Improving the clinical value and utility of CGM systems: issues and recommendations : A joint statement of the European Association for the Study of Diabetes and the American Diabetes Association Diabetes Technology Working Group

Metabolic effect of adrenaline infusion in people with type 1 diabetes and healthy individuals

AIMS/HYPOTHESIS

As a result of early loss of the glucagon response, adrenaline is the primary counter-regulatory hormone in type 1 diabetes. Diminished adrenaline responses to hypoglycaemia due to counter-regulatory failure are common in type 1 diabetes, and are probably induced by exposure to recurrent hypoglycaemia, however, the metabolic effects of adrenaline have received less research attention, and also there is conflicting evidence regarding adrenaline sensitivity in type 1 diabetes. Thus, we aimed to investigate the metabolic response to adrenaline and explore whether it is modified by prior exposure to hypoglycaemia.

METHODS

Eighteen participants with type 1 diabetes and nine healthy participants underwent a three-step ascending adrenaline infusion during a hyperinsulinaemic-euglycaemic clamp. Continuous glucose monitoring data obtained during the week before the study day were used to assess the extent of hypoglycaemia exposure.

RESULTS

While glucose responses during the clamp were similar between people with type 1 diabetes and healthy participants, plasma concentrations of NEFAs and glycerol only increased in the group with type 1 diabetes (p<0.001). Metabolomics revealed an increase in the most common NEFAs (p<0.01). Other metabolic responses were generally similar between participants with type 1 diabetes and healthy participants. Exposure to hypoglycaemia was negatively associated with the NEFA response; however, this was not statistically significant.

CONCLUSIONS/INTERPRETATION

In conclusion, individuals with type 1 diabetes respond with increased lipolysis to adrenaline compared with healthy participants by mobilising the abundant NEFAs in plasma, whereas other metabolic responses were similar. This may suggest that the metabolic sensitivity to adrenaline is altered in a pathway-specific manner in type 1 diabetes.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05095259.

Ultra rapid lispro improves postprandial glucose control versus lispro in combination with basal insulin: a study based on CGM in type 2 diabetes in China

Aim

To evaluate the efficacy and safety of URLi (ultra rapid lispro insulin) compared to insulin lispro as bolus insulin with basal insulin using CGM in the individuals with type 2 diabetes(T2D) in China.

Methods

This was a double-blind, randomized, parallel, prospective, phase 3 study. Subjects with uncontrolled T2D were recruited and randomized 1:2 into the insulin lispro and URLi groups. Subjects received a consistent basal insulin regimen during the study and self-administered insulin lispro or URLi before each meal throughout the treatment period. Subjects underwent a 3-day continuous glucose monitoring (CGM) at the baseline and endpoint respectively, and then CGM data were analyzed. The primary endpoint was to compare the difference in postprandial glucose (PPG) control using CGM between the two groups.

Results

A total of 57 subjects with T2D completed the study. Our CGM data showed that postprandial glucose excursions after breakfast (BPPGE) in the URLi group was lower than that in the insulin lispro group (1.59 ± 1.57 mmol/L vs 2.51 ± 1.73 mmol/L, p = 0.046). 1-hour PPG was observed to decrease more in the URLi group than that in the insulin lispro group (-1.37 ± 3.28 mmol/L vs 0.24 ± 2.58 mmol/L, p = 0.047). 2-hour PPG was observed to decrease more in the URLi group than that in the insulin lispro group (-1.12 ± 4.00 mmol/L vs 1.22 ± 2.90 mmol/L, p = 0.021). The mean HbA1c level decreased by 1.1% in the URLi group and 0.99% in the insulin lispro group, with no treatment difference (p = 0.642). In the CGM profile, TBR was not significantly different between the two groups (p = 0.743). The weight gain also did not differ between the two groups (p = 0.303).

Conclusion

URLi can control breakfast PPG better than insulin lispro in adults with T2D in China, while it is non-inferior in improving HbA1c. The incidence of hypoglycemic and weight gain were similar between the two groups.

Continuous Glucose Monitoring Systems in Noninsulin-Treated People with Type 2 Diabetes: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Introduction: Continuous glucose monitoring (CGM) has shown favorable outcomes in patients with type 2 diabetes (T2D) who are on insulin therapy. However, the efficacy of CGM in managing glucose levels in noninsulin-treated people with T2D remains controversial. Methods: PubMed, Cochrane, and Embase were searched for randomized controlled trials (RCTs) comparing CGM to self-monitoring of blood glucose (SMBG) in people with T2D not using insulin. We computed weighted mean differences (WMDs) and standard mean differences (SMD) for continuous outcomes, with 95% confidence intervals (CIs). Heterogeneity was assessed using I2 statistics. Statistical analyses were performed using R version 4.2.3. Results: We included six RCTs comprising 407 noninsulin-treated people with T2D of whom 228 were randomized to CGM. Diabetes duration ranged from 5.4 to 13.9 years. The mean age was 57.9 years and the mean body mass index was 30.8 kg/m2. Four trials used real-time CGM (rt-CGM) and two intermittent scanning CGM (is-CGM). Compared with SMBG, CGM significantly reduced the glycated hemoglobin level (WMD -0.31%; 95% CI -0.42 to -0.21; I2 = 0%), glucose level (WMD -11.16 mg/dL; 95% CI -19.94 to -2.39; I2 = 0%), time in hypoglycemia level 2 (WMD -0.28%; 95% CI -0.52 to -0.03; I2 = 91%), glucose time >180 mg/dL (WMD -7.75%; 95% CI -12.04 to -3.45; I2 = 0%), and the standard deviation of glucose variation (WMD -4.00 mg/dL; 95% CI -6.86 to -1.14; I2 = 0%). CGM also increased time in range (WMD 8.63%; 95% CI 4.54-12.71; I2 = 0%) and treatment satisfaction (SMD 0.79; 95% CI 0.54-1.05; I2 = 0%). Conclusion: In this meta-analysis, rt-CGM and is-CGM were associated with improvement in glycemic control in people with T2D not using insulin when compared to SMBG.

Continuous glucose monitoring metrics in pregnancy with type 1 diabetes mellitus

Managing diabetes during pregnancy is challenging, given the significant risk it poses for both maternal and foetal health outcomes. While traditional methods involve capillary self-monitoring of blood glucose level monitoring and periodic HbA1c tests, the advent of continuous glucose monitoring (CGM) systems has revolutionized the approach. These devices offer a safe and reliable means of tracking glucose levels in real-time, benefiting both women with diabetes during pregnancy and the healthcare providers. Moreover, CGM systems have shown a low rate of side effects and high feasibility when used in pregnancies complicated by diabetes, especially when paired with continuous subcutaneous insulin infusion pump as hybrid closed loop device. Such a combined approach has been demonstrated to improve overall blood sugar control, lessen the occurrence of preeclampsia and neonatal hypoglycaemia, and minimize the duration of neonatal intensive care unit stays. This paper aims to offer a comprehensive evaluation of CGM metrics specifically tailored for pregnancies impacted by type 1 diabetes mellitus.

Glycemic outcomes and patient satisfaction and self-management improves in transition from standard to virtual multidisciplinary care

AIMS

With advances in cloud-based technologies, there has been a rise in remote T1D care. We hypothesized that transitioning T1DM care to a virtual, multidisciplinary clinic could improve measures beyond HbA1c.

METHODS

To assess the impact of transitioning from standard to virtual T1DM care, we evaluated glycemic measures and patient reported outcomes.

RESULTS

Sixty-one adults with T1DM were included, with mean age 40.2 ± 13.5 years and diabetes duration 16.9 ± 9.0 years. Most patients were treated with insulin pumps and CGM. The number of annual diabetes care encounters rose from 2.1 ± 4.2 to 12.8 ± 5.5. Baseline HbA1c was 7.9 ± 1.6 %(63 ± 16.9 mmol/mol), declining to 7.3 ± 1.1 %(56 ± 8.5 mmol/mol) and 7.1 ± 1.0 %(54 ± 7.7 mmol/mol) at 6 and 12 months respectively (p < 0.001 for both). In parallel, TIR improved from 63.1 ± 19.3 % to 69.2 ± 13.8 % (p < 0.001) and 67.5 ± 19.4 % (p = 0.03) at 6 and 12 months respectively, while TBR declined. Scores from validated diabetes treatment and self-management questionnaires rose significantly and these rises were associated with a reduction in HbA1c, the latter score was also associated with increased TIR. There was a trend toward a correlation between encounter frequency and improvement in HbA1c and TIR.

CONCLUSIONS

Transitioning from standard to virtual, coordinated, multidisciplinary T1DM care is associated with increased visit frequency, improving glycemic control, treatment satisfaction and self-care behaviors.

Continuous glucose monitoring in older adults with diabetes: Data from the diabetes prospective follow-up (DPV) registry

AIMS

To analyse predictors for continuous glucose monitoring (CGM) use in people with diabetes aged ≥60 years using insulin therapy and to assess the rates of CGM use during recent years (2019-2021).

RESEARCH DESIGN AND METHODS

Prospective study including 6849 individuals with diabetes and insulin therapy (type 2 diabetes: n = 5320; type 1 diabetes: n = 1529) aged ≥60 years. Data from 129 treatment centres were retrieved from the Diabetes Prospective Follow-up Registry (DPV) in March 2023.

RESULTS

Sensor use in individuals aged ≥60 years has increased in type 1 (2019: 28%, 2020: 39%, 2021: 45%) and type 2 diabetes (2019: 10%, 2020: 16%, 2021: 18%). Predictors for sensor use in older individuals with type 1 diabetes are younger age and CSII use (p < 0.001). Predictors in older individuals with type 2 diabetes are younger age, longer diabetes duration, higher BMI and CSII use (p < 0.001).

CONCLUSIONS

CGM has become more common in older adults with diabetes and will presumably increase further. Age is a predictor for sensor use in older adults with diabetes. Age-related physical barriers and insufficient usability of devices, lack of interest in technologies, but possibly also effects of prejudice on the grounds of age may contribute to this finding.

The Evolution of Diabetes Technology - Options Towards Personalized Care

Advances in diabetes technology, especially in the last few decades, have transformed our ability to deliver care to persons with diabetes (PWD). Developments in glucose monitoring, especially continuous glucose monitoring systems (CGM), have revolutionized diabetes care and empowered our patients to manage their disease. CGM has also played an integral role in advancing automated insulin delivery systems. Currently available and upcoming advanced hybrid-closed loop systems aim to decrease patient involvement and are approaching the functionality of a fully automated artificial pancreas. Other advances, such as smart insulin pens and daily patch pumps, offer more options for patients and require less complicated and costly technology. Evidence to support the role of diabetes technology is growing, and PWD and clinicians must choose the right type of technology with a personalized strategy to manage diabetes effectively. Here, we review currently available diabetes technologies, summarize their individual features and highlight key patient factors to consider when creating a personalized treatment plan. We also address current challenges and barriers to the adoption of diabetes technologies.

Automated insulin delivery: benefits, challenges, and recommendations. A Consensus Report of the Joint Diabetes Technology Working Group of the European Association for the Study of Diabetes and the American Diabetes Association

A technological solution for the management of diabetes in people who require intensive insulin therapy has been sought for decades. The last 10 years have seen substantial growth in devices that can be integrated into clinical care. Driven by the availability of reliable systems for continuous glucose monitoring, we have entered an era in which insulin delivery through insulin pumps can be modulated based on sensor glucose data. Over the past few years, regulatory approval of the first automated insulin delivery (AID) systems has been granted, and these systems have been adopted into clinical care. Additionally, a community of people living with type 1 diabetes has created its own systems using a do-it-yourself approach by using products commercialised for independent use. With several AID systems in development, some of which are anticipated to be granted regulatory approval in the near future, the joint Diabetes Technology Working Group of the European Association for the Study of Diabetes and the American Diabetes Association has created this consensus report. We provide a review of the current landscape of AID systems, with a particular focus on their safety. We conclude with a series of recommended targeted actions. This is the fourth in a series of reports issued by this working group. The working group was jointly commissioned by the executives of both organisations to write the first statement on insulin pumps, which was published in 2015. The original authoring group was comprised by three nominated members of the American Diabetes Association and three nominated members of the European Association for the Study of Diabetes. Additional authors have been added to the group to increase diversity and range of expertise. Each organisation has provided a similar internal review process for each manuscript prior to submission for editorial review by the two journals. Harmonisation of editorial and substantial modifications has occurred at both levels. The members of the group have selected the subject of each statement and submitted the selection to both organisations for confirmation.

Continuous glucose monitoring and metrics for clinical trials: an international consensus statement

Randomised controlled trials and other prospective clinical studies for novel medical interventions in people with diabetes have traditionally reported HbA1c as the measure of average blood glucose levels for the 3 months preceding the HbA1c test date. The use of this measure highlights the long-established correlation between HbA1c and relative risk of diabetes complications; the change in the measure, before and after the therapeutic intervention, is used by regulators for the approval of medications for diabetes. However, with the increasing use of continuous glucose monitoring (CGM) in clinical practice, prospective clinical studies are also increasingly using CGM devices to collect data and evaluate glucose profiles among study participants, complementing HbA1c findings, and further assess the effects of therapeutic interventions on HbA1c. Data is collected by CGM devices at 1-5 min intervals, which obtains data on glycaemic excursions and periods of asymptomatic hypoglycaemia or hyperglycaemia (ie, details of glycaemic control that are not provided by HbA1c concentrations alone that are measured continuously and can be analysed in daily, weekly, or monthly timeframes). These CGM-derived metrics are the subject of standardised, internationally agreed reporting formats and should, therefore, be considered for use in all clinical studies in diabetes. The purpose of this consensus statement is to recommend the ways CGM data might be used in prospective clinical studies, either as a specified study endpoint or as supportive complementary glucose metrics, to provide clinical information that can be considered by investigators, regulators, companies, clinicians, and individuals with diabetes who are stakeholders in trial outcomes. In this consensus statement, we provide recommendations on how to optimise CGM-derived glucose data collection in clinical studies, including the specific glucose metrics and specific glucose metrics that should be evaluated. These recommendations have been endorsed by the American Association of Clinical Endocrinologists, the American Diabetes Association, the Association of Diabetes Care and Education Specialists, DiabetesIndia, the European Association for the Study of Diabetes, the International Society for Pediatric and Adolescent Diabetes, the Japanese Diabetes Society, and the Juvenile Diabetes Research Foundation. A standardised approach to CGM data collection and reporting in clinical trials will encourage the use of these metrics and enhance the interpretability of CGM data, which could provide useful information other than HbA1c for informing therapeutic and treatment decisions, particularly related to hypoglycaemia, postprandial hyperglycaemia, and glucose variability.

Making sense of glucose sensors in end-stage kidney disease: A review

Diabetes mellitus remains the leading cause of end-stage kidney disease worldwide. Inadequate glucose monitoring has been identified as one of the gaps in care for hemodialysis patients with diabetes, and lack of reliable methods to assess glycemia has contributed to uncertainty regarding the benefit of glycemic control in these individuals. Hemoglobin A1c, the standard metric to evaluate glycemic control, is inaccurate in patients with kidney failure, and does not capture the full range of glucose values for patients with diabetes. Recent advances in continuous glucose monitoring have established this technology as the new gold standard for glucose management in diabetes. Glucose fluctuations are uniquely challenging in patients dependent on intermittent hemodialysis, and lead to clinically significant glycemic variability. This review evaluates continuous glucose monitoring technology, its validity in the setting of kidney failure, and interpretation of glucose monitoring results for the nephrologist. Continuous glucose monitoring targets for patients on dialysis have yet to be established. While continuous glucose monitoring provides a more complete picture of the glycemic profile than hemoglobin A1c and can mitigate high-risk hypoglycemia and hyperglycemia in the context of the hemodialysis procedure itself, whether the technology can improve clinical outcomes merits further investigation.

Dynamic circadian fluctuations of glycemia in patients with type 2 diabetes mellitus

BACKGROUND

Diabetes mellitus (DM) has glucose variability that is of such relevance that the appearance of vascular complications in patients with DM has been attributed to hyperglycemic and dysglycemic events. It is known that T1D patients mainly have glycemic variability with a specific oscillatory pattern with specific circadian characteristics for each patient. However, it has not yet been determined whether an oscillation pattern represents the variability of glycemic in T2D. This is why our objective is to determine the characteristics of glycemic oscillations in T2D and generate a robust predictive model.

RESULTS

Showed that glycosylated hemoglobin, glycemia, and body mass index were all higher in patients with T2D than in controls (all p < 0.05). In addition, time in hyperglycemia and euglycemia was markedly higher and lower in the T2D group (p < 0.05), without significant differences for time in hypoglycemia. Standard deviation, coefficient of variation, and total power of glycemia were significantly higher in the T2D group than Control group (all p < 0.05). The oscillatory patterns were significantly different between groups (p = 0.032): the control group was mainly distributed at 2-3 and 6 days, whereas the T2D group showed a more homogeneous distribution across 2-3-to-6 days.

CONCLUSIONS

The predictive model of glycemia showed that it is possible to accurately predict hyper- and hypoglycemia events. Thus, T2D patients exhibit specific oscillatory patterns of glycemic control, which are possible to predict. These findings may help to improve the treatment of DM by considering the individual oscillatory patterns of patients.

Recent developments in adjunct therapies for type 1 diabetes

INTRODUCTION

There have been many recent advances in the treatment of type 1 diabetes (T1D) including in insulin formulations, continuous glucose monitoring (CGM) technology and automated insulin delivery. However, long-term optimal glycemic control is still only achieved in a minority.

AREAS COVERED

Adjunct therapy - the use of therapeutic agents other than insulin - is one strategy aimed at improving outcomes. An ideal adjunct agent would improve glycemic control, reduce weight (or weight gain), reduce insulin requirement and prevent complications (e.g. cardiorenal) without increasing hypoglycemia. The amylin analogue pramlintide has been licensed in the USA, while the sodium glucose co-transporter-2 inhibitor (SGLT2i) dapagliflozin, was briefly (2019 - 2021) licensed for type 1 diabetes in Europe and the UK. However, other agents from the type 2 diabetes (T2D) arena including metformin, other SGLT2is, glucagon-like peptide-1 receptor agonists (GLP-1RA) and dipeptidyl peptidase-IV (DPP-4) inhibitors have been investigated.

EXPERT OPINION

As evidence emerges for cardiorenal protection by SGLT2is and GLP-1RAs in T2D, it has become increasingly important to know whether people with T1D can also benefit. Here, we review recent trials of adjunct agents in T1D and discuss the efficacy and safety of these agents (alone and in combination) in an era in which continuous glucose monitoring is becoming standard of care.

Adverse Event Data for Years 2018 to 2020 for Diabetes Devices

Unlike performance evaluations, which are often conducted under ideal conditions, adverse events occur during actual device use for people with diabetes. This report summarizes the number of adverse events for the years 2018 to 2020 for the 3 diabetes devices: blood glucose meters (BG), continuous glucose monitors (CGM), and insulin pumps. A text example of a CGM injury is provided. Possible reasons are suggested for trends. Whereas the rate per test result (events/usage) is exceedingly small, the rate per patient (events/people with diabetes that use insulin) is of concern. Hence, it is important to determine event causes and provide corrective actions. The first step is to put in place routine analysis of adverse event data for diabetes devices.

Hollow Microneedles on a Paper Fabricated by Standard Photolithography for the Screening Test of Prediabetes

Microneedle (MN) is a novel technique of the biomedical engineering field because of its ability to evaluate bioinformation via minimal invasion. One of the urgent requirements for ground-breaking health care monitoring is persistent monitoring. Hollow microneedles are extremely attractive to extract skin interstitial fluid (ISF) for analysis, which makes them perfect for sensing biomarkers and facilitating diagnosis. Nevertheless, its intricate fabrication process has hampered its extensive application. The present research demonstrates an easy one-step preparation approach for hollow MNs on the foundation of the refraction index variations of polyethylene glycol diacrylate (PEGDA) in the process of photopolymerization. The fabricated hollow microneedle exhibited ideal mechanical characteristics to penetrate the skin. Hydrodynamic simulations showed that the liquid was risen in a hollow microneedle by capillary force. Furthermore, a paper-based glucose sensor was integrated with the hollow microneedle. We also observed that the MN array smoothly extracted ISF in vitro and in vivo by capillary action. The outcomes displayed the applicability of the MN patch to persistent blood glucose (GLU) monitoring, diagnosis-related tests for patients and pre-diabetic individuals.

Acetylated Trifluoromethyl Diboronic Acid Anthracene with a Large Stokes Shift and Long Excitation Wavelength as a Glucose-Selective Probe

Continuous control of blood glucose levels is important for the effective treatment of diabetes. The short-term use of enzymatic continuous monitoring systems involves expensive maintenance and is inconvenient, which limits their widespread use by diabetes patients. The fluorescent diboronic anthracene-embedded system has demonstrated in vivo continuous glucose monitoring for 12 times longer than enzymatic systems by protecting the dye from reactive oxygen species. However, its small Stokes shift and low excitation and emission wavelength should be heavily considered for easy fabrication. We successfully synthesized a derivative of bis-phenyl boronate with a large Stokes shift and long excitation wavelength by adding an acetyl moiety to the anthracene ring. This resulted in a ~90-nm Stokes shift and 15-nm and 80-nm redshifts of the excitation and emission wavelengths, respectively. The fluorescence of the synthesized probe increased proportionally with the glucose concentration because the formation of the boronic acid-glucose complex prevented photoinduced electron transfer. The association constant and quantum yield for acetyl-substituted diboronic anthracene with glucose was 20% and 13% higher than that of the analog, respectively. While keeping resistance to the oxidation by reactive oxygen species, the improved optical properties and glucose-detecting performances of the newly synthesized dye will allow better pairing of the source and detecting unit for in vivo continuous glucose monitoring, leading to easy fabrication and then contributing more to utilization by diabetes patients.

Adherence to Mediterranean Diet Is Associated With Better Glycemic Control in Children With Type 1 Diabetes: A Cross-Sectional Study

Type 1 diabetes (T1D) is a chronic condition, with increased morbidity and mortality, due to a higher rate of cardiovascular disease among other factors. Cardiovascular risk increases with the worse glycemic profile. Nutrition has a deep impact on diabetes control. Adherence to the Mediterranean diet (MD) has been shown to decrease cardiovascular risk in children and adults with obesity and adults with type 2 diabetes, but its impact on T1D children has been scarcely analyzed. We hypothesized that the degree of adherence to MD could relate to the increased time in range in children with T1D.

Patients and Methods

Cross-sectional analysis involving two university hospitals. We measured the adherence to MD with the Mediterranean Diet Quality Index for children and teenagers (KIDMED) questionnaire, which is a validated tool for this purpose. A score of &lt;5 indicates poor adherence to MD, while a good adherence is indicated by a score of &gt;7. Demographic and clinical data were registered on the same day that the questionnaire was taken, with informed consent. Additionally, the patients' ambulatory glucose profiles (AGPs), were registered from the participants' glucose monitors (continuous or flash devices), and daily insulin needs were recorded from patients' insulin pumps (n=28). Other cardiovascular risk factors such as lipid profile, vitamin D levels, and other biochemical parameters were registered from a blood test, performed 2 weeks before recruitment, as part of the patients' annual screening.

Results

Ninety-seven patients (44 girls), with an average age of 11.4 years (± 3.01), were included. Seventy-one of them were on multiple daily injection regimens, and all had either continuous or flash glucose monitoring. Fifty-three had HbA1c levels of &lt;7.5%, while only 21 had a time in range (TIR) of &gt;70%. Contingency analysis showed that the odds of having HbA1c &lt;7.5% increase in children with KIDMED score of &gt;7 (O.R. 2.38; ICR 1.05–5.41; p = 0.036). Moreover, the KIDMED score and the HbA1c levels were negatively correlated (R: −0.245; p-value: 0.001), while the KIDMED score and TIR showed a positive correlation (R: 0.200; p-value: 0.009).

Conclusions

Our data suggest that adherence to MD may contribute to better glycemic control in children. This should be taken into account at the time of nutritional education on T1D patients and their families.

Towards the Integration of an Islet-Based Biosensor in Closed-Loop Therapies for Patients With Type 1 Diabetes

In diabetes mellitus (DM) treatment, Continuous Glucose Monitoring (CGM) linked with insulin delivery becomes the main strategy to improve therapeutic outcomes and quality of patients' lives. However, Blood Glucose (BG) regulation with CGM is still hampered by limitations of algorithms and glucose sensors. Regarding sensor technology, current electrochemical glucose sensors do not capture the full spectrum of other physiological signals, i.e., lipids, amino acids or hormones, relaying the general body status. Regarding algorithms, variability between and within patients remains the main challenge for optimal BG regulation in closed-loop therapies. This work highlights the simulation benefits to test new sensing and control paradigms which address the previous shortcomings for Type 1 Diabetes (T1D) closed-loop therapies. The UVA/Padova T1DM Simulator is the core element here, which is a computer model of the human metabolic system based on glucose-insulin dynamics in T1D patients. That simulator is approved by the US Food and Drug Administration (FDA) as an alternative for pre-clinical testing of new devices and closed-loop algorithms. To overcome the limitation of standard glucose sensors, the concept of an islet-based biosensor, which could integrate multiple physiological signals through electrical activity measurement, is assessed here in a closed-loop insulin therapy. This investigation has been addressed by an interdisciplinary consortium, from endocrinology to biology, electrophysiology, bio-electronics and control theory. In parallel to the development of an islet-based closed-loop, it also investigates the benefits of robust control theory against the natural variability within a patient population. Using 4 meal scenarios, numerous simulation campaigns were conducted. The analysis of their results then introduces a discussion on the potential benefits of an Artificial Pancreas (AP) system associating the islet-based biosensor with robust algorithms.

Continuous glucose monitoring devices: A brief presentation (Review)

As diabetes prevalence is continuously increasing, better management is needed to achieve blood glucose control, in order to prevent complications and lessen the burden of this disease. Since the first measurement of glycosuria at the beginning of the 1900s', huge advances were made in monitoring glycemia. Continuous glucose monitoring systems revolutionized diabetes management, especially for patients with type 1 diabetes. Avoiding glycemic variability and maintaining optimal glycemic control is crucial for the evolution of patients with type 1 diabetes. The usefulness of glycemic monitoring devices can be extended to patients with type 2 diabetes. It is also important to note that in those patients at risk of developing high glycemic variability (e.g. patients with advanced chronic kidney disease), continuous glycemic monitoring may improve their prognosis. These monitoring systems can be classified according to the analytical method, the degree of invasiveness, the data availability and the mode of usage. The technology is constantly improving in bioanalytical performance, biocompatibility, length of wearing time, safety and clinical features. The aim of this review was to briefly present the main characteristics of glucose biosensors, glucose monitoring systems and their clinically utility.

Continuous Glucose Monitoring for the Internist

Continuous glucose monitoring system is a convenient wearable device that provides glucose readings from the interstitial fluid every few minutes. Continuous glucose monitoring has revolutionized diabetes care. Patients with type 1 diabetes mellitus and type 2 diabetes mellitus, regardless of the type of treatment regimen, can benefit from continuous glucose monitoring. Continuous glucose monitoring systems provide patients with diabetes and their providers with an ambulatory glucose report that summarizes and also gives graphical representations of the glucose data. This wealth of information helps to better understand patients' glycemic patterns, and thereby reduces hemoglobin A_1c and hypoglycemia.

Early Glycemic Control Assessment Based on Consensus CGM Metrics. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021;2021:1269-1275. [PMID: 34891517 DOI: 10.1109/embc46164.2021.9631015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Continuous glucose monitoring (CGM) has revolutionized the world of diabetes and transformed the approach to diabetes care. In this context, an expert panel has reached consensus on clinical targets for CGM data interpretation based on eight CGM metrics. At least 70% of 14 consecutive CGM days (referred to as a period) are recommended to assess glycemic control based on the metrics. In clinical practice less CGM data may be available. Therefore, the primary aim of this study is to explore the ability to recover the consensus metrics utilizing less than 14 days of CGM data (intra-period). As a secondary aim, we investigate the recovery considering two consecutive periods (inter-period). The analyses are based on real-world CGM data from 484 diabetes users (4726 periods) acquired from the Cornerstones4Care® Powered by Glooko app. Using up to 14 accumulated days, the consensus metrics are calculated for each user and period, and compared to the fully 14 accumulated intra- and inter-period days. Relatively low deviations were observed for time in range (TIR) and average based metrics when using less than 14 days, however, we observed large deviations in metrics characterizing infrequent events such as time below range (TBR). Furthermore, the consensus metrics obtained in two consecutive 14 day periods have clear discrepancies (inter-period). Recovering consensus metrics using less than 14 days might still be valuable in terms of interpreting CGM data in certain clinical contexts. However, caution should be taken if treatment decisions would be made with less than 14 days of data on critical metrics such as TBR, since the metrics characterizing infrequent events deviate substantially when less data are available. Substantial deviation is also seen when comparing across two consecutive periods, which means that care should be taken not to over-generalize consensus metric based glycemic control conclusions from one period to subsequent periods.

Integrating an Islet-Based Biosensor in the Artificial Pancreas: In Silico Proof-of-Concept

OBJECTIVE

Current treatment of type 1 diabetes by closed-loop approaches depends on continuous glucose monitoring. However, glucose readings alone are insufficient for an artificial pancreas to truthfully restore glucose homeostasis where additional physiological regulators of insulin secretion play a considerable role. Previously, we have developed an electrophysiological biosensor of pancreatic islet activity, which integrates these additional regulators through electrical measurement. This work aims at investigating the performance of the biosensor in a blood glucose control loop, to establish an in silico proof-of-concept.

METHODS

Two islet algorithm models were identified on experimental data recorded with the biosensor. First, we validated electrical measurement as a means to exploit the inner regulation capabilities of islets for intravenous glucose measurement and insulin infusion. Then, an artificial pancreas integrating the islet-based biosensor was compared to standard treatment approaches using subcutaneous routes. The closed-loop simulations were performed in the UVA/Padova T1DM Simulator where a series of realistic meal scenarios were applied to virtual diabetic patients.

RESULTS

With intravenous routes, the endogenous islet algorithms successfully restored glucose homeostasis for all patient categories (mean time in range exceeds 90%) while mitigating the risk of adverse glycaemic events (mean BGI < 2). Using subcutaneous routes, the biosensor-based artificial pancreas was as performing as standard treatments, and outperformed them under challenging conditions.

CONCLUSION

This work validates the concept of using pancreatic islets algorithms in an artificial pancreas in silico.

SIGNIFICANCE

Pancreatic islet endogenous algorithms obtained via an electrophysiological biosensor successfully regulate blood glucose levels of virtual type 1 diabetic patients.

Improvement in Glucose Regulation Using a Digital Tracker and Continuous Glucose Monitoring in Healthy Adults and Those with Type 2 Diabetes

INTRODUCTION

While continuous glucose monitoring (CGM) has been shown to decrease both hyper- and hypoglycemia in insulin-treated diabetes, its value in non-insulin-treated type 2 diabetes (T2D) and prediabetes is unclear. Studies examining the reduction in hyperglycemia with the use of CGM in non-insulin-treated T2D are limited.

METHODS

We investigated the potential benefit of CGM combined with a mobile app that links each individual's glucose tracing to meal composition, heart rate, and physical activity in a cohort of 1022 individuals, ranging from nondiabetic to non-insulin-treated T2D, spanning a wide range of demographic, geographic, and socioeconomic characteristics. The primary endpoint was the change in time in range (TIR), defined as 54-140 mg/dL for healthy and prediabetes, and 54-180 mg/dL for T2D, from the beginning to end of a 10-day period of use of the Freestyle Libre CGM. Logged food intake, physical activity, continuous glucose, and heart rate data were captured by a smartphone-based app that continuously provided feedback to participants, overlaying daily glucose patterns with activity and food intake, including macronutrient breakdown, glycemic load (GL), and glycemic index (GI).

RESULTS

A total of 665 participants meeting eligibility and data requirements were included in the final analysis. Among self-reported nondiabetic participants, CGM identified glucose excursions in the diabetic range among 15% of healthy and 36% of those with prediabetes. In the group as a whole, TIR improved significantly (p < 0.001). Among the 51.4% of participants who improved, TIR increased by an average of 6.4% (p < 0.001). Of those with poor baseline TIR, defined as TIR below comparable A1c thresholds for T2D and prediabetes, 58.3% of T2D and 91.7% of healthy/prediabetes participants improved their TIR by an average of 22.7% and 23.2%, respectively. Predictors of improved response included no prior diagnosis of T2D and lower BMI.

CONCLUSIONS

These results indicate that 10-day use of CGM as a part of multimodal data collection, with synthesis and feedback to participants provided by a mobile health app, can significantly reduce hyperglycemia in non-insulin-treated individuals, including those with early stages of glucose dysregulation.

Important Drop in Rate of Acute Diabetes Complications in People With Type 1 or Type 2 Diabetes After Initiation of Flash Glucose Monitoring in France: The RELIEF Study

OBJECTIVE

The RELIEF study assessed rates of hospitalization for acute diabetes complications in France before and after initiation of the FreeStyle Libre system.

RESEARCH DESIGN AND METHODS

A total of 74,011 patients with type 1 diabetes or type 2 diabetes who initiated the FreeStyle Libre system were identified from the French national claims database with use of ICD-10 codes, from hospitalizations with diabetes as a contributing diagnosis, or the prescription of insulin. Patients were subclassified based on self-monitoring of blood glucose (SMBG) strip acquisition prior to starting FreeStyle Libre. Hospitalizations for diabetic ketoacidosis (DKA), severe hypoglycemia, diabetes-related coma, and hyperglycemia were recorded for the 12 months before and after initiation.

RESULTS

Hospitalizations for acute diabetes complications fell in type 1 diabetes (-49.0%) and in type 2 diabetes (-39.4%) following FreeStyle Libre initiation. DKA fell in type 1 diabetes (-56.2%) and in type 2 diabetes (-52.1%), as did diabetes-related comas in type 1 diabetes (-39.6%) and in type 2 diabetes (-31.9%). Hospitalizations for hypoglycemia and hyperglycemia decreased in type 2 diabetes (-10.8% and -26.5%, respectively). Before initiation, hospitalizations were most marked for people noncompliant with SMBG and for those with highest acquisition of SMBG, which fell by 54.0% and 51.2%, respectively, following FreeStyle Libre initiation. Persistence with FreeStyle Libre at 12 months was at 98.1%.

CONCLUSIONS

This large retrospective study on hospitalizations for acute diabetes complications shows that a significantly lower incidence of admissions for DKA and for diabetes-related coma is associated with use of flash glucose monitoring. This study has significant implications for patient-centered diabetes care and potentially for long-term health economic outcomes.

Impact of blinded retrospective continuous glucose monitoring on clinical decision making and glycemic control in persons with type 2 diabetes on insulin therapy

BACKGROUND AND AIMS

Blinded retrospective continuous glucose monitoring (rCGM) provides detailed information about real-life glycaemic profile. In persons with type 2 diabetes without adequate glycaemic control, the structured introduction of rCGM may be beneficial to sustain improvements in diabetes management.

METHODS AND RESULTS

102 individuals with insulin-treated type 2 diabetes, age less than 66 years old and HbA1c >7.5%, were recruited. Participants performed a 7-day blinded rCGM (iPro2) every four months for one year. Biochemical, anthropometric, and rCGM data was collected. Participants' and healthcare professionals' perceptions were assessed. 90 participants completed the protocol. HbA1c was 9.1 ± 0.1% one year prior to enrolment and 9.4 ± 0.1% at enrolment (p < 0.01). With the rCGM-based intervention, a decrease in HbA1c was achieved at 4 months (8.4 ± 0.1%, p < 0.0001), and 12 months (8.1 ± 0.1%, p < 0.0001). A significant increase in time-in-range was observed (50.8 ± 2.4 at baseline vs 61.5 ± 2.2% at 12 months, for 70-180 mg/dL, p < 0.001), with no difference in exposure time to hypoglycaemia. After 12 months, there was an increase in self-reported diabetes treatment satisfaction (p < 0.05).

CONCLUSION

In persons with type 2 diabetes and poor metabolic control, specific data from blinded rCGM informed therapeutic changes and referral to targeted education consultations on nutrition and insulin administration technique. Therapeutic changes were made more frequently and targeted to changes in medication dose, timing, and/or type, as well as to lifestyle. Together, these brought significant improvements in clinical outcomes, effective shared decision-making, and satisfaction with treatment.

REGISTRATION NUMBER

NCT04141111.

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.

Improved Estimation of Glycated Hemoglobin from Continuous Glucose Monitoring and Past Glycated Hemoglobin Data

Background: Accurate estimation of glycated hemoglobin (HbA1c) from continuous glucose monitoring (CGM) remains challenging in clinic. We propose two statistical models and validate them in real-life conditions against the current standard, glucose management indicator (GMI). Materials and Methods: Modeling utilized routinely collected data from patients with type 1 diabetes from central Poland (eligibility criteria: age >1 year, diabetes duration >3 months, and CGM use between 01/01/2015 and 12/31/2019). CGM records were extracted from dedicated Medtronic/Abbott databases and cross-referenced with HbA1c values; 28-day periods preceding HbA1c measurement with >75% of the sensor-active time were analyzed. We developed a mixed linear regression, including glycemic variability indices and patient's ID (glucose variability-based patient specific model, GV-PS) intended for closed-group use and linear regression using patient-specific error of GMI (proportional error-based patient agnostic model, PE-PA) for general use. Models were validated with either new HbA1cs from closed-group patients or separate patient-HbA1c pool. External validation was performed with data from clinical trials. Performance metrics included bias, its 95% confidence interval (95% CI), coefficient of determination (R²), and root mean square error (RMSE). Results: We included 723 HbA1c-CGM pairs from 174 patients (mean age 9.9 ± 4.4 years and diabetes duration 3.7 ± 3.6 years). GMI yielded R² = 0.58, with different bias between Medtronic and Abbott devices [0.120% vs. -0.152%, P < 0.0001], and overall 95% CI = -0.9% to +1%, RMSE = 0.47%. GV-PS successfully captured patient-specific variance (closed-group validation: R² = 0.83, bias = 0.026%, 95% CI = -0.562% to 0.591%, RMSE = 0.31%). PE-PA performed similarly on new patients (R² = 0.76, bias = -0.069%, 95% CI = -0.790% to 0.653%, RMSE = 0.37%). In external validation GMI, GV-PS, and PE-PA produced 73.8%, 87.5%, and 91.0% predictions within 0.5% (5.5 mmol/mol) from the true value. Conclusion: Constructed models performed better than GMI. PE-PA provided an accurate estimate of HbA1c with fast and straightforward implementation.

GLU: a software package for analysing continuously measured glucose levels in epidemiology

Continuous glucose monitors (CGM) record interstitial glucose levels 'continuously', producing a sequence of measurements for each participant (e.g. the average glucose level every 5 min over several days, both day and night). To analyse these data, researchers tend to derive summary variables such as the area under the curve (AUC), to then use in subsequent analyses. To date, a lack of consistency and transparency of precise definitions used for these summary variables has hindered interpretation, replication and comparison of results across studies. We present GLU, an open-source software package for deriving a consistent set of summary variables from CGM data. GLU performs quality control of each CGM sample (e.g. addressing missing data), derives a diverse set of summary variables (e.g. AUC and proportion of time spent in hypo-, normo- and hyper- glycaemic levels) covering six broad domains, and outputs these (with quality control information) to the user. GLU is implemented in R and is available on GitHub at https://github.com/MRCIEU/GLU. Git tag v0.2 corresponds to the version presented here.

Oscillatory pattern of glycemic control in patients with diabetes mellitus

Daily glucose variability is higher in diabetic mellitus (DM) patients which has been related to the severity of the disease. However, it is unclear whether glycemic variability displays a specific pattern oscillation or if it is completely random. Thus, to determine glycemic variability pattern, we measured and analyzed continuous glucose monitoring (CGM) data, in control subjects and patients with DM type-1 (T1D). CGM data was assessed for 6 days (day: 08:00-20:00-h; and night: 20:00-08:00-h). Participants (n = 172; age = 18-80 years) were assigned to T1D (n = 144, females = 65) and Control (i.e., healthy; n = 28, females = 22) groups. Anthropometry, pharmacologic treatments, glycosylated hemoglobin (HbA1c) and years of evolution were determined. T1D females displayed a higher glycemia at 10:00-14:00-h vs. T1D males and Control females. DM patients displays mainly stationary oscillations (deterministic), with circadian rhythm characteristics. The glycemia oscillated between 2 and 6 days. The predictive model of glycemia showed that it is possible to predict hyper and hypoglycemia (R² = 0.94 and 0.98, respectively) in DM patients independent of their etiology. Our data showed that glycemic variability had a specific oscillation pattern with circadian characteristics, with episodes of hypoglycemia and hyperglycemia at day phases, which could help therapeutic action for this population.

Digital Health Services among Patients with Diabetes during the COVID-19 Pandemic: A Scoping Review

BACKGROUND AND AIMS

COVID-19 pandemic causes massive disruption of the global health system. The diabetic patients are the vulnerable parts population who are predicted to have a significant issue during the pandemic regarding the conventional type of consultation by face-to-face which may result in the higher risk of COVID-19 exposure. This study aims to observe the use of digital health services for diabetes management during COVID-19 pandemic.

METHODS

A scoping review was conducted in PubMed, ScienceDirect, and Google Scholar during August until September 2020. The keywords that are used on the searching process are diabetes AND digital service OR telemedicine OR technology AND COVID-19. The criteria included the selection of scientific publication as an original research and reviews.

RESULTS

All published articles were gathered from 3 search engines; PubMed, Science Direct, and Google Scholar. The discussion explicates the practical considerations that are in accordance with the current condition of each country. In order to do so, the evidence is classified based on the level of global digital health framework in the developed and developing countries. It was found that the minimal level of digital health that connects diabetes patients with healthcare providers was at level 2, which is by using the video mode. The most advanced is at level 3B, which is applied by using the CGM devices, which provide active monitoring, diagnosis, and treatment based on timely clinical judgment.

CONCLUSION

It is feasible to utilize the digital health service during the COVID-19. This review is projected to be beneficial for the patient and health care providers to select the most feasible approach of digital health that merits the contextual resource.

Fasting Glucose of 6.1 mmol/L as a Possible Optimal Target for Type 2 Diabetic Patients with Insulin Glargine: A Randomized Clinical Trial

To observe whether different insulin glargine titration algorithms based on fasting blood glucose (FBG) levels lead to different glycaemic variations (GVs) in type 2 diabetes (T2D) patients, a prospective, randomized, single-centre, comparative, three-arm parallel-group, open-label, treat-to-target, 24-week study was performed. A total of 71 uncontrolled T2D patients were recruited and randomized 1 : 3 : 3 into Groups 1, 2, and 3 (insulin titration goals of FBG ≤ 5.6, ≤6.1, and ≤7.0) for this study. The initiated insulin glargine dose was recommended at 0.2 U/kg/day and was then titrated following the FBG target. Patients were subjected to two 3-day continuous glucose monitoring (CGM) at baseline and the endpoint, wherein the CGM data were analysed, and the study's primary endpoint was the difference in 24 hrs mean amplitude of glycaemic excursion (MAGE) among the three groups. We observed that patients in the three groups had similar MAGE levels at the endpoint; however, Group 2 achieved a significant decrease in the MAGE level from baseline to the endpoint as compared to Groups 1 and 3 (all p < 0.05). We also observed that these patients had significant glycated haemoglobin A1c (HbA1c) value improvements as compared to the other two groups (all p < 0.05). Therefore, choosing an FBG level of 6.1 mmol/L as an insulin titration target provided significant GVs and HbA1c value improvements in T2D patients. Moreover, our data indicated that an FBG of 6.1 mmol/L could possibly be an insulin glargine titration target in T2D patients.

Evaluation of a Novel Noninvasive Blood Glucose Monitor Based on Mid-Infrared Quantum Cascade Laser Technology and Photothermal Detection

BACKGROUND

A prototype of a noninvasive glucometer combining skin excitation by a mid-infrared quantum cascade laser with photothermal detection was evaluated in glucose correlation tests including 100 volunteers (41 people with diabetes and 59 healthy people).

METHODS

Invasive reference measurements using a clinical glucometer and noninvasive measurements at a finger of the volunteer were simultaneously recorded in five-minute intervals starting from fasting glucose values for healthy subjects (low glucose values for diabetes patients) over a two-hour period. A glucose range from >50 to <350 mg/dL was covered. Machine learning algorithms were used to predict glucose values from the photothermal spectra. Data were analyzed for the average percent disagreement of the noninvasive measurements with the clinical reference measurement and visualized in consensus error grids.

RESULTS

98.8% (full data set) and 99.1% (improved algorithm) of glucose results were within Zones A and B of the grid, indicating the highest accuracy level. Less than 1% of the data were in Zone C, and none in Zone D or E. The mean and median percent differences between the invasive as a reference and the noninvasive method were 12.1% and 6.5%, respectively, for the full data set, and 11.3% and 6.4% with the improved algorithm.

CONCLUSIONS

Our results demonstrate that noninvasive blood glucose analysis combining mid-infrared spectroscopy and photothermal detection is feasible and comparable in accuracy with minimally invasive glucometers and finger pricking devices which use test strips. As a next step, a handheld version of the present device for diabetes patients is being developed.

Time in range-A1c hemoglobin relationship in continuous glucose monitoring of type 1 diabetes: a real-world study

INTRODUCTION

The availability of easily accessible continuous glucose monitoring (CGM) metrics can improve glycemic control in diabetes, and they may even become a viable alternative to hemoglobin A1c (HbA1c) laboratory tests in the next years. The REALISM-T1D study (REAl-Life glucoSe Monitoring in Type 1 Diabetes) was aimed at contributing, with real-world data, to a deeper understanding of these metrics, including the time in range (TIR)-HbA1c relationship, to facilitate their adoption by diabetologists in everyday practice.

RESEARCH DESIGN AND METHODS

70 adults affected by type 1 diabetes were monitored for 1 year by means of either flash (FGM) or real-time (rtCGM) glucose monitoring devices. Follow-up visits were performed after 90, 180 and 365 days from baseline and percentage TIR^70-180 evaluated for the 90-day time period preceding each visit. HbA1c tests were also carried out in the same occasions and measured values paired with the corresponding TIR data.

RESULTS

A monovariate linear regression analysis confirms a strong correlation between TIR and HbA1c as found in previous studies, but leveraging more homogeneous data (n=146) collected in real-life conditions. Differences were determined between FGM and rtCGM devices in Pearson's correlation (r_FGM=0.703, r_rtCGM=0.739), slope (β_1,FGM=-11.77, β_1,rtCGM=-10.74) and intercept (β_0,FGM=141.19, β_0,rtCGM=140.77) coefficients. Normality of residuals and homoscedasticity were successfully verified in both cases.

CONCLUSIONS

Regression lines for two patient groups monitored through FGM and rtCGM devices, respectively, while confirming a linear relationship between TIR and A1c hemoglobin (A1C) in good accordance with previous studies, also show a statistically significant difference in the regression intercept, thus suggesting the need for different models tailored to device characteristics. The predictive power of A1C as a TIR estimator also deserves further investigations.

Glucose measurement in body fluids: A ready reckoner for clinicians

BACKGROUND AND AIMS

Blood glucose measurement is central to the diagnosis and management of patients with diabetes. Considering that a clinician relies heavily on blood (or rarely other body fluid) glucose values for decision making, an understanding of the basic aspects of glucose measurement in body fluids is necessary.

METHODS

A literature search was conducted in PubMed for articles in English on measurement of glucose in body fluids.

RESULTS

Glucose can be measured in several body fluids, namely blood, interstitial fluid, urine, cerebrospinal fluid, pleural fluid and ascitic fluid in appropriate clinical settings. For blood glucose measurement, the present-day enzymatic methods have replaced the older reducing and condensation methods on account of their better accuracy. It is important to consider preanalytical factors such as sample collection, storage and transport when analyzing a laboratory blood glucose report. The measurement of glucose in interstitial fluid using continuous glucose monitoring system (CGMS) enables better understanding of glucose trends and fluctuations. The CGMS data should be reported using standard metrics which include parameters such as mean 24-h glucose, glycemic variability and time-in, below and above range. The measurement of glucose in urine sample is rarely ever used these days and should be reserved for exceptional circumstances.

CONCLUSION

This review provides a detailed account of various aspects of glucose measurement including their evolution, pitfalls, and their utility in current clinical practice.

Flexible and porous microneedles of PDMS for continuous glucose monitoring

Microneedle (MN) is a key technology of the biomedical engineering field due to its capability of accessing the biological information in a minimally invasive manner. One of the huge demands for next-generation healthcare monitoring is continuous monitoring, especially of blood glucose concentration. For this, MN should be kept inserted into the human skin for a certain period of time, enduring stresses induced by daily human motion and at the same time measuring biomarkers in ISF. However, conventional MNs for biosensing are not suitable for a long term insertion due to the rigid structure and biological risks of MN breakage. In this study, a novel MN structure is proposed and investigated by combining flexible "sponge-like" porous PDMS matrix and coating by biodissolving hyaluronic acid (HA). The fabricated porous MNs coated with HA show ideal mechanical characteristics, by which the MNs are rigid enough to penetrate the skin and become flexible after insertion into the skin. It is also shown that the MN array successfully extracts ISF in vitro and in vivo not by capillary action but by repeated compressions. The results show the applicability of the flexible MNs to continuous blood glucose monitoring.

The Calculation of the Glucose Management Indicator Is Influenced by the Continuous Glucose Monitoring System and Patient Race

Objective: To determine whether the glucose management indicator (GMI), an estimate of hemoglobin A1c (HbA1c) derived from continuous glucose monitoring (CGM) mean glycemia, differs by CGM system and patient race. Methods: One hundred three patients with prediabetes or stable diabetes and a minimum of 10 days of CGM data collected with the FreeStyle Libre CGM system immediately before measurement of HbA1c were included in this clinic-based observational study that used data from electronic health records in an academic endocrinology clinic. HbA1c and Libre CGM-measured mean glucose were plotted to derive a race-agnostic and race-specific regression equations to calculate a Libre-specific GMI (GMI_Li). The mean GMI derived from the published formula (GMI_P) was compared with GMI_Li. Results: Mean ± SD (standard deviation) age of patients was 61.9 ± 13.3 years; 50% were of nonwhite race and 77% had type 2 diabetes; mean HbA1c was 62 mmol/mol (7.8%). The mean (range) number of days with available CGM data was 26 (10-90). The mean ± SD GMI_Li was higher than the GMI_P in the entire cohort (7.9% ± 1.0% vs. 7.5% ± 1.0%, respectively; P = 0.01) and among Asian patients (7.9% ± 0.9% vs. 7.2% ± 1.0%, respectively; P = 0.03). Conclusions: In a cohort with prediabetes or stable diabetes, the regression equation to calculate GMI varied by CGM system and patient race. The development of device- and race-specific regression equations for GMI may be warranted.

Impact of acute-phase insulin secretion on glycemic variability in insulin-treated patients with type 2 diabetes

AIMS

The association between β-cell function and glycemic variability remains to be clarified in insulin-treated patients with type 2 diabetes. Therefore, the study sought to examine the association of various indices of β-cell function with glycemic variability in Chinese insulin-treated patients with type 2 diabetes.

METHODS

Glycemic variability was assessed by the coefficient of variation (CV) of glucose levels with the use of continuous glucose monitoring (CGM). Basal β-cell function was evaluated by fasting C-peptide (FCP) and the homeostasis model assessment 2 for β-cell function (HOMA2-%β). Postload β-cell function was measured by 2-hour C-peptide (2hCP) and the acute C-peptide response (ACPR) to arginine.

RESULTS

When a cutoff value of CV ≥ 36% was used to define unstable glucose, the multivariable-adjusted odds ratios for labile glycemic control were 0.34 (95% CI 0.18-0.64) for each 1 ng/mL increase in ACPR, 0.47 (95% CI 0.27-0.81) for each 1 ng/mL increase in FCP, 0.77 (95% CI 0.61-0.97) for each 1 ng/mL increase in 2hCP, and 1.00 (95% CI 0.98-1.01) for each 1% increase in HOMA2-%β. When we further adjusted for 2hCP and HOMA2-%β in the ACPR and FCP analyses, and adjusted for ACPR or FCP in the 2hCP analyses, only ACPR but not FCP or 2hPC remained to be a significant and inverse predictor for labile glycemic control.

CONCLUSIONS

ACPR evaluated by the arginine stimulation test may be superior to other commonly used β-cell function parameters to reflect glycemic fluctuation in insulin-treated patients with type 2 diabetes.

How tightly controlled do fluctuations in blood glucose levels need to be to reduce the risk of developing complications in people with Type 1 diabetes?

In 2011, the James Lind Alliance published a 'top 10' list of priorities for Type 1 diabetes research based on a structured consultation process. Whether reducing fluctuations in blood glucose can prevent long-term microvascular and macrovascular complications was one of these. In this narrative review, 8 years on, we have assessed the updated evidence for the assertion that increased glucose variability plays an independent and clinically important role in the complications of Type 1 diabetes, over and above mean blood glucose and the effects of hypoglycaemia: the 'glucose variability hypothesis'. Although studies in cultured cells and ex vivo vessels have been suggestive, most studies in Type 1 diabetes have been small and/or cross-sectional, and based on 'finger-prick' glucose measurements that capture glucose variability only in waking hours and are affected by missing data. A recent analysis of the Diabetes Control and Complications Trial that formally imputed missing data found no independent effect of short-term glucose variability on long-term complications. Few other high-quality longitudinal studies have directly addressed the glucose variability hypothesis in Type 1 diabetes. We conclude that there is little substantial evidence to date to support this hypothesis in Type 1 diabetes, although increasing use of continuous glucose monitoring provides an opportunity to test it more definitively. In the meantime, we recommend that control of glycaemia in Type 1 diabetes should continue to focus on the sustained achievement of target HbA_1c and avoidance of hypoglycaemia.

Positioning time in range in diabetes management

Recent upswings in the use of continuous glucose monitoring (CGM) technologies have given people with diabetes and healthcare professionals unprecedented access to a range of new indicators of glucose control. Some of these metrics are useful research tools and others have been welcomed by patient groups for providing insights into the quality of glucose control not captured by conventional laboratory testing. Among the latter, time in range (TIR) is an intuitive metric that denotes the proportion of time that a person's glucose level is within a desired target range (usually 3.9-10.0 mmol/l [3.5-7.8 mmol/l in pregnancy]). For individuals choosing to use CGM technology, TIR is now often part of the expected conversation between patient and healthcare professional, and consensus recommendations have recently been produced to facilitate the adoption of standardised TIR targets. At a regulatory level, emerging evidence linking TIR to risk of complications may see TIR being more widely accepted as a valid endpoint in future clinical trials. However, given the skewed distribution of possible glucose values outside of the target range, TIR (on its own) is a poor indicator of the frequency or severity of hypoglycaemia. Here, the state-of-the-art linking TIR with complications risk in diabetes and the inverse association between TIR and HbA_1c are reviewed. Moreover, the importance of including the amount and severity of time below range (TBR) in any discussions around TIR and, by inference, time above range (TAR) is discussed. This review also summarises recent guidance in setting 'time in ranges' goals for individuals with diabetes who wish to make use of these metrics. For most people with type 1 or type 2 diabetes, a TIR >70%, a TBR <3.9 mmol/l of <4%, and a TBR <3.0 mmol/l of <1% are recommended targets, with less stringent targets for older or high-risk individuals and for those under 25 years of age. As always though, glycaemic targets should be individualised and rarely is that more applicable than in the personal use of CGM and the data it provides.

Acceptability of Continuous Glucose Monitoring in Elderly Diabetes Patients Using Multiple Daily Insulin Injections

Background: Integrative diabetes care is lifelong and encompasses patient-reported outcome measures (PROMs). Understanding older adults' perceptions of continuous glucose monitoring (CGM) benefits and potential annoyances is important to assist with introducing it in this population. The aim of this study was to investigate PROMs and effectiveness of CGM introduction in elderly multiple daily injection (MDI) users with well-controlled diabetes. Methods: MDI-treated elderly (n = 25, mean age 67.6 ± 1.2 years, HbA1c = 7.1% ± 0.2%, 56% type 1 diabetes) were instructed to use a CGM device. PROMs were measured by questionnaires. CGM-recorded glycemic control metrics (time in range [TIR], time in hypoglycemia, coefficient of variation [CV]) were compared during blinded CGM and real-time CGM. Results: Satisfaction with CGM use was high; with perceived advantages as "very common" (4.22 out of 5) and annoyances as "modest" (1.82 out of 5). In total 95% of participants expressed improved sense of security with CGM use, 68% reported of improved sleep quality, and 82% were willing to use a CGM device after finishing the study protocol. CGM introduction did not impose additional diabetes-related distress (measured by the Problem Areas in Diabetes questionnaire). Significant improvements in TIR (3.9-10.0 mmol/L) (66.3% ± 2.6% vs. 76.9% ± 3.0%; P < 0.001), time in hypoglycemia (9.6% ± 2.1% vs. 5.2% ± 1.1%; P = 0.041), as well as reduced glycemic variability (%CV) (37.3 ± 11.1 vs. 32.9 ± 6.3; P < 0.001) were observed. Conclusion: Introduction of CGM in elderly patients with well-controlled diabetes resulted in high satisfaction without imposing additional diabetes distress. Furthermore, an added benefit in glucose control with stabilizing glycemia in target range was proven.

Continuous Glucose Monitoring: A Review of Available Systems

Continuous glucose monitoring offers patients with diabetes a new option for monitoring their glucose levels on a regular basis, without the need for perpetual finger-sticks and myriad supplies.

Efficacy Comparison of Preprandial and Postprandial Prandilin 25 Administration in Patients with Newly Diagnosed Type 2 Diabetes Using a Continuous Glucose Monitoring System

INTRODUCTION

The aim of this study was to determine the clinical efficacy of preprandial and postprandial Prandilin 25 (premixed insulin lispro 25) administration in patients with newly diagnosed type 2 diabetes mellitus (T2DM) using a continuous glucose monitoring (CGM) system.

METHODS

This was a single-center, self-controlled comparative clinical trial. Newly diagnosed T2DM patients with hemoglobin A1c > 8.0% were hospitalized and received Prandilin 25 plus metformin treatment. Glycemic control was reached after a 7-to-8-day run-in period. Patients underwent 2 days of treatment consisting of preprandial Prandilin 25 on day 1 and postprandial Prandilin 25 on day 2 at the same dosage. The primary outcome was the 24-h mean amplitude of glycemic excursion (24 hMAGE); secondary outcomes were other daily glycemic variability parameters, including 24-h mean blood glucose (24hMBG), 24-h standard deviation of blood glucose (24hSDBG), large amplitude of glycemic excursion (LAGE), incremental area under the curve (AUC) values for different glucose levels, postprandial glucose excursion, and incidence of hypoglycemia, which were assessed using a CGM system.

RESULTS

Eighty-five patients completed this study. There was no statistically significant difference in 24hMAGE, 24hMBG, 24hSDBG, or LAGE between the preprandial injection group and the postprandial injection group. Similarly, there was no between-treatment difference in the AUC for a blood glucose level below 3.9 mmol/L, in the AUC for a blood glucose level above 10.0 mmol/L, or in the percentages of time that the blood glucose level was below 3.9 mmol/L or above 10.0 mmol/L. Further analysis showed that the pre-meal glucose, peak height, and time to peak after each meal, the relative areas under the CGM curve at 1-4 h after each meal, as well as the incidence of hypoglycemia, were similar for the preprandial and postprandial Prandilin 25 groups.

CONCLUSION

In patients with T2DM managed with premixed insulin lispro 25, postprandial injection (within 30 min of meal onset) may be an acceptable alternative to preprandial injection when the regular preprandial insulin dose is omitted.

TRIAL REGISTRATION

Chinese Clinical Trial Register identifier: ChiCTR1800015828.

Evaluating a Glucose-Sensor-Based Tool to Help Clinicians and Adults With Type 1 Diabetes Improve Self-Management Skills

BACKGROUND

The goal of this uncontrolled pilot study was to assess the feasibility of a self-care management mobile app, called Sugar Sleuth, which incorporates the FreeStyle Libre™ glucose sensor, to help clinicians and people with type 1 diabetes (PWD) identify and mitigate self-care behaviors that contribute to glucose variability.

METHODS

PWDs with a baseline A1c between 7.5 and 9.0% used the mobile app for 14 weeks. The app prompted the PWD to enter the suspected cause of detected glycemic excursions, and to record food and insulin information. PWDs met with clinicians to collaboratively review data, identify challenges, and devise a specific self-care plan. Outcome measures included a single glycemic outcome score (SGOS) and attitude rating scales to better understand how participant attitudes could affect glycemic outcome.

RESULTS

Thirty enrolled PWDs had a mean age of 55 ± 2.6 years, and a mean diabetes duration of 32 ± 2.9 years. A significant average reduction in A1c of 0.5 ± 0.07% ( P < .01) and in mean daily carbohydrate intake of 43 ± 21 grams ( P = .05) was found. No statistically significant change in glycemic metrics, body weight, or total daily insulin dose was found. A significant negative association occurred between SGOS and "hypoglycemia tolerance" ( P = .04), and a positive correlation occurred that approached significance with "motivation to change behavior" ( P = .06).

CONCLUSIONS

These findings suggest that this mobile app system, in conjunction with CGM, provides a useful platform for helping clinicians and adults with T1D improve self-management skills to improve glycemic control.

Biopsychosocial Factors Associated With Satisfaction and Sustained Use of Artificial Pancreas Technology and Its Components: a Call to the Technology Field

PURPOSE OF REVIEW

Summarize biopsychosocial factors associated with using continuous glucose monitors (CGMs), insulin pumps, and artificial pancreas (AP) systems and provide a "call to the field" about their importance to technology uptake and maintained use.

RECENT FINDINGS

Insulin pumps and CGMs are becoming standard of care for individuals with type 1 diabetes (T1D). AP systems combining a CGM, insulin pump, and automated dosing algorithm are available for commercial use. Despite improved glycemic control with AP system use, numerous barriers exist which may limit their benefit. Studies on components of AP systems (pumps, CGMs) are limited and demonstrate mixed results of their impact on fear of hypoglycemia, adherence, quality of life, depression and anxiety, and diabetes distress. Studies examining biopsychological factors associated specifically with sustained use of AP systems are also sparse. Biological, psychological and social impacts of AP systems have been understudied and the information they provide has not been capitalized upon.

Digital diabetes: Perspectives for diabetes prevention, management and research

Digital medicine, digital research and artificial intelligence (AI) have the power to transform the field of diabetes with continuous and no-burden remote monitoring of patients' symptoms, physiological data, behaviours, and social and environmental contexts through the use of wearables, sensors and smartphone technologies. Moreover, data generated online and by digital technologies - which the authors suggest be grouped under the term 'digitosome' - constitute, through the quantity and variety of information they represent, a powerful potential for identifying new digital markers and patterns of risk that, ultimately, when combined with clinical data, can improve diabetes management and quality of life, and also prevent diabetes-related complications. Moving from a world in which patients are characterized by only a few recent measurements of fasting glucose levels and glycated haemoglobin to a world where patients, healthcare professionals and research scientists can consider various key parameters at thousands of time points simultaneously will profoundly change the way diabetes is prevented, managed and characterized in patients living with diabetes, as well as how it is scientifically researched. Indeed, the present review looks at how the digitization of diabetes can impact all fields of diabetes - its prevention, management, technology and research - and how it can complement, but not replace, what is usually done in traditional clinical settings. Such a profound shift is a genuine game changer that should be embraced by all, as it can provide solid research results transferable to patients, improve general health literacy, and provide tools to facilitate the everyday decision-making process by both healthcare professionals and patients living with diabetes.

Accuracy of a Fourth-Generation Continuous Glucose Monitoring System in Children and Adolescents with Type 1 Diabetes

BACKGROUND

This study evaluated the safety and performance of the Guardian™ continuous glucose monitoring (CGM) system in children and adolescents with type 1 diabetes (T1D).

MATERIALS AND METHODS

Subjects 2-18 years of age (mean ± standard deviation [SD] 13.1 ± 3.9 years) with T1D and duration of diagnosis ≥1 year were enrolled at 11 sites in the United States and wore two Guardian Sensor 3 sensors in the abdomen and/or buttock. Sensors were connected to a transmitter paired with either a Guardian Connect system (i.e., mobile device with software application allowing display of sensor glucose [SG] values) or a Guardian Link 3 transmitter used as a Glucose Sensor Recorder (GSR). There were 145 participants who underwent a 6-h in-clinic frequent sample testing (FST) on day 1 (n = 54), day 3 (n = 48), or day 7 (n = 43) postsensor insertion. During FST, SG values were compared with a Yellow Springs Instrument (YSI) plasma reference every 5-15 min (n = 124, 7-18 years of age; n = 2, 2-6 years of age), or to a self-monitoring of blood glucose (SMBG) reference every 5-30 min (n = 19, 2-6 years of age).

RESULTS

The overall mean absolute relative difference (ARD ± SD) between SG and reference values (YSI or SMBG) when calibrating approximately every 12 h, was 10.9% ± 10.7% (3102 paired points) for sensors communicating with the Guardian Connect system and 11.1% ± 10.6% (2624 paired points) for sensors connected to the GSR. The overall percentage of SG values within ±20% of reference values >80 mg/dL or within 20 mg/dL of reference values ≤80 mg/dL was 87.8% for the Guardian Connect system and 86.7% for the GSR, respectively. There was one device-related adverse event of contact dermatitis, but no serious device-related adverse events.

CONCLUSIONS

The Guardian CGM system demonstrated good accuracy in children and adolescents. These findings support its use in sensor-integrated insulin pump platforms, as well as a standalone technology, for managing diabetes in pediatric populations.