International Consensus on Use of Continuous Glucose Monitoring

Diabetes and Ramadan: Utility of flash-glucose monitoring derived markers of glycaemic control and comparison with glycosylated haemoglobin

AIMS

Flash glucose monitoring (FGM)-derived markers of glucose control and variability and laboratory measured HbA1c among patients with diabetes on insulin in context of Ramadan fasting (RF) were examined and compared.

METHODS

FGM data on insulin-treated patients (n = 20, age 42.3 ± 11.4 years; 18 male, 2 female; 13 with type 1 and 7 with type 2 diabetes) who fasted during Ramadan were used to calculate Q-score as an indicator of glycaemia before, during and after RF. Post-hoc analysis in a group of patients (n = 12) who had HbA1c available and appropriate for these periods was performed. Other relevant data were extracted from patient records.

RESULTS

Mean glucose (9.6 ± 1.32 v 10.78 ± 1.64 mmol/l; P < 0.0001) and Q-score increased significantly with Ramadan fasting and reduced after Ramadan. Post-hoc subgroup analysis showed a significant rise in eA1c (7.2 ± 0.4%; 55.0 ± 4.4 mmol/mol v 7.7 ± 0.5%; 61.0 ± 5.5 mmol/mol) but not in laboratory HbA1c with Ramadan fasting; eA1c reduced after Ramadan (P = 0.018).

CONCLUSIONS

Ramadan fasting was associated with a deterioration in overall glucose control and time in hyperglycaemia in insulin-treated patients. FGM-derived markers are useful and a preferable alternative to HbA1c in Ramadan studies.

Fast Assessment of Glycemic Control based on Continuous Glucose Monitoring Data

Diabetes has become a major public health problem in the world. In this context, early assessment of glycemic control is essential in order to avoid life-threatening health complications. A panel of diabetes experts have recently proposed a list of recommendations when using Continuous Glucose Monitoring (CGM) for glycemic control assessment including a minimum of two weeks of CGM data. A recent study has further introduced a metric called Glucose Profile Indicator (GPI) for CGM based diabetes management including a subset of the recommended CGM metrics. In this pilot study, it was investigated if less than two weeks of CGM data would impact the performance of GPI compared to the proposed two weeks of CGM data. Furthermore, logistic regression (LR) was used to examine if an improvement could be achieved taking as input the CGM metrics used to quantify GPI. The population mean accuracy for accumulated day 1 to 13 varied between 72.8 ± 2.0% - 98.3 ± 0.4% with no clear sign of improvement using LR. Hence, this indicates a trade-off between the amount of available CGM data and the precision in which the GPI outcome using all 14 days can be achieved when considering features of the GPI alone. Future work is needed to investigate if this trade-off can be improved by the use of additional features of the CGM.

A Review of Continuous Glucose Monitoring Data Interpretation in the Age of Automated Insulin Delivery

Using a continuous glucose monitor (CGM) improves glycemic control in patients with type 1 diabetes. The ambulatory glucose profile (AGP) has been recommended as a standard method for reporting CGM data. However, in recently developed automated insulin delivery (AID) systems, a standard format for reporting data has not yet been developed. Instead, reports are specific to each system being used. Currently, the only FDA approved AID system is a hybrid closed-loop insulin pump. In these systems, the patient is still required to announce a meal, respond to alerts, and keep the system in automated insulin delivery. The integrated pump and sensor information provides insights into how the system is performing, and how to make changes to tunable parameters, such as carbohydrate to insulin ratios. The reports also offer a window into human behavior related to performing diabetes tasks, responding to alarms, reasons for exiting HCL, and how glycemic goals are being met. This article reviews the pump and CGM data provided by several of the current closed-loop systems with a focus on systems that are currently approved in the United States (MiniMed™ 670G, Tandem Basal:IQ) and those used by patients using do-it-yourself systems. A step-wise approach to reviewing the nuances of these systems is provided. The comparison may reinforce the importance of the continued need for streamlining a standard report for providers to be able to interpret the CGM data of these systems.

Continuous glucose monitoring in pregnant women with type 1 diabetes: an observational cohort study of 186 pregnancies

AIMS/HYPOTHESIS

The aim of this study was to analyse patterns of continuous glucose monitoring (CGM) data for associations with large for gestational age (LGA) infants and an adverse neonatal composite outcome (NCO) in pregnancies in women with type 1 diabetes.

METHODS

This was an observational cohort study of 186 pregnant women with type 1 diabetes in Sweden. The interstitial glucose readings from 92 real-time (rt) CGM and 94 intermittently viewed (i) CGM devices were used to calculate mean glucose, SD, CV%, time spent in target range (3.5-7.8 mmol/l), mean amplitude of glucose excursions and also high and low blood glucose indices (HBGI and LBGI, respectively). Electronic records provided information on maternal demographics and neonatal outcomes. Associations between CGM indices and neonatal outcomes were analysed by stepwise logistic regression analysis adjusted for confounders.

RESULTS

The number of infants born LGA was similar in rtCGM and iCGM users (52% vs 53%). In the combined group, elevated mean glucose levels in the second and the third trimester were significantly associated with LGA (OR 1.53, 95% CI 1.12, 2.08, and OR 1.57, 95% CI 1.12, 2.19, respectively). Furthermore, a high percentage of time in target in the second and the third trimester was associated with lower risk of LGA (OR 0.96, 95% CI 0.94, 0.99 and OR 0.97, 95% CI 0.95, 1.00, respectively). The same associations were found for mean glucose and for time in target and the risk of NCO in all trimesters. SD was significantly associated with LGA in the second trimester and with NCO in the third trimester. Glucose patterns did not differ between rtCGM and iCGM users except that rtCGM users had lower LBGI and spent less time below target.

CONCLUSIONS/INTERPRETATION

Higher mean glucose levels, higher SD and less time in target range were associated with increased risk of LGA and NCO. Despite the use of CGM throughout pregnancy, the day-to-day glucose control was not optimal and the incidence of LGA remained high.

New Paradigm of Personalized Glycemic Control Using Glucose Temporal Density Histograms

BACKGROUND

Current methods used to assess glycemic control use averaged measures and provide little information on the glycemic pathology of the patients. In this article we propose visual tools and their related mathematical formulas that allow for improved characterization of the glycemic behavior and achieve better glycemic control.

METHODS

We present a reanalysis of published data, based on SMBG measurements from clinical trials of both men and women older than 18 years who were either healthy volunteers, prediabetes, or type 1 or type 2 diabetes. New graphic visualizations of glycemia as well as mathematical formulas that describe the glycemic behavior are presented and described, as well as suggested methods for their use to improve glycemic control.

RESULTS

Patients with different problems in their glycemic control had different histogram shapes. In addition, patients who had the same HbA1c level at the time of the trial revealed significantly different glucose histograms with different shapes, variability and glycemic burden. The derived graphic visualizations provided information about the temporal evolution of the glycemic control.

CONCLUSIONS

A paradigm change of the existing model of diabetes control is proposed, shifting from standardized treatment algorithms based on HbA1c follow-up to a new controlling approach that is based on the personal glucose density histogram. The histogram is an informative, detailed tool for the current patient glycemic behavior, and a future histogram can be targeted for a successful treatment. In addition, the glucose burden and the glucose severity index are proposed as informative markers for successful treatment. This is applicable to any glycemic data, by means of invasive and noninvasive glucometers.

The Relationships Between Time in Range, Hyperglycemia Metrics, and HbA1c

BACKGROUND

As the use of continuous glucose monitoring (CGM) increases, there is a need to better understand key metrics of time in range 70-180 mg/dL (TIR^70-180) and hyperglycemia and how they relate to hemoglobin A1c (A1C).

METHODS

Analyses were conducted utilizing datasets from four randomized trials encompassing 545 adults with type 1 diabetes (T1D) who had central-laboratory measurements of A1C. CGM metrics were calculated and compared with each other and A1C cross-sectionally and longitudinally.

RESULTS

Correlations among CGM metrics (TIR^70-180, time >180 mg/dL, time >250 mg/dL, mean glucose, area under the curve above 180 mg/dL, high blood glucose index, and time in range 70-140 mg/dL) were typically 0.90 or greater. Correlations of each metric with A1C were lower (absolute values 0.66-0.71 at baseline and 0.73-0.78 at month 6). For a given TIR^70-180 percentage, there was a wide range of possible A1C levels that could be associated with that TIR^70-180 level. On average, a TIR^70-180 of 70% and 50% corresponded with an A1C of approximately 7% and 8%, respectively. There also was considerable spread of change in A1C for a given change in TIR^70-180, and vice versa. An increase in TIR^70-180 of 10% (2.4 hours per day) corresponded to a decrease in A1C of 0.6%, on average.

CONCLUSIONS

In T1D, CGM measures reflecting hyperglycemia (including TIR and mean glucose) are highly correlated with each other but only moderately correlated with A1C. For a given TIR or change in TIR there is a wide range of possible corresponding A1C values.

A Century of Diabetes Technology: Signals, Models, and Artificial Pancreas Control

Arguably, diabetes mellitus is one of the best-quantified human conditions: elaborate in silico models describe the action of the human metabolic system; real-time signals such as continuous glucose monitoring are readily available; insulin delivery is being automated; and control algorithms are capable of optimizing blood glucose fluctuation in patients' natural environments. The transition of the artificial pancreas (AP) to everyday clinical use is happening now, and is contingent upon seamless concerted work of devices encompassing the patient in a digital treatment ecosystem. This review recounts briefly the story of diabetes technology, which began a century ago with the discovery of insulin, progressed through glucose monitoring and subcutaneous insulin delivery, and is now rapidly advancing towards fully automated clinically viable AP systems.

Improving pregnancy outcomes in women with diabetes mellitus: modern management

Women with pre-existing (type 1 or type 2) diabetes mellitus are at increased risk of pregnancy complications, such as congenital malformations, preeclampsia and preterm delivery, compared with women who do not have diabetes mellitus. Approximately half of pregnancies in women with pre-existing diabetes mellitus are complicated by fetal overgrowth, which results in infants who are overweight at birth and at risk of birth trauma and, later in life, the metabolic syndrome, cardiovascular disease and type 2 diabetes mellitus. Strict glycaemic control with appropriate diet, use of insulin and, if necessary, antihypertensive treatment is the cornerstone of diabetes mellitus management to prevent pregnancy complications. New technology for managing diabetes mellitus is evolving and is changing the management of these conditions in pregnancy. For instance, in Europe, most women with pre-existing diabetes mellitus are treated with insulin analogues before and during pregnancy. Furthermore, many women are on insulin pumps during pregnancy, and the use of continuous glucose monitoring is becoming more frequent. In addition, smartphone application technology is a promising educational tool for pregnant women with diabetes mellitus and their caregivers. This Review covers how modern diabetes mellitus management with appropriate diet, insulin and antihypertensive treatment in patients with pre-existing diabetes mellitus can contribute to reducing the risk of pregnancy complications such as congenital malformations, fetal overgrowth, preeclampsia and preterm delivery.

Advanced Technology in the Management of Diabetes: Which Comes First-Continuous Glucose Monitor or Insulin Pump?

PURPOSE OF REVIEW

In this article, we consider advanced technologies for the management of diabetes.

RECENT FINDINGS

Specifically, we pose the question of which should come first: an insulin pump (CSII) or a continuous glucose monitor (CGM)? Historical perspective on both insulin delivery and glucose measurement is provided. Recently published clinical trials are reviewed. Practical issues including quality of life, patient education, and out-of-pocket cost are discussed. Based on available evidence and clinical experience, we favor CGM as a first-line technology recommendation for the treatment of type 1 diabetes (T1D).

Pathophysiology and management of diabetic gastroenteropathy

Polyneuropathy is a common complication to diabetes. Neuropathies within the enteric nervous system are associated with gastroenteropathy and marked symptoms that severely reduce quality of life. Symptoms are pleomorphic but include nausea, vomiting, dysphagia, dyspepsia, pain, bloating, diarrhoea, constipation and faecal incontinence. The aims of this review are fourfold. First, to provide a summary of the pathophysiology underlying diabetic gastroenteropathy. Secondly to give an overview of the diagnostic methods. Thirdly, to provide clinicians with a focussed overview of current and future methods for pharmacological and nonpharmacological treatment modalities. Pharmacological management is categorised according to symptoms arising from the upper or lower gut as well as sensory dysfunctions. Dietary management is central to improvement of symptoms and is discussed in detail, and neuromodulatory treatment modalities and other emerging management strategies for diabetic gastroenteropathy are discussed. Finally, we propose a diagnostic/investigation algorithm that can be used to support multidisciplinary management.

Diabetes Care Editors' Expert Forum 2018: Managing Big Data for Diabetes Research and Care

Technological progress in the past half century has greatly increased our ability to collect, store, and transmit vast quantities of information, giving rise to the term "big data." This term refers to very large data sets that can be analyzed to identify patterns, trends, and associations. In medicine-including diabetes care and research-big data come from three main sources: electronic medical records (EMRs), surveys and registries, and randomized controlled trials (RCTs). These systems have evolved in different ways, each with strengths and limitations. EMRs continuously accumulate information about patients and make it readily accessible but are limited by missing data or data that are not quality assured. Because EMRs vary in structure and management, comparisons of data between health systems may be difficult. Registries and surveys provide data that are consistently collected and representative of broad populations but are limited in scope and may be updated only intermittently. RCT databases excel in the specificity, completeness, and accuracy of their data, but rarely include a fully representative sample of the general population. Also, they are costly to build and seldom maintained after a trial's end. To consider these issues, and the challenges and opportunities they present, the editors of Diabetes Care convened a group of experts in management of diabetes-related data on 21 June 2018, in conjunction with the American Diabetes Association's 78th Scientific Sessions in Orlando, FL. This article summarizes the discussion and conclusions of that forum, offering a vision of benefits that might be realized from prospectively designed and unified data-management systems to support the collective needs of clinical, surveillance, and research activities related to diabetes.

Comparison of flash glucose monitoring with real time continuous glucose monitoring in children and adolescents with type 1 diabetes treated with continuous subcutaneous insulin infusion

AIMS

In 2016 intermittently scanned continuous glucose monitoring (isCGM) became the first reimbursed CGM system in Belgium. Many children with type 1 diabetes (T1D) treated with multiple daily injections as well as with continuous subcutaneous insulin infusion (CSII) switched from self-monitoring of blood glucose to isCGM to monitor their treatment. In 2017 the Enlite® real-time CGM (rtCGM) system was reimbursed enabling its use with the Minimed® 640G insulin pump with integrated SmartGuard technology. In this study we compared the metabolic control during CSII with isCGM with that during rtCGM. Patient's satisfaction and side effects of the rtCGM system were also evaluated.

METHODS

20 children with T1D, aged 5-16 years, were included. Metabolic control during the last month of isCGM use was compared to that during the 3rd and 6th month of rtCGM.

RESULTS

Three patients stopped early rtCGM mainly due to calibration burden. The HbA1c level and the mean glucose value in the other patients did not change after switching to the rtCGM system. Glucose variability was smaller (46.2% vs 38.4% and 36.4%, p = 0.000). Time in hypoglycemia (<70 mg/dl) was lower (7.4% vs 1.6% and 1.5%, p = 0.000). The main patient inconvenience was the sensor calibration.

CONCLUSIONS

Our data show that during Enlite® rtCGM with the Minimed® 640G pump system glucose variability was smaller and the patients spent less time in hypoglycemia than during isCGM. The need for timely calibrations is considered as the main drawback of the system.

Real-Life Management and Effectiveness of Insulin Pump with or Without Continuous Glucose Monitoring in Adults with Type 1 Diabetes

INTRODUCTION

To describe and compare the routine use of continuous subcutaneous insulin infusion (CSII) in type 1 diabetes (T1D) patients with and without continuous glucose monitoring (CGM) in routine clinical practice and its relationship with glycemic outcomes.

METHODS

Retrospective observational case-control study collecting routine use of CSII and CGM in T1D patients between January 2016 and December 2016. Patients with T1D using sensor augmented pump (SAP) were matched by sex and disease duration in a 1:3 ratio with those treated only with CSII. Patients used a Paradigm Veo or 640G Medtronic-Minimed^® insulin pump with or without a glucose sensor (Enlite, Medtronic-Minimed^®) for at least 12 months.

RESULTS

A total of 160 subjects with T1D were included, 40 using SAP and 120 on CSII (age 47 ± 12 years, 88 women, diabetes duration 29 ± 9.0 years, 10 ± 4.7 years on CSII, HbA_1C 7.6 ± 0.8%). Those in SAP therapy used the sensor 63% of time, performed less self-monitored blood glucose (SMBG)/day (3.3 ± 1.9 vs. 4.5 ± 2.0; p < 0.01), more bolus/day (6.2 ± 3.6 vs. 4.8 ± 1.6; p < 0.05), more basal insulin segment/day (6.5 ± 2.1 vs. 5.9 ± 1.5; p < 0.05), and more suspension time of the pump (97 ± 93 vs. 9.6 ± 20 min/day; p < 0.0001). Regarding metabolic control, SAP therapy patients had lower HbA_1c (7.4 ± 0.7 vs. 7.7 ± 0.9%; p = 0.068), lower average SMBG value (151 ± 32 vs. 163 ± 30 mg/dL; p < 0.05), a lower percentage of SMBG values greater than 180 mg/dL (30 ± 19 vs. 37 ± 16%; p < 0.05) with no differences in SMBG values less than 70 mg/dL (12 ± 8.0 vs. 9.8 ± 9.8%; p = 0.33) compared with patients on CSII. There were no differences in bolus wizard targets or in insulin/carbohydrate ratios per day.

CONCLUSION

In a real-world setting, SAP therapy is associated with more self-adjustments of insulin therapy when compared to CSII alone. This could result in an improvement in glucose control.

Beyond HbA1c : using continuous glucose monitoring metrics to enhance interpretation of treatment effect and improve clinical decision-making

Assessment of glycaemic outcomes in the management of Type 1 and Type 2 diabetes has been revolutionized in the past decade with the increasing availability of accurate, user-friendly continuous glucose monitoring (CGM). This advancement has brought a need for new techniques to appropriately analyse and understand the voluminous and complex CGM data for application in research-related goals and clinical guidance for individuals. Traditionally, HbA_1c was established using the Diabetes Control and Complications Trial (DCCT) and other trials as the ultimate measure of glycaemic control in terms of efficacy and, by default, risk of microvascular complications of diabetes. However, it is acknowledged that HbA_1c alone is inadequate at describing an individual's daily glycaemic variation and risks for hypo- and hyperglycaemia, and it does not provide the guidance needed to decrease those risks. CGM data provide means by which to characterize an individual's daily glycaemic excursions on a different time scale measured in minutes rather than months. As a consequence, clinical reports, such as the ambulatory glucose profile, increasingly include summary statistics related to averages (mean glucose, time in range) as well as markers related to glycaemic variability (coefficient of variation, standard deviation). However, there is a need to translate those metrics into specific risks that can be addressed in an actionable plan by individuals with diabetes and providers. This review presents several clinical scenarios of glycaemic outcomes from CGM data that can be analysed to describe glycaemic variability and its attendant risks of hyperglycaemia and hypoglycaemia, moving towards relevant interpretation of the complex CGM data streams.

Effect of Education on Impaired Hypoglycemia Awareness and Glycemic Variability in Children and Adolescents with Type 1 Diabetes Mellitus

OBJECTIVE

The aim of this study was to determine the prevalence of impaired hypoglycemia awareness (IHA) in children and adolescents with type 1 diabetes mellitus using a professional continuous glucose monitoring (CGM) system and to show the effect of structured education on glycemic variability (GV) in children and adolescents with IHA.

METHODS

Forty type 1 diabetic children and adolescents with a diabetes duration of at least five years were eligible for inclusion in this prospective, quantitative study. All subjects were asked about their history of being aware of the symptoms of hypoglycemia using a questionnaire. Professional CGM was conducted in all of the patients for six days. The frequency of IHA detected by comparison of CGM and logbook reports were analyzed. Patients with identified IHA underwent a structured training program. After three months, CGM was re-applied to patients with IHA.

RESULTS

The study was completed by 37 diabetic children and adolescents. After the initial CGM, nine patients (24.3%) were found to have had episodes of IHA. Area under the curve (AUC) for hypoglycemia and number of low excursions were; 1.81±0.95 and 8.33±3.60 for the IHA group at the beginning of the study. AUC for hypoglycemia was 0.43±0.47 after three months of structured education the IHA patients (p=0.01). Coefficient of variation which shows primary GV decreased significantly although unstable at the end of education in IHA patients (p=0.03).

CONCLUSION

CGM is a valuable tool to diagnose IHA. IHA, GV and time in range can be improved by education-based intervention.

Hybrid Closed-Loop Control Is Safe and Effective for People with Type 1 Diabetes Who Are at Moderate to High Risk for Hypoglycemia

Background: Typically, closed-loop control (CLC) studies excluded patients with significant hypoglycemia. We evaluated the effectiveness of hybrid CLC (HCLC) versus sensor-augmented pump (SAP) in reducing hypoglycemia in this high-risk population. Methods: Forty-four subjects with type 1 diabetes, 25 women, 37 ± 2 years old, HbA1c 7.4% ± 0.2% (57 ± 1.5 mmol/mol), diabetes duration 19 ± 2 years, on insulin pump, were enrolled at the University of Virginia (N = 33) and Stanford University (N = 11). Eligibility: increased risk of hypoglycemia confirmed by 1 week of blinded continuous glucose monitor (CGM); randomized to 4 weeks of home use of either HCLC or SAP. Primary/secondary outcomes: risk for hypoglycemia measured by the low blood glucose index (LBGI)/CGM-based time in ranges. Results: Values reported: mean ± standard deviation. From baseline to the final week of study: LBGI decreased more on HCLC (2.51 ± 1.17 to 1.28 ± 0.5) than on SAP (2.1 ± 1.05 to 1.79 ± 0.98), P < 0.001; percent time below 70 mg/dL (3.9 mmol/L) decreased on HCLC (7.2% ± 5.3% to 2.0% ± 1.4%) but not on SAP (5.8% ± 4.7% to 4.8% ± 4.5%), P = 0.001; percent time within the target range 70-180 mg/dL (3.9-10 mmol/L) increased on HCLC (67.8% ± 13.5% to 78.2% ± 10%) but decreased on SAP (65.6% ± 12.9% to 59.6% ± 16.5%), P < 0.001; percent time above 180 mg/dL (10 mmol/L) decreased on HCLC (25.1% ± 15.3% to 19.8% ± 10.1%) but increased on SAP (28.6% ± 14.6% to 35.6% ± 17.6%), P = 0.009. Mean glucose did not change significantly on HCLC (144.9 ± 27.9 to 143.8 ± 14.4 mg/dL [8.1 ± 1.6 to 8.0 ± 0.8 mmol/L]) or SAP (152.5 ± 24.3 to 162.4 ± 28.2 [8.5 ± 1.4 to 9.0 ± 1.6]), P = ns. Conclusions: Compared with SAP therapy, HCLC reduced the risk and frequency of hypoglycemia, while improving time in target range and reducing hyperglycemia in people at moderate to high risk of hypoglycemia.

Glucose Variables in Type 1 Diabetes Studies With Dapagliflozin: Pooled Analysis of Continuous Glucose Monitoring Data From DEPICT-1 and -2

OBJECTIVE

This pooled analysis assessed continuous glucose monitoring (CGM) in patients with inadequately controlled type 1 diabetes (HbA_1c ≥7.7 to ≤11.0% [≥61 to ≤97 mmol/mol]) who received dapagliflozin as an adjunct to adjustable insulin.

RESEARCH DESIGN AND METHODS

CGM data were pooled from two 24-week, double-blind, randomized, phase 3 studies: Dapagliflozin Evaluation in Patients with Inadequately Controlled Type 1 Diabetes (DEPICT-1 and DEPICT-2). These studies comprised 1,591 patients receiving dapagliflozin 5 mg (n = 530), dapagliflozin 10 mg (n = 529), or placebo (n = 532).

RESULTS

Baseline characteristics were balanced between treatment groups. Patients receiving dapagliflozin 5 mg or 10 mg both spent more time with blood glucose in the range >3.9 to ≤10.0 mmol/L (>70 to ≤180 mg/dL) over 24 h than those receiving the placebo. The adjusted mean (SE) change from baseline at week 24 was 6.48% (0.60) with dapagliflozin 5 mg, 8.08% (0.60) with dapagliflozin 10 mg, and -2.59% (0.61) with placebo. At week 24, the mean amplitude of glucose excursion over 24 h, mean 24-h glucose values, and postprandial glucose values were also improved in patients receiving dapagliflozin over those receiving placebo. No marked differences were found at week 24 between dapagliflozin 5 or 10 mg and placebo in the percentage of glucose values ≤3.9 mmol/L (≤70 mg/dL) or ≤3.0 mmol/L (≤54 mg/dL) over 24 h, or in nocturnal (0000-0559 h) glucose values ≤3.9 mmol/L (≤70 mg/dL).

CONCLUSIONS

In patients with type 1 diabetes, treatment with dapagliflozin over 24 weeks improved time in range, mean glucose, and glycemic variability without increasing the time spent in the range indicating hypoglycemia.

Utilizing the Ambulatory Glucose Profile to Standardize and Implement Continuous Glucose Monitoring in Clinical Practice

Use of continuous glucose monitoring (CGM) is recognized as a valuable component of diabetes self-management and is increasingly considered a standard of care for individuals with diabetes who are treated with intensive insulin therapy. As the clinical use of CGM technology expands, consistent and standardized glycemic metrics and glucose profile visualization have become increasingly important. A common set of CGM metrics has been proposed by an international expert panel in 2017, including standard definitions of time in ranges, glucose variability, and adequacy of data collection. We describe the core CGM metrics, as well as the standardized glucose profile format consolidating 2 weeks of CGM measurements, referred to as the ambulatory glucose profile (AGP), which was also recommended by the CGM expert panel. We present an updated AGP report featuring the core CGM metrics and a visualization of glucose patterns that need clinical attention. New tools for use by clinicians and patients to interpret AGP data are reviewed. Strategies based on the authors' experience in implementing CGM technology across the clinical care spectrum are highlighted.

A View Beyond HbA1c: Role of Continuous Glucose Monitoring

Hemoglobin A1C (HbA1c) is used as an index of average blood glucose measurement over a period of months and is a mainstay of blood glucose monitoring. This metric is easy to measure and relatively inexpensive to obtain, and it predicts diabetes-related microvascular complications. However, HbA1c provides only an approximate measure of glucose control; it does not address short-term glycemic variability (GV) or hypoglycemic events. Continuous glucose monitoring (CGM) is a tool which helps clinicians and people with diabetes to overcome the limitations of HbA1c in diabetes management. Time spent in the glycemic target range and time spent in hypoglycemia are the main CGM metrics that provide a more personalized approach to diabetes management. Moreover, the glucose management indicator (GMI), which calculates an approximate HbA1c level based on the average CGM-driven glucose level, facilitates individual decision-making when the laboratory-measured HbA1c and estimated HbA1c are discordant. GV, on the other hand, is a measure of swings in blood glucose levels over hours or days and may contribute to diabetes-related complications. In addition, addressing GV is a major challenge during the optimization of glycemia. The degree of GV is associated with the frequency, duration, and severity of the hypoglycemic events. Many factors affect GV in a patient, including lifestyle, diet, the presence of comorbidities, and diabetes therapy. Recent evidence supports the use of some glucose-lowering agents to improve GV, such as the new ultra-long acting insulin analogs, as these agents have a smoother pharmacodynamic profile and improve glycemic control with fewer fluctuations and fewer nocturnal hypoglycemic events. These newer glucose-lowering agents (such as incretin hormones or sodium-glucose cotransporter 2 inhibitors) can also reduce the degree of GV. However, randomized trials are needed to evaluate the effect of GV on important diabetes outcomes. In this review, we discuss the role of HbA1c as a measure of glycemic control and its limitations. We also explore additional glycemic metrics, with a focus on time (duration) in glucose target range, time (duration) in hypoglycemia, GV, GMI, and their correlation with clinical outcomes.

Efficacy and safety of suspend-before-low insulin pump technology in hypoglycaemia-prone adults with type 1 diabetes (SMILE): an open-label randomised controlled trial

BACKGROUND

Hypoglycaemia unawareness and severe hypoglycaemia can increase fear of hypoglycaemia and the risk of subsequent hypoglycaemic events. We aimed to assess the safety and efficacy of insulin pump therapy with integrated continuous glucose monitoring (CGM) and a suspend-before-low feature (Medtronic MiniMed 640G with SmartGuard) in hypoglycaemia-prone adults with type 1 diabetes.

METHODS

SMILE was an open-label randomised controlled trial done in people aged 24-75 years with type 1 diabetes for 10 years or longer, HbA_1c values of 5·8-10·0% (40-86 mmol/mol), and at high risk of hypoglycaemia (recent severe hypoglycaemia or hypoglycaemia unawareness defined by a Clarke or Gold score ≥4). Participants were enrolled from 16 centres (eg, clinics, hospitals, or university medical centres) in Canada, France, Italy, the Netherlands, and the UK. After baseline run-in phase (2 weeks), participants were randomly assigned to the MiniMed 640G pump (continuous subcutaneous insulin infusion) with self-monitoring of blood glucose (control group) or to the MiniMed 640G system with the suspend-before-low feature enabled (intervention group), for 6 months. The study statistician analysing the data was masked to group assignment until final database lock; because of the nature of the intervention, participants and treating clinicians could not be masked to group assignment. The primary outcome was the mean number of sensor hypoglycaemic events, defined as 55 mg/dL (3·1 mmol/L) or lower, and was analysed on an intention-to-treat basis in all randomly assigned participants. This trial is registered with ClinicalTrials.gov, number NCT02733991, and is completed.

FINDINGS

Between Dec 7, 2016, and March 27, 2018, 153 participants with a mean age 48·2 [12·4] years were randomly assigned: 77 to the control group (mean age 47·4 [12·5] years) and 76 to the intervention group (mean age 49·0 [12·2] years). After 6 months, the intervention group had significantly fewer hypoglycaemic events per participant per week (1·1 [SD 1·2] vs 4·1 [3·4] mean events, model-based treatment effect -2·9 [95% CI -3·5 to -2·3]; p<0·0001) and fewer severe hypoglycaemic events (instances requiring third-party assistance with carbohydrate or glucagon administration, or other resuscitative actions) overall (three vs 18; p=0·0036). The most common adverse events were hypoglycaemia (observed in ten [13%] of 77 participants in the control group vs four [5%] of 76 in the intervention group) and hyperglycaemia (observed in seven [9%] of 77 vs seven [9%] of 76). No serious adverse device effects or episodes of diabetic ketoacidosis were reported.

INTERPRETATION

Insulin pump therapy with integrated CGM and a suspend-before-low feature reduced the frequency of sensor hypoglycaemic and severe hypoglycaemic events in hypoglycaemia-prone adults compared with use of continuous subcutaneous insulin infusion without real-time CGM. These results suggest that this technology could be beneficial in this high-risk population.

FUNDING

Medtronic International Trading Sàrl and Medtronic Canada.

Development of a Single-Site Device for Conjoined Glucose Sensing and Insulin Delivery in Type-1 Diabetes Patients

OBJECTIVE

Diabetes patients are increasingly using a continuous glucose sensor to monitor blood glucose and an insulin pump connected to an infusion cannula to administer insulin. Applying these devices requires two separate insertion sites, one for the sensor and one for the cannula. Integrating sensor with cannula to perform glucose sensing and insulin infusion through a single insertion site would significantly simplify and improve diabetes treatment by reducing the overall system size and the number of necessary needle pricks. Presently, several research groups are pursuing the development of combined glucose sensing and insulin infusion devices, termed single-port devices, by integrating sensing and infusion technologies created from scratch.

METHODS

Instead of creating the device from scratch, we utilized already existing technologies and introduced three design concepts of integrating commercial glucose sensors and infusion cannulas. We prototyped and evaluated each concept according to design simplicity, ease of insertion, and sensing accuracy.

RESULTS

We found that the best single-port device is the one in which a Dexcom sensor is housed inside a Medtronic cannula so that its glucose sensitive part protrudes from the cannula tip. The low degree of component modification required to arrive at this configuration allowed us to test the efficiency and safety of the device in humans.

CONCLUSION

Results from these studies indicate the feasibility of combining commercial glucose sensing and insulin delivery technologies to realize a functional single-port device.

SIGNIFICANCE

Our development approach may be generally useful to provide patients with innovative medical devices faster and at reduced costs.

Point-of-care testing in diabetes management

The prevalence of diabetes mellitus (DM) has rapidly increased over the last decades, reaching epidemic magnitudes, particularly in lowand middle-income countries. Point-of-care (POC) technology enables decision making near or at the site of patient care. Portable blood glucose meters and HbA1c testing are used by the healthcare provider and millions of patients with diabetes to monitor the safety and effectiveness of the diabetes treatment. However, POC capillary blood glucose and POC HbA1c testing are not recommended for diabetes diagnosis. Rather, they have been used for screening diabetes in lowand middle-income countries to decrease the disease burden.

Flash glucose monitoring for the safe use of a 2-day intermittent energy restriction in patients with type 2 diabetes at risk of hypoglycaemia: An exploratory study

AIMS

Two medication change protocols were tested, both based on haemoglobin A1c (HbA1c), with one protocol also accounting for hypoglycaemic events. The aim was to compare the two protocols during intermittent energy restriction (5:2 diet).

METHODS

Forty-two adults with type 2 diabetes (HbA1c ≥ 7% [53 mmol/mol], BMI of ≥27 kg/m²) treated with sulphonylureas and/or insulin were recruited and randomised 1:1 to fixed or adjusted medication protocols. Participants experiencing hypoglycaemia during a 2-week usual diet period then followed the 5:2 diet for 2 weeks (2 non-consecutive very-low-calorie days [500-600 kcal] and 5 habitual eating days/week), following the allocated medication protocol. The primary outcome was to determine if the adjusted protocol was superior to the fixed protocol at reducing hypoglycaemic events during the 5:2 diet. Flash glucose monitoring was used throughout to detect hypoglycaemia.

RESULTS

There was a significant difference in change in the number of hypoglycaemic events between fixed and adjusted protocols (-1.0 vs. -3.5; P = 0.04). Over 60% of participants on the adjusted protocol had no hypoglycaemic events.

CONCLUSIONS

This pilot study demonstrates the importance of assessing the risk of hypoglycaemia before starting a 5:2 diet and that the adjusted medication protocol is likely the best option for patients at risk.

CLINICAL TRIAL REGISTRY

This study has been registered with the Australia New Zealand Clinical Trial Registry (ANZCTR) www.anzctr.org.au and given the registration number ACTRN12617000512325.

Improved Time in Range and Glycemic Variability With Sotagliflozin in Combination With Insulin in Adults With Type 1 Diabetes: A Pooled Analysis of 24-Week Continuous Glucose Monitoring Data From the inTandem Program

OBJECTIVE

To evaluate effects of the dual sodium-glucose cotransporter (SGLT) 1 and SGLT2 inhibitor sotagliflozin in combination with insulin on glucose time in range (TIR) and glucose excursions, postprandial glucose (PPG), and other glycemic metrics in adults with type 1 diabetes using masked continuous glucose monitoring (CGM).

RESEARCH DESIGN AND METHODS

Data sets from the inTandem1 (clinical trial reg. no. NCT02384941) and inTandem2 (clinical trial reg. no. NCT02421510) double-blind randomized trials evaluating sotagliflozin versus placebo in adults with type 1 diabetes treated with optimized insulin were pooled for analyses of masked CGM data from a subset of participants in each trial. The pooled cohort included patients randomized to receive placebo (n = 93), sotagliflozin 200 mg (n = 89), or sotagliflozin 400 mg (n = 96). The primary outcome was change from baseline to week 24 in glucose TIR (3.9-10.0 mmol/L [70-180 mg/dL]). Secondary end points included time below and above the target range and 2-h PPG level assessed after a standardized mixed meal.

RESULTS

Mean percentage of glucose TIR/percentage time spent at <3.9 mmol/L (<70 mg/dL) during week 24 was 51.6%/5.9%, 57.8%/5.5%, and 64.2%/5.5% with placebo, sotagliflozin 200 mg, and sotagliflozin 400 mg, respectively, which corresponded to a placebo-adjusted change from a baseline of +5.4%/-0.3% (P = 0.026; +1.3/-0.1 h/day) for sotagliflozin 200 mg and +11.7%/-0.1% (P < 0.001; +2.8/-0.02 h/day) for sotagliflozin 400 mg. Placebo-adjusted PPG reductions were 1.9 ± 0.7 mmol/L (35 ± 13 mg/dL; P = 0.004) and 2.8 ± 0.7 mmol/L (50 ± 13 mg/dL; P < 0.001) with sotagliflozin 200 and 400 mg, respectively.

CONCLUSIONS

Combined with optimized insulin in type 1 diabetes, sotagliflozin significantly increased glucose TIR without increasing time spent at <3.9 mmol/L and reduced PPG, thereby improving glycemic control.

Comparison of Continuous Glucose Monitoring Accuracy Between Abdominal and Upper Arm Insertion Sites

Background: The aim was to compare the accuracy of the Dexcom^® G4 Platinum continuous glucose monitor (CGM) sensor inserted on the upper arm and the abdomen in adults. Methods: Fourteen adults with type 1 diabetes wore two CGMs, one placed on the upper arm and one placed on the abdomen. Three in-clinic visits of 5 h with YSI (2300 STAT, Yellow Springs Instrument) measurements as comparator were performed. Each visit was followed by 4 days with seven-point self-monitoring of blood glucose (SMBG) in free-living conditions. Accuracy analyses on the paired CGM-YSI and CGM-SMBG measurements of the two CGM sensors were performed. Results: Using YSI as comparator, the overall Mean Absolute Relative Difference (MARD) for the CGM_abd was 12.3% and CGM_arm was 12.0%. The percentage of the CGM measurements in zone A of Clarke error grid analysis for the CGM_abd was 85.6% and CGM_arm was 86.0%. The hypoglycemia sensitivity for the CGM_abd and CGM_arm was 69.3%. Using SMBG as comparator, the overall MARD for the CGM_abd was 12.5% and CGM_arm was 12.0%. The percentage of the CGM measurements in zone A for the CGM_abd was 84.1% and the CGM_arm was 85.0%. The hypoglycemia sensitivity for the CGM_abd was 60.0% and the CGM_arm was 71.1%. All the P-values from the comparisons between the accuracy of CGM_abd and CGM_arm were >0.05. Conclusion: The accuracy of a Dexcom G4 Platinum CGM sensor placed on the upper arm was not different from the accuracy of the sensor placed on the abdomen in adults with type 1 diabetes.

Is there an optimal strategy for real-time continuous glucose monitoring in pediatrics? A 12-month French multi-center, prospective, controlled randomized trial (Start-In!)

AIM

To compare the efficacy of three strategies for real-time continuous glucose monitoring (RT-CGM) over 12 months in children and adolescents with type 1 diabetes.

METHODS

A French multicenter trial (NCT00949221) with a randomized, controlled, prospective, open, and parallel-group design was conducted. After 3 months of RT-CGM, patients were allocated to one of three groups: return to self-monitoring of blood glucose, continuous CGM (80% of the time), or discontinuous CGM (40% of the time). The primary outcome was hemoglobin A1c (HbA1c) levels from 3 to 12 months. The secondary outcomes were acute metabolic events, hypoglycemia, satisfaction with CGM and cost.

RESULTS

We included 151 subjects, aged 2 to 17 years, with a mean HbA1c level of 8.5% (SD0.7; 69 mmol/mol). The longitudinal change in HbA1c levels was similar in all three groups, at 3, 6, 9 and 12 months. The medical secondary endpoints did not differ between groups. The rate of severe hypoglycemia was significantly lower than that for the pretreatment year for the entire study population. Subjects reported consistent use and good tolerance of the device, regardless of age or insulin treatment. The use of full-time RT-CGM for 3 months costs the national medical insurance system €2629 per patient.

CONCLUSION

None of the three long-term RT-CGM strategies evaluated in pediatric type 1 diabetes was superior to the others in terms of HbA1c levels. CGM-use for 3 months decreased rates of severe hypoglycemia. Our results confirm the feasibility of long-term RT-CGM-use and the need to improve educational support for patients and caregivers.

Suboptimal Nocturnal Glucose Control Is Associated With Large for Gestational Age in Treated Gestational Diabetes Mellitus

OBJECTIVE

Continuous glucose monitoring (CGM) provides far greater detail about fetal exposure to maternal glucose across the 24-h day. Our aim was to examine the role of temporal glucose variation on the development of large for gestational age (LGA) infants in women with treated gestational diabetes mellitus (GDM).

RESEARCH DESIGN AND METHODS

We performed a prospective observational study of 162 pregnant women with GDM in specialist multidisciplinary antenatal diabetes clinics. Participants undertook 7-day masked CGM at 30-32 weeks' gestation. Standard summary indices and glycemic variability measures of CGM were calculated. Functional data analysis was applied to determine differences in temporal glucose profiles. LGA was defined as birth weight ≥90th percentile adjusted for infant sex, gestational age, maternal BMI, ethnicity, and parity.

RESULTS

Mean glucose was significantly higher in women who delivered an LGA infant (6.2 vs. 5.8 mmol/L, P = 0.025, or 111.6 mg/dL vs. 104.4 mg/dL). There were no significant differences in percentage time in, above, or below the target glucose range or in glucose variability measures (all P > 0.05). Functional data analysis revealed that the higher mean glucose was driven by a significantly higher glucose for 6 h overnight (0030-0630 h) in mothers of LGA infants (6.0 ± 1.0 mmol/L vs. 5.5 ± 0.8 mmol/L, P = 0.005, and 108.0 ± 18.0 mg/dL vs. 99.0 ± 14.4 mg/dL).

CONCLUSIONS

Mothers of LGA infants run significantly higher glucose overnight compared with mothers without LGA infants. Detecting and addressing nocturnal glucose control may help to further reduce rates of LGA in women with GDM.

Translating glycated hemoglobin A1c into time spent in glucose target range: A multicenter study

BACKGROUND

Approximately 90% of children and adolescents with type 1 diabetes in Sweden use continuous glucose monitoring (CGM), either as real-time CGM or intermittently scanned CGM to monitor their glucose levels. Time in target range (TIT) is an easily understandable metric for assessing glycemic control.

OBJECTIVE

The aim of this study was to examine the relation between TIT and hemoglobin A1c (HbA1c).

SUBJECTS AND METHODS

Subjects were recruited from three diabetes care centers in Sweden. Glucose data were collected for 133 children and adolescents with type 1 diabetes through CGM using Diasend. Subjects with registration time over 80% were included in the analysis. HbA1c was collected from SWEDIABKIDS, the Swedish pediatric diabetes quality registry. TIT was defined as 3.9 to 7.8 mmol/L (70-140 mg/dL) and time in range (TIR) as 3.9 to 10 mmol/L (70-180 mg/dL).

RESULTS

During the period of 60 days, 105 subjects provided complete data for analysis. Mean age was 12.2 (±3.3) years, mean HbA1c was 53.9 (±8.2) mmol/mol or 7.1% (±0.7%). Mean sensor glucose value was 8.6 (±1.3) mmol/L, mean coefficient of variation was 42.2% (±7.2%), mean TIT was 40.9% (±SD 12.2%), and mean TIR was 60.8% (±13.1%). There was a significant nonlinear relation between TIT during 60 days and HbA1c, R² = 0.69.

CONCLUSION

This study suggests a nonlinear relation between time spent in glucose target range and HbA1c. The finding implies that time spent in TIT could be a useful metric in addition to HbA1c to assess glycemic control.

The use of real time continuous glucose monitoring or flash glucose monitoring in the management of diabetes: A consensus view of Italian diabetes experts using the Delphi method

Until recently, in Italy, the use of continuous glucose monitoring (CGM) systems has been limited, but is now rapidly increasing, including the so-called real-time CGM (rtCGM) and the intermittently viewed CGM (iCGM), also called Flash Glucose Monitoring (FGM). These technologies overcome many of the limitations of self-monitoring of blood glucose (SMBG) by fingerprick and allow to go beyond HbA1c to check glucose control in diabetes. However, standardized protocols for applying and interpreting rtCGM and FGM data are lacking. In this paper, we delineate a consensus amongst Italian diabetes physicians on the attributes of rtCGM and FGM technologies, and introduce a consistent approach for their use by Italian healthcare professionals. Most experts consider rtCGM and FGM as two separate categories of interstitial subcutaneous fluid (ISF) sensing technologies, and see them as superior to SMBG. Furthermore, there is strong consensus that rtCGM and FGM reduce hypoglycemia risk, increase the amount of time in the target glucose range and augment treatment satisfaction. However, there is still no agreement on the indication of the FGM for subjects who suffer asymptomatic hypoglycemia. Consensus on the role of education in initiating and optimizing use of rtCGM/FGM and about the interpretation of glucose trends was near unanimous, whereas no consensus was reached on the statement that there are no disadvantages/risks of rtCGM/FGM. Some issues remain in rtCGM/FGM management: a) risk of excessive correction of high or low glucose; b) risk of alert fatigue leading to alert silencing or rtCGM termination; c) allergic reaction to the adhesive keeping rtCGM or FGM sensors in place. The panel almost unanimously agreed that sensor accuracy depends on multiple variables, that alarm setting should be individualized, and that global glycemic profile represent an useful tool in interpreting glucose data. More clinical studies and a wider use of these devices will increase the efficacy and effectiveness of continuous glucose monitoring in Italy.

Assessment of glucose variability in subjects with prediabetes

The aim of the study was to assess glucose variability in subjects with prediabetes by means of CGM.

MATERIAL AND METHODS

32 subjects with prediabetes - mean age 56.6 ± 9.6 years, mean BMI 30.3 ± 5.3 kg/m² and 18 subjects with normal glucose tolerance (NGT) - mean age 54.4 ± 9.9 years, mean BMI 24.8 ± 6.9 kg/m², were enrolled. Glucose tolerance was studied during OGTT. HbA1c was measured by NGSP certified method. CGM was performed with FreeStyle Libre Pro sensor.

RESULTS

The following indices of glucose variability were significantly higher in the prediabetes group - CV (p < 0.041), J-index (p < 0.014), CONGA (p < 0.047) and GRADE (p < 0.036). A significant increase in HbA1c (p < 0.036), mean interstitial glucose (p < 0.025), time above range (p < 0.018) and a significant decrease in time in range (p < 0.014) was found in prediabetes compared to NGT. Significant correlations between HbA1c and LBGI (r = -0.33, p = 0.02), HBGI (r = 0.31, p = 0.03), CONGA (r = 0.36, p = 0.01), J-index (r = 0.37, p = 0.01) and M-value (r = -0.34, p = 0.02) were established.

CONCLUSION

Glucose variability is significantly increased in prediabetes and is an additional parameter in the assessment of glucose homeostasis even at these early stages of glucose dysregulation.

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.

Hypoglycemia in People with Type 2 Diabetes and CKD

BACKGROUND AND OBJECTIVES

Among people with diabetes mellitus, CKD may promote hypoglycemia through altered clearance of glucose-lowering medications, decreased kidney gluconeogenesis, and blunted counter-regulatory response. We conducted a prospective observational study of hypoglycemia among 105 individuals with type 2 diabetes treated with insulin or a sulfonylurea using continuous glucose monitors.

DESIGN, SETTING, PARTICIPANTS & MEASUREMENTS

We enrolled 81 participants with CKD, defined as eGFR<60 ml/min per 1.73 m², and 24 control participants with eGFR≥60 ml/min per 1.73 m² frequency-matched on age, duration of diabetes, hemoglobin A1c, and glucose-lowering medications. Each participant wore a continuous glucose monitor for two 6-day periods. We examined rates of sustained level 1 hypoglycemia (<70 mg/dl) and level 2 hypoglycemia (<54 mg/dl) among participants with CKD. We then tested differences compared with control participants as well as a second control population (n=73) using Poisson and linear regression, adjusting for age, sex, and race.

RESULTS

Over 890 total days of continuous glucose monitoring, participants with CKD were observed to have 255 episodes of level 1 hypoglycemia, of which 68 episodes reached level 2 hypoglycemia. Median rate of hypoglycemic episodes was 5.3 (interquartile range, 0.0-11.7) per 30 days and mean time spent in hypoglycemia was 28 (SD 37) minutes per day. Hemoglobin A1c and the glucose management indicator were the main clinical correlates of time in hypoglycemia (adjusted differences 6 [95% confidence interval, 2 to 10] and 13 [95% confidence interval, 7 to 20] fewer minutes per day per 1% higher hemoglobin A1c or glucose management indicator, respectively). Compared with control populations, participants with CKD were not observed to have significant differences in time in hypoglycemia (adjusted differences 4 [95% confidence interval, -12 to 20] and -12 [95% confidence interval, -29 to 5] minutes per day).

CONCLUSIONS

Among people with type 2 diabetes and moderate to severe CKD, hypoglycemia was common, particularly with tighter glycemic control, but not significantly different from groups with similar clinical characteristics and preserved eGFR.

Efficacy and safety of dual SGLT 1/2 inhibitor sotagliflozin in type 1 diabetes: meta-analysis of randomised controlled trials

OBJECTIVE

To assess the efficacy and safety of dual sodium glucose cotransporter (SGLT) 1/2 inhibitor sotagliflozin in type 1 diabetes mellitus.

DESIGN

Meta-analysis of randomised controlled trials.

DATA SOURCES

Medline; Cochrane Library; Embase; international meeting abstracts; international and national clinical trial registries; and websites of US, European, and Japanese regulatory authorities, up to 10 January 2019.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

Randomised controlled trials evaluating the effect of sotagliflozin versus active comparators or placebo on glycaemic and non-glycaemic outcomes and on adverse events in type 1 diabetes in participants older than 18. Three reviewers extracted data for study characteristics, outcomes of interest, and risk of bias and summarised strength of evidence using the grading of recommendations assessment, development, and evaluation approach. Main outcomes were pooled using random effects models.

RESULTS

Of 739 records identified, six randomised placebo controlled trials (n=3238, duration 4-52 weeks) were included. Sotagliflozin reduced levels of glycated haemoglobin (HbA1c; weighted mean difference -0.34% (95% confidence interval -0.41% to -0.27%), P<0.001); fasting plasma glucose (-16.98 mg/dL, -22.1 to -11.9; 1 mg/dL=0.0555 mmol/L) and two hour-postprandial plasma glucose (-39.2 mg/dL, -50.4 to -28.1); and daily total, basal, and bolus insulin dose (-8.99%, -10.93% to -7.05%; -8.03%, -10.14% to -5.93%; -9.14%, -12.17% to -6.12%; respectively). Sotagliflozin improved time in range (weighted mean difference 9.73%, 6.66% to 12.81%) and other continuous glucose monitoring parameters, and reduced body weight (-3.54%, -3.98% to -3.09%), systolic blood pressure (-3.85 mm Hg, -4.76 to -2.93), and albuminuria (albumin:creatinine ratio -14.57 mg/g, -26.87 to -2.28). Sotagliflozin reduced hypoglycaemia (weighted mean difference -9.09 events per patient year, -13.82 to -4.36) and severe hypoglycaemia (relative risk 0.69, 0.49 to 0.98). However, the drug increased the risk of ketoacidosis (relative risk 3.93, 1.94 to 7.96), genital tract infections (3.12, 2.14 to 4.54), diarrhoea (1.50, 1.08 to 2.10), and volume depletion events (2.19, 1.10 to 4.36). Initial HbA1c and basal insulin dose adjustment were associated with the risk of diabetic ketoacidosis. A sotagliflozin dose of 400 mg/day was associated with a greater improvement in most glycaemic and non-glycaemic outcomes than the 200 mg/day dose, without increasing the risk of adverse events. The quality of evidence was high to moderate for most outcomes, but low for major adverse cardiovascular events and all cause death. The relatively short duration of trials prevented assessment of long term outcomes.

CONCLUSIONS

In type 1 diabetes, sotagliflozin improves glycaemic and non-glycaemic outcomes and reduces hypoglycaemia rate and severe hypoglycaemia. The risk of diabetic ketoacidosis could be minimised by appropriate patient selection and down-titration of the basal insulin dose.

Beyond type 2 diabetes: sodium glucose co-transporter-inhibition in type 1 diabetes

Use of sodium glucose cotransporter (SGLT) inhibitors are a well-established therapeutic option in type 2 diabetes (T2D) with a variety of proven therapeutic benefits. They have become a pillar of current treatment guidelines. In type 1 diabetes (T1D), initial exploratory studies have shown benefits in glycemic control, weight control, and cardiovascular risk parameters, leading to trials aiming for regulatory submission with several agents. Results from four 1-year trials, which included a total of 3052 patients, are now available, demonstrating promising findings that target the unmet needs of patients with T1D with a novel insulin-independent adjunct therapy. However, these positive effects must be balanced against the risks associated with this class of drugs. Specifically, current T1D studies have shown an increased risk of diabetic ketoacidosis (DKA), which, in some cases, presented with only slightly elevated glucose levels. While this complication may be clinically manageable once detected, the metabolic shift towards ketogenesis associated with this class of agents mandates appropriate patient selection. Currently, there are no validated tools for DKA risk assessment. Although the experience gained in studies and off-label use provides some indication for appropriate patient selection, this would have to be evaluated closely in the event that these drugs would receive regulatory approval. Risk mitigation includes training in ketone measurement (preferably as blood β-hydroxybutyrate testing), teaching the concept of euglycemic DKA, and providing a clear treatment algorithm to avoid progression of ketosis to full-blown DKA. Because similar unmet needs also exist in pediatric population studies, risk mitigation in youth should be initiated as well to allow an evidence-based, risk-benefit assessment in this vulnerable population.

Using Flash Continuous Glucose Monitoring in Primary Practice

IN BRIEF Obstacles to realizing the clinical benefits of continuous glucose monitoring (CGM) for daily diabetes management are being overcome with more affordable, user-friendly technologies. This article describes a novel category of CGM known as "flash" that may allow more routine use of continuous data for greater numbers of patients treated in primary care.

A head-to-head comparison of personal and professional continuous glucose monitoring systems in people with type 1 diabetes: Hypoglycaemia remains the weak spot

To compare the performance of a professional continuous glucose monitoring (proCGM) and a personal continuous glucose monitoring (persCGM) system worn in parallel under standardized conditions in individuals with type 1 diabetes (T1D), two CGM systems (iPro2 - proCGM; Minimed 640G - persCGM) worn in parallel using the same sensor (Enlite 2) were compared. Ten people with T1D were included in this single-centre, open-label study in which CGM performance was evaluated. The study consisted of a 24-hours inpatient phase (meals, exercise, glycaemic challenges) and a 4-day home phase. Analyses included fulfilment of ISO 15197:2013 criteria, mean absolute relative difference (MARD), Parkes Error Grid and Bland-Altman plots. During the inpatient stay, ISO 15197:2013 criteria fulfilment was 58.4% (proCGM) and 57.8% (persCGM). At home, the systems met ISO 15197:2013 criteria by 66.5% (proCGM) and 65.3% (persCGM). No difference of MARD in inpatient phase (19.1 ± 16.7% vs. 19.0 ± 19.6; P = 0.83) and home phase (18.6 ± 26.8% vs. 17.4 ± 21.3%, P = 0.87) was observed. All sensors performed less accurately during hypoglycaemia. ProCGM and persCGM showed similar performance during daytime and night-time for the inpatient and the home phase. However, sensor performance was reduced during hypoglycaemia for both systems.

Glycemic Variability Is a Powerful Independent Predictive Factor of Midterm Major Adverse Cardiac Events in Patients With Diabetes With Acute Coronary Syndrome

OBJECTIVE

Acute glucose fluctuations are associated with hypoglycemia and are emerging risk factors for cardiovascular outcomes. However, the relationship between glycemic variability (GV) and the occurrence of midterm major cardiovascular events (MACE) in patients with diabetes remains unclear. This study investigated the prognostic value of GV in patients with diabetes and acute coronary syndrome (ACS).

RESEARCH DESIGN AND METHODS

This study included consecutive patients with diabetes and ACS between January 2015 and November 2016. GV was assessed using SD during initial hospitalization. MACE, including new-onset myocardial infarction, acute heart failure, and cardiac death, were recorded. The predictive effects of GV on patient outcomes were analyzed with respect to baseline characteristics and cardiac status.

RESULTS

A total of 327 patients with diabetes and ACS were enrolled. MACE occurred in 89 patients (27.2%) during a mean follow-up of 16.9 months. During follow-up, 24 patients (7.3%) died of cardiac causes, 35 (10.7%) had new-onset myocardial infarction, and 30 (9.2%) were hospitalized for acute heart failure. Multivariable logistic regression analysis showed that GV >2.70 mmol/L, a Synergy between PCI with Taxus and Cardiac Surgery (SYNTAX) score >34, and reduced left ventricular ejection fraction of <40% were independent predictors of MACE, with odds ratios (ORs) of 2.21 (95% CI 1.64-2.98; P < 0.001), 1.88 (1.26-2.82; P = 0.002), and 1.71 (1.14-2.54; P = 0.009), respectively, whereas a Global Registry of Acute Coronary Events (GRACE) risk score >140 was not (OR 1.07 [0.77-1.49]; P = 0.69).

CONCLUSIONS

A GV cutoff value of >2.70 mmol/L was the strongest independent predictive factor for midterm MACE in patients with diabetes and ACS.

A Review of Emerging Technologies in Diabetes Management for Multiple-Dose Insulin-Injecting Patients With Type 2 Diabetes Who Self-monitor Blood Glucose

Objective: The management of diabetes mellitus requires a precise interpretation of blood glucose (BG) data by patients and providers and is increasingly associated with a need for medical technologies that aid in achieving patient-specific outcomes while making the process convenient. This review aims to summarize the current landscape in diabetes management technology, focusing specifically on devices that assist with pattern management in patients with type 2 diabetes (T2DM) who are on multiple-dose insulin regimens. Data Sources: The authors searched MEDLINE to identify articles from 2007 to 2018 that evaluated technologies for BG pattern management and diabetes monitoring. Additional references were generated through review of identified literature citations. Article selection was based on mutual agreement for inclusion. Data Selection and Data Extraction: Relevant articles were defined as English-language articles, describing technologies that assist with diabetes management in insulin-injecting patients with T2DM. Articles that focused exclusively on type 1 diabetes were excluded. Data Synthesis: The literature search yielded 334 articles, of which 21 were included for synthesis. The current BG monitoring practices emphasize the benefit of the structured self-monitoring of BG approach. Several randomized controlled trials conclude that the available technology aids in comprehensive data collection and facilitates communication between patients and providers. Digitally enabled “smart” devices are valuable tools that may help improve outcomes while providing a flexible, personalized approach. Conclusions: Integration of digital technology with diabetes management allows for accurate collection and analysis of data. Emergence of digital tools promotes a comprehensive, precise, and objective approach to glucose monitoring and encourages patient-provider collaborations.

The impact of a structured education and treatment programme (FLASH) for people with diabetes using a flash sensor-based glucose monitoring system: Results of a randomized controlled trial

AIMS

Flash sensor-based glucose monitoring (FSGM) provides people with diabetes considerably more information on their glycaemic control. We have developed and evaluated a structured education and treatment programme, termed FLASH, to assist FSGM users to understand and use the available glycaemic information for optimization of their diabetes treatment.

METHODS

We report on a multi-centre, randomized, parallel trial with a six-month follow-up involving 216 eligible participants (16-75 years old) on intensive insulin therapy. The primary outcome was HbA1c change from baseline to six months. Secondary outcomes were measures of glucose control as assessed by FSGM, as well as changes in behavioural and psychosocial measures.

RESULTS

At six months, the between-group difference in HbA1c reduction was significant, favouring FLASH education compared to the control group receiving no FLASH education (-0.28%, 95% CI -0.16% to -0.40% vs.-0.11%, 95% CI 0.00% to -0.22%; with a between-group difference of -0.17%, 95% CI -0.01% to -0.33%; p = 0.033). Participation in FLASH education also resulted in significant improvements in time spent in the target glucose range, in diabetes-related distress scores and in satisfaction with the glucose monitoring method. FLASH education also resulted in significant improvements in the use of glycaemic information provided by FSGM and in reduced self-monitoring of blood glucose (SMBG) fingerstick testing.

CONCLUSION

FLASH is an effective programme to improve glycaemic control and lower diabetes-related distress in users of FSGM. The study was registered in ClinicalTrials: NCT03175315.

Higher blood glucose and larger fluctuations detected postoperatively using continuous glucose monitoring: a preliminary study following total knee or hip arthroplasty

BACKGROUND

The control of diabetes mellitus (DM) should help reduce the incidence of periprosthetic joint infection (PJI). Self-monitoring of blood glucose (SMBG) concentration is usually undertaken at fixed time-points. Therefore, the extent of postoperative blood glucose fluctuation might be underestimated. To provide a more comprehensive assessment, continuous glucose monitoring (CGM) is beginning to be used. However, no previous studies have evaluated blood glucose concentrations using CGM following orthopedic surgery. Therefore, the differences between the maximum blood glucose concentrations measured using SMBG and CGM, and the mean amplitude of the glycemic fluctuation in patients with frank diabetes mellitus (DM) or pre-diabetes were evaluated. Blood glucose was measured in 20 patients who had undergone total hip or total knee arthroplasty (12 patients with DM and eight with pre-diabetes). Patients were fitted with a CGM device in the operating room, which was worn for 6 days postoperatively, and used to evaluate blood glucose concentration continuously. SMBG was performed simultaneously for the same period.

RESULTS

The mean difference between the maximum blood glucose concentrations measured using SMBG and CGM was 25.0 ± 20.3 mg/dl (range, - 17 to 81 mg/dl), with the concentrations measured using CGM tending to be higher than those measured using SMBG (P = 0.04). Blood glucose concentrations measured using CGM tended to be higher than those measured using SMBG until postoperative day 2, and to decrease gradually after postoperative day 4. There were no significant differences in the standard deviation of the blood glucose concentrations between the two groups.

CONCLUSIONS

Blood glucose concentrations > 200 mg/dl and larger fluctuations were more frequently recorded using CGM than SMBG, especially until postoperative day 2. Thus, CGM is more useful for the identification of high blood glucose concentrations and larger fluctuations. However, this information was not provided in real time.

IMPAIRED AWARENESS OF HYPOGLYCEMIA CONTINUES TO BE A RISK FACTOR FOR SEVERE HYPOGLYCEMIA DESPITE THE USE OF CONTINUOUS GLUCOSE MONITORING SYSTEM IN TYPE 1 DIABETES

Objective: Impaired awareness of hypoglycemia (IAH) is a risk factor for severe hypoglycemia in patients with type 1 diabetes (T1D) not using a continuous glucose monitoring (CGM) system. The current study investigated the prevalence of IAH and its relationship with severe hypoglycemia in T1D patients using CGM systems. Methods: This cross-sectional observational study enrolled 135 patients with T1D and ongoing real-time CGM use. A survey was conducted to assess hypoglycemia awareness with the Gold, Clarke, and Pedersen-Bjergaard questionnaires and the 6-month history of severe hypoglycemia. Other diabetes histories and the CGM glucose data were collected. Results: The Gold, Clarke, and Pedersen-Bjergaard questionnaires demonstrated the overall prevalence of IAH/abnormal awareness to be 33.3%, 43.7%, and 77.0%, respectively. Participant age and duration of T1D were consistently related to IAH or hypoglycemia unawareness with all three questionnaires (P<.05). Amongst the patients using CGM for >6 months, 24.5% were found to have at least one episode of severe hypoglycemia in the preceding 6 months. IAH identified by the Gold and Clarke questionnaires and hypoglycemia unawareness identified by the Pedersen-Bjergaard questionnaire were related to 6-, 4.63-, and 5.83-fold increased risk of severe hypoglycemia (P = .001, .004, and .013), respectively. IAH identified by the Gold/Clarke questionnaires was associated with a longer duration of CGM glucose <54 mg/dL and higher glucose coefficients of variation (P<.05). Conclusion: IAH is highly prevalent and related to a higher risk for severe hypoglycemia in T1D patients using CGM. Abbreviations: CGM = continuous glucose monitoring; CI = confidence interval; HAAF = hypoglycemia-associated autonomic failure; HbA1c = hemoglobin A1C; IAH = impaired awareness of hypoglycemia; T1D = type 1 diabetes.

Managing free-living hyperglycemia with exercise or interrupted sitting in type 2 diabetes

Breaking up sitting with light physical activity (PA) is effective in reducing hyperglycemia in the laboratory. Whether the same effects are observed in the free-living environment remains unknown. We evaluated how daily and postprandial glycemia is impacted by 20, 40, or 60 min of activity performed as either breaks from sitting after each meal (BR) or as one continuous walk after breakfast (WALK). Thirty individuals with type 2 diabetes completed three experimental conditions [BR, WALK, and control (CON)] in a randomized crossover design. Conditions were performed in a free-living environment with strict dietary control over 7 days. Participants increased PA in BR and WALK by 20, 40, or 60 min ( n = 10 in each group) and maintained habitual levels of PA during CON. A continuous glucose monitor (iPro2) and activPAL activity monitor were worn to quantify glycemic control and PA. Using linear mixed models with repeated measures, we 1) compared postprandial glucose (PPG) across conditions and 2) assessed the relationship between activity volume and glucose responses. Whereas WALK tended to shorten the daily duration of hyperglycemia compared with CON ( P = 0.0875), BR was not different from CON. BR and WALK significantly attenuated the breakfast PPG versus CON ( P ≤ 0.05), but lunch and dinner PPG were unaffected by BR and WALK. In conclusion, continuous walking was more effective than breaks from sitting in lowering daily hyperglycemia for the group, but both conditions lowered breakfast PPG. In contrast to tightly controlled laboratory studies, breaks from sitting did not lower hyperglycemia in the free-living environment.

NEW & NOTEWORTHY Our “ecolabical” approach is new and noteworthy. This approach combines the external validity of the free-living environment (ecological) with the control of key confounding variables in the laboratory and allows for highly translatable findings by minimizing confounding variables. We found that both postmeal continuous walking and short breaks from sitting similarly attenuated the postprandial glucose (PPG) response to breakfast. Unlike previous laboratory studies, neither condition (walk after breakfast or postmeal breaks) significantly impacted PPG at lunch or dinner.

Continuous Glucose Monitoring: A Brief Review for Primary Care Practitioners

Glycated hemoglobin A1c (HbA1c) is routinely used as a marker of average glycemic control, but it fails to provide data on hypoglycemia and glycemic variability, both of which are associated with adverse clinical outcomes. Self-monitoring of blood glucose (SMBG), particularly in insulin-treated patients, is a cornerstone in the management of patients with diabetes. SMBG helps with treatment decisions that aim to reduce high glucose levels while avoiding hypoglycemia and limiting glucose variability. However, repeated SMBG can be inconvenient to patients and difficult to maintain in the long term. By contrast, continuous glucose monitoring (CGM) provides a convenient, comprehensive assessment of blood glucose levels, allowing the identification of high and low glucose levels, in addition to evaluating glycemic variability. CGM using newer detection and visualization systems can overcome many of the limitations of an HbA1c-based approach while addressing the inconvenience and fragmented glucose data associated with SMBG. When used together with HbA1c monitoring, CGM provides complementary information on glucose levels, thus facilitating the optimization of diabetes therapy while reducing the fear and risk of hypoglycemia. Here we review the capabilities and benefits of CGM, including cost-effectiveness data, and discuss the potential limitations of this glucose-monitoring strategy for the management of patients with diabetes. FUNDING: Sanofi US, Inc.

Ascorbic acid supplementation improves postprandial glycaemic control and blood pressure in individuals with type 2 diabetes: Findings of a randomized cross-over trial

AIM

The primary aim of this study was to investigate whether ascorbic acid (AA) supplementation improves postprandial glucose responses under free-living conditions in individuals with type 2 diabetes. A secondary aim was to investigate the effect of AA supplementation on blood pressure.

MATERIALS AND METHODS

A total of 31 individuals with type 2 diabetes (26 males and 5 females; aged 61.8 ± 6.8 years; duration of diabetes, 5.6 ± 4.6 years; HbA1c, 7.6% ± 0.7% [mean ± SD]) were enrolled in a randomized cross-over study involving 4 months of supplementation with oral AA (2 × 500 mg/d) or placebo. Participants wore continuous glucose monitors for 48 hours and consumed standardized meals pre- and post-supplementation. Measurements included postprandial glucose incremental areas under the curve (iAUC), duration of day in hyper- and hypo-glycaemia status, average 24-hour and daily postprandial glucose concentrations, HbA1c, insulin, blood pressure (BP) and oxidative stress (F₂ -isoprostanes).

RESULTS

Following AA supplementation, significant decreases were observed in daily postprandial glucose iAUC (-36%), in duration of day with hyperglycaemia (-2.8 h/d) and postprandial hyperglycaemia (-1.7 h/d), in average 24-hour glucose (-0.8 mmol/L) and daily postprandial glucose (-1.1 mmol/L) concentrations, in systolic (-7 mm Hg) and diastolic (-5 mm Hg) blood pressures and in a specific fraction of free plasma F₂ -isoprostanes (-47 pg/mL) as compared to placebo.

CONCLUSIONS

Individuals with type 2 diabetes experienced improved postprandial and 24-hour glycaemia and decreased BP after 4 months of AA supplementation as compared to placebo. These findings offer evidence for the proposed use of AA as an adjunct therapy to improve glycaemic and BP control in individuals with type 2 diabetes.

Validation of Time in Range as an Outcome Measure for Diabetes Clinical Trials

OBJECTIVE

This study evaluated the association of time in range (TIR) of 70-180 mg/dL (3.9-10 mmol/L) with the development or progression of retinopathy and development of microalbuminuria using the Diabetes Control and Complications Trial (DCCT) data set in order to validate the use of TIR as an outcome measure for clinical trials.

RESEARCH DESIGN AND METHODS

In the DCCT, blood glucose concentrations were measured at a central laboratory from seven fingerstick samples (seven-point testing: pre- and 90-min postmeals and at bedtime) collected during 1 day every 3 months. Retinopathy progression was assessed every 6 months and urinary microalbuminuria development every 12 months. Proportional hazards models were used to assess the association of TIR and other glycemic metrics, computed from the seven-point fingerstick data, with the rate of development of microvascular complications.

RESULTS

Mean TIR of seven-point profiles for the 1,440 participants was 41 ± 16%. The hazard rate of development of retinopathy progression was increased by 64% (95% CI 51-78), and development of the microalbuminuria outcome was increased by 40% (95% CI 25-56), for each 10 percentage points lower TIR (P < 0.001 for each). Results were similar for mean glucose and hyperglycemia metrics.

CONCLUSIONS

Based on these results, a compelling case can be made that TIR is strongly associated with the risk of microvascular complications and should be an acceptable end point for clinical trials. Although hemoglobin A_1c remains a valuable outcome metric in clinical trials, TIR and other glycemic metrics-especially when measured with continuous glucose monitoring-add value as outcome measures in many studies.

Validation of Time in Range as an Outcome Measure for Diabetes Clinical Trials

OBJECTIVE

This study evaluated the association of time in range (TIR) of 70-180 mg/dL (3.9-10 mmol/L) with the development or progression of retinopathy and development of microalbuminuria using the Diabetes Control and Complications Trial (DCCT) data set in order to validate the use of TIR as an outcome measure for clinical trials.

RESEARCH DESIGN AND METHODS

In the DCCT, blood glucose concentrations were measured at a central laboratory from seven fingerstick samples (seven-point testing: pre- and 90-min postmeals and at bedtime) collected during 1 day every 3 months. Retinopathy progression was assessed every 6 months and urinary microalbuminuria development every 12 months. Proportional hazards models were used to assess the association of TIR and other glycemic metrics, computed from the seven-point fingerstick data, with the rate of development of microvascular complications.

RESULTS

Mean TIR of seven-point profiles for the 1,440 participants was 41 ± 16%. The hazard rate of development of retinopathy progression was increased by 64% (95% CI 51-78), and development of the microalbuminuria outcome was increased by 40% (95% CI 25-56), for each 10 percentage points lower TIR (P < 0.001 for each). Results were similar for mean glucose and hyperglycemia metrics.

CONCLUSIONS

Based on these results, a compelling case can be made that TIR is strongly associated with the risk of microvascular complications and should be an acceptable end point for clinical trials. Although hemoglobin A1c remains a valuable outcome metric in clinical trials, TIR and other glycemic metrics-especially when measured with continuous glucose monitoring-add value as outcome measures in many studies.