Nick Oliver

Glucose sensors: a review of current and emerging technology

Glucose monitoring technology has been used in the management of diabetes for three decades. Traditional devices use enzymatic methods to measure glucose concentration and provide point sample information. More recently continuous glucose monitoring devices have become available providing more detailed data on glucose excursions. In future applications the continuous glucose sensor may become a critical component of the closed loop insulin delivery system and, as such, must be selective, rapid, predictable and acceptable for continuous patient use. Many potential sensing modalities are being pursued including optical and transdermal techniques. This review aims to summarize existing technology, the methods for assessing glucose sensing devices and provide an overview of emergent sensing modalities.

Effectiveness of mobile phone messaging in prevention of type 2 diabetes by lifestyle modification in men in India: a prospective, parallel-group, randomised controlled trial

BACKGROUND Type 2 diabetes can often be prevented by lifestyle modification; however, successful lifestyle intervention programmes are labour intensive. Mobile phone messaging is an inexpensive alternative way to deliver educational and motivational advice about lifestyle modification. We aimed to assess whether mobile phone messaging that encouraged lifestyle change could reduce incident type 2 diabetes in Indian Asian men with impaired glucose tolerance. METHODS We did a prospective, parallel-group, randomised controlled trial between Aug 10, 2009, and Nov 30, 2012, at ten sites in southeast India. Working Indian men (aged 35-55 years) with impaired glucose tolerance were randomly assigned (1:1) with a computer-generated randomisation sequence to a mobile phone messaging intervention or standard care (control group). Participants in the intervention group received frequent mobile phone messages compared with controls who received standard lifestyle modification advice at baseline only. Field staff and participants were, by necessity, not masked to study group assignment, but allocation was concealed from laboratory personnel as well as principal and co-investigators. The primary outcome was incidence of type 2 diabetes, analysed by intention to treat. This trial is registered with ClinicalTrials.gov, number NCT00819455. RESULTS We assessed 8741 participants for eligibility. 537 patients were randomly assigned to either the mobile phone messaging intervention (n=271) or standard care (n=266). The cumulative incidence of type 2 diabetes was lower in those who received mobile phone messages than in controls: 50 (18%) participants in the intervention group developed type 2 diabetes compared with 73 (27%) in the control group (hazard ratio 0·64, 95% CI 0·45-0·92; p=0·015). The number needed to treat to prevent one case of type 2 diabetes was 11 (95% CI 6-55). One patient in the control group died suddenly at the end of the first year. We recorded no other serious adverse events. INTERPRETATION Mobile phone messaging is an effective and acceptable method to deliver advice and support towards lifestyle modification to prevent type 2 diabetes in men at high risk. FUNDING The UK India Education and Research Initiative, the World Diabetes Foundation.

Normal Reference Range for Mean Tissue Glucose and Glycemic Variability Derived from Continuous Glucose Monitoring for Subjects Without Diabetes in Different Ethnic Groups

BACKGROUND Glycemic variability has been proposed as a contributing factor in the development of diabetes complications. Multiple measures exist to calculate the magnitude of glycemic variability, but normative ranges for subjects without diabetes have not been described. For treatment targets and clinical research we present normative ranges for published measures of glycemic variability. METHODS Seventy-eight subjects without diabetes having a fasting plasma glucose of <120 mg/dL (6.7 mmol/L) underwent up to 72 h of continuous glucose monitoring (CGM) with a Medtronic Minimed (Northridge, CA) CGMS(®) Gold device. Glycemic variability was calculated using EasyGV(©) software (available free for non-commercial use at www.easygv.co.uk ), a custom program that calculates the SD, M-value, mean amplitude of glycemic excursions (MAGE), average daily risk ratio (ADRR), Lability Index (LI), J-Index, Low Blood Glucose Index (LBGI), High Blood Glucose Index (HBGI), continuous overlapping net glycemic action (CONGA), mean of daily differences (MODD), Glycemic Risk Assessment in Diabetes Equation (GRADE), and mean absolute glucose (MAG). RESULTS Eight CGM traces were excluded because there were inadequate data. From the remaining 70 traces, normative reference ranges (mean±2 SD) for glycemic variability were calculated: SD, 0-3.0; CONGA, 3.6-5.5; LI, 0.0-4.7; J-Index, 4.7-23.6; LBGI, 0.0-6.9; HBGI, 0.0-7.7; GRADE, 0.0-4.7; MODD, 0.0-3.5; MAGE-CGM, 0.0-2.8; ADDR, 0.0-8.7; M-value, 0.0-12.5; and MAG, 0.5-2.2. CONCLUSIONS We present normative ranges for measures of glycemic variability in adult subjects without diabetes for use in clinical care and academic research.

Use of microneedle array devices for continuous glucose monitoring: a review.

Microneedle array devices provide the opportunity to overcome the barrier characteristics of the outermost skin layer, the stratum corneum. This novel technology can be used as a therapeutic tool for transdermal drug delivery, including insulin, or as a diagnostic tool providing access to dermal biofluids, with subsequent analysis of its contents. Over the last decade, the use of microneedle array technology has been the focus of extensive research in the field of transdermal drug delivery. More recently, the diagnostic applications of microneedle technology have been developed. This review summarizes the existing evidence for the use of microneedle array technology as biosensors for continuous monitoring of the glucose content of interstitial fluid, focusing also on mechanics of insertion, microchannel characteristics, and safety profile.

Robust Fault Detection System for Insulin Pump Therapy Using Continuous Glucose Monitoring

Background: The popularity of continuous subcutaneous insulin infusion (CSII), or insulin pump therapy, as a way to deliver insulin more physiologically and achieve better glycemic control in diabetes patients has increased. Despite the substantiated therapeutic advantages of using CSII, its use has also been associated with an increased risk of technical malfunctioning of the device, which leads to an increased risk of acute metabolic complications, such as diabetic ketoacidosis. Current insulin pumps already incorporate systems to detect some types of faults, such as obstructions in the infusion set, but are not able to detect other types of fault such as the disconnection or leakage of the infusion set. Methods: In this article, we propose utilizing a validated robust model-based fault detection technique, based on interval analysis, for detecting disconnections of the insulin infusion set. For this purpose, a previously validated metabolic model of glucose regulation in type 1 diabetes mellitus (T1DM) and a continuous glucose monitoring device were used. As a first step to assess the performance of the presented fault detection system, a Food and Drug Administration-accepted T1DM simulator was employed. Results: Of the 100 in silico tests (10 scenarios on 10 subjects), only two false negatives and one false positive occurred. All faults were detected before plasma glucose concentration reached 300 mg/dl, with a mean plasma glucose detection value of 163 mg/dl and a mean detection time of 200 min. Conclusions: Interval model-based fault detection has been proven (in silico) to be an effective tool for detecting disconnection faults in sensor-augmented CSII systems. Proper quantification of the uncertainty associated with the employed model has been observed to be crucial for the good performance of the proposed approach.

A bio-inspired glucose controller based on pancreatic β-cell physiology.

Introduction: Control algorithms for closed-loop insulin delivery in type 1 diabetes have been mainly based on control engineering or artificial intelligence techniques. These, however, are not based on the physiology of the pancreas but seek to implement engineering solutions to biology. Developments in mathematical models of the β-cell physiology of the pancreas have described the glucose-induced insulin release from pancreatic β cells at a molecular level. This has facilitated development of a new class of bio-inspired glucose control algorithms that replicate the functionality of the biological pancreas. However, technologies for sensing glucose levels and delivering insulin use the subcutaneous route, which is nonphysiological and introduces some challenges. In this article, a novel glucose controller is presented as part of a bio-inspired artificial pancreas. Methods: A mathematical model of β-cell physiology was used as the core of the proposed controller. In order to deal with delays and lack of accuracy introduced by the subcutaneous route, insulin feedback and a gain scheduling strategy were employed. A United States Food and Drug Administration-accepted type 1 diabetes mellitus virtual population was used to validate the presented controller. Results: Premeal and postmeal mean ± standard deviation blood glucose levels for the adult and adolescent populations were well within the target range set for the controller [(70, 180) mg/dl], with a percent time in range of 92.8 ± 7.3% for the adults and 83.5 ± 14% for the adolescents. Conclusions: This article shows for the first time very good glucose control in a virtual population with type 1 diabetes mellitus using a controller based on a subcellular β-cell model.

A Composite Model of Glucagon-Glucose Dynamics for In Silico Testing of Bihormonal Glucose Controllers

Background: The utility of simulation environments in the development of an artificial pancreas for type 1 diabetes mellitus (T1DM) management is well established. The availability of a simulator that incorporates glucagon as a counterregulatory hormone to insulin would allow more efficient design of bihormonal glucose controllers. Existing models of the glucose regulatory system that incorporates glucagon action are difficult to identify without using tracer data. In this article, we present a novel model of glucagon-glucose dynamics that can be easily identified with standard clinical research data. Methods: The minimal model of plasma glucose and insulin kinetics was extended to account for the action of glucagon on net endogenous glucose production by incorporating a new compartment. An existing subcutaneous insulin absorption model was used to account for subcutaneous insulin delivery. The same model of insulin pharmacokinetics was employed to model the pharmacokinetics of subcutaneous glucagon absorption. Finally, we incorporated an existing gastrointestinal absorption model to account for meal intake. Data from a closed-loop artificial pancreas study using a bihormonal controller on T1DM subjects were employed to identify the composite model. To test the validity of the proposed model, a bihormonal controller was designed using the identified model. Results: Model parameters were identified with good precision, and an excellent fitting of the model with the experimental data was achieved. The proposed model allowed the design of a bihormonal controller and demonstrated its ability to improve glycemic control over a single-hormone controller. Conclusions: A novel composite model, which can be easily identified with standard clinical data, is able to account for the effect of exogenous insulin and glucagon infusion on glucose dynamics. This model represents another step toward the development of a bihormonal artificial pancreas.

Psychosocial assessment of artificial pancreas (AP): commentary and review of existing measures and their applicability in AP research.

AIM This study aimed to systematically review the evidence base for the use of existing psychological and psychosocial measures suitable for use in artificial pancreas (AP) research. MATERIALS AND METHODS This systematic review of published literature, gray literature, previous systematic reviews, and qualitative and economic studies was conducted using terms and abbreviations synonymous with diabetes, AP, and quality of life (QoL). RESULTS Two hundred ninety-two abstracts were identified that reported psychosocial assessment of diabetes-related technologies. Of these, nine met the inclusion criteria and were included. Only four of 103 ongoing trials evaluated psychosocial aspects as an outcome in the trial. Of these, treatment satisfaction, acceptance and use intention of AP, fear of hypoglycemia episodes, satisfaction with AP, and an unspecified QoL measure were used. CONCLUSIONS A better understanding of the psychosocial side of AP systems and the extent to which human factors play a role in the uptake and efficient use of these systems will ultimately lead to the most benefit for people with diabetes.

A randomized controlled pilot study of continuous glucose monitoring and flash glucose monitoring in people with Type 1 diabetes and impaired awareness of hypoglycaemia

Hypoglycaemia in Type 1 diabetes is associated with mortality and morbidity, especially where awareness of hypoglycaemia is impaired. Clinical pathways for access to continuous glucose monitoring (CGM) and flash glucose monitoring technologies are unclear. We assessed the impact of CGM and flash glucose monitoring in a high‐risk group of people with Type 1 diabetes.

Gestational diabetes mellitus: does an effective prevention strategy exist?

The overall incidence of gestational diabetes mellitus (GDM) is increasing worldwide. Preventing pathological hyperglycaemia during pregnancy could have several benefits: a reduction in the immediate adverse outcomes during pregnancy, a reduced risk of long-term sequelae and a decrease in the economic burden to healthcare systems. In this Review we examine the evidence supporting lifestyle modification strategies in women with and without risk factors for GDM, and the efficacy of dietary supplementation and pharmacological approaches to prevent this disease. A high degree of heterogeneity exists between trials so a generalised recommendation is problematic. In population studies of dietary or combined lifestyle measures, risk of developing GDM is not improved and those involving a physical activity intervention have yielded conflicting results. In pregnant women with obesity, dietary modification might reduce fetal macrosomia but in these patients, low compliance and no significant reduction in the incidence of GDM has been observed in trials investigating physical activity. Supplementation with probiotics or myoinositol have reduced the incidence of GDM but confirmatory studies are still needed. In randomized controlled trials, metformin does not prevent GDM in certain at-risk groups. Given the considerable potential for reducing disease burden, further research is needed to identify strategies that can be easily and effectively implemented on a population level.