Explore the vast range of titles available.

Introduction We have evaluated the performance of the FreeStyle Libre® 3 continuous glucose monitoring system (FSL3) compared to (1) the venous plasma reference for participants aged ≥ 6 years and (2) the fingerstick capillary blood glucose (BG) reference for pediatric participants aged 4 and 5 years. The analytical performance of the third-generation factory-calibrated FSL3 CGM system was compared to the plasma venous blood glucose reference using the YSI 2300 STAT PLUS Glucose and Lactate Analyzer (the YSI reference) and the self-monitoring blood glucose (SMBG) reference for participants aged ≥ 6 years and participants aged 4 and 5 years, respectively. Methods A total of 108 participants aged ≥ 4 years with type 1 or type 2 diabetes from four sites in the USA were enrolled in the study. The data of 100 participants were ultimately evaluated. Adult participants (aged ≥ 18 years) participated in three in-clinic sessions, and pediatric participants (aged 4–17 years) participated in up to two in-clinic sessions, all stratified to provide data for days 1, 2, 3, 7, 8, 9, 12, 13 or 14 of sensor wear. Performance evaluation included accuracy measures, such as proportion of CGM values that fell within ± 20% or ± 20 mg/dL (1.1 mmol/L) of the reference glucose values, and difference measures, such as the mean absolute relative difference (MARD) between the CGM and reference values. Results Data from the 100 study participants were analyzed. The overall MARD was 7.8%, and 93.4% of the CGM values were within ± 20% or ± 20 mg/dL of the YSI reference for participants aged ≥ 6 years, with 6845 CGM-YSI matched pairs. The performance was stable over the 14-day wear period. For participants aged 4–5 years, MARD was 10.0%, and 88.9% of the CGM values were within 20%/20 mg/dL compared to a SMBG reference. No serious adverse events were reported. Conclusions The FSL3 CGM system demonstrated accurate performance across the dynamic glycemic range during the 14-day sensor wear period.

Aims/hypothesis Continuous glucose monitoring (CGM) is increasingly used in the treatment of type 2 diabetes, but the effects on glycaemic control are unclear. The aim of this systematic review and meta-analysis is to provide a comprehensive overview of the effect of CGM on glycaemic control in adults with type 2 diabetes. Methods We performed a systematic review using Embase, MEDLINE, Web of Science, Scopus and ClinicalTrials.gov from inception until 2 May 2023. We included RCTs investigating real-time CGM (rtCGM) or intermittently scanned CGM (isCGM) compared with self-monitoring of blood glucose (SMBG) in adults with type 2 diabetes. Studies with an intervention duration <6 weeks or investigating professional CGM, a combination of CGM and additional glucose-lowering treatment strategies or GlucoWatch were not eligible. Change in HbA 1c and the CGM metrics time in range (TIR), time below range (TBR), time above range (TAR) and glycaemic variability were extracted. We evaluated the risk of bias using the Cochrane risk-of-bias tool version 2. Data were synthesised by performing a meta-analysis. We also explored the effects of CGM on severe hypoglycaemia and micro- and macrovascular complications. Results We found 12 RCTs comprising 1248 participants, with eight investigating rtCGM and four isCGM. Compared with SMBG, CGM use (rtCGM or isCGM) led to a mean difference (MD) in HbA 1c of −3.43 mmol/mol (−0.31%; 95% CI −4.75, −2.11, p <0.00001, I 2 =15%; moderate certainty). This effect was comparable in studies that included individuals using insulin with or without oral agents (MD −3.27 mmol/mol [−0.30%]; 95% CI −6.22, −0.31, p =0.03, I 2 =55%), and individuals using oral agents only (MD −3.22 mmol/mol [−0.29%]; 95% CI −5.39, −1.05, p =0.004, I 2 =0%). Use of rtCGM showed a trend towards a larger effect (MD −3.95 mmol/mol [−0.36%]; 95% CI −5.46 to −2.44, p <0.00001, I 2 =0%) than use of isCGM (MD −1.79 mmol/mol [−0.16%]; 95% CI −5.28, 1.69, p =0.31, I 2 =64%). CGM was also associated with an increase in TIR (+6.36%; 95% CI +2.48, +10.24, p =0.001, I 2 =9%) and a decrease in TBR (−0.66%; 95% CI −1.21, −0.12, p =0.02, I 2 =45%), TAR (−5.86%; 95% CI −10.88, −0.84, p =0.02, I 2 =37%) and glycaemic variability (−1.47%; 95% CI −2.94, −0.01, p =0.05, I 2 =0%). Three studies reported one or more events of severe hypoglycaemia and macrovascular complications. In comparison with SMBG, CGM use led to a non-statistically significant difference in the incidence of severe hypoglycaemia (RR 0.66, 95% CI 0.15, 3.00, p =0.57, I 2 =0%) and macrovascular complications (RR 1.54, 95% CI 0.42, 5.72, p =0.52, I 2 =29%). No trials reported data on microvascular complications. Conclusions/interpretation CGM use compared with SMBG is associated with improvements in glycaemic control in adults with type 2 diabetes. However, all studies were open label. In addition, outcome data on incident severe hypoglycaemia and incident microvascular and macrovascular complications were scarce. Registration This systematic review was registered on PROSPERO (ID CRD42023418005). Graphical Abstract

Introduction Continuous glucose monitoring (CGM) has significantly advanced diabetes management, evolving from early glucose testing methods to modern, FDA‐approved systems. Despite its benefits, challenges related to data security, affordability, and awareness of CGM devices remain. Aim This article explores the historical development, current advancements, and ongoing challenges of CGM systems in diabetes management. It aims to provide insights into how these technologies have transformed patient care and highlight areas needing further improvement. Methods A comprehensive literature review was conducted, focusing on advancements in CGM technology. Sources included PubMed, Google Scholar, and recent guidelines and reviews on CGM systems and their impact on diabetes management. Results The evolution from the Dextrostix test strip to modern CGM systems, including over‐the‐counter devices, has enhanced glucose monitoring and patient outcomes. Recent innovations, such as machine learning models for predicting glucose fluctuations, promise to improve diabetes management. However, issues like data security and device accessibility persist. Conclusion To maximize the benefits of CGM systems, addressing data security, improving affordability, and increasing awareness of CGM devices are crucial. Continued advancements in CGM technology and supportive policies are essential for enhancing diabetes care and patient outcomes globally.

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.

Physical exercise is an important component in the management of type 1 diabetes across the lifespan. Yet, acute exercise increases the risk of dysglycaemia, and the direction of glycaemic excursions depends, to some extent, on the intensity and duration of the type of exercise. Understandably, fear of hypoglycaemia is one of the strongest barriers to incorporating exercise into daily life. Risk of hypoglycaemia during and after exercise can be lowered when insulin-dose adjustments are made and/or additional carbohydrates are consumed. Glycaemic management during exercise has been made easier with continuous glucose monitoring (CGM) and intermittently scanned continuous glucose monitoring (isCGM) systems; however, because of the complexity of CGM and isCGM systems, both individuals with type 1 diabetes and their healthcare professionals may struggle with the interpretation of given information to maximise the technological potential for effective use around exercise (i.e. before, during and after). This position statement highlights the recent advancements in CGM and isCGM technology, with a focus on the evidence base for their efficacy to sense glucose around exercise and adaptations in the use of these emerging tools, and updates the guidance for exercise in adults, children and adolescents with type 1 diabetes.

Abstract Glucose and insulin metabolism in patients with diabetes are profoundly altered by advanced chronic kidney disease (CKD). Risk of hypoglycemia is increased by failure of kidney gluconeogenesis, impaired insulin clearance by the kidney, defective insulin degradation due to uremia, increased erythrocyte glucose uptake during hemodialysis, impaired counterregulatory hormone responses (cortisol, growth hormone), nutritional deprivation, and variability of exposure to oral antihyperglycemic agents and exogenous insulin. Patients with end-stage kidney disease frequently experience wide glycemic excursions, with common occurrences of both hypoglycemia and hyperglycemia. Assessment of glycemia by glycated hemoglobin (HbA1c) is hampered by a variety of CKD-associated conditions that can bias the measure either to the low or high range. Alternative glycemic biomarkers, such as glycated albumin or fructosamine, are not fully validated. Therefore, HbA1c remains the preferred glycemic biomarker despite its limitations. Based on observational data for associations with mortality and risks of hypoglycemia with intensive glycemic control regimens in advanced CKD, an HbA1c range of 7% to 8% appears to be the most favorable. Emerging data on the use of continuous glucose monitoring in this population suggest promise for more precise monitoring and treatment adjustments to permit fine-tuning of glycemic management in patients with diabetes and advanced CKD. Graphical Abstract Graphical Abstract

Community Gold Mining (CGM) in Indonesia faces significant challenges, with a specific concern being the use of mercury. Mercury is a highly toxic chemical commonly utilized in the Trommel Mercury (TM) gold extraction method, known locally as the Glundung method. Although the government has initiated programs to reduce mercury usage, such as encouraging researchers to develop non-mercury gold extraction methods, progress has been slow, and the impact has been limited. The growth of new CGM sites is outpacing these efforts, leading to an increased use of mercury and unmanageable chemical risks. Previous research has identified a vicious cycle within the CGM sector. However, no existing model illustrates this cycle. This study seeks to map the scope of CGM at its essential stages and translate them into variables to create a causal and basic model. However, Sukabumi Regency in Indonesia hosts numerous CGM sites, and a case study was conducted in the Simpenan Sub-District between 2018 and 2020. A recent site visit in August 2023 revealed continued growth in CGM site numbers within the broader area. This growth corresponds to an increase in mercury released into the environment, which poses a growing threat to public health. The study employed ArcGIS and Powersim 10 System Dynamics Software, utilizing data collected through observations, investigative methods, and reference studies. The results include two significant contributions: first, a model of current CGM activities in the form of a Causal Loops Diagram (CLD) called “the Turtle Map CLD Model of the CGM”. Second, a model depicting “the vicious cycle of CGM” highlights problematic stages within CGM. Both models represent the current state of CGM in Indonesia, showcasing the existence of vicious cycles in ongoing CGM sites. These models can guide future efforts to identify progressive solutions, especially in support of programs aimed at reducing mercury usage.

Physical exercise is an important component in the management of type 1 diabetes across the lifespan. Yet, acute exercise increases the risk of dysglycaemia, and the direction of glycaemic excursions depends, to some extent, on the intensity and duration of the type of exercise. Understandably, fear of hypoglycaemia is one of the strongest barriers to incorporating exercise into daily life. Risk of hypoglycaemia during and after exercise can be lowered when insulin-dose adjustments are made and/or additional carbohydrates are consumed. Glycaemic management during exercise has been made easier with continuous glucose monitoring (CGM) and intermittently scanned continuous glucose monitoring (isCGM) systems; however, because of the complexity of CGM and isCGM systems, both individuals with type 1 diabetes and their healthcare professionals may struggle with the interpretation of given information to maximise the technological potential for effective use around exercise (ie, before, during and after). This position statement highlights the recent advancements in CGM and isCGM technology, with a focus on the evidence base for their efficacy to sense glucose around exercise and adaptations in the use of these emerging tools, and updates the guidance for exercise in adults, children and adolescents with type 1 diabetes.

Diabetes patients suffer from abnormal blood glucose levels, which can cause diverse health disorders that affect their kidneys, heart and vision. Due to these conditions, diabetes patients have traditionally checked blood glucose levels through Self-Monitoring of Blood Glucose (SMBG) techniques, like pricking their fingers multiple times per day. Such techniques involve a number of drawbacks that can be solved by using a device called Continuous Glucose Monitor (CGM), which can measure blood glucose levels continuously throughout the day without having to prick the patient when carrying out every measurement. This article details the design and implementation of a system that enhances commercial CGMs by adding Internet of Things (IoT) capabilities to them that allow for monitoring patients remotely and, thus, warning them about potentially dangerous situations. The proposed system makes use of smartphones to collect blood glucose values from CGMs and then sends them either to a remote cloud or to distributed fog computing nodes. Moreover, in order to exchange reliable, trustworthy and cybersecure data with medical scientists, doctors and caretakers, the system includes the deployment of a decentralized storage system that receives, processes and stores the collected data. Furthermore, in order to motivate users to add new data to the system, an incentive system based on a digital cryptocurrency named GlucoCoin was devised. Such a system makes use of a blockchain that is able to execute smart contracts in order to automate CGM sensor purchases or to reward the users that contribute to the system by providing their own data. Thanks to all the previously mentioned technologies, the proposed system enables patient data crowdsourcing and the development of novel mobile health (mHealth) applications for diagnosing, monitoring, studying and taking public health actions that can help to advance in the control of the disease and raise global awareness on the increasing prevalence of diabetes.

Introduction: Continuous glucose monitoring (CGM) systems were primarily developed for patients with diabetes mellitus. However, these systems are increasingly being used by individuals who do not have diabetes mellitus. This mini review describes possible applications of CGM systems in healthy adults in health care, wellness, and sports. Results: CGM systems can be used for early detection of abnormal glucose regulation. Learning from CGM data how the intake of foods with different glycemic loads and physical activity affect glucose responses can be helpful in improving nutritional and/or physical activity behavior. Furthermore, states of stress that affect glucose dynamics could be made visible. Physical performance and/or regeneration can be improved as CGM systems can provide information on glucose values and dynamics that may help optimize nutritional strategies pre-, during, and post-exercise. Conclusions: CGM has a high potential for health benefits and self-optimization. More scientific studies are needed to improve the interpretation of CGM data. The interaction with other wearables and combined data collection and analysis in one single device would contribute to developing more precise recommendations for users.