Feasibility of an Orthogonal Redundant Sensor incorporating Optical plus Redundant Electrochemical Glucose Sensing

Combining an Electrochemical Continuous Glucose Sensor With an Insulin Delivery Cannula: A Feasibility Study

BACKGROUND

Combining a continuous glucose monitor with an insulin delivery cannula (CGM-IS) could benefit clinical outcomes. We evaluated the feasibility of a single-needle insertion electrochemical investigational CGM-IS (Pacific Diabetes Technologies, Portland, Oregon) in type 1 diabetes adults.

METHODS

Following 48 hours run-in using a Medtronic 780G in manual mode with a commercial insulin set, 12 participants commenced insulin delivery using the CGM-IS. A standardized test meal was eaten on the mornings of days 1 and 4. Venous samples were collected every 10 minutes one hour prior to and 15 minutes post-meal for four hours. CGM-IS glucose measurements were post-processed with a single capillary blood calibration during warm-up and benchmarked against YSI. A Dexcom G6 sensor was worn post-consent to study end.

RESULTS

Mean absolute relative difference (MARD) for the CGM-IS glucose measurements was 9.2% (484 paired data points). Consensus error grid revealed 88.6% within zone A and 100% in A + B. Mean (SD) % bias was -3.5 (11.7) %. There were 35 paired YSI readings <100 mg/dL cutoff and 449 ≥100 mg/dL with 81.4% within ±15 mg/dL or ±15%, and 89.9% within ±20 mg/dL or ±20%. Two cannula occlusions required discontinuation of insulin delivery: one at 70 hours post insertion and another during the day 4 meal test. Mean (SD) Dexcom glucose measurements during run-in and between meal tests was respectively 161.3 ± 27.3 mg/dL versus 158.0 ± 25.6 mg/dL; P = .39 and corresponding mean total daily insulin delivered by the pump was 58.0 ± 25.4 Units versus 57.1 ± 28.8 Units; P = .47.

CONCLUSIONS

Insulin delivery and glucose sensing with the investigational CGM-IS was feasible. Longer duration studies are needed.

Clinical Performance Evaluation of Continuous Glucose Monitoring Systems: A Scoping Review and Recommendations for Reporting

The use of different approaches for design and results presentation of studies for the clinical performance evaluation of continuous glucose monitoring (CGM) systems has long been recognized as a major challenge in comparing their results. However, a comprehensive characterization of the variability in study designs is currently unavailable. This article presents a scoping review of clinical CGM performance evaluations published between 2002 and 2022. Specifically, this review quantifies the prevalence of numerous options associated with various aspects of study design, including subject population, comparator (reference) method selection, testing procedures, and statistical accuracy evaluation. We found that there is a large variability in nearly all of those aspects and, in particular, in the characteristics of the comparator measurements. Furthermore, these characteristics as well as other crucial aspects of study design are often not reported in sufficient detail to allow an informed interpretation of study results. We therefore provide recommendations for reporting the general study design, CGM system use, comparator measurement approach, testing procedures, and data analysis/statistical performance evaluation. Additionally, this review aims to serve as a foundation for the development of a standardized CGM performance evaluation procedure, thereby supporting the goals and objectives of the Working Group on CGM established by the Scientific Division of the International Federation of Clinical Chemistry and Laboratory Medicine.

Human-in-the-Loop Insulin Dosing

The last ten years of efforts in developing automated insulin dosing systems have led to one hybrid closed-loop device in the US market with more in the late stages of development. Much of the focus has been on algorithms, including closed-loop, detection of sensor and pump faults, and safety. There has been less discussion in the open literature about user interface design and related options. This article provides perspectives on automated insulin delivery (AID) system design by analyzing commonly used devices, such as bicycles and car entertainment systems. The recent Boeing 737 Max 8 disasters are used to highlight related challenges with AID systems. The role that system engineers can play in the do it yourself artificial pancreas system movement is also discussed. The human-in-the-loop remains by far the most important "component" of any AID system.

Modeling the Error of the Medtronic Paradigm Veo Enlite Glucose Sensor

Continuous glucose monitors (CGMs) are prone to inaccuracy due to time lags, sensor drift, calibration errors, and measurement noise. The aim of this study is to derive the model of the error of the second generation Medtronic Paradigm Veo Enlite (ENL) sensor and compare it with the Dexcom SEVEN PLUS (7P), G4 PLATINUM (G4P), and advanced G4 for Artificial Pancreas studies (G4AP) systems. An enhanced methodology to a previously employed technique was utilized to dissect the sensor error into several components. The dataset used included 37 inpatient sessions in 10 subjects with type 1 diabetes (T1D), in which CGMs were worn in parallel and blood glucose (BG) samples were analyzed every 15 ± 5 min Calibration error and sensor drift of the ENL sensor was best described by a linear relationship related to the gain and offset. The mean time lag estimated by the model is 9.4 ± 6.5 min. The overall average mean absolute relative difference (MARD) of the ENL sensor was 11.68 ± 5.07% Calibration error had the highest contribution to total error in the ENL sensor. This was also reported in the 7P, G4P, and G4AP. The model of the ENL sensor error will be useful to test the in silico performance of CGM-based applications, i.e., the artificial pancreas, employing this kind of sensor.

Moving Toward a Unified Platform for Insulin Delivery and Sensing of Inputs Relevant to an Artificial Pancreas

Advances in insulin pump and continuous glucose monitoring technology have primarily focused on optimizing glycemic control for people with type 1 diabetes. There remains a need to identify ways to minimize the physical burden of this technology. A unified platform with closely positioned or colocalized interstitial fluid glucose sensing and hormone delivery components is a potential solution. Present challenges to combining these components are interference of glucose sensing from proximate insulin delivery and the large discrepancy between the life span of current insulin infusion sets and glucose sensors. Addressing these concerns is of importance given that the future physical burden of this technology is likely to be even greater with the ongoing development of the artificial pancreas, potentially incorporating multiple hormone delivery, glucose sensing redundancy, and sensing of other clinically relevant nonglucose biochemical inputs.