Utility of Continuous Glucose Monitoring in Type 1 and Type 2 Diabetes

Demonstrating the Clinical Impact of Continuous Glucose Monitoring Within an Integrated Healthcare Delivery System

BACKGROUND

Approximately 30 million Americans currently suffer from diabetes, and nearly 55 million people will be impacted by 2030. Continuous glucose monitoring (CGM) systems help patients manage their care with real-time data. Although approximately 95% of those with diabetes suffer from type 2, few studies have measured CGM's clinical impact for this segment within an integrated healthcare system.

METHODS

A parallel randomized, multisite prospective trial was conducted using a new CGM device (Dexcom G6) compared to a standard of care finger stick glucometer (FSG) (Contour Next One). All participants received usual care in primary care clinics for six consecutive months while using these devices. Data were collected via electronic medical records, device outputs, exit surveys, and insurance company (SelectHealth) claims in accordance with institutional review board approval.

RESULTS

Ninety-nine patients were randomized for analysis (n = 50 CGM and n = 49 FSG). CGM patients significantly decreased hemoglobin A1c (p = .001), total visits (p = .009), emergency department encounters (p = .018), and labs ordered (p = .001). Among SelectHealth non-Medicare Advantage patients, per member per month savings were $417 for CGM compared to FSG, but $9 more for Medicare Advantage. Seventy percent of CGM users reported that the technology helped them better understand daily activity and diet compared to only 16% for FSG.

DISCUSSION

Participants using CGM devices had meaningful improvements in clinical outcomes, costs, and self-reported measures compared to the FSG group. Although a larger study is necessary to confirm these results, CGM devices appear to improve patient outcomes while making treatment more affordable.

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

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

Optimizing type 1 diabetes after multiple daily injections and capillary blood monitoring: Pump or sensor first? A meta-analysis using pooled differences in outcome measures

AIMS

Most people living with type 1 diabetes self-manage using multiple daily injection (MDI) insulin regimens and self-monitoring of blood glucose (SMBG). Continuous subcutaneous insulin infusion (CSII) and continuous glucose monitoring (CGM) are adjuncts to education and support self-management optimization. The aim of this systematic review and meta-analysis was to assess which first-line technology is most effective.

METHODS

Electronic databases (MEDLINE, EMBASE and WEB OF SCIENCE) were systematically searched from 1999 to September 2020. Randomized controlled trials comparing either CSII with MDI or CGM with SMBG in adults with type 1 diabetes were included. Data were extracted in duplicate by two reviewers, and were analysed to assess individual and overall treatment effect measures (PROSPERO registration: CRD42020149915).

RESULTS

Glycated haemoglobin was significantly reduced for CGM when compared with SMBG [Cohen's d - 0.62 (95% CI -0.79 to -0.45)] and for CSII when compared with MDI [Cohen's d - 0.44 (95% CI -0.67 to -0.22)]. Rates of severe hypoglycaemia were significantly reduced with CGM compared with SMBG, but did not change for CSII when compared with MDI. Episodes of diabetic ketoacidosis were more likely to occur with CSII than MDI. Both CSII and CGM reduced glucose standard deviation, compared with MDI and SMBG respectively.

CONCLUSIONS

Both CGM and CSII remain impactful interventions compared with SMBG and MDI but in adults with type 1 diabetes and in the contexts in which they have been studied, CGM might have a greater positive impact on glycaemic variability and severe hypoglycaemia than CSII, when added to MDI and SMBG. A head-to-head study, including patient reported outcomes, is required to explore these findings further.

Telehealth Adoption Among Endocrinologists During The Covid-19 Pandemic

OBJECTIVE

Telehealth is a timely solution for delivering health care during the coronavirus disease 2019 (COVID-19) pandemic. The practice of endocrinology is suited to provide virtual care to patients with a variety of endocrine disorders. In this survey, we aimed to gauge the adoption of telehealth practices during the COVID-19 pandemic among endocrinologists in the United States (U.S.).

METHODS

This was a cross-sectional, online survey-based study. Members of the Facebook group "Endocrinologists" were invited to participate in the survey. Characteristics of respondents and their rates of adoption of telehealth were described and analyzed for statistically significant associations using the Pearson chi-square test.

RESULTS

A total of 181 physicians responded to the survey. The majority of respondents were females (75%), younger than or equal to 40 years of age (51%), employed (72%) either by a private group/hospital or by an academic setting, worked in an urban area (88.4%), and were adult endocrinologists (93%). With the COVID-19 outbreak, more than two-fifths (44.2%) of participants switched to completely virtual visits, and an additional 44.2% switched to a majority of virtual visits, with some in-person visits in the outpatient setting. Additionally, there was a significantly higher adoption rate of telehealth among endocrinologists younger than or equal to 40 years of age (P = .02) and among those who practiced in northeastern, midwestern, and the western geographic regions of the U.S. (P = .04).

CONCLUSION

The majority of the responding endocrinologists from the U.S. appeared to have swiftly adapted by using telehealth within a few weeks of COVID-19 being declared a national emergency.

ABBREVIATIONS

CMS = Centers for Medicare and Medicaid Services; COVID-19 = coronavirus disease 2019; PPE = personal protective equipment; U.S. = United States.

Is it possible to constantly and accurately monitor blood sugar levels, in people with Type 1 diabetes, with a discrete device (non-invasive or invasive)?

Real-time continuous glucose monitors using subcutaneous needle-type sensors continue to develop. The limitations of currently available systems, however, include time lag behind changes in blood glucose, the invasive nature of such systems, and in some cases, their accuracy. Non-invasive techniques have been developed, but, to date, no commercial device has been successful. A key research priority for people with Type 1 diabetes identified by the James Lind Alliance was to identify ways of monitoring blood glucose constantly and accurately using a discrete device, invasive or non-invasive. Integration of such a sensor is important in the development of a closed-loop system and the technology must be rapid, selective and acceptable for continuous use by individuals. The present review provides an update on existing continuous glucose-sensing technologies, and an overview of emergent techniques, including their accuracy and limitations.

Enzyme free glucose sensing by amino-functionalized silicon quantum dot

Silicon quantum dots have become one of the most popular nanomaterials in biological applications for their excellent biocompatibility and optical properties. Herein, we synthesized amino-functionalized silicon quantum dots (NH₂@SiQDs) via a simple microemulsion method, in which silicon tetrachloride and allylamine were used as source of silicon and functional group. NH₂@SiQDs exhibits good water-solubility, high fluorescence quantum yield and optical stability. A non-enzymatic biosensor of glucose was developed based on the fluorescence quenching of NH₂@SiQDs in response to glucose. The fluorescence response was linearly proportional to glucose in the concentration range of 1.0 × 10^-6-9.0 × 10^-5 mol/L and the detection limit was determined to be 3.0 × 10^-7 mol/L. The developed glucose sensor was successfully applied in blood glucose analysis of human serum. Satisfactory result that agreed very well with traditional method was obtained.

PERCEPTION OF GRADUATING ENDOCRINOLOGY, DIABETES, AND METABOLISM FELLOWS ON THE BENEFITS OF WEARING A CONTINUOUS GLUCOSE MONITOR AND/OR INSULIN PUMP FOR THEIR EDUCATION

Objectives: To our knowledge, no prior research has explored the prevalence of wearing continuous glucose monitors (CGMs) and/or insulin pumps among in-training fellows and their perception of doing so as part of their education. Our objectives therefore were to estimate the frequency with which wearing a CGM and/or insulin pump is used as a learning opportunity and explore the main motivators and perception on its value. Methods: A multiple-choice survey that addressed each fellow's level of training, type of fellowship training program, and use of CGM and/or insulin pump was sent to all Accreditation Council for Graduate Medical Education endocrinology, diabetes, and metabolism program coordinators or program directors. We asked them to forward this survey to their graduating fellows. Their perception on the value of wearing these devices was addressed. Results: Fifty-one graduating fellows responded to the survey; 78.43% and 62.5% of them wore a CGM and insulin pump, respectively. A total of 89.48% and 90% of those who wore a CGM and insulin pump, respectively, thought it was above-average value for their education, and the most common reasons were to learn the technical aspects and understand what patients with diabetes go through. Conclusion: Wearing a CGM and/or insulin pump is perceived by endocrinology graduating fellows as valuable to their education, specifically, to learn the technical aspects, understand the patient's experience, and develop empathy. Abbreviations: ACGME = Accreditation Council for Graduate Medical Education; CGM = continuous glucose monitor.

The 30-year cost-effectiveness of alternative strategies to achieve excellent glycemic control in type 1 diabetes: An economic simulation informed by the results of the diabetes control and complications trial/epidemiology of diabetes interventions and complications (DCCT/EDIC)

OBJECTIVE

To simulate the cost-effectiveness of historical and modern treatment scenarios that achieve excellent vs. poor glycemic control in type 1 diabetes (T1DM).

RESEARCH DESIGN AND METHODS

We describe and compare the costs of intensive and conventional therapies for T1DM as performed during DCCT, and modern intensive and basic therapy scenarios using insulin analogs, pens, pumps, and continuous glucose monitoring (CGM) to achieve excellent or poor glycemic control. We then assess the differences in treatment costs and the costs of outcomes over 30 years and report incremental cost-effectiveness ratios.

RESULTS

Over 30 years, DCCT intensive therapy cost $127,500 to $181,600 more per participant than DCCT conventional therapy, and modern intensive therapy cost $87,700 to $409,000 more per individual than modern basic therapy. Excellent glycemic control averted as much as $90,900 in costs from complications and added ~1.62 quality-adjusted life-years (QALYs) per participant over 30 years. When costs and QALYs were discounted at 3% annually, DCCT intensive therapy and modern intensive therapies that use multiple daily injections (MDI) or pumps are cost-saving or cost-effective (<$100,000/QALY-gained). If applied to all patients with T1DM, modern intensive therapy using pumps and CGM is not cost-effective (>$250,000/QALY-gained) but would be more cost-effective if associated with less hypoglycemia, better glycemic control, fewer complications, or improved health-related quality-of-life.

CONCLUSIONS

Use of the least expensive intensive therapy needed to safely achieve treatment goals for patients with T1DM represents a good value for money.

TRIAL REGISTRATION

clinicaltrials.govNCT00360815 and NCT00360893.

Challenges in diagnosing and monitoring diabetes in patients with chronic liver diseases

The prevalence and mortality of diabetes mellitus and liver disease have risen in recent years. The liver plays an important role in glucose homeostasis, and various chronic liver diseases have a negative effect on glucose metabolism with the consequent emergence of diabetes. Some aspects related to chronic liver disease can affect diagnostic tools and the monitoring of diabetes and other glucose metabolism disorders, and clinicians must be aware of these limitations in their daily practice. In cirrhotic patients, fasting glucose may be normal in up until 23% of diabetes cases, and glycated hemoglobin provides falsely low results, especially in advanced cirrhosis. Similarly, the performance of alternative glucose monitoring tests, such as fructosamine, glycated albumin and 1,5-anhydroglucitol, also appears to be suboptimal in chronic liver disease. This review will examine the association between changes in glucose metabolism and various liver diseases as well as the particularities associated with the diagnosis and monitoring of diabetes in liver disease patients. Alternatives to routinely recommended tests will be discussed.

Calibration of Minimally Invasive Continuous Glucose Monitoring Sensors: State-of-The-Art and Current Perspectives

Minimally invasive continuous glucose monitoring (CGM) sensors are wearable medical devices that provide real-time measurement of subcutaneous glucose concentration. This can be of great help in the daily management of diabetes. Most of the commercially available CGM devices have a wire-based sensor, usually placed in the subcutaneous tissue, which measures a "raw" current signal via a glucose-oxidase electrochemical reaction. This electrical signal needs to be translated in real-time to glucose concentration through a calibration process. For such a scope, the first commercialized CGM sensors implemented simple linear regression techniques to fit reference glucose concentration measurements periodically collected by fingerprick. On the one hand, these simple linear techniques required several calibrations per day, with the consequent patient's discomfort. On the other, only a limited accuracy was achieved. This stimulated researchers to propose, over the last decade, more sophisticated algorithms to calibrate CGM sensors, resorting to suitable signal processing, modelling, and machine-learning techniques. This review paper will first contextualize and describe the calibration problem and its implementation in the first generation of CGM sensors, and then present the most recently-proposed calibration algorithms, with a perspective on how these new techniques can influence future CGM products in terms of accuracy improvement and calibration reduction.

Nocturnal Hypoglycemia in Type 2 Diabetes

Background and aims: It is known that the majority of critical unacknowledged hypoglycemia has an increased incidence in patients with type 1 diabetes (T1DM) with a long evolution. The aim of this research is to evaluate the variability of glucose level and hypoglycemic events in patients with type 2 diabetes (T2DM) having pharmacological interventions with hypoglycemic risk. These events are sometimes asymptomatic also in T2DM: frequently in elderly, patients with autonomic neuropathy, or having a long evolution of disease.

Material and method: This analysis includes 72 patients with T2DM, with a relative good metabolic control, and possible glucose fluctuations. Glucose variability was appreciated using continuous glucose monitoring systems (CGMS) used for more than 72 hours in hospital or ambulatory setting.

Results: The incidence, duration and severity of hypoglycemia are not correlated with HbA1c value, age, disease duration or treatment. Approximately a quarter of patients had nocturnal hypoglycemia and in 37,5% of events hypoglycemia was prolonged, more 45 minutes. Clinical manifestations in diurnal hypoglycemia were presents in only 40% of the recorded events.

Conclusions: The study suggested that CGMS is beneficial for patients with type 2 diabetes, with hypoglycemic risk and complications, to adjusted medication, education and prevention the cardiovascular events.

Impact of flash glucose monitoring on hypoglycaemia in adults with type 1 diabetes managed with multiple daily injection therapy: a pre-specified subgroup analysis of the IMPACT randomised controlled trial

AIMS/HYPOTHESIS

Evidence for the effectiveness of interstitial glucose monitoring in individuals with type 1 diabetes using multiple daily injection (MDI) therapy is limited. In this pre-specified subgroup analysis of the Novel Glucose-Sensing Technology and Hypoglycemia in Type 1 Diabetes: a Multicentre, Non-masked, Randomised Controlled Trial' (IMPACT), we assessed the impact of flash glucose technology on hypoglycaemia compared with capillary glucose monitoring.

METHODS

This multicentre, prospective, non-masked, RCT enrolled adults from 23 European diabetes centres. Individuals were eligible to participate if they had well-controlled type 1 diabetes (diagnosed for ≥5 years), HbA_1c ≤ 58 mmol/mol [7.5%], were using MDI therapy and on their current insulin regimen for ≥3 months, reported self-monitoring of blood glucose on a regular basis (equivalent to ≥3 times/day) for ≥2 months and were deemed technically capable of using flash glucose technology. Individuals were excluded if they were diagnosed with hypoglycaemia unawareness, had diabetic ketoacidosis or myocardial infarction in the preceding 6 months, had a known allergy to medical-grade adhesives, used continuous glucose monitoring (CGM) within the previous 4 months or were currently using CGM or sensor-augmented pump therapy, were pregnant or planning pregnancy or were receiving steroid therapy for any disorders. Following 2 weeks of blinded (to participants and investigator) sensor wear by all participants, participants with sensor data for more than 50% of the blinded wear period (or ≥650 individual sensor results) were randomly assigned, in a 1:1 ratio by a central interactive web response system (IWRS) using the biased-coin minimisation method, to flash sensor-based glucose monitoring (intervention group) or self-monitoring of capillary blood glucose (control group). The control group had two further 14 day blinded sensor-wear periods at the 3 and 6 month time points. Participants, investigators and staff were not masked to group allocation. The primary outcome was the change in time in hypoglycaemia (<3.9 mmol/l) between baseline and 6 months in the full analysis set.

RESULTS

Between 4 September 2014 and 12 February 2015, 167 participants using MDI were enrolled. After screening and the baseline phase, participants were randomised to intervention (n = 82) and control groups (n = 81). One woman from each group was excluded owing to pregnancy; the full analysis set included 161 randomised participants. At 6 months, mean time in hypoglycaemia was reduced by 46.0%, from 3.44 h/day to 1.86 h/day in the intervention group (baseline adjusted mean change, -1.65 h/day), and from 3.73 h/day to 3.66 h/day in the control group (baseline adjusted mean change, 0.00 h/day), with a between-group difference of -1.65 (95% CI -2.21, -1.09; p < 0.0001). For participants in the intervention group, the mean ± SD daily sensor scanning frequency was 14.7 ± 10.7 (median 12.3) and the mean number of self-monitored blood glucose tests performed per day reduced from 5.5 ± 2.0 (median 5.4) at baseline to 0.5 ± 1.0 (median 0.1). The baseline frequency of self-monitored blood glucose tests by control participants was maintained (from 5.6 ± 1.9 [median 5.2] to 5.5 ± 2.6 [median 5.1] per day). Treatment satisfaction and perception of hypo/hyperglycaemia were improved compared with control. No device-related hypoglycaemia or safety-related issues were reported. Nine serious adverse events were reported for eight participants (four in each group), none related to the device. Eight adverse events for six of the participants in the intervention group were also reported, which were related to sensor insertion/wear; four of these participants withdrew because of the adverse event.

CONCLUSIONS/INTERPRETATION

Use of flash glucose technology in type 1 diabetes controlled with MDI therapy significantly reduced time in hypoglycaemia without deterioration of HbA_1c, and improved treatment satisfaction.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02232698 FUNDING: Abbott Diabetes Care, Witney, UK.

Toward Calibration-Free Continuous Glucose Monitoring Sensors: Bayesian Calibration Approach Applied to Next-Generation Dexcom Technology

BACKGROUND

Continuous glucose monitoring (CGM) sensors need to be calibrated twice/day by using self-monitoring of blood glucose (SMBG) samples. Recently, to reduce the calibration frequency, we developed an online calibration algorithm based on a multiple-day model of sensor time variability and Bayesian parameter estimation. When applied to Dexcom G4 Platinum (DG4P) sensor data, the algorithm allowed the frequency of calibrations to be reduced to one-every-four-days without significant worsening of sensor accuracy. The aim of this study is to assess the same methodology on raw CGM data acquired by a next-generation Dexcom CGM sensor prototype and compare the results with that obtained on DG4P.

METHODS

The database consists of 55 diabetic subjects monitored for 10 days by a next-generation Dexcom CGM sensor prototype. The new calibration algorithm is assessed, retrospectively, by simulating an online procedure using progressively fewer SMBG samples until zero. Accuracy is evaluated with mean absolute relative differences (MARD) between blood glucose versus CGM values.

RESULTS

The one-per-day and one-every-two-days calibration scenarios in the next-generation CGM data have an accuracy of 8.5% MARD (vs. 11.59% of DG4P) and 8.4% MARD (vs. 11.63% of DG4P), respectively. Accuracy slightly worsens to 9.2% (vs. 11.62% of DG4P) when calibrations are reduced to one-every-four-days. The calibration-free scenario results in 9.3% MARD (vs. 12.97% of DG4P).

CONCLUSIONS

In next-generation Dexcom CGM sensor data, the use of an online calibration algorithm based on a multiple-day model of sensor time variability and Bayesian parameter estimation aids in the shift toward a calibration-free scenario with even better results than those obtained in present-generation sensors.

The effect of acute caffeine intake on insulin sensitivity and glycemic control in people with diabetes

The prevalence of diabetes is growing globally, and with no current cure for the disease, management is focused on optimizing blood glucose control to limit complications. The purpose of this review was to examine the effect of caffeine intake on blood glucose levels in people with diabetes. Electronic searches were completed using Pub Med, CINAHL, and Web of Science using the search terms "coffee and insulin," "caffeine and insulin," "caffeine and diabetes," "caffeine and type 1 diabetes," "caffeine and type 2 diabetes," and "caffeine and glycemia." Seven trials were found to meet the search criteria. Five of the 7 studies suggest caffeine intake increases blood glucose levels, and prolongs the period of high blood glucose levels. Future research should focus on larger clinical trials to confirm the relationship and mechanism of action related to caffeine intake and glycemic control in individuals with diabetes.

Wearable Continuous Glucose Monitoring Sensors: A Revolution in Diabetes Treatment

Worldwide, the number of people affected by diabetes is rapidly increasing due to aging populations and sedentary lifestyles, with the prospect of exceeding 500 million cases in 2030, resulting in one of the most challenging socio-health emergencies of the third millennium. Daily management of diabetes by patients relies on the capability of correctly measuring glucose concentration levels in the blood by using suitable sensors. In recent years, glucose monitoring has been revolutionized by the development of Continuous Glucose Monitoring (CGM) sensors, wearable non/minimally-invasive devices that measure glucose concentration by exploiting different physical principles, e.g., glucose-oxidase, fluorescence, or skin dielectric properties, and provide real-time measurements every 1–5 min. CGM opened new challenges in different disciplines, e.g., medicine, physics, electronics, chemistry, ergonomics, data/signal processing, and software development to mention but a few. This paper first makes an overview of wearable CGM sensor technologies, covering both commercial devices and research prototypes. Then, the role of CGM in the actual evolution of decision support systems for diabetes therapy is discussed. Finally, the paper presents new possible horizons for wearable CGM sensor applications and perspectives in terms of big data analytics for personalized and proactive medicine.

Use of Flash Glucose-Sensing Technology for 12 months as a Replacement for Blood Glucose Monitoring in Insulin-treated Type 2 Diabetes

INTRODUCTION

Published evaluations of sensor glucose monitoring use in insulin treated type 2 diabetes are limited. The aim of this study was to assess the impact of flash glucose-sensing technology as a replacement for self-monitoring of blood glucose (SMBG) over a 12-month period in participants with type 2 diabetes who were on intensive insulin therapy.

METHODS

An open-label, randomized, controlled study in adults with type 2 diabetes on intensive insulin therapy from 26 European diabetes centers aimed at assessing flash glucose sensing technology was conducted. Participants (N = 224) were randomized (1:2 respectively) to a control group (n = 75) that used SMBG (FreeStyle Lite™) or to an intervention group (n = 149) which used sensor glucose data (FreeStyle Libre™ Flash Glucose Monitoring System) for self-management over 6 months. All intervention group participants who completed the 6-month treatment phase continued into an additional 6-month open-access phase.

RESULTS

A total of 139 intervention participants completed the 6-month treatment phase and continued into the open-access phase. At 12 months (end of open-access period), time in hypoglycemia [sensor glucose <3.9 mmol/L (70 mg/dL)] was reduced by 50% compared to baseline [-0.70 ± 1.85/24 h (mean ± standard deviation); p = 0.0002]. Nocturnal hypoglycemia [2300 to 0600 hours, <3.9 mmol/L (70 mg/dL)] was reduced by 52%; p = 0.0002. There was no change in time in range [sensor glucose 3.9-10.0 mmol/L (70-180 mg/dL)]. SMBG testing fell from a mean of 3.9 (median 3.9) times/day at baseline to 0.2 (0.0), with an average frequency of sensor scanning of 7.1 (5.7) times/day at 12 months, and mean sensor utilization was 83.6 ± 13.8% (median 88.3%) during the open-access phase. During this 6-month extension period no device-related serious adverse events were reported. Nine participants reported 16 instances of device-related adverse events (e.g. infection, allergy) and 28 participants (20.1%) experienced 134 occurrences of anticipated skin symptoms/sensor-insertion events expected with device use (e.g. erythema, itching and rash).

CONCLUSION

The use of flash glucose-sensing technology for glycemic management in individuals with type 2 diabetes treated by intensive insulin therapy over 12 months was associated with a sustained reduction in hypoglycemia and safely and effectively replaced SMBG.

TRIAL REGISTRATION

ClinicalTrials.gov identifier, NCT02082184.