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.

Accuracy of a first-generation intravenous blood glucose monitoring system in subjects with diabetes mellitus: a multicenter study.

BACKGROUND: Hyperglycemia and hypoglycemia in hospitalized patients have been associated with increased morbidity and mortality. Improvements in glucose monitoring technology may be helpful in the clinical management of critically ill patients with abnormal glucose levels. A first-generation intravenous blood glucose monitoring (IVBG) system was developed to facilitate glycemic control therapy in hospitalized patients. A nonrandomized, single-arm, multicenter study was performed to evaluate the safety and accuracy of the IVBG system in insulin-treated subjects with diabetes mellitus. METHODS: The IVBG system is a bedside monitor that automatically measures venous blood glucose (BG) concentration. In this study, BG was measured every 7.5 min by the IVBG system. Reference samples [venous blood samples measured on the Yellow Springs Instruments (YSI) glucose analyzer] were drawn every 15 min during inpatient studies on days 1, 2, and 3. Fifty insulin-treated healthy volunteers with diabetes were studied, and a maximum of 72 reference samples were collected. Effectiveness was primarily evaluated by assessing the proportion of IVBG BG measurements within the 15 mg/dl or 20% criterion [15 mg/dl (for YSI <75 mg/dl) or 20% (for YSI ≥75 mg/dl)] compared with YSI. Adverse events and adverse device effects were evaluated. RESULTS: A total of 95% of all IVBG values were within the 15 mg/dl or 20% criterion. The IVBG system BG measurement showed significant linear relationship with the laboratory YSI standard. Catheter insertion site irritation was mild and infrequent. No serious adverse events were reported. A total of 33% of the sensors were replaced during the 3-day use due to problematic IV lines or sensor/system errors. CONCLUSIONS: This clinical performance evaluation demonstrates that the IVBG system provides accurate and safe continuous BG measurements in healthy insulin-treated patients with diabetes.

Development of a fully automated closed loop artificial pancreas control system with dual pump delivery of insulin and glucagon.

Patients with diabetes have difficulty controlling their blood sugar and suffer from acute effects of hypoglycemia and long-term effects of hyperglycemia, which include disease of the eyes, kidneys and nerves/feet. In this paper, we describe a new system that is used to automatically control blood sugar in people with diabetes through the fully automated measurement of blood glucose levels and the delivery of insulin and glucagon via the subcutaneous route. When a patient's blood sugar goes too high, insulin is given to the patient to bring his/her blood sugar back to a normal level. To prevent a patient's blood sugar from going too low, the patient is given a hormone called glucagon which raises the patient's blood sugar. While other groups have described methods for automatically delivering insulin and glucagon, many of these systems still require human interaction to enter the venous blood sugar levels into the control system. This paper describes the development of a fully automated closed-loop dual sensor bi-hormonal artificial pancreas system that does not require human interaction. The system described in this paper is comprised of two sensors for measuring glucose, two pumps for independent delivery of insulin and glucagon, and a laptop computer running a custom software application that controls the sensor acquisition and insulin and glucagon delivery based on the glucose values recorded. Two control algorithms are designed into the software: (1) an algorithm that delivers insulin and glucagon according to their proportional and derivative errors and proportional and derivative gains and (2) an adaptive algorithm that adjusts the gain factors based on the patient's current insulin sensitivity as determined using a mathematical model. Results from this work may ultimately lead to development of a portable, easy to use, artificial pancreas device that can enable far better glycemic control in patients with diabetes.

Methods of evaluating the utility of continuous glucose monitor alerts.

BACKGROUND: The evaluation of continuous glucose monitor (CGM) alert performance should reflect patient use in real time. By evaluating alerts as real-time events, their ability to both detect and predict low and high blood glucose (BG) events can be examined. METHOD: True alerts (TA) were defined as a CGM alert occurring within +/- 30 minutes from the beginning of a low or a high BG event. The TA time to detection was calculated as [time of CGM alert] - [beginning of event]. False alerts (FA) were defined as a BG event outside of the alert zone within +/- 30 minutes from a CGM alert. Analysis was performed comparing DexCom SEVEN PLUS CGM data to BG measured with a laboratory analyzer. RESULTS: Of 49 low glucose events (BG < or =70 mg/dl), with the CGM alert set to 90 mg/dl, the TA rate was 91.8%. For 50% of TAs, the CGM alert preceded the event by at least 21 minutes. The FA rate was 25.0%. Similar results were found for high alerts. CONCLUSION: Continuous glucose monitor alerts are capable of both detecting and predicting low and high BG events. The setting of alerts entails a trade-off between predictive ability and FA rate. Realistic analysis of this trade-off will guide patients in the effective utilization of CGM.

Analysis of time lags and other sources of error of the DexCom SEVEN continuous glucose monitor.

BACKGROUND: It has been assumed that continuous glucose sensors show substantial time lags versus blood glucose. This assumption has led to suggestions that sensors are less accurate during rapidly changing glucose levels and that sensors should only be calibrated when glucose levels are stable. The analysis presented here tests the assumption of substantial sensor time lag and its suggested effects using clinical data from the DexCom (San Diego, CA) SEVEN. METHODS: Sensor and blood glucose data were collected from 117 adult subjects with insulin-dependent diabetes. Each subject wore the sensor for 7 days and underwent an 8-10-h in-clinic tracking study during which blood glucose was measured every 15-20 min. Accuracy (absolute relative difference [ARD]) versus blood glucose rate of change was evaluated on the in-clinic data set. The effect on accuracy of calibration during rapid rates of change was evaluated on the combined home-use and in-clinic data set. RESULTS: Average sensor time lag versus blood glucose was 5.7 min. Mean ARD versus rate of change (less than -2 to >2 mg/dL/minute) ranged between 15.0% to 16.3%. Across rates of change during calibration, mean ARD after calibration ranged between 13.2% and 16.0%. Calibration with reference measurements instead of patient measurements improved overall mean ARD from 16.0% to 8.5%. CONCLUSIONS: For this sensor, the assumption of substantial time lag and its suggested effects may be incorrect. The main source of error is the calibration process.