensor in volunteer subjects with type 1 diabetes mellitus.

BACKGROUND: Stress hyperglycemia in the critically ill has been found to be associated with increased morbidity and mortality. Studies have found significant improvements in morbidity and mortality in postsurgical patients whose glucose levels were closely maintained in the euglycemic range. However, subsequent studies, in particular the Normoglycemia in Intensive Care Evaluation and Survival Using Glucose Algorithm Regulation (NICE-SUGAR) study, found no improvement in subjects with tight glycemic control. In addition to differences in protocol design, patients in the tight glycemic control arm of the NICE-SUGAR study experienced high rates of hypoglycemia compared with other studies. One interpretation of the NICE-SUGAR study results is that it is difficult to achieve normal glycemia in critically ill patients with existing glucose monitoring technology. The purpose of the study reported here was to evaluate the safety and performance of a continuous intravascular glucose sensor that could be used in the future in critically ill patients. METHODS: A first-generation prototype of an intravascular continuous glucose sensor was evaluated in 29 volunteer subjects with type 1 diabetes mellitus. The sensor operates on the principle of quenched fluorescence. The fluorescent emission from the sensor chemistry is nonlinear, resulting in improved accuracy in the hypoglycemic range. The duration of each study was 8 hours. Sensor output was compared with temporally correlated reference measurements made from venous samples on a laboratory glucose analyzer. RESULTS: Data were obtained from 18 of the 29 subjects in the study. Data were analyzed retrospectively using a factory calibration plus a one-point in vivo calibration. The mean absolute relative difference was 7.97%, and 95.1% of all the points were in zone A of the Clarke error grid. CONCLUSIONS: This pilot study was the first use in human subjects of a prototype of the GluCath Intravascular Continuous Glucose Monitoring System (GluCath System). The GluCath System is based on a novel fluorescent sensor chemistry. The study found the GluCath System had a high level of accuracy as compared with a laboratory reference analyzer.