Continuous Glucose Monitoring with Multiple Daily Insulin Treatment: Outcome Studies

Combining uncertainty-aware predictive modeling and a bedtime Smart Snack intervention to prevent nocturnal hypoglycemia in people with type 1 diabetes on multiple daily injections

OBJECTIVE

Nocturnal hypoglycemia is a known challenge for people with type 1 diabetes, especially for physically active individuals or those on multiple daily injections. We developed an evidential neural network (ENN) to predict at bedtime the probability and timing of nocturnal hypoglycemia (0-4 vs 4-8 h after bedtime) based on several glucose metrics and physical activity patterns. We utilized these predictions in silico to prescribe bedtime carbohydrates with a Smart Snack intervention specific to the predicted minimum nocturnal glucose and timing of nocturnal hypoglycemia.

MATERIALS AND METHODS

We leveraged free-living datasets collected from 366 individuals from the T1DEXI Study and Glooko. Inputs to the ENN used to model nocturnal hypoglycemia were derived from demographic information, continuous glucose monitoring, and physical activity data. We assessed the accuracy of the ENN using area under the receiver operating curve, and the clinical impact of the Smart Snack intervention through simulations.

RESULTS

The ENN achieved an area under the receiver operating curve of 0.80 and 0.71 to predict nocturnal hypoglycemic events during 0-4 and 4-8 h after bedtime, respectively, outperforming all evaluated baseline methods. Use of the Smart Snack intervention reduced probability of nocturnal hypoglycemia from 23.9 ± 14.1% to 14.0 ± 13.3% and duration from 7.4 ± 7.0% to 2.4 ± 3.3% in silico.

DISCUSSION

Our findings indicate that the ENN-based Smart Snack intervention has the potential to significantly reduce the frequency and duration of nocturnal hypoglycemic events.

CONCLUSION

A decision support system that combines prediction of minimum nocturnal glucose and proactive recommendations for bedtime carbohydrate intake might effectively prevent nocturnal hypoglycemia and reduce the burden of glycemic self-management.

Intermittent closed-loop blood glucose control for people with type 1 diabetes on multiple daily injections

BACKGROUND AND OBJECTIVES

Recent advances in Automated Insulin Delivery systems have been shown to dramatically improve glycaemic control and reduce the risk of hypoglycemia in people with type 1 diabetes. However, they are complex systems that require specific training and are not affordable for most. Attempts to reduce the gap with closed-loop therapies using advanced dosing advisors have so far failed, mainly because they require too much human intervention. With the advent of smart insulin pens, one of the main constraints (having reliable bolus and meal information) disappears and new strategies can be employed. This is our starting hypothesis, which we have validated in a very demanding simulator. In this paper, we propose an intermittent closed-loop control system specifically intended for multiple daily injection therapy to bring the benefits of artificial pancreas to the application of multiple daily injections.

METHODS

The proposed control algorithm is based on model predictive control and integrates two patient-driven control actions. Correction insulin boluses are automatically computed and recommended to the patient to minimize the duration of hyperglycemia. Rescue carbohydrates are also triggered to avoid hypoglycemia episodes. The algorithm can adapt to different patient lifestyles with customizable triggering conditions, closing the gap between practicality and performance. The proposed algorithm is compared with conventional open-loop therapy, and its superiority is demonstrated through extensive in silico evaluations using realistic cohorts and scenarios. The evaluations were conducted in a cohort of 47 virtual patients. We also provide detailed explanations of the implementation, imposed constraints, triggering conditions, cost functions, and penalties for the algorithm.

RESULTS

The in-silico outcomes combining the proposed closed-loop strategy with slow-acting insulin analog injections at 09:00 h resulted in percentages of time in range (TIR) (70-180 mg/dL) of 69.5%, 70.6%, and 70.4% for glargine-100, glargine-300, and degludec-100, respectively, and injections at 20:00 h resulted in percentages of TIR of 70.5%, 70.3%, and 71.6%, respectively. In all the cases, the percentages of TIR were considerably higher than those obtained from the open-loop strategy, being only 50.7%, 53.9%, and 52.2% for daytime injection and 55.5%, 54.1%, and 56.9% for nighttime injection. Overall, the occurrence of hypoglycemia and hyperglycemia was notably reduced using our approach.

CONCLUSIONS

Event-triggering model predictive control in the proposed algorithm is feasible and may meet clinical targets for people with type 1 diabetes.

Emerging drugs for the treatment of type 1 diabetes mellitus: a review of phase 2 clinical trials

INTRODUCTION

Despite therapeutic advances in the field of diabetes management since the discovery of insulin 100 years ago, there are still unmet clinical needs for people with type 1 diabetes mellitus (T1DM).

AREAS COVERED

Genetic testing and islet autoantibodies testing allow researchers to design prevention studies. This review discusses the emerging therapy for prevention of T1DM, disease modification therapy in early course of T1DM, and therapies and technologies for established T1DM. We focus on phase 2 clinical trials with promising results, thus avoiding the exhausted list of every new therapy for T1DM.

EXPERT OPINION

Teplizumab has demonstrated potential as a preventative agent for individuals at risk prior to the onset of overt dysglycemia. However, these agents are not without side effects, and there are uncertainties on long-term safety. Technological advances have led a substantial influence on quality of life of people suffering from T1DM. There remains variation in uptake of new technologies across the globe. Novel insulins (ultra-long acting), oral insulin, and inhaled insulin attempt to narrow the gap of unmet needs. Islet cell transplant is another exciting field, and stem cell therapy might have potential to provide unlimited supply of islet cells.

A simulator with realistic and challenging scenarios for virtual T1D patients undergoing CSII and MDI therapy

In silico simulations have become essential for the development of diabetes treatments. However, currently available simulators are not challenging enough and often suffer from limitations in insulin and meal absorption variability, which is unable to realistically reflect the dynamics of people with type 1 diabetes (T1D). Additionally, T1D simulators are mainly designed for the testing of continuous subcutaneous insulin infusion (CSII) therapies. In this work, a simulator is presented that includes a generated virtual patient (VP) cohort and both fast- and long-acting Glargine-100 U/ml (Gla-100), Glargine-300 U/ml (Gla-300), and Degludec-100 U/ml (Deg-100) insulin models. Therefore, in addition to CSII therapies, multiple daily injections (MDI) therapies can also be tested. The Hovorka model and its published parameter probability distributions were used to generate cohorts of VPs that represent a T1D population. Valid patients are filtered through restrictions that guarantee that they are physiologically acceptable. To obtain more realistic scenarios, basal insulin profile patterns from the literature have been used to identify variability in insulin sensitivity. A library of mixed meals identified from real data has also been included. This work presents and validates a methodology for the creation of realistic VP cohorts that include physiological variability and a simulator that includes challenging and realistic scenarios for in silico testing. A cohort of 47 VPs has been generated and in silico simulations of both CSII and MDI therapies were performed in open-loop. The simulation outcome metrics were contrasted with literature results.

Changes in glycaemic control of oral anti-diabetic medications assessed by continuous glucose monitors among patients with type 2 diabetes: a protocol of network meta-analysis

BACKGROUND

Continuous glucose monitors (CGMs) can measure interstitial fluid glucose levels to provide comprehensive real-time glucose profile among people with type 2 diabetes. These can accurately detect glucose levels, hyperglycaemia and hypoglycaemia events compared with conventional self-monitoring. Increased application of CGMs provides a valuable opportunity to evaluate glucose control on oral anti-diabetic medications. This review will compare the efficacy and safety of oral anti-diabetic medications among patients with type 2 diabetes, evaluated by CGM.

METHODS

The following databases will be searched: Cochrane Library, PubMed, EMBASE, CINAHL, PsycINFO, Scopus and grey literature (ClinicalTrials.gov, PsycEXTRA, ProQuest Dissertations, Google Scholar and Theses Global) for the identification of studies. The review will include and summarise evidence from randomised clinical trials that use CGMs for blood glucose management in adults (aged ≥ 18 years), published in English between January 2000 and May 2021 without any restrictions of countries. Reference list of all selected articles will independently be screened to identify additional studies left out in the initial search. Primary outcomes will be HbA1c (≤ 7.0%), time spent with hypoglycaemia (< 70 mg/dl) or hyperglycaemia (≥ 180 mg/dl). Secondary outcomes will be change in weight, blood pressure and related comorbidities (cardiovascular mortality, heart failure events, myocardial infarction and stroke). Study selection, data extraction and quality assessment will be conducted independently by at least two reviewers. A third reviewer will determine and resolve discrepancies. At least two independent reviewers will cross-check data synthesis. The quality of evidence of the review will be assessed according to the Grading of Recommendations Assessment, Development and Evaluation (GRADE) Tool.

DISCUSSION

The review is anticipated to provide up to date evidence for further studies and clinic practices regarding glycaemic control, hypoglycaemia, and hyperglycaemia issues. The results will be published in a peer-reviewed journal.

TRIAL REGISTRATION

PROSPERO CRD42020188399 .

Hybrid Closed-Loop Systems for the Treatment of Type 1 Diabetes: A Collaborative, Expert Group Position Statement for Clinical Use in Central and Eastern Europe

In both pediatric and adult populations with type 1 diabetes (T1D), technologies such as continuous subcutaneous insulin infusion (CSII), continuous glucose monitoring (CGM), or sensor-augmented pumps (SAP) can consistently improve glycemic control [measured as glycated hemoglobin (HbA1c) and time in range (TIR)] while reducing the risk of hypoglycemia. Use of technologies can thereby improve quality of life and reduce the burden of diabetes management compared with self-injection of multiple daily insulin doses (MDI). Novel hybrid closed-loop (HCL) systems represent the latest treatment modality for T1D, combining modern glucose sensors and insulin pumps with a linked control algorithm to offer automated insulin delivery in response to blood glucose levels and trends. HCL systems have been associated with increased TIR, improved HbA1c, and fewer hypoglycemic events compared with CSII, SAP, and MDI, thereby potentially improving quality of life for people with diabetes (PwD) while reducing the costs of treating short- and long-term diabetes-related complications. However, many barriers to their use and regional inequalities remain in Central and Eastern Europe (CEE). Published data suggest that access to diabetes technologies is hindered by lack of funding, underdeveloped health technology assessment (HTA) bodies and guidelines, unfamiliarity with novel therapies, and inadequacies in healthcare system capacities. To optimize the use of diabetes technologies in CEE, an international meeting comprising experts in the field of diabetes was held to map the current regional access, to present the current national reimbursement guidelines, and to recommend solutions to overcome uptake barriers. Recommendations included regional and national development of HTA bodies, efficient allocation of resources, and structured education programs for healthcare professionals and PwD. The responsibility of the healthcare community to ensure that all individuals with T1D gain access to modern technologies in a timely and economically responsible manner, thereby improving health outcomes, was emphasized, particularly for interventions that are cost-effective.

The Cost-Effectiveness of an Advanced Hybrid Closed-Loop System in People with Type 1 Diabetes: a Health Economic Analysis in Sweden

INTRODUCTION

Swedish National Diabetes Registry data show a correlation of improved glycemic control in people with type 1 diabetes (T1D) with increased use of diabetes technologies over the past 25 years. However, novel technologies are often associated with a high initial outlay. The aim of the present study was to evaluate the long-term cost-effectiveness of the advanced hybrid closed-loop (AHCL) MiniMed 780G system versus intermittently scanned continuous glucose monitoring (isCGM) plus self-injection of multiple daily insulin (MDI) or continuous subcutaneous insulin infusion (CSII) in people with T1D in Sweden.

METHODS

Outcomes were projected over patients' lifetimes using the IQVIA CORE Diabetes Model (v9.0). Clinical data, including changes in glycated hemoglobin (HbA1c) and hypoglycemia rates, were sourced from observational studies and a randomized crossover trial. Modeled patients were assumed to receive the treatments for their lifetimes, with HbA1c kept constant following the application of treatment effects. Costs were accounted from a societal perspective and expressed in Swedish krona (SEK). Utilities and days off work estimates were taken from published sources.

RESULTS

The MiniMed 780G system was associated with an improvement in life expectancy of 0.16 years and an improvement in quality-adjusted life expectancy of 1.95 quality-adjusted life years (QALYs) versus isCGM plus MDI or CSII. These clinical benefits were due to a reduced incidence and a delayed time to onset of diabetes-related complications. Combined costs were estimated to be SEK 727,408 (EUR 72,741) higher with MiniMed 780G, with treatment costs partially offset by direct cost savings from the avoidance of diabetes-related complications and indirect cost savings from the avoidance of lost workplace productivity. The MiniMed 780G system was associated with an incremental cost-effectiveness ratio of SEK 373,700 per QALY gained.

CONCLUSIONS

Based on a willingness-to-pay threshold of SEK 500,000 per QALY gained, the MiniMed 780G system was projected to be cost-effective versus isCGM plus MDI or CSII for the treatment of T1D in Sweden.

Flash glucose monitoring system: impact on glycemic control and body mass index in type 1 diabetes mellitus

OBJECTIVE

Flash glucose monitoring (FGM) is increasingly used in type 1 diabetes mellitus (T1D) management. This study aimed to assess glycated hemoglobin (HbA1c) and body mass index (BMI) in the first year of FGM use in patients with T1D and to identify predictive factors of benefit associated with its use.

METHODS

Retrospective study of T1D patients, using FGM for ≥ 6 months and under intensive insulin therapy with multiple daily injections.

RESULTS

In 179 patients with a median (Md) age of 43.0 years (P25 31.0; P75 52.0) and disease duration of 18.0 years (P25 10.0; P75 28.0), initial HbA1c was 7.9% (P25 7.2; P75 8.8) and initial BMI was 24.0 kg/m2 (P25 21.9; P75 26.2). With FGM, HbA1c improved significantly to 7.6% (P25 7.0; P75 8.3) at 6 months and 7.7% (P25 6.95; P75 8.5) at 12 months (p < 0.05), with more patients with HbA1c < 7% (16.1% vs 22.5%) and fewer patients with HbA1c ≥ 8% (49.1% vs 35.8%) (p < 0.05). Initial HbA1c 8.0-8.9% (HR 1.886; 95% CI 1.321-2.450) and ≥ 9.0% (HR 3.108, 95% CI 2.454-3.761) predicted greater HbA1c reduction. BMI increased significantly, especially between 6 and 12 months (BMI Md 23.8 [P25 21.9; P75 26.2] kg/m2 and 24.0 [P25 22.0; P75 26.2] kg/m2, respectively) (p < 0.05). Overweight (HR 4.319, 95% CI 3.185-5.453) and obesity (HR 8.112, 95% CI 3.919-12.306) predicted greater weight gain.

CONCLUSION

FGM use was associated with significant improvement in HbA1c, mainly in patients with worse previous glycemic control. It was also associated with increased BMI, especially if baseline BMI ≥ 25 kg/m2, so weight control strategies should be emphasized.

Effect of flash glucose monitoring in adults with type 1 diabetes: a nationwide, longitudinal observational study of 14,372 flash users compared with 7691 glucose sensor naive controls

AIMS/HYPOTHESIS

The aim of this work was to evaluate changes in glycaemic control (HbA_1c) and rates of severe hypoglycaemia over a 2 year period after initiation of flash glucose monitoring (FM) in type 1 diabetes.

METHODS

Using data from the Swedish National Diabetes Registry, 14,372 adults with type 1 diabetes with a new registration of FM during 2016-2017 and with continued FM for two consecutive years thereafter, and 7691 control individuals using conventional self-monitoring of blood glucose (SMBG) during the same observation period, were included in a cohort study. Propensity sores and inverse probability of treatment weighting (IPTW) were used to balance FM users with SMBG users. Changes in HbA_1c and events of severe hypoglycaemia were compared.

RESULTS

After the start of FM, the difference in IPTW change in HbA_1c was slightly greater in FM users compared with the control group during the follow-up period, with an estimated mean absolute difference of -1.2 mmol/mol (-0.11%) (95% CI -1.64 [-0.15], -0.75 [-0.07]; p < 0.0001) after 15-24 months. The change in HbA_1c was greatest in those with baseline HbA_1c ≥70 mmol/mol (8.5%), with the estimated mean absolute difference being -2.5 mmol/mol (-0.23%) (95% CI -3.84 [-0.35], -1.18 [-0.11]; p = 0.0002) 15-24 months post index. The change was also significant in the subgroups with initial HbA_1c ≤52 mmol/mol (6.9%) and 53-69 mmol/mol (7.0-8.5%). Risk of severe hypoglycaemic episodes was reduced by 21% for FM users compared with control individuals using SMBG (OR 0.79 [95% CI 0.69, 0.91]; p = 0.0014)].

CONCLUSIONS/INTERPRETATION

In this large cohort, the use of FM was associated with a small and sustained improvement in HbA_1c, most evident in those with higher baseline HbA_1c levels. In addition, FM users experienced lower rates of severe hypoglycaemic events compared with control individuals using SMBG for self-management of glucose control.

Characteristics of Continuous Glucose Monitoring Metrics in Persons with Type 1 and Type 2 Diabetes Treated with Multiple Daily Insulin Injections

Background: Although guidelines advocate similar continuous glucose monitoring (CGM) targets for insulin-treated persons with type 1 diabetes (T1D) and type 2 diabetes (T2D), it is unclear how these persons differ with respect to hypoglycemia, glucose variability, and other CGM metrics in clinical practice. Methods: We used data from 2 multicenter randomized-controlled trials (GOLD and MDI-Liraglutide) where 161 persons with T1D and 124 persons with T2D treated with multiple daily injections were included and monitored with masked CGM. Results: Persons from both cohorts had similar mean glucose levels, 10.9 mmol/L (196 mg/dL) in persons with T1D and 10.8 mmol/L (194 mg/dL) in persons with T2D. Time in hypoglycemia (<3.9 mmol/L [70 mg/dL]) was 5.1% and 1.0% for persons with T1D and T2D, respectively (P < 0.001). Corresponding estimates for the standard deviations of mean glucose levels were 4.4 mmol/L (79 mg/dL) versus 3.0 (54 mg/dL) (P < 0.001), for coefficient of variation 41% versus 28% (P < 0.001), and for time in range 38.2% versus 45.3%, respectively (P = 0.004). Mean C-peptide levels were 0.05 nmol/L and 0.67 nmol/L (P < 0.001) for persons with T1D and T2D, respectively. Conclusions: Persons with T1D compared with persons with T2D treated with multiple daily insulin injections spend considerably more time in hypoglycemia, have higher glucose variability, and less "time in range." This needs to be taken into account in daily clinical care and in recommended targets for CGM metrics.

Predicting and Preventing Nocturnal Hypoglycemia in Type 1 Diabetes Using Big Data Analytics and Decision Theoretic Analysis

Background: Despite new glucose sensing technologies, nocturnal hypoglycemia is still a problem for people with type 1 diabetes (T1D) as symptoms and sensor alarms may not be detected while sleeping. Accurately predicting nocturnal hypoglycemia before sleep may help minimize nighttime hypoglycemia. Methods: A support vector regression (SVR) model was trained to predict, before bedtime, the overnight minimum glucose and overnight nocturnal hypoglycemia for people with T1D. The algorithm was trained on continuous glucose measurements and insulin data collected from 124 people (22,804 valid nights of data) with T1D. The minimum glucose threshold for announcing nocturnal hypoglycemia risk was derived by applying a decision theoretic criterion to maximize expected net benefit. Accuracy was evaluated on a validation set from 10 people with T1D during a 4-week trial under free-living sensor-augmented insulin-pump therapy. The primary outcome measures were sensitivity and specificity of prediction, the correlation between predicted and actual minimum nocturnal glucose, and root-mean-square error. The impact of using the algorithm to prevent nocturnal hypoglycemia is shown in-silico. Results: The algorithm predicted 94.1% of nocturnal hypoglycemia events (<3.9 mmol/L, 95% confidence interval [CI], 71.3-99.9) with an area under the receiver operating characteristic curve of 0.86 (95% CI, 0.75-0.98). Correlation between actual and predicted minimum glucose was high (R = 0.71, P < 0.001). In-silico simulations showed that the algorithm could reduce nocturnal hypoglycemia by 77.0% (P = 0.006) without impacting time in target range (3.9-10 mmol/L). Conclusion: An SVR model trained on a big data set and optimized using decision theoretic criterion can accurately predict at bedtime if overnight nocturnal hypoglycemia will occur and may help reduce nocturnal hypoglycemia.

Hypoglycemia unawareness and autonomic dysfunction in diabetes: Lessons learned and roles of diabetes technologies

Impaired awareness of hypoglycemia (IAH) is a reduction in the ability to recognize low blood glucose levels that would otherwise prompt an appropriate corrective therapy. Identified in approximately 25% of patients with type 1 diabetes, IAH has complex pathophysiology, and might lead to serious and potentially lethal consequences in patients with diabetes, particularly in those with more advanced disease and comorbidities. Continuous glucose monitoring systems can provide real-time glucose information and generate timely alerts on rapidly falling or low blood glucose levels. Given their improvements in accuracy, affordability and integration with insulin pump technology, continuous glucose monitoring systems are emerging as critical tools to help prevent serious hypoglycemia and mitigate its consequences in patients with diabetes. This review discusses the current knowledge on IAH and effective diagnostic methods, the relationship between hypoglycemia and cardiovascular autonomic neuropathy, a practical approach to evaluating cardiovascular autonomic neuropathy for clinicians, and recent evidence from clinical trials assessing the effects of the use of CGM technologies in patients with type 1 diabetes with IAH.

Hypoglycemia in patient with type 2 diabetes treated with insulin: it can happen

There are many misconceptions about the prevalence and effects of hypoglycemia in people with type 2 diabetes (T2D), including hypoglycemia does not occur or does not have adverse consequences in T2D. This narrative review aims to help dispel these myths. Around 25% of people with T2D taking insulin for >5 years were found to have severe hypoglycemic events, which is comparable to the severe hypoglycemia rate in adults with type 1 diabetes (T1D) diagnosed within 5 years. The total number of hypoglycemic events among insulin-treated T2D, including severe hypoglycemia, is as high or higher than among those with T1D. Recent evidence suggests serious consequences of hypoglycemia may, in some respects, be greater in individuals with T2D, particularly regarding effects on the cardiovascular system. Hypoglycemia is generally patient-reported. Issues with hypoglycemia unawareness, limited glucose testing, limited recall, lack of event logging and fear of failure or shaming limits the number of hypoglycemic episodes reported by people with diabetes. Barriers to healthcare provider inquiry and reporting include lack of knowledge regarding the problem's magnitude, competing priorities during patient visits, lack of incentives to report and limitations to documentation systems for adequate reporting. All people with diabetes should be encouraged to discuss their experiences with hypoglycemia without judgment or shame. Glucose targets, testing schedules (blood glucose or continuous glucose monitoring) and treatment plans should be reviewed often and individualized to the minimize risk of hypoglycemia. Finally, people with T2D on insulin should always be encouraged to have oral glucose and rescue medication immediately available.

Comparing effects of continuous glucose monitoring systems (CGMs) and self-monitoring of blood glucose (SMBG) amongst adults with type 2 diabetes mellitus: a systematic review protocol

BACKGROUND

Continuous glucose monitorings (CGMs) have been used to manage diabetes with reasonable glucose control amongst patients with type 2 diabetes (T2D) in recent decades. CGMs measure interstitial fluid glucose levels to provide information about glucose levels, which identify fluctuation that would not have been identified with conventional self-monitoring. Self-monitoring of blood glucose (SMBG) is a classical tool to measure glycaemic changes. However, the effectiveness of glucose control, hypoglycemia, weight change, quality of life and user satisfaction, are needed to evaluate and compare CGMs and SMBG amongst adults with T2D.

METHODS

The review will compare the various forms of CGM systems (i.e flash CGM, real-time CGM, retrospective CGM) versus SMBG or usual intervention regarding diabetes management amongst adults with T2D. The following databases will be searched: Cochrane Library, PubMed, EMBASE, CINAHL, PsycINFO, Scopus and grey literature (ClinicalTrials.gov, PsycEXTRA, ProQuest Dissertations, Google Scholar and Theses Global) for the identification of studies. The studies involving adults (aged ≥ 18 years old) will be included. We will only include and summarise randomised clinical trials (RCTs) with respect to authors, publication type, year, status and type of devices. Studies published in English between February 2010 and March 2020, will be included as the field of CGMs amongst T2D patients has emerged over the last decade. Primary outcomes will be HbA1c (glycosylated haemoglobin level) (mmol/L), body weight (kg), time spent with hypoglycaemia (< 70 mg/dl) or hyperglycaemia (≥ 180 mg/dl), blood pressure (< 140/90 mmHg is considered as good management) and quality of life (understanding and feeling of living situation based on culture and value system). Secondary outcome measures will be user satisfaction (patient or treatment/intervention satisfaction or satisfaction scale) and barriers (physical and mental difficulties or issues). Study selection, data extraction and risk of bias assessment will be conducted independently by at least two reviewers. A third reviewer will determine and resolve discrepancies. Moreover, the quality of the evidence of the review will be assessed according to the Grading of Recommendations Assessment, Development and Evaluation tool (GRADE).

DISCUSSION

The review will synthesise evidence on the comparison between using CGMs and SMBG. The results will support researchers and health professionals to determine the most effective methods/technologies in the overall diabetes management.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42020149212.

Clinical Practice Recommendations on the Routine Use of Eversense, the First Long-Term Implantable Continuous Glucose Monitoring System

Background: The use of real-time continuous glucose monitoring (rtCGM) systems has proved to positively impact the management of type 1 diabetes with the potential to lower HbA1c, reduce frequency and time spent in hypoglycemia, and lower glycemic variability. Nevertheless, the acceptance of rtCGM remains below expectations and the dropout rate within the first year has been reported to be 27%. Besides financial reasons due to limited reimbursement, reasons include the need for frequent sensor replacement, the discomfort of wearing a sensor, the presence of adverse skin reactions, or privacy. Thus, novel approaches to rtCGM are desired to overcome these barriers. The first long-term implantable rtCGM system diversifies the field of glucose monitoring further. However, due to its novelty, there are no published clinical practice guidelines available. Aims: The aim of this article is to set the foundation for a best clinical practice for the everyday clinical care using a long-term implantable CGM system. Methods: An international expert panel for the long-term implantable CGM system developed this best practice guidance. All participants were certified and experienced in the use of the Eversense® long-term implantable CGM system. The workflows from the respective clinics were presented, discussed and are summarized in an ideal care workflow outlined in these practice recommendations. Results: The participants agreed on the following aspects: definition of the patient population that will benefit from a long-term implantable CGM device; real-world experience on safety and accuracy of a long-term CGM; definition of the ideal sensor position; description of the optimal process for sensor insertion, removal, and replacement.

Approach to Using Trend Arrows in the FreeStyle Libre Flash Glucose Monitoring Systems in Adults

The use of personal continuous glucose monitoring (CGM) has expanded dramatically among individuals with diabetes. CGM systems provide retrospective data, as well as the current glucose value and trend arrow data, which indicate the direction and velocity of changing glucose. In 2017, Aleppo and colleagues developed a simplified approach for adults with diabetes to safely adjust rapid-acting insulin doses using trend arrow information in the Dexcom G5 CGM system. Since then, the FreeStyle Libre and FreeStyle Libre 14-day CGM systems have become available in the United States; however, guidance on using trend arrow data that take the unique features of these systems into consideration is lacking. Specifically, the FreeStyle Libre systems do not have automatic alarms, which impact how the system and trend arrow data are used. The Endocrine Society convened an expert panel to address this gap and develop an approach to adjusting rapid-acting insulin doses for adults using trend arrows in the FreeStyle Libre systems. We based our approach on previous work and expanded upon engagement and scanning recommendations, and we incorporated pre-exercise planning specific to these systems. Our approach provides insulin dose adjustments as discrete insulin units based on an individual’s insulin sensitivity and directionality of the trend arrow. We focus on the needs of patients treated with multiple daily injections because these individuals currently make up a greater proportion of individuals on intensive insulin therapy. Our recommendations are intended to provide a safe, practical approach to using trend arrows in the FreeStyle Libre systems.

The new FreeStyle libre flash glucose monitoring system improves the glycaemic control in a cohort of people with type 1 diabetes followed in real-life conditions over a period of one year

AIMS

Using the novel FreeStyle Libre (FSL), glucose monitoring (FGM) system becomes increasingly popular among people with type 1 diabetes (T1D) and is associated with less and shorter hypoglycaemic events without deterioration of HbA1c. There are not yet data reporting the impact of FGM in people with T1D in real-life conditions. We sought of evaluating the tolerance, the acceptance and the efficacy of the FGM system in routine medical practice.

METHODS

This 12-month observational study included 120 individuals with T1D evaluated every 3 months. After having been instructed about FGM utilization, participants were trained to optimize the glycaemic control.

RESULTS

Participants stopped immediately of measuring capillary blood glucose (2.88 ± 0.12 per day) (mean ± SEM) after having received the first FSL device and the number of scans per day increased up to 8.87 ± 0.58 per day. HbA1c levels decreased from 8.51% ± 0.14% at baseline to 7.77% ± 0.09% after 3 months to slightly increase to 7.92% ± 0.09% at 12 months, in correlation with the number of scans per day. The number (but not the duration) of hypoglycaemic events slightly increased from 16.9 ± 1.44 per month at baseline to 24.0 ± 2.91 per month at 12 months, after reaching a peak of 26.4 ± 2.31 per month at 6 months. They were correlated with improved HbA1c.

CONCLUSION

Our study shows that using the FGM system improves HbA1c levels in people with T1D along with a moderate increase in the number of mild hypoglycaemic events. The new FGM system facilitates the therapeutic empowerment of people with T1D, but in a context of structured education.

Optimization of Insulin Regimen and Glucose Outcomes with Short-Term Real-Time Continuous Glucose Monitoring in Adult Type 1 Diabetes Patients with Suboptimal Control on Multiple Daily Injections: The Adult DIACCOR Study

BACKGROUND

The impact of a 7-day real-time continuous glucose monitoring (RT-CGM) on type 1 diabetes (T1D) management remains unclear in patients suboptimally controlled by multiple daily injections (MDI). The DIACCOR Study aimed to describe treatment decisions and glucose outcomes after a short-term RT-CGM sequence.

PATIENTS AND METHODS

This French multicenter longitudinal observational study included T1D patients with HbA1c >7.5% or history of severe hypoglycemia (SH) or recurrent documented hypoglycemia. A sensor was inserted at the inclusion visit, treatment changes were proposed by the investigator within 7-15 days ("INT" = MDI intensification, "CSII" = switch to continuous insulin infusion, or "ER" = educational reinforcement with no change in insulin regimen), and a 4-month follow-up visit (M4) was scheduled.

RESULTS

Four hundred fifty-nine patients were recruited by 155 diabetologists, 17.0% had SH history, and 24.2% had recurrent hypoglycemia. Baseline HbA1c was 8.34% ± 1.21% (>7.5% in 79.6%). Overall, 253 (64.4%), 64 (16.3%), and 76 patients (19.3%) were, respectively, included in the "INT," "CSII," and "ER" subgroups. The number of patients who experienced SH or recurrent hypoglycemia dropped dramatically (7.9% vs. 17.0% and 10.8% vs. 24.2%, respectively). The same trend was observed for ketoacidosis and ketosis (0.3% vs. 3.3% and 2.2% vs. 4.8%). At M4, HbA1c was significantly reduced in the whole cohort to 7.98% ± 1.01% (P < 0.0001). The adjusted differences in HbA1c level in the INT, CSII, and ER subgroups were, respectively, -0.32%, -0.69%, and -0.50% (P < 0.0001 for all).

CONCLUSION

In real-life setting, a 1-week diagnostic RT-CGM supports appropriate treatment changes in patients with uncontrolled T1D resulting in better glucose control and less hypoglycemia.