Continuous glucose monitoring: A review of the technology and clinical use

Glucose biosensors in clinical practice: principles, limits and perspectives of currently used devices

The demand of glucose monitoring devices and even of updated guidelines for the management of diabetic patients is dramatically increasing due to the progressive rise in the prevalence of diabetes mellitus and the need to prevent its complications. Even though the introduction of the first glucose sensor occurred decades ago, important advances both from the technological and clinical point of view have contributed to a substantial improvement in quality healthcare. This review aims to bring together purely technological and clinical aspects of interest in the field of glucose devices by proposing a roadmap in glucose monitoring and management of patients with diabetes. Also, it prospects other biological fluids to be examined as further options in diabetes care, and suggests, throughout the technology innovation process, future directions to improve the follow-up, treatment, and clinical outcomes of patients.

Families' Experiences of Continuous Glucose Monitoring in the Management of Congenital Hyperinsulinism: A Thematic Analysis

BACKGROUND AND AIMS

In patients with congenital hyperinsulinism (CHI), recurrent hypoglycaemia can lead to longstanding neurological impairments. At present, glycaemic monitoring is with intermittent fingerprick blood glucose testing but this lacks utility to identify patterns and misses hypoglycaemic episodes between tests. Although continuous glucose monitoring (CGM) is well established in type 1 diabetes, its use has only been described in small studies in patients with CHI. In such studies, medical perspectives have been provided without fully considering the views of families using CGM. In this qualitative study, we aimed to explore families' experiences of using CGM in order to inform future clinical strategies for the management of CHI.

METHODS

Ten patients with CHI in a specialist centre used CGM for twelve weeks. All were invited to participate. Semi-structured interviews were conducted with nine families in whom patient ages ranged between two and seventeen years. Transcripts of the audio-recorded interviews were analysed using an inductive thematic analysis method.

RESULTS

Analysis revealed five core themes: CGM's function as an educational tool; behavioural changes; positive experiences; negative experiences; and design improvements. Close monitoring and retrospective analysis of glucose trends allowed for enhanced understanding of factors that influenced glucose levels at various times of the day. Parents noted more hypoglycaemic episodes than previously encountered through fingerprick tests; this new knowledge prompted modification of daily routines to prevent and improve the management of hypoglycaemia. CGM use was viewed favourably as offering parental reassurance, reduced fingerprick tests and predictive warnings. However, families also reported unfavourable aspects of alarms and questionable accuracy at low glucose levels. Adolescents were frustrated by the short proximity range for data transmission resulting in the need to always carry a separate receiver. Overall, families were positive about the use of CGM but expected application to be tailored to their child's medical condition.

CONCLUSIONS

Patients and families with CHI using CGM noticed trends in glucose levels which motivated behavioural changes to reduce hypoglycaemia with advantages outweighing disadvantages. They expected CHI-specific modifications to enhance utility. Future design of CGM should incorporate end users' opinions and experiences for optimal glycaemic monitoring of CHI.

Fourth-generation glucose sensors composed of copper nanostructures for diabetes management: A critical review

More than five decades have been invested in understanding glucose biosensors. Yet, this immensely versatile field has continued to gain attention from the scientific world to better understand and diagnose diabetes. However, such extensive work done to improve glucose sensing devices has still not yielded desirable results. Drawbacks like the necessity of the invasive finger-pricking step and the lack of optimization of diagnostic interventions still need to be considered to improve the testing process of diabetic patients. To upgrade the glucose-sensing devices and reduce the number of intermediary steps during glucose measurement, fourth-generation glucose sensors (FGGS) have been introduced. These sensors, made using robust electrocatalytic copper nanostructures, improve diagnostic efficiency and cost-effectiveness. This review aims to present the essential scientific progress in copper nanostructure-based FGGS in the past 10 years (2010 to present). After a short introduction, we presented the working principles of these sensors. We then highlighted the importance of copper nanostructures as advanced electrode materials to develop reliable real-time FGGS. Finally, we cover the advantages, shortcomings, and prospects for developing highly sensitive, stable, and specific FGGS.

Diabetes Technology Use in Remote Pediatric Patients with Type 1 Diabetes Using Clinic-to-Clinic Telemedicine

Background: Clinic-to-clinic telemedicine can increase visit frequency in pediatric patients with type 1 diabetes (T1D) living far from a diabetes specialty clinic, but the impact on adoption of diabetes technology is unclear. Materials and Methods: Pediatric patients with T1D in Colorado and surrounding states who received diabetes care using clinic-to-clinic telemedicine were enrolled. Medical records and surveys were reviewed to ascertain technology use, and data were compared to patients from the main clinic population. Results: Patients (N = 128, baseline mean age 12.4 ± 4.2 years, median T1D duration 3.3 years [IQR 1.4-7.7], mean A1c 8.9% ± 1.8%, 60% male, 75% non-Hispanic white, 77% private insurance) who utilized telemedicine were included. Technology use among telemedicine patients was not associated with gender, T1D duration, insurance, distance from the main clinic or rural designation but was associated with ethnicity and A1c. Compared to the main clinic cohort (N = 3636), continuous glucose monitor (CGM) use and pump/CGM combination use was lower among patients participating in clinic-to-clinic telemedicine (CGM: 29.7% vs. 56.0%, P < 0.001; CGM/pump combination: 27.3% vs. 40.3%, P = 0.004). Technology use was associated with lower A1c regardless of cohort. Conclusions: Compared to patients attending in-person clinic, pediatric T1D patients who use clinic-to-clinic telemedicine due to their distance from the main clinic, have lower CGM and combination CGM/pump use. For both telemedicine and main clinic patients, CGM and CGM/pump combination was associated with lower A1c. Additional research is needed to explore reasons for this discrepancy and find methods to improve CGM use in this population.

Efficacy of continuous glucose monitoring on maternal and neonatal outcomes in gestational diabetes mellitus: a systematic review and meta-analysis of randomized clinical trials

AIMS

This systematic review aims to evaluate the effect of continuous glucose monitoring (CGM) on maternal and neonatal outcomes in gestational diabetes mellitus (GDM).

METHODS

Two authors conducted a systematic search using PubMed, Embase, CENTRAL, CINAHL, Scopus, Web of Science, ClinicalTrials.gov and the World Health Organization International Clinical Trials Registry Platform. The inclusion criteria for the systematic review were randomized clinical trials that compared the effects of CGM and blood glucose monitoring (BGM) in women with GDM. A restricted maximum likelihood random-effects model was used for the meta-analysis. The measures of effect were risk ratios for categorical data and mean differences for continuous data.

RESULTS

Of the 457 studies reviewed, six randomized clinical trials met the inclusion criteria. A total of 482 patients were included in the meta-analysis. The use of CGM was associated with lower HbA1c levels at the end of pregnancy (mean difference: -0.22; 95%CI -0.42 to -0.03) compared to BGM. Women using CGM also had less gestational weight gain (mean difference: -1.17, 95%CI -2.15 to -0.19), and their children had lower birth weight (mean difference: -116.26, 95%CI -224.70 to -7.81). No differences were observed in the other outcomes evaluated.

CONCLUSION

Women with GDM using CGM may achieve lower average blood glucose levels, lower maternal weight gain and infant birth weight than women using BGM. Nevertheless, current evidence is limited by the low number of studies and the small sample sizes of these studies. Larger clinical trials are needed to better understand the effects of CGM in GDM.

REGISTRATION

PROSPERO registration ID CRD42021225651.

Glucose Concentrations from Continuous Glucose Monitoring Devices Compared to Those from Blood Plasma during an Oral Glucose Tolerance Test in Healthy Young Adults

Continuous glucose monitoring devices measure glucose in interstitial fluid. The devices are effective when used by patients with type 1 and 2 diabetes but are increasingly being used by researchers who are interested in the effects of various behaviours of glucose concentrations in healthy participants. Despite their more frequent application in this setting, the devices have not yet been validated for use under such conditions. A total of 124 healthy participants were recruited to a ten-day laboratory study. Each participant underwent four oral glucose tolerance tests, and a total of 3315 out of a possible 4960 paired samples were included in the final analysis. Bland-Altman plots and mean absolute relative differences were used to determine the agreement between the two methods. Bland-Altman analyses revealed that the continuous glucose monitoring devices had proportional bias (R = 0.028, p < 0.001) and a mean bias of -0.048 mmol/L, and device measurements were more variable as glucose concentrations increased. Ninety-nine per cent of paired values were in Zones A and B of the Parkes Error Grid plot, and there was an overall mean absolute relative difference of 16.2% (±15.8%). There was variability in the continuous glucose monitoring devices, and this variability was higher when glucose concentrations were higher. If researchers were to use continuous glucose monitoring devices to measure glucose concentrations during an oral glucose tolerance test in healthy participants, this variability would need to be considered.

Continuous Glucose Monitoring System in Acromegalic Patients: Possible Role in the Assessment of Glycemia Control

BACKGROUND

Acromegaly is characterized by an insulin resistance condition. There is a significant difference between the different types of therapy in relation to the glycometabolic framework. The blinded continuous glucose monitoring system (CGMS), throughout a period of maximum 6 days for a total of 288 glycemic registrations per day, identifies glycemic excursions and could constitute a valid device to understand the 24-hour glycemic profiles.

AIM OF THE STUDY

To compare the oral glucose tolerance test (OGTT) and CGMS methods in acromegalic patients to evaluate their glycemic profiles, in relation to different treatments for acromegaly.

METHODS

Thirty-five acromegalic patients were divided into 18 somatostatin analogs (SSA), 9 pegvisomant, and 8 successfully surgically treated. A 72-hour CGM was performed and, immediately after, an OGTT.

RESULTS

Results obtained from OGTT: 11/35 impaired fasting glucose, 6/35 impaired glucose tolerance, and 4/35 diabetes mellitus. A positive significant correlation was demonstrated between the OGTT peak and CGM peak in all of the patients, CGM peak of patients treated with SSA and those surgically treated, OGTT average and CGM area under concentration-time curve (AUC) for hyperglycemia of patients treated with SSA and those surgically treated, and CGM AUC for hyperglycemia of patients treated with SSA and those surgically treated.

CONCLUSIONS

Our results show a significantly higher response in terms of mean and peak OGTT in patients treated with SSA, both compared to the CGM study, and compared to the group of patients receiving pegvisomant. The CGM system could represent an instrument for the evaluation of the glycemic trend of acromegalic patients.

Automated Adaptation of Insulin Treatment in Type 1 Diabetes

Individuals with type 1 diabetes (T1D) need life-long insulin therapy to compensate for the lack of endogenous insulin due to the autoimmune damage to pancreatic beta-cells. Treatment is based on basal and bolus insulin, to cover fasting and postprandial periods, respectively, according to three insulin dosing parameters: basal rate (BR), carbohydrate-to-insulin ratio (CR), and correction factor (CF). Suboptimal BR, CR, and CF profiles leading to incorrect insulin dosing may be the cause of undesired glycemic events, which carry dangerous short-term and long-term effects. Therefore, correct tuning of these parameters is of the utmost importance. In this work, we propose a new algorithm to optimize insulin dosing parameters in individuals with T1D who use a continuous glucose monitor and an insulin pump. The algorithm was tested using the University of Virginia/Padova T1D Simulator and led to an improvement in the quality of glycemic control. Future efforts will be devoted to test the algorithm in human clinical trials.

Lower Interstitial Glucose Concentrations but Higher Glucose Variability during Low-Energy Diet Compared to Regular Diet-An Observational Study in Females with Obesity

This is an observational study of interstitial glucose (IG) concentrations, IG variability and dietary intake under free-living conditions in 46 females with obesity but without diabetes. We used continuous glucose monitoring, open-ended food recording and step monitoring during regular dietary intake followed by a low-energy diet (LED). Thirty-nine participants completed both study periods. The mean BMI at baseline was 43.6 ± 6.2 kg/m2. Three weeks of LED resulted in a mean weight loss of 5.2% with a significant reduction in diurnal IG concentration but with greater glycemic variability observed during LED. The mean 24 h IG concentration decreased from 5.8 ± 0.5 mmol/L during the regular diet period to 5.4 ± 0.5 mmol/L (p < 0.001) during LED, while the mean amplitude of glycemic excursion increased from 1.5 ± 0.7 to 1.7 ± 0.7 mmol/L (p = 0.031). The positive incremental area under the curve at breakfast was significantly larger for LED compared to regular diet. The daily fiber intake and the glycemic index of breakfast meals were significantly associated with the glycemic variability during regular dietary intake. In conclusion, the 24 h mean IG concentration was lower but with more pronounced glycemic variability during LED compared to a regular diet.

US Emergency Department Visits Attributed to Medication Harms, 2017-2019

IMPORTANCE

Assessing the scope of acute medication harms to patients should include both therapeutic and nontherapeutic medication use.

OBJECTIVE

To describe the characteristics of emergency department (ED) visits for acute harms from both therapeutic and nontherapeutic medication use in the US.

DESIGN, SETTING, AND PARTICIPANTS

Active, nationally representative, public health surveillance based on patient visits to 60 EDs in the US participating in the National Electronic Injury Surveillance System-Cooperative Adverse Drug Event Surveillance Project from 2017 through 2019.

EXPOSURES

Medications implicated in ED visits, with visits attributed to medication harms (adverse events) based on the clinicians' diagnoses and supporting data documented in the medical record.

MAIN OUTCOMES AND MEASURES

Nationally weighted estimates of ED visits and subsequent hospitalizations for medication harms.

RESULTS

Based on 96 925 cases (mean patient age, 49 years; 55% female), there were an estimated 6.1 (95% CI, 4.8-7.5) ED visits for medication harms per 1000 population annually and 38.6% (95% CI, 35.2%-41.9%) resulted in hospitalization. Population rates of ED visits for medication harms were higher for patients aged 65 years or older than for those younger than 65 years (12.1 vs 5.0 [95% CI, 7.4-16.8 vs 4.1-5.8] per 1000 population). Overall, an estimated 69.1% (95% CI, 63.6%-74.7%) of ED visits for medication harms involved therapeutic medication use, but among patients younger than 45 years, an estimated 52.5% (95% CI, 48.1%-56.8%) of visits for medication harms involved nontherapeutic use. The proportions of ED visits for medication harms involving therapeutic use were lowest for barbiturates (6.3%), benzodiazepines (11.1%), nonopioid analgesics (15.7%), and antihistamines (21.8%). By age group, the most frequent medication types and intents of use associated with ED visits for medication harms were therapeutic use of anticoagulants (4.5 [95% CI, 2.3-6.7] per 1000 population) and diabetes agents (1.8 [95% CI, 1.3-2.3] per 1000 population) for patients aged 65 years and older; therapeutic use of diabetes agents (0.8 [95% CI, 0.5-1.0] per 1000 population) for patients aged 45 to 64 years; nontherapeutic use of benzodiazepines (1.0 [95% CI, 0.7-1.3] per 1000 population) for patients aged 25 to 44 years; and unsupervised medication exposures (2.2 [95% CI, 1.8-2.7] per 1000 population) and therapeutic use of antibiotics (1.4 [95% CI, 1.0-1.8] per 1000 population) for children younger than 5 years.

CONCLUSIONS AND RELEVANCE

According to data from 60 nationally representative US emergency departments, visits attributed to medication harms in 2017-2019 were frequent, with variation in products and intent of use by age.

Analysis and Design Process for Predicting and Controlling Blood Glucose in Type 1 Diabetic Patients

Engineering smart software that can monitor, predict, and control blood glucose is critical to improving patients' quality of treatments with type 1 Diabetic Mellitus (T1DM). However, ensuring a reasonable glycemic level in diabetic patients is quite challenging, as many methods do not adequately capture the complexities involved in glycemic control. This problem introduces a new level of complexity and uncertainty to the patient's psychological state, thereby making this problem nonlinear and unobservable. In this paper, we formulated a mathematical model using carbohydrate counting, insulin requirements, and the Harris-Benedict energy equations to establish the framework for predicting and controlling blood glucose level regulation in T1DM. We implemented the framework and evaluated its performance using root mean square error (RMSE) and mean absolute error (MAE) on a case study. Our framework had less error rate in terms of RMSE and MAE, which indicates a better fit with reasonable accuracy.

A retrospective in-depth analysis of continuous glucose monitoring datasets for patients with hepatic glycogen storage disease: Recommended outcome parameters for glucose management

Continuous glucose monitoring (CGM) systems have great potential for real-time assessment of glycemic variation in patients with hepatic glycogen storage disease (GSD). However, detailed descriptions and in-depth analysis of CGM data from hepatic GSD patients during interventions are scarce. This is a retrospective in-depth analysis of CGM parameters, acquired in a continuous, real-time fashion describing glucose management in 15 individual GSD patients. CGM subsets are obtained both in-hospital and at home, upon nocturnal dietary intervention (n = 1), starch loads (n = 11) and treatment of GSD Ib patients with empagliflozin (n = 3). Descriptive CGM parameters, and parameters reflecting glycemic variation and glycemic control are considered useful CGM outcome parameters. Furthermore, the combination of first and second order derivatives, cumulative sum and Fourier analysis identified both subtle and sudden changes in glucose management; hence, aiding assessment of dietary and medical interventions. CGM data interpolation for nocturnal intervals reduced confounding by physical activity and diet. Based on these analyses, we conclude that in-depth CGM analysis can be a powerful tool to assess glucose management and optimize treatment in individual hepatic GSD patients.

Neutral Nonenzymatic Glucose Biosensors Based on Electrochemically Deposited Pt/Au Nanoalloy Electrodes

Background

Type I diabetes occurs when the pancreas can only make limited or minimal insulin. Patients with type 1 diabetes need effective approaches to manage diabetes and maintain their blood-glucose concentration. Recently, continuous glucose monitoring (CGM) has been used to help control blood-glucose levels in patients with type 1 diabetes. Patients with type 2 diabetes may also benefit from CGM on multiple insulin injections, basal insulin, or sulfonylureas. Enzyme-free glucose detection in a neutral environment is the recent development trend of CGM.

Materials and Methods

Pt/Au alloy electrodes for enzyme-free glucose detection in a neutral environment were formed by electrochemically depositing Pt/Au alloy on a thin polycarbonate (PC) membrane surface with a uniformly distributed micro-hemisphere array. The PC membranes were fabricated using semiconductor microelectromechanical manufacturing processes, precision micro-molding, and hot embossing. Amperometry was used to measure the glucose concentration in PBS (pH 7.4) and artificial human serum.

Results

The Pt/Au nanoalloy electrode had excellent specificity for glucose detection, according to the experimental results. The device had a sensitivity of 2.82 μA mM⁻¹ cm⁻², a linear range of 1.39–13.9 mM, and a detection limit of 0.482 mM. Even though the complex interfering species in human blood can degrade the sensing signal, further experiments conducted in artificial serum confirmed the feasibility of the proposed Pt/Au nanoalloy electrode in clinical applications.

Conclusion

The proposed Pt/Au nanoalloy electrode can catalyze glucose reactions in neutral solutions with enhancing sensing performance by the synergistic effect of bimetallic materials and increasing detection surface area. This novel glucose biosensor has advantages, such as technology foresight, good detection performance, and high mass production feasibility. Thus, the proposed neutral nonenzymatic glucose sensor can be further used in CGMs.

Benefits of the addition of continuous or flash glucose monitoring versus standard practice using self-monitored blood glucose and haemoglobin A1c in the primary care of diabetes mellitus: a systematic review protocol

INTRODUCTION

Studies demonstrate that optimal glycaemic control reduces morbidity from diabetes mellitus but remains elusive in a significant portion of patients. Although research shows that continuous glucose monitoring (CGM) and flash glucose monitoring (FGM) improves glycaemic control in selected subsets of patients with diabetes in specialty practices, we found no systematic reviews evaluating the use of CGM/FGM in primary care, where the majority of patients with diabetes are cared for.This systematic review aims to answer the questions: 'compared with usual care of self-monitoring blood glucose and haemoglobin A1c (HbA1c), does the addition of CGM/FGM use in the primary care of patients with diabetes improve glycaemic control, decrease rates of hypoglycaemia, and improve patient and physician satisfaction?' and if so, 'what subgroups of primary care patients with diabetes are most likely to benefit?'.

METHODS AND ANALYSIS

Aligning with the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols guidelines, a search will be conducted in PubMed, EMBASE, Scopus, CINAHL, Cochrane Central Register of Controlled Trials and Web of Science. We will include studies investigating CGM/FGM use and reporting the primary outcome measure of HbA1c and secondary outcome measures of hypoglycaemia, time in range, time below range, time above range and patient/staff satisfaction. We will examine which patient populations appear to benefit from CGM/FGM. Three independent researchers will use the Covidence systematic review software for blinded screening and study selection. The National Heart, Lung, and Blood Institute quality assessment tool and Grading of Recommendations Assessment, Development and Evaluation will be used to assess the risk of bias and quality of evidence.

ETHICS AND DISSEMINATION

The systematic review methodology does not require ethics approval due to the nature of the study design. Study findings will be publicly available to a wide readership across disciplines and will be published in a peer-reviewed journal.

PROSPERO REGISTRATION NUMBER

CRD42021229416.

RF. Fatigue Testing of Wearable Sensing Technologies: Issues and Opportunities

Standards for the fatigue testing of wearable sensing technologies are lacking. The majority of published fatigue tests for wearable sensors are performed on proof-of-concept stretch sensors fabricated from a variety of materials. Due to their flexibility and stretchability, polymers are often used in the fabrication of wearable sensors. Other materials, including textiles, carbon nanotubes, graphene, and conductive metals or inks, may be used in conjunction with polymers to fabricate wearable sensors. Depending on the combination of the materials used, the fatigue behaviors of wearable sensors can vary. Additionally, fatigue testing methodologies for the sensors also vary, with most tests focusing only on the low-cycle fatigue (LCF) regime, and few sensors are cycled until failure or runout are achieved. Fatigue life predictions of wearable sensors are also lacking. These issues make direct comparisons of wearable sensors difficult. To facilitate direct comparisons of wearable sensors and to move proof-of-concept sensors from "bench to bedside", fatigue testing standards should be established. Further, both high-cycle fatigue (HCF) and failure data are needed to determine the appropriateness in the use, modification, development, and validation of fatigue life prediction models and to further the understanding of how cracks initiate and propagate in wearable sensing technologies.

Modulating the foreign body response of implants for diabetes treatment

Diabetes Mellitus is a group of diseases characterized by high blood glucose levels due to patients' inability to produce sufficient insulin. Current interventions often require implants that can detect and correct high blood glucose levels with minimal patient intervention. However, these implantable technologies have not reached their full potential in vivo due to the foreign body response and subsequent development of fibrosis. Therefore, for long-term function of implants, modulating the initial immune response is crucial in preventing the activation and progression of the immune cascade. This review discusses the different molecular mechanisms and cellular interactions involved in the activation and progression of foreign body response (FBR) and fibrosis, specifically for implants used in diabetes. We also highlight the various strategies and techniques that have been used for immunomodulation and prevention of fibrosis. We investigate how these general strategies have been applied to implants used for the treatment of diabetes, offering insights on how these devices can be further modified to circumvent FBR and fibrosis.

Smoking is Associated With Increased Risk of Not Achieving Glycemic Target, Increased Glycemic Variability, and Increased Risk of Hypoglycemia for People With Type 1 Diabetes

BACKGROUND

The prevalence of smoking and diabetes is increasing in many developing countries. The aim of this study was to investigate the association of smoking with inadequate glycemic control and glycemic variability with continuous glucose monitoring (CGM) data in people with type 1 diabetes.

METHODS

Forty-nine smokers and 320 nonsmokers were obtained from the Novo Nordisk Onset 5 trial. After 16 weeks of treatment with continuous subcutaneous insulin infusion, risk of not achieving glycemic target and glycemic variability from six CGM measures was investigated. Analyzes were carried out with logistic regression models (glycemic target) and general linear models (glycemic variability). Finally, CGM median profiles were examined for the identification of daily glucose excursions.

RESULTS

A 4.7-fold (95% confidence interval: 1.5-15.4) increased risk of not achieving glycemic target was observed for smokers compared with nonsmokers. Increased time in hyperglycemia, decreased time in range, increased time in hypoglycemia (very low interstitial glucose), and increased fluctuation were observed for smokers compared with nonsmokers from CGM measures. CGM measures of coefficient of variation and time in hypoglycemia were not statistically significantly different. Examination of CGM median profiles revealed that risk of morning hypoglycemia is increased for smokers.

CONCLUSIONS

In conclusion, smoking is associated with inadequate glycemic control and increased glycemic variability for people with type 1 diabetes with especially risk of morning hypoglycemia. It is important for clinicians to know that if the patient has type 1 diabetes and is smoking, a preemptive action to treat high glycated hemoglobin levels should not necessarily be treatment intensification due to the risk of hypoglycemia.

The Triple Health Threat of Diabetes, Obesity, and Cancer-Epidemiology, Disparities, Mechanisms, and Interventions

Obesity and type 2 diabetes are both chronic, relapsing, progressive diseases that are recognized as risk factors for the development of multiple types of cancer. In a recent symposium titled "Hitting A Triple-Diabetes, Obesity, and the Emerging Links to Cancer Risk," convened by The Obesity Society during ObesityWeek 2019, experts in the field presented the current science and highlighted existing research gaps. Topics included (1) the epidemiology of obesity and diabetes and their links to cancer risk; (2) racial and ethnic differences in obesity, diabetes, and cancer risk; (3) biological mechanisms common to obesity and diabetes that may increase cancer risk; and (4) innovative interventions that can be used to prevent the development of cancers related to obesity and diabetes. This report provides an overview of the symposium and describes key research gaps and pressing questions in need of answers to advance the field. The collective burden of obesity, diabetes, and cancer represents one of the largest public health challenges of the century. Although the symposium was titled "hitting a triple," it was recognized that being able to disrupt the linkages among obesity, diabetes, and cancer would be a "grand slam" for public health and medicine.

The clinical utility of professional continuous glucose monitoring by pharmacists for patients with type 2 diabetes

BACKGROUND

There are limited data regarding the use of diabetes technologies, such as professional continuous glucose monitoring (CGM), as part of a pharmacist-managed diabetes service.

OBJECTIVE

To assess how professional CGM affected treatment decisions and glucose control as part of a pharmacist-managed service for patients with type 2 diabetes.

PRACTICE DESCRIPTION

Clinical Pharmacy Specialists (CPS's) within an outpatient diabetes management service provide comprehensive diabetes care under a scope of practice that includes prescriptive privileges.

PRACTICE INNOVATION

Insight into glucose patterns is paramount for pharmacists to use their medication expertise to its fullest capacity. CGM technology can provide detailed data on glucose trends, including percentage of time spent in a target range. Pharmacists involved in the provision of diabetes care have the opportunity to integrate professional CGM into their practice to acquire data for targeted therapeutic adjustments.

EVALUATION METHODS

A retrospective analysis was conducted of patients with type 2 diabetes who had professional CGM used as part of their routine diabetes care with the CPS from 2017-2019. The primary outcome was the percentage of patients meeting their individualized A1c goal at baseline versus 6 months post placement of the professional CGM. A McNemar's test was used to compare the percentage of patients achieving A1c goal pre and postintervention. A P value of <0.05 denoted the presence of a statistically significant difference.

RESULTS

Patients who implemented professional CGM had an average duration of diabetes of 15.6 years and an average A1c of 9.1%. The majority (76.7%) were not meeting their individualized A1c goal. Hypoglycemia was identified in 57% of the patients; almost half of patients evaluated had periods of nocturnal hypoglycemia. Hyperglycemia was present on the vast majority of reports (83%) with postprandial elevations being the most common trend identified overall. Mean A1c decreased from 9.11% ± 1.4 at baseline to 8.64% ± 1.3 at 3 months and 8.19% ± 0.8 at 6 months. Compared with baseline, more than 2 times the number of patients were within their A1c goal range at 3 and 6 months (23.3%, 53.6% and 69.6% respectively.) This represented a statistically significant difference at both time points (P = 0.008 at 3 months and P = 0.006 at 6 months.) CONCLUSION: The use of CGM technology may overcome treatment barriers, such as insufficient self-monitoring of blood glucose and lack of discernment of glucose trends with traditional A1c testing. Pharmacists employing professional CGM as part of a diabetes management service were able to achieve targets for significantly more patients with type 2 diabetes on a wide range of treatment regimens at 6 months compared with baseline. Widespread use of professional CGM in pharmacist-managed diabetes services may provide valuable care and improve outcomes more broadly. Larger randomized trials are warranted to examine ideal patient selection and optimal frequency of use.

The effects of continuous glucose monitoring system on patient outcomes and associated costs in a real-world setting

AIMS

Continuous glucose monitoring system (CGMS) technologies may alert unaware hypoglycaemia or near hypoglycaemia events. However, costs are a significant concern in general CGMS use. This study describes the real-world effects of both clinical outcomes and associated costs in a major Health Maintenance Organization, 1 year following preauthorization of CGMS for each patient.

METHODS

Cohort study. Type 1 diabetes patients who were preauthorized CGMS were identified, and their medical records during the year before preauthorization were compared to the following year. Data were collected for glucose control, medical services utilization and related costs.

RESULTS

We identified 524 eligible patients, 57% males. Adherence to CGMS use was improved by age. The proportion of patients reaching HbA_1c  < 7.5% (58 mmol/mol) increased in the high-adherence group and decreased in the low-adherence group. There were no significant changes in outpatient medical services utilization. However, there was a decrease in emergency room visit rates (30%-19%, p < 0.01) and hospitalization rates (22%-12%, p < 0.01) with the highest decrease among the high-adherence group. Hospitalization duration also decreased. However, the total costs per patient were higher as CGMS adherence increased.

CONCLUSION

Continuous glucose monitoring system technologies have the potential of both improving blood glucose control and reducing inpatient utilization. However, CGMS technologies costs may put a significant burden on healthcare systems.

Wearable Devices for Physical Activity and Healthcare Monitoring in Elderly People: A Critical Review

The availability of wearable devices (WDs) to collect biometric information and their use during activities of daily living is significantly increasing in the general population. These small electronic devices, which record fitness and health-related outcomes, have been broadly utilized in industries such as medicine, healthcare, and fitness. Since they are simple to use and progressively cheaper, they have also been used for numerous research purposes. However, despite their increasing popularity, most of these WDs do not accurately measure the proclaimed outcomes. In fact, research is equivocal about whether they are valid and reliable methods to specifically evaluate physical activity and health-related outcomes in older adults, since they are mostly designed and produced considering younger subjects' physical and mental characteristics. Additionally, their constant evolution through continuous upgrades and redesigned versions, suggests the need for constant up-to-date reviews and research. Accordingly, this article aims to scrutinize the state-of-the-art scientific evidence about the usefulness of WDs, specifically on older adults, to monitor physical activity and health-related outcomes. This critical review not only aims to inform older consumers but also aid researchers in study design when selecting physical activity and healthcare monitoring devices for elderly people.

Impact of Switching from Intermittently Scanned to Real-Time Continuous Glucose Monitoring Systems in a Type 1 Diabetes Patient French Cohort: An Observational Study of Clinical Practices

Aim: Assess the impact of switching from intermittently scanned (FreeStyle Libre [FSL]) to real-time (Dexcom G4 platinum [DG4]) continuous glucose monitoring systems on glycemia control in type 1 diabetes (T1D) patients with high risk of hypoglycemia and/or elevated glycated hemoglobin (HbA1c). Methods: We conducted an observational study in 18 T1D adults with poor glycemic control on FSL. Ambulatory glucose profile data were collected during the last 3 months of FSL use before inclusion (M0 period), during the first 3 months (M3 period) and the last 3 months (M6 period) of DG4 use. Data were then expressed as 24-h averages. Biological HbA1c was measured for all three periods. Patients were their own-controls and statistics were performed using paired t-test or Wilcoxon for matched-pairs. Results: The switch to DG4 at M3 resulted in a higher time-in-range (TIR) 70-180 mg/dL (median [Q1;Q3], 53.1 [44.5;67.3] vs. 41.5 [28.5;62.0], P = 0.0008), and a lower time-below-range <70 mg/dL (TBR mean ± standard deviation (SD), 5.4 ± 3.7 vs. 10.9 ± 7.1, P = 0.0009) and in the glucose % coefficient of variation (%CV mean ± SD, 40.1 vs. 46.9, P = 0.0001). Mean (SD) changes were +10.3 (8.0) percentage points for TIR, -5.5 (5.8) percentage points for TBR, and -6.8 (5.8) percentage points for %CV. These results were confirmed at the M6 period. Conclusions: Switching from FSL to DG4 appears to provide a beneficial therapeutic option without changing insulin delivery systems, regardless of the origin of the patient's initial glycemic issue.

Continuous Glucose Monitoring in the Hospital

Continuous glucose monitors (CGMs) have suddenly become part of routine care in many hospitals. The coronavirus disease 2019 (COVID-19) pandemic has necessitated the use of new technologies and new processes to care for hospitalized patients, including diabetes patients. The use of CGMs to automatically and remotely supplement or replace assisted monitoring of blood glucose by bedside nurses can decrease: the amount of necessary nursing exposure to COVID-19 patients with diabetes; the amount of time required for obtaining blood glucose measurements, and the amount of personal protective equipment necessary for interacting with patients during the blood glucose testing. The United States Food and Drug Administration (FDA) is now exercising enforcement discretion and not objecting to certain factory-calibrated CGMs being used in a hospital setting, both to facilitate patient care and to obtain performance data that can be used for future regulatory submissions. CGMs can be used in the hospital to decrease the frequency of fingerstick point of care capillary blood glucose testing, decrease hyperglycemic episodes, and decrease hypoglycemic episodes. Most of the research on CGMs in the hospital has focused on their accuracy and only recently outcomes data has been reported. A hospital CGM program requires cooperation of physicians, bedside nurses, diabetes educators, and hospital administrators to appropriately select and manage patients. Processes for collecting, reviewing, storing, and responding to CGM data must be established for such a program to be successful. CGM technology is advancing and we expect that CGMs will be increasingly used in the hospital for patients with diabetes.

Forecasting of Glucose Levels and Hypoglycemic Events: Head-to-Head Comparison of Linear and Nonlinear Data-Driven Algorithms Based on Continuous Glucose Monitoring Data Only

In type 1 diabetes management, the availability of algorithms capable of accurately forecasting future blood glucose (BG) concentrations and hypoglycemic episodes could enable proactive therapeutic actions, e.g., the consumption of carbohydrates to mitigate, or even avoid, an impending critical event. The only input of this kind of algorithm is often continuous glucose monitoring (CGM) sensor data, because other signals (such as injected insulin, ingested carbs, and physical activity) are frequently unavailable. Several predictive algorithms fed by CGM data only have been proposed in the literature, but they were assessed using datasets originated by different experimental protocols, making a comparison of their relative merits difficult. The aim of the present work was to perform a head-to-head comparison of thirty different linear and nonlinear predictive algorithms using the same dataset, given by 124 CGM traces collected over 10 days with the newest Dexcom G6 sensor available on the market and considering a 30-min prediction horizon. We considered the state-of-the art methods, investigating, in particular, linear black-box methods (autoregressive; autoregressive moving-average; and autoregressive integrated moving-average, ARIMA) and nonlinear machine-learning methods (support vector regression, SVR; regression random forest; feed-forward neural network, fNN; and long short-term memory neural network). For each method, the prediction accuracy and hypoglycemia detection capabilities were assessed using either population or individualized model parameters. As far as prediction accuracy is concerned, the results show that the best linear algorithm (individualized ARIMA) provides accuracy comparable to that of the best nonlinear algorithm (individualized fNN), with root mean square errors of 22.15 and 21.52 mg/dL, respectively. As far as hypoglycemia detection is concerned, the best linear algorithm (individualized ARIMA) provided precision = 64%, recall = 82%, and one false alarm/day, comparable to the best nonlinear technique (population SVR): precision = 63%, recall = 69%, and 0.5 false alarms/day. In general, the head-to-head comparison of the thirty algorithms fed by CGM data only made using a wide dataset shows that individualized linear models are more effective than population ones, while no significant advantages seem to emerge when employing nonlinear methodologies.

Continuous Glucose Monitoring in Patients With Insulinoma Treated by Endoscopic Ultrasound-Guided Ethanol Injection

OBJECTIVES

The aims of this study were to analyze the continuous glucose monitoring (CGM) profiles of patients with insulinoma before and after treatment with endoscopic ultrasound-guided ethanol injection and assess the value of CGM in curative effect evaluating.

METHODS

We included 8 patients, and CGM was performed for 3 to 5 days before and after treatment.

RESULTS

The proportion of monitoring points at which the glucose level was lower than 3.9 mmol/L after treatment decreased in patient 5 (from 4% to 3%) and patient 8 (from 30% to 12%), whereas the proportion increased in patient 1 (from 1% to 16%), patient 3 (from 5% to 23%), and patient 7 (from 7% to 63%). There was no mean significant difference between CGM values (5.75 [standard deviation, 2.49] mmol/L) and self-monitoring of blood glucose values (5.76 [standard deviation, 2.32] mmol/L) (P > 0.05). Pearson correlation analysis showed positive correlation between CGM values and self-monitoring of blood glucose values (r = 0.88, P < 0.05). Clarke Error Grid Analysis showed that 91.5% of pairs were located in areas A and B.

CONCLUSIONS

Continuous glucose monitoring is useful for detecting hypoglycemia and evaluating curative effect, but the correction of fingertip blood glucose is necessary when the blood glucose is relatively low.

Enhancing the Long-Term Stability of a Polymer Dot Glucose Transducer by Using an Enzymatic Cascade Reaction System

Impaired glucose metabolism in diabetes causes severe acute and long-term complications, making real-time detection of blood glucose indispensable for diabetic patients. Existing continuous glucose monitoring systems are unsuitable for long-term clinical glycemic management due to poor long-term stability. Polymer dot (Pdot) glucose transducers are implantable optical nanosensors that exhibit excellent brightness, sensitivity, selectivity, and biocompatibility. Here, it is shown that hydrogen peroxide-a product of glucose oxidation in Pdot glucose sensors-degrades sensor performance via photobleaching, reduces glucose oxidase activity, and generates cytotoxicity. By adding catalase to a glucose oxidase-based Pdot sensor to create an enzymatic cascade, the hydrogen peroxide product of glucose oxidation is rapidly decomposed by catalase, preventing its accumulation and improving the sensor's photostability, enzymatic activity, and biocompatibility. Thus, a next-generation Pdot glucose transducer with a multienzyme reaction system (Pdot-GOx/CAT) that provides excellent sensing characteristics as well as greater detection system stability is presented. Pdot glucose transducers that incorporate this enzymatic cascade to eliminate hydrogen peroxide will possess greater long-term stability for improved continuous glucose monitoring in diabetic patients.

Evaluation of the SPECTRUM training programme for real-time continuous glucose monitoring: A real-world multicentre prospective study in 120 adults with type 1 diabetes

AIMS

Comprehensive knowledge, specific skills and data-analysis competences are prerequisites for the successful use of continuous glucose monitoring (CGM) systems. SPECTRUM is a structured training programme for real-time CGM (rtCGM) consisting of a web-based introduction and six group sessions of 90 min each. The 'CGM-TRAIN study' evaluated the efficacy and acceptance of SPECTRUM and rtCGM systems among adults with insulin therapy.

METHODS

Participants (n = 120) were recruited from 10 German diabetes centres in which they were treated under usual care conditions. Outcome measures were rtCGM knowledge, practical skills, satisfaction with the training programme, satisfaction and acceptance of rtCGM system and glycaemic control. Data were collected at study entry, after training completion and at 6-month follow-up.

RESULTS

All participants were diagnosed with type 1 diabetes (56% women, mean age 42.4 ± 13.4 years, diabetes duration 21.6 ± 11.6 years), 110 participants completed the course. After training completion, rtCGM-specific knowledge had improved by 43% (scale: 0-40 points) from 21.2 ± 7.6 to 30.4 ± 4.5 points; p < 0.001. The knowledge-level persisted until follow-up (29.4 ± 4.5). Participants were able to master nearly all the practical requirements of the technology. In addition, rtCGM was highly accepted, and participants were motivated to use their systems continuously. HbA_1c improved slightly from 61 ± 14 mmol/mol (7.7 ± 1.3%) before training to 60 ± 14 mmol/mol (7.6 ± 1.3%) at follow-up (p = 0.04). The training programme itself was favourably rated by participants.

CONCLUSIONS

Under usual out-patient daily care conditions, the training programme SPECTRUM improved knowledge and skills about rtCGM in adults with type 1 diabetes. This was associated with a reduced HbA_1c , high satisfaction and acceptance of rtCGM (Clinical Trials Registry no.: DRKS00014380).

Masked hypertension and its associations with glycemic variability metrics in children and adolescents with type 1 diabetes

BACKGROUND

Masked hypertension defined as having normal office blood pressure (BP) but hypertension detected by continuous BP monitoring has been observed in children and adolescents with type 1 diabetes (T1D). However, no study has evaluated whether masked hypertension is associated with glycemic variability (GV) in these patients. We hypothesized that masked hypertension might be associated with high GV in patients with T1D.

METHODS

This cross-sectional study performed continuous glucose monitoring (CGM) in parallel with ambulatory blood pressure monitoring (ABPM) in T1D patients aged 6-21 years. Patients who had known hypertension were excluded. CGM data from the same day as ABPM was calculated for GV including standard deviation (SD), coefficient of variation (CV) of glucose levels, and unstable glycemia which was defined as having a CV of glucose levels ≥ 36%.

RESULTS

Thirty-three patients had complete ABPM and CGM data. Mean (SD) age was 13.8 (3.8) years and mean (SD) duration of T1D was 5.4 (3.6) years. All patients had normal office BP, but ABPM showed masked hypertension in 9 patients (27%). In comparison with normotensive patients, patients with masked hypertension had longer duration of T1D (7.4 vs. 4.6 years, p = 0.049), higher insulin requirement (1.2 vs. 0.9 units/kg/day, p = 0.049), and higher SD of glucose (70.3 vs. 47.9 mg/dl, p = 0.038). Masked hypertension group had a greater number of patients (71% vs. 19%, p = 0.02) with unstable glycemia. Multivariate analysis revealed that unstable glycemia was associated with masked hypertension.

CONCLUSIONS

The presence of unstable glycemia in children and adolescents with T1D is associated with masked hypertension. Graphical abstract.

Titration of Long-Acting Insulin Using Continuous Glucose Monitoring and Smart Insulin Pens in Type 1 Diabetes: A Model-Based Carbohydrate-Free Approach

OBJECTIVE

Multiple daily injections (MDI) therapy is the most common treatment for type 1 diabetes (T1D), consisting of long-acting insulin to cover fasting conditions and rapid-acting insulin to cover meals. Titration of long-acting insulin is needed to achieve satisfactory glycemia but is challenging due to inter-and intra-individual metabolic variability. In this work, a novel titration algorithm for long-acting insulin leveraging continuous glucose monitoring (CGM) and smart insulin pens (SIP) data is proposed.

METHODS

The algorithm is based on a glucoregulatory model that describes insulin and meal effects on blood glucose fluctuations. The model is individualized on patient's data and used to extract the theoretical glucose curve in fasting conditions; the individualization step does not require any carbohydrate records. A cost function is employed to search for the optimal long-acting insulin dose to achieve the desired glycemic target in the fasting state. The algorithm was tested in two virtual studies performed within a validated T1D simulation platform, deploying different levels of metabolic variability (nominal and variance). The performance of the method was compared to that achieved with two published titration algorithms based on self-measured blood glucose (SMBG) records. The sensitivity of the algorithm to carbohydrate records was also analyzed.

RESULTS

The proposed method outperformed SMBG-based methods in terms of reduction of exposure to hypoglycemia, especially during the night period (0 am-6 am). In the variance scenario, during the night, an improvement in the time in the target glycemic range (70-180 mg/dL) from 69.0% to 86.4% and a decrease in the time in hypoglycemia (<70 mg/dL) from 10.7% to 2.6% was observed. Robustness analysis showed that the method performance is non-sensitive to carbohydrate records.

CONCLUSION

The use of CGM and SIP in people with T1D using MDI therapy has the potential to inform smart insulin titration algorithms that improve glycemic control. Clinical studies in real-world settings are warranted to further test the proposed titration algorithm.

SIGNIFICANCE

This algorithm is a step towards a decision support system that improves glycemic control and potentially the quality of life, in a population of individuals with T1D who cannot benefit from the artificial pancreas system.

Advances in applied supramolecular technologies

Supramolecular chemistry has successfully built a foundation of fundamental understanding. However, with this now achieved, we show how this area of chemistry is moving out of the laboratory towards successful commercialisation.

Machine Learning-Based Adherence Detection of Type 2 Diabetes Patients on Once-Daily Basal Insulin Injections

BACKGROUND

Lack of treatment adherence can lead to life-threatening health complications for people with type 2 diabetes (T2D). Recent improvements and availability in continuous glucose monitoring (CGM) technology have enabled various possibilities to monitor diabetes treatment. Detection of missed once-daily basal insulin injections can be used to provide feedback to patients, thus improving their diabetes management. In this study, we explore how machine learning (ML) based on CGM data can be used for detecting adherence to once-daily basal insulin injections.

METHODS

In-silico CGM data were generated to simulate a cohort of T2D patients on once-daily insulin injection (Tresiba®). Deep learning methods within ML based on automatic feature extraction including convolutional neural networks were explored and compared with simple feature-engineered ML classification models for adherence detection. It was further investigated whether fused expert-dependent and automatically learned features could improve performance, resulting in a comparison of six different detection models. Adherence was detected throughout each day with an increasing amount of CGM data available.

RESULTS

The adherence detection accuracy improved as more CGM data became available on the day of classification. The three classification models based on expert-engineered features obtained mean accuracies of 78.6%, 78.2%, and 78.3%. The classification model based purely on learned features obtained a mean accuracy of 79.7%. The two classification models fusing expert-engineered and learned features obtained mean accuracies of 79.7% and 79.8%. All the mentioned results were obtained 16 hours after time of injection.

CONCLUSION

The results suggest that adherence detection based on CGM data is feasible. Even though our study based on in-silico data indicates only slightly improved performance of more complex models, the question remains whether advanced models would outperform the simple in a real-world setting. Thus, future studies on adherence monitoring using real CGM data are relevant.

Effectiveness of real-time continuous glucose monitoring to improve glycaemic control and pregnancy outcome in patients with gestational diabetes mellitus: a study protocol for a randomised controlled trial

INTRODUCTION

Real-time continuous glucose monitoring (rt-CGM) informs users about current interstitial glucose levels and allows early detection of glycaemic excursions and timely adaptation by behavioural change or pharmacological intervention. Randomised controlled studies adequately powered to evaluate the impact of long-term application of rt-CGM systems on the reduction of adverse obstetric outcomes in women with gestational diabetes (GDM) are missing. We aim to assess differences in the proportion of large for gestational age newborns in women using rt-CGM as compared with women with self-monitored blood glucose (primary outcome). Rates of neonatal hypoglycaemia, caesarean section and shoulder dystocia are secondary outcomes. A comparison of glucose metabolism and quality of life during and after pregnancy completes the scope of this study.

METHODS AND ANALYSIS

Open-label multicentre randomised controlled trial with two parallel groups including 372 female patients with a recent diagnosis of GDM (between 24+0 until 31+6 weeks of gestation): 186 with rt-CGM (Dexcom G6) and 186 with self-monitored blood glucose (SMBG). Women with GDM will be consecutively recruited and randomised to rt-CGM or control (SMBG) group after a run-in period of 6-8 days. The third visit will be scheduled 8-10 days later and then every 2 weeks. At every visit, glucose measurements will be evaluated and all patients will be treated according to the standard care. The control group will receive a blinded CGM for 10 days between the second and third visit and between week 36+0 and 38+6. Cord blood will be sampled immediately after delivery. 48 hours after delivery neonatal biometry and maternal glycosylated haemoglobin A1c (HbA1c) will be assessed, and between weeks 8 and 16 after delivery all patients receive a re-examination of glucose metabolism including blinded CGM for 8-10 days.

ETHICS AND DISSEMINATION

This study received ethical approval from the main ethic committee in Vienna. Data will be presented at international conferences and published in peer-reviewed journals.

TRIAL REGISTRATION NUMBER

NCT03981328; Pre-results.

Impact of provision of optimum diabetes care on the safety of fasting in Ramadan in adult and adolescent patients with type 1 diabetes mellitus

BACKGROUND

All diabetes and Ramadan guidelines advice against fasting for people with type 1 diabetes, however, many insist on fasting. Consequently, this causes a challenge due to the risk of hypoglycaemia, hyperglycemia ± diabetic ketoacidosis.

AIM

To assess the impact of optimum care, which includes Ramadan-focused education, flash glucose monitoring, dietary advice and treatment adjustment on the safety of Ramadan fasting in people with type 1 diabetes.

METHODS

Thirty persons with type 1 diabetes who insisted to fast during Ramadan were recruited to the study. At pre-Ramadan visit, all patients received Ramadan focused education and Freestyle Libre (FSL) sensor insertion and training. Patients used the sensor for 6 weeks (pre-Ramadan and during Ramadan). The physical and biological parameters were collected 2-4 weeks before and after Ramadan.

RESULTS

22 patients on basal bolus insulin and 2 on an insulin pump had FSL data. Average number of days fasted were 24. Learning benefits was reported by 95% of patients following pre-Ramadan educational session. There was no clinically significant change in physical and/or biological data between pre and post-Ramadan. 63% reported making insulin dose adjustments in Ramadan. Flash glucose monitoring data showed 46.7% of patients had more than 10 hypoglycemic episodes in the 2 weeks prior to Ramadan compared to 29.2% during Ramadan. However, none of the data were statistically significant apart from HbA1c which reduced from prior to RamadanHbA1c of 8.2% to 7.9% post Ramadan (P 0.010). There was one DKA on 2nd day of Ramadan, reported due to missing insulin dose to avoid hypoglycemia.

CONCLUSION

Optimal care of selective patients with type 1 diabetes with a low complication rate may allow Ramadan fasting with improvement in glycemic control and without an increase in hypoglycemia, biometric or metabolic parameters. Larger, randomized controlled trials are required to be able to generalize this as a recommendation.

Reducing Inpatient Hypoglycemia in the General Wards Using Real-time Continuous Glucose Monitoring: The Glucose Telemetry System, a Randomized Clinical Trial

OBJECTIVE

Use of real-time continuous glucose monitoring (RT-CGM) systems in the inpatient setting is considered investigational. The objective of this study was to evaluate whether RT-CGM, using the glucose telemetry system (GTS), can prevent hypoglycemia in the general wards.

RESEARCH DESIGN AND METHODS

In a randomized clinical trial, insulin-treated patients with type 2 diabetes at high risk for hypoglycemia were recruited. Participants were randomized to RT-CGM/GTS or point-of-care (POC) blood glucose testing. The primary outcome was difference in inpatient hypoglycemia.

RESULTS

Seventy-two participants were included in this interim analysis, 36 in the RT-CGM/GTS group and 36 in the POC group. The RT-CGM/GTS group experienced fewer hypoglycemic events (<70 mg/dL) per patient (0.67 [95% CI 0.34-1.30] vs. 1.69 [1.11-2.58], P = 0.024), fewer clinically significant hypoglycemic events (<54 mg/dL) per patient (0.08 [0.03-0.26] vs. 0.75 [0.51-1.09], P = 0.003), and a lower percentage of time spent below range <70 mg/dL (0.40% [0.18-0.92%] vs. 1.88% [1.26-2.81%], P = 0.002) and <54 mg/dL (0.05% [0.01-0.43%] vs. 0.82% [0.47-1.43%], P = 0.017) compared with the POC group. No differences in nocturnal hypoglycemia, time in range 70-180 mg/dL, and time above range >180-250 mg/dL and >250 mg/dL were found between the groups. The RT-CGM/GTS group had no prolonged hypoglycemia compared with 0.20 episodes <54 mg/dL and 0.40 episodes <70 mg/dL per patient in the POC group.

CONCLUSIONS

RT-CGM/GTS can decrease hypoglycemia among hospitalized high-risk insulin-treated patients with type 2 diabetes.

A highly sensitive quartz crystal microbalance sensor modified with antifouling microgels for saliva glucose monitoring

Saliva glucose detection based on quartz crystal microbalance (QCM) technology has become an important research direction of non-invasive blood glucose monitoring. However, the performance of this label-free glucose sensor is heavily deteriorated by the large amount of protein contaminants in saliva. Here, we successfully achieved the direct detection of saliva glucose by endowing the microgels on the QCM chip with superior protein-resistive and glucose-sensitive properties. Specifically, the microgel networks provide plenty of boric acid binding sites to amplify the signals of targeted glucose. The amino acid layer wrapped around the microgel and crosslinking layer can effectively eliminate the impact of non-specific proteins in saliva. The designed QCM sensor has a good linearity in the glucose concentration range of 0-40 mg L^-1 in the pH range of 6.8-7.5, satisfying the physiological conditions of saliva glucose. Moreover, the sensor has excellent ability to tolerate proteins, enabling it to detect glucose in 50% human saliva. This result provides a new approach for non-invasive blood glucose monitoring based on QCM.

Armstrong D. The Potential Role of Sensors, Wearables and Telehealth in the Remote Management of Diabetes-Related Foot Disease

Diabetes-related foot disease (DFD), which includes foot ulcers, infection and gangrene, is a leading cause of the global disability burden. About half of people who develop DFD experience a recurrence within one year. Long-term medical management to reduce the risk of recurrence is therefore important to reduce the global DFD burden. This review describes research assessing the value of sensors, wearables and telehealth in preventing DFD. Sensors and wearables have been developed to monitor foot temperature, plantar pressures, glucose, blood pressure and lipids. The monitoring of these risk factors along with telehealth consultations has promise as a method for remotely managing people who are at risk of DFD. This approach can potentially avoid or reduce the need for face-to-face consultations. Home foot temperature monitoring, continuous glucose monitoring and telehealth consultations are the approaches for which the most highly developed and user-friendly technology has been developed. A number of clinical studies in people at risk of DFD have demonstrated benefits when using one of these remote monitoring methods. Further development and evidence are needed for some of the other approaches, such as home plantar pressure and footwear adherence monitoring. As yet, no composite remote management program incorporating remote monitoring and the management of all the key risk factors for DFD has been developed and implemented. Further research assessing the feasibility and value of combining these remote monitoring approaches as a holistic way of preventing DFD is needed.

Continuous glucose monitoring for hypoglycaemia in children: Perspectives in 2020

Hypoglycaemia in children is a major risk factor for adverse neurodevelopment with rates as high as 50% in hyperinsulinaemic hypoglycaemia (HH). A key part of management relies upon timely identification and treatment of hypoglycaemia. The current standard of care for glucose monitoring is by infrequent fingerprick plasma glucose testing but this carries a high risk of missed hypoglycaemia identification. High-frequency Continuous Glucose Monitoring (CGM) offers an attractive alternative for glucose trend monitoring and glycaemic phenotyping but its utility remains largely unestablished in disorders of hypoglycaemia. Attempts to determine accuracy through correlation with plasma glucose measurements using conventional methods such as Mean Absolute Relative Difference (MARD) overestimate accuracy at hypoglycaemia. The inaccuracy of CGM in true hypoglycaemia is amplified by calibration algorithms that prioritize hyperglycaemia over hypoglycaemia with minimal objective evidence of efficacy in HH. Conversely, alternative algorithm design has significant potential for predicting hypoglycaemia to prevent neuroglycopaenia and consequent brain dysfunction in childhood disorders. Delays in the detection of hypoglycaemia, alarm fatigue, device calibration and current high cost are all barriers to the wider adoption of CGM in disorders of hypoglycaemia. However, machine learning, artificial intelligence and other computer-generated algorithms now offer significant potential for further improvement in CGM device technology and widespread application in childhood hypoglycaemia.

Review of the Omnipod® 5 Automated Glucose Control System Powered by Horizon™ for the treatment of Type 1 diabetes

Type 1 diabetes (T1D) is a medical condition that requires constant management, including monitoring of blood glucose levels and administration of insulin. Advancements in diabetes technology have offered methods to reduce the burden on people with T1D. Several hybrid closed-loop systems are commercially available or in clinical trials, each with unique features to improve care for patients with T1D. This article reviews the Omnipod® 5 Automated Glucose Control System Powered by Horizon™ and the safety and efficacy data to support its use in the management of T1D.

Advanced Diabetes Management Using Artificial Intelligence and Continuous Glucose Monitoring Sensors

Wearable continuous glucose monitoring (CGM) sensors are revolutionizing the treatment of type 1 diabetes (T1D). These sensors provide in real-time, every 1-5 min, the current blood glucose concentration and its rate-of-change, two key pieces of information for improving the determination of exogenous insulin administration and the prediction of forthcoming adverse events, such as hypo-/hyper-glycemia. The current research in diabetes technology is putting considerable effort into developing decision support systems for patient use, which automatically analyze the patient's data collected by CGM sensors and other portable devices, as well as providing personalized recommendations about therapy adjustments to patients. Due to the large amount of data collected by patients with T1D and their variety, artificial intelligence (AI) techniques are increasingly being adopted in these decision support systems. In this paper, we review the state-of-the-art methodologies using AI and CGM sensors for decision support in advanced T1D management, including techniques for personalized insulin bolus calculation, adaptive tuning of bolus calculator parameters and glucose prediction.

The Use of a Smart Bolus Calculator Informed by Real-time Insulin Sensitivity Assessments Reduces Postprandial Hypoglycemia Following an Aerobic Exercise Session in Individuals With Type 1 Diabetes

OBJECTIVE

Insulin dosing in type 1 diabetes (T1D) is oftentimes complicated by fluctuating insulin requirements driven by metabolic and psychobehavioral factors impacting individuals' insulin sensitivity (IS). In this context, smart bolus calculators that automatically tailor prandial insulin dosing to the metabolic state of a person can improve glucose management in T1D.

RESEARCH DESIGN AND METHODS

Fifteen adults with T1D using continuous glucose monitors (CGMs) and insulin pumps completed two 24-h admissions in a hotel setting. During the admissions, participants engaged in an early afternoon 45-min aerobic exercise session, after which they received a standardized dinner meal. The dinner bolus was computed using a standard bolus calculator or smart bolus calculator informed by real-time IS estimates. Glucose control was assessed in the 4 h following dinner using CGMs and was compared between the two admissions.

RESULTS

The IS-informed bolus calculator allowed for a reduction in postprandial hypoglycemia as quantified by the low blood glucose index (2.02 vs. 3.31, P = 0.006) and percent time <70 mg/dL (8.48% vs. 15.18%, P = 0.049), without increasing hyperglycemia (high blood glucose index: 3.13 vs. 2.09, P = 0.075; percent time >180 mg/dL: 13.24% vs. 10.42%, P = 0.5; percent time >250 mg/dL: 2.08% vs. 1.19%, P = 0.317). In addition, the number of hypoglycemia rescue treatments was reduced from 12 to 7 with the use of the system.

CONCLUSIONS

The study shows that the proposed IS-informed bolus calculator is safe and feasible in adults with T1D, appropriately reducing postprandial hypoglycemia following an exercise-induced IS increase.

InRange: Comparison of the Second-Generation Basal Insulin Analogues Glargine 300 U/mL and Degludec 100 U/mL in Persons with Type 1 Diabetes Using Continuous Glucose Monitoring-Study Design

INTRODUCTION

Suboptimal glycaemic control among people with type 1 diabetes (T1D) is known to lead to long-term micro- and macrovascular complications and, unfortunately, it is still prevalent even in the most affluent societies. Although glycated haemoglobin monitoring is considered to be the gold standard for assessing glycaemic control, such monitoring is unable to reliably measure acute glycaemic excursions. Continuous glucose monitoring (CGM) has been shown to improve glucose control and reduce the incidence of hypoglycaemia, and also allow a more complete assessment of overall glycaemic control and hyper- and hypoglycaemic excursions. The use of CGM has led to time-in-range, which is the time that a patient is within the glycaemic range of 70 to 180 mg/dL, to be adopted as a treatment target. To date, only limited data comparing the second-generation insulins glargine 300 U/mL (Gla-300) and degludec 100 U/mL (IDeg-100) in people with T1D are available, and there is no CGM literature on comparisons of the use of CGM results to assess primary, secondary and tertiary endpoints. The aim of the InRange study was to address this unmet need.

METHODS

InRange is a multicentre, randomised, active-controlled, parallel-group, 12-week, open-label, phase 4, comparative study. Adults with T1D will be randomised to receive once-daily Gla-300 or IDeg-100 by subcutaneous injection in the morning. Following an 8-week titration period, CGM data will be collected over 20 consecutive days.

PLANNED OUTCOMES

The primary objective is to demonstrate that Gla-300 is noninferior to IDeg-100 in terms of glycaemic control [time-in-range ≥ 70 to ≤ 180 mg/dL (≥ 3.9 to ≤ 10 mmol/L)] and variability, as assessed using CGM, in adults with T1D. The results are expected to help confirm the utility of CGM in clinical practice in this population and provide insight into its application as an outcome measure in clinical practice.

TRIAL REGISTRATION

NCT04075513.

Therapeutic Inertia in Pediatric Diabetes: Challenges to and Strategies for Overcoming Acceptance of the Status Quo

Despite significant advances in therapies for pediatric type 1 diabetes, achievement of glycemic targets remains elusive, and management remains burdensome for patients and their families. This article identifies common challenges in diabetes management at the patient-provider and health care system levels and proposes practical approaches to overcoming therapeutic inertia to enhance health outcomes for youth with type 1 diabetes.