Real-World Hypoglycemia Avoidance with a Continuous Glucose Monitoring System's Predictive Low Glucose Alert

Diabetes Technology in People with Type 2 Diabetes: Novel Indications

PURPOSE OF REVIEW

Diabetes technology has been continuously evolving. Current versions of continuous glucose monitors (CGM) use minimally invasive designs, monitor glucose values with high accuracy, and can be used to guide insulin dosing. Extensive evidence supports the use of diabetes technology for monitoring and insulin administration in people with type 1 diabetes. However, there is emerging evidence for people with type 2 diabetes. In this review, we present the different technological devices used to monitor glucose and deliver insulin and the evidence supporting their use in people with type 2 diabetes.

RECENT FINDINGS

The use of CGMs in people with type 2 diabetes treated with insulin or non-insulin therapies has been associated with improvements in glycemic control and time spent in hypoglycemia. Smart insulin pens and smart connected devices are options to track compliance and guide insulin delivery in people who do not require insulin pump therapy. Mechanical patch pumps can be used to reduce the burden of multiple daily insulin injections. Automated insulin delivery algorithms improve glycemic control without an increase in hypoglycemia. The use of technology in the management of type 2 diabetes generates glycemic data previously inaccessible, reduces barriers for insulin initiation, improves glycemic control, tracks adherence to therapy, and improves user satisfaction.

Switching from Intermittently Scanned Continuous Glucose Monitoring to Real-Time Continuous Glucose Monitoring with a Predictive Urgent Low Soon Alert Reduces Exposure to Hypoglycemia

Differences in the effectiveness of real-time continuous glucose monitoring (rtCGM) and intermittently scanned continuous glucose monitoring (isCGM) in type 1 diabetes (T1D) are reported. The impact on percent time in range of switching from an isCGM with glucose threshold-based optional alerts only (FreeStyle Libre 2 [FSL2]) to an rtCGM (Dexcom G7) with an urgent low soon predictive alert was assessed, alongside other secondary outcomes including hemoglobin A1c (HbA1c) and other continuous glucose monitoring metrics. Adults with T1D using FSL2 were switched to Dexcom G7 for 12 weeks. HbA1c and continuous glucose data during FSL2 and Dexcom G7 use were compared. Data from 29 participants (aged 44.8 ± 16.5 years, 12 male and 17 female) were analyzed. After switching to rtCGM, participants spent less time in hypoglycemia below 3.9 mmol/L (70 mg/dL) (3.0% [1.0%, 5.0%] vs. 2.0% [1.0%, 3.0%], P = 0.006) and had higher percentage achievement of time below 3.9 mmol/L (70 mg/dL) of <4% (55.2% vs. 82.8%, P = 0.005). Coefficient of variation was lower (39.3 ± 6.6% vs. 37.2 ± 5.6%, P = 0.008). In conclusion, adults with T1D who switched from isCGM to rtCGM may benefit from reduced exposure to hypoglycemia and glycemic variability.

Integration of a Safety Module to Prevent Rebound Hypoglycemia in Closed-Loop Artificial Pancreas Systems

BACKGROUND

With automated insulin delivery (AID) systems becoming widely adopted in the management of type 1 diabetes, we have seen an increase in occurrences of rebound hypoglycemia or generated hypoglycemia induced by the controller's response to rapid glucose rises following rescue carbohydrates. Furthermore, as AID systems aim to enable complete automation of prandial control, algorithms are designed to react even more strongly to glycemic rises. This work introduces a rebound hypoglycemia prevention layer (HypoSafe) that can be easily integrated into any AID system.

METHODS

HypoSafe constrains the maximum permissible insulin delivery dose based on the minimum glucose reading from the previous hour and the current glucose level. To demonstrate its efficacy, we integrated HypoSafe into the latest University of Virginia (UVA) AID system and simulated two scenarios using the 100-adult cohort of the UVA/Padova T1D simulator: a nominal case including three unannounced meals, and another case where hypoglycemia was purposely induced by an overestimated manual bolus.

RESULTS

In both simulation scenarios, rebound hypoglycemia events were reduced with HypoSafe (nominal: from 39 to 0, hypo-induced: from 55 to 7) by attenuating the commanded basal (nominal: 0.27U vs. 0.04U, hypo-induced: 0.27U vs. 0.03U) and bolus (nominal: 1.02U vs. 0.05U, hypo-induced: 0.43U vs. 0.02U) within the 30-minute interval after treating a hypoglycemia event. No clinically significant changes resulted for time in the range of 70 to 180 mg/dL or above 180 mg/dL.

CONCLUSION

HypoSafe was shown to be effective in reducing rebound hypoglycemia events without affecting achieved time in range when combined with an advanced AID system.

The development and evolution of insulin pumps: from early beginnings to future prospects

Diabetes technology has proliferated extensively over the past few decades with vast ameliorations in glucose monitoring and in insulin delivery systems. From a treatment based on daily insulin injections, we have moved to increasingly advanced technologies. Despite such advancements which have allowed better glycemic control, decreased diabetes-related complications, and improved the quality of life among diabetic patients, it has left many individuals unsatisfied with the current rate of commercial artificial pancreas development, stemming the need for further research into novel technologies. Accordingly, the Juvenile Diabetes Research Foundation has marked three generations for the development of an artificial pancreas comprising historical landmarks and future prospects which aim to produce an advanced technological system that attempts to mimic the endogenous pancreas, eliminating the need for user input. This review presents a synopsis of the development and evolution of insulin pumps, starting with the earliest technologies available such as continuous subcutaneous insulin infusion and continuous glucose monitoring as separate components, to currently available integrated advanced closed-loop hybrid systems and possible future technologies. The aim of the review is to provide insight of the advantages and limitations of past and currently available insulin pumps with the hope of driving research into novel technologies that attempt to mimic endogenous pancreatic function as closely as possible.

Real-World Continuous Glucose Monitoring Data from a Population with Type 1 Diabetes in South Korea: Nationwide Single-System Analysis

BACKGROUND

We used continuous glucose monitoring (CGM) data to investigate glycemic outcomes in a real-world population with type 1 diabetes (T1D) from South Korea, where the widespread use of CGM and the nationwide education program began almost simultaneously.

METHODS

Data from Dexcom G6 users with T1D in South Korea were collected between January 2019 and January 2023. Users were included if they provided at least 90 days of glucose data and used CGM at least 70% of the days in the investigational period. The relationship between CGM utilization and glycemic metrics, including the percentage of time in range (TIR), time below range (TBR), and time above range (TAR), was assessed.

RESULTS

A total of 2,288 users were included. Mean age was 41.5 years (57% female), with average uploads of 428 days. Mean TIR was 62.4±18.5%, mean TBR<70 mg/dL was 2.6±2.8%, mean TAR>180 mg/dL was 35.0±19.3%, mean glucose was 168.1±35.8 mg/dL, mean glucose management indicator was 7.2±0.9%, and mean coefficient of variation was 36.7±6.0%. Users with higher CGM utilization had higher TIR (67.8% vs. 52.7%), and lower TBR<70 mg/dL (2.3% vs. 4.7%) and TAR>180 mg/dL (30.0% vs. 42.6%) than those with low CGM utilization (p<0.001 for all). Users whose data were shared with others had higher TIR than those who did not (63.3% vs. 60.8%, p=0.001).

CONCLUSIONS

In this South Korean population, higher CGM utilization was associated with a favorably higher mean TIR, which was close to the internationally recommended target. Using its remote data-sharing feature showed beneficial impact on TIR.

Accuracy and Potential Interferences of Continuous Glucose Monitoring Sensors in the Hospital

For years, the standard of care for monitoring dysglycemia in hospitalized patients was capillary blood glucose (CBG) testing with point-of-care glucose meters. Recently, there has been a revolution in novel factory-calibrated continuous glucose monitoring (CGM) systems. Newer CGMs are smaller and less expensive, have improved accuracy and longer wear time, and do not require fingerstick CBG for calibration, resulting in increased utilization in ambulatory settings. Consequently, hospitals have noticed increased usability of CGMs among hospitalized patients and expect a progressive continued increase. During the COVID-19 pandemic, there was a critical need for innovative approaches to glycemic monitoring, with several pilot implementation projects using CGM in the intensive care unit and non-intensive care unit settings, further boosting the evidence in this area. Hence, recent guidelines have provided recommendations for the use of CGM in specific hospital scenarios and highlighted the potential of CGM to overcome CBG limitations for glucose monitoring in the inpatient setting. In this review, we provide the following: 1) an up-to-date review of the accuracy of the newer CGMs in hospitalized patients, 2) a discussion of standards for CGM accuracy metrics, 3) a contemporary overview of potential interferences that may cause inaccuracies or poor CGM performance, and 4) required steps for full regulatory approval of CGMs in the hospital and future research steps to advance the field forward.

Real-life data of hypoglycemic events in children and adolescents with type 1 diabetes

INTRODUCTION

Hypoglycemia composes an always present risk in the treatment of type 1 diabetes (T1D) and can be a fatal complication. Many studies on hypoglycemic events are based on self-reported data or focused on the aggregated time below range. We have processed continuous glucose monitoring (CGM) data in children and adolescents with T1D in order to examine all occurring hypoglycemic events.

RESEARCH DESIGN AND METHODS

CGM data (mean 168±3 days) from 214 children and adolescents with T1D were analyzed using computer-based algorithms. Patients were divided into three groups based on estimated HbA1c (eHbA1c): (1) ≤48 mmol/mol (n=58); (2) 49-64 mmol/mol (n=113); (3) ≥65 mmol/mol (n=43). The groups were compared concerning descriptive data and CGM metrics with emphasis on the frequency of hypoglycemic events.

RESULTS

Only one self-reported event of severe hypoglycemia was registered, while 54 390 hypoglycemic events (<3.9 mmol/L (<70 mg/dL)) were identified from CGM data out of which 11 740 were serious (<3.0 mmol/L (<54 mg/dL)). On average there were 1.5±0.1 hypoglycemic events per 24 hours out of which 1.2±0.1 were mild (3.0-3.9 mmol/L) and 0.3±0.02 serious. Group 1 had a higher frequency of both total and mild hypoglycemic events compared with both groups 2 and 3. However, the frequency of serious hypoglycemic events was similar in all groups. A negative correlation was observed for eHbA1c and total daily and mild hypoglycemic events (r=-0.57 and r=-0.66, respectively, p<0.0001), whereas for serious hypoglycemic events there was only a borderline significance (r=-0.13, p=0.05).

CONCLUSIONS

This study shows that hypoglycemic events are a frequent phenomenon in children and adolescents with T1D, occurring regardless of overall metabolic control. Although patients with an HbA1c ≤48 mmol/mol had a higher frequency of mild hypoglycemic events there was no increase in serious hypoglycemic events.

Development and Validation of Binary Classifiers to Predict Nocturnal Hypoglycemia in Adults With Type 1 Diabetes

BACKGROUND

One of the biggest challenges for people with type 1 diabetes (T1D) using multiple daily injections (MDIs) is nocturnal hypoglycemia (NH). Recurrent NH can lead to serious complications; hence, prevention is of high importance. In this work, we develop and externally validate, device-agnostic Machine Learning (ML) models to provide bedtime decision support to people with T1D and minimize the risk of NH.

METHODS

We present the design and development of binary classifiers to predict NH (blood glucose levels occurring below 70 mg/dL). Using data collected from a 6-month study of 37 adult participants with T1D under free-living conditions, we extract daytime features from continuous glucose monitor (CGM) sensors, administered insulin, meal, and physical activity information. We use these features to train and test the performance of two ML algorithms: Random Forests (RF) and Support Vector Machines (SVMs). We further evaluate our model in an external population of 20 adults with T1D using MDI insulin therapy and wearing CGM and flash glucose monitoring sensors for two periods of eight weeks each.

RESULTS

At population-level, SVM outperforms RF algorithm with a receiver operating characteristic-area under curve (ROC-AUC) of 79.36% (95% CI: 76.86%, 81.86%). The proposed SVM model generalizes well in an unseen population (ROC-AUC = 77.06%), as well as between the two different glucose sensors (ROC-AUC = 77.74%).

CONCLUSIONS

Our model shows state-of-the-art performance, generalizability, and robustness in sensor devices from different manufacturers. We believe it is a potential viable approach to inform people with T1D about their risk of NH before it occurs.

G6 continuous glucose monitoring system feature use and its associations with glycaemia in Europe

AIMS

Current continuous glucose monitoring (CGM) devices provide features that alert individuals with diabetes about their current and impending adverse glycaemic events. The use of these features has been associated with glycaemic improvements. However, how these features are utilised under real-world conditions has not been well studied. We queried a large database to quantify utilisation of the Dexcom G6 system features and how utilisation impacted glycaemic outcomes within a cohort of European users.

METHODS

This 6-month retrospective, observational, large database analysis utilised anonymised data from a sample of 47,784 Europe-based G6 users. Primary outcome measures were associations between utilisation and customisation of High/Low threshold alerts, 'urgent low soon' (ULS) alert, and established CGM metrics.

RESULTS

Users in the Germany, Austria, Switzerland region (n = 20,257), the Nordic countries (n = 10,314), United Kingdom (n = 9006), Italy (n = 4747), France (n = 2130) and Spain (1330) were included. All alert features were utilised by >75% of the cohort across all regions/countries and age groups. Enabling the Low alert and ULS alert was associated with lower percentage of time below range compared to disabling the Low alert (p < 0.001). Enabling the High alert was associated with higher percentage of time in range (%TIR) and lower percentage of time above range (%TAR) %TAR compared to disabling the High alert (p < 0.001). Paediatric patients and older adults tended to set a higher threshold for High/Low alerts, while younger adults tended to use lower threshold values for High/Low alerts.

CONCLUSIONS

Individuals who utilised the Dexcom G6 features showed better glycaemic control, particularly among those who utilised more sensitive High alert and Low alert settings, than users who did not utilise the system features.

Assessing non-adjunctive CGM safety at home and in new markets (ANSHIN)

INTRODUCTION

Continuous glucose monitoring (CGM) can guide treatment for people with type 1 (T1D) and type 2 diabetes (T2D). The ANSHIN study assessed the impact of non-adjunctive CGM use in adults with diabetes using intensive insulin therapy (IIT).

MATERIALS AND METHODS

This single-arm, prospective, interventional study enrolled adults with T1D or T2D who had not used CGM in the prior 6 months. Participants wore blinded CGMs (Dexcom G6) during a 20-day run-in phase, with treatment based on fingerstick glucose values, followed by a 16-week intervention phase and then a randomized 12-week extension phase with treatment based on CGM values. The primary outcome was change in HbA1c. Secondary outcomes were CGM metrics. Safety endpoints were the number of severe hypoglycaemic (SH) and diabetic ketoacidosis (DKA) events.

RESULTS

Of the 77 adults enrolled, 63 completed the study. Those enrolled had mean (SD) baseline HbA1c of 9.8% (1.9%), 36% had T1D, and 44% were ≥65 years old. Mean HbA1c decreased by 1.3, 1.0 and 1.0 percentage points for participants with T1D, T2D or age ≥65, respectively (p < .001 for each). CGM-based metrics including time in range also improved significantly. SH events decreased from the run-in period (67.3 per 100 person-years) to the intervention period (17.0 per 100 person-years). Three DKA events unrelated to CGM use occurred during the total intervention period.

CONCLUSIONS

Non-adjunctive use of the Dexcom G6 CGM system improved glycaemic control and was safe for adults using IIT.

Longitudinal analysis of users transitioning from the Dexcom G5 to the G6 RT-CGM system in Germany, Sweden and the United Kingdom (2018-2020)

AIMS

Regional variations in the adoption of diabetes technology may be reflected in population-level metrics of glycaemic control. In this observational study, we aimed to assess the glycaemic impacts of transitioning from the Dexcom G5 Real-Time Continuous Glucose Monitoring (RT-CGM) System to the Dexcom G6 in three European countries.

METHODS

Anonymised RT-CGM data (uploaded to the Dexcom Clarity app) were from users in Germany, Sweden, and the United Kingdom (UK) who transitioned from G5 to G6 between 9-12 months after G6 launched in 2018. Primary endpoints were percent time in hypoglycaemia, percent time in range (TIR), user retention rates, device utilisation, and urgent low soon (ULS) alert utilisation. Metrics were computed for 3-month intervals in the 2-year study window.

RESULTS

In all three countries, the transition from G5 to G6 was associated with a clear decrease in hypoglycaemia. In months 0-3 after transitioning, the median percent time 〈3 mmol/L (54 mg/dL) and 〈3.9 mmol/L (70 mg/dL) decreased by [0.12-0.28] and [0.40-0.43] percentage points, respectively, with another [0.11-0.21] and [0.34-0.65] percentage point decrease in months 3-6 in the three countries analysed. TIR and CGM utilisation were sustained or improved slightly across all countries. At the end of the study window, the retention rate was [88.8-94.8%] and ULS utilization was [83.9-86.9%] in the three countries analysed.

CONCLUSIONS

Similar RT-CGM trends were observed across Germany, Sweden, and the UK. Improvements in hypoglycaemia occurred in all countries. The high retention of users may lead to sustained glycaemic benefits associated with RT-CGM use.

Intermittent-scanned continuous glucose monitoring with low glucose alarms decreases hypoglycemia incidence in middle-aged adults with type 1 diabetes in real-life setting

OBJECTIVE

There is limited real-life data demonstrating that hypo-/hyperglycemic alarms added to continuous glucose monitoring (CGM) improve metabolic control in adults with type 1 diabetes (T1D). We evaluated the usefulness of switching from a flash or intermittent-scanned continuous glucose monitoring (is-CGM) device without low or higher glucose alarms to a is-CGM device with alarms to prevent hypoglycemia in adults with T1D.

METHODS

Individuals with T1D and fearful of hypoglycemia, prone to hypoglycemia unawareness, and/or experiencing severe hypoglycemia while using is-CGM Free Style Libre 1 (FSL1) were switched to FSL2 with individually-programmable low glucose alarms. The primary endpoint was the changes in % time below range (TBR%) <70 mg/dl [3.9 mmol/l] and <54 mg/dl [3.0 mmol/l] after 12 weeks on FSL2 compared with FSL1. Secondary endpoints were changes in % time in range (TIR% 70-180 mg/dl [3.9-10.0 mmol/l]), % time above range (TAR%) >180 [10.0 mmol/l], mean interstitial glucose, glycemic management indicator (GMI), interstitial glucose coefficient of variation (CV%), hemoglobin A1c, and sensor's scans/day.

RESULTS

We included 108 individuals (57.4 % men), aged 58.2 ± 17.3 [95 % CI: 55.0 to 61.5] years, with mean diabetes duration 25 ± 14.6 [95 % CI: 22.1 to 27.7] years. Among individuals, 40 (37.0 %) had hypoglycemia awareness with Clarke's score ≥4 and 19 (17.5 %) had a history of severe hypoglycemia. The median low glucose alarm threshold was 70 [IQR: 65-70] mg/dl (3.9 [IQR: 3.6-3.9] mmol/L). By comparison of first 12 weeks on FSL2 vs. last 12 weeks on FSL1, TBR% <70 mg/dl decreased from 4.5 ± 4.4 to 2.3 ± 2.8 % (p < 0.001), TBR% <54 mg/dl decreased from 1.4 ± 2.2 to 0.3 ± 0.9 % (p < 0.001). TIR% was not significantly different (51.5 ± 14.9 vs. 52.9 ± 16 % (p = 0.13)), nor was TAR% (43.8 ± 16.2 vs. 44.7 ± 16.5 % (p = 0.5)). CV% decreased from 39.4 ± 6.9 to 37.9 ± 6.1 % (p < 0.001). Those at risk for hypoglycemia (TBR >4 % and >1 %, respectively, at baseline) showed a significant decrease in the incidence of hypoglycemia <70 and <54 mg/dl (p < 0.0001). Patients' satisfaction with hypoglycemia alarms was high, since all individuals opted to pursue using individual alarm beyond the study period.

CONCLUSION

Switching from FSL1 to FSL2 with low glucose alarms reduced the frequency of hypoglycemia in middle-age adults with T1D, particularly in those who were prone to hypoglycemia awareness or severe hypoglycemia.

Diabetes Therapy Podcast: Real-World Data for Glucose Sensing Technologies in Type 1 Diabetes

For people living with type 1 diabetes (T1D), home glucose monitoring has evolved from occasional qualitative urine tests to frequently sampled continuous data providing hundreds of data points per day to inform optimal self-management. Continuous glucose monitoring technologies have a robust evidence base derived from randomized controlled trials (RCTs) over the last 20 years, and are now implemented in routine clinical practice, reflecting their clinical and cost effectiveness. However, while randomized studies are the gold standard, they can be slow to set-up, unrepresentative and do not provide data for efficacy in large, unselected populations. Real-world data can be responsive to rapid product cycles in technologies, provide a large, representative population, and have a lower regulatory burden. In this podcast we discuss the advantages and pitfalls of using real-world data to assess the efficacy of continuous glucose sensing technologies in people with T1D, with reference to examples of real-world data for real-time and intermittently scanned continuous glucose monitoring. Large datasets confirm the RCT data for real-time technologies and additionally provide data for work absenteeism and hospital admissions, as well as showing the impact of advanced technology features that can be difficult to assess in randomized studies. Real-world data for intermittently scanned monitoring also confirm the randomized controlled trial data, provide additional insights not shown in controlled study environments and highlight the importance of health equality. A mature real-world dataset for automated insulin delivery systems is now available and the future of glucose sensing is also discussed.

Cost-Effectiveness of a Real-Time Continuous Glucose Monitoring System Versus Self-Monitoring of Blood Glucose in People with Type 2 Diabetes on Insulin Therapy in the UK

INTRODUCTION

Real-time continuous glucose monitoring (rt-CGM) involves the measurement and display of glucose concentrations, potentially improving glucose control among insulin-treated patients with type 2 diabetes (T2D). The present analysis aimed to conduct a cost-effectiveness analysis of rt-CGM versus self-monitoring of blood glucose (SMBG) based on a USA retrospective cohort study in insulin-treated people with T2D adapted to the UK.

METHODS

Long-term costs and clinical outcomes were estimated using the CORE Diabetes Model, with clinical input data sourced from a retrospective cohort study. Patients were assumed to have a baseline glycated hemoglobin (HbA1c) of 8.3%. Patients using rt-CGM were assumed to have a 0.56% reduction in HbA1c based on the mean difference between groups after 12 months of follow-up. Reduced fingerstick testing when using rt-CGM was associated with a quality of life (QoL) benefit. The analysis was performed over a lifetime time horizon from a National Health Service (NHS) perspective, including only direct costs from published data. Future costs and clinical outcomes were discounted at 3.5% per annum. Extensive sensitivity analyses were performed.

RESULTS

Projections showed that rt-CGM was associated with increased quality-adjusted life expectancy of 0.731 quality-adjusted life years (QALYs) and increased mean total lifetime costs of Great British pounds (GBP) 2694, and an incremental cost-effectiveness ratio of GBP 3684 per QALY compared with SMBG. Key drivers of outcomes included HbA1c reduction and reduced fingerstick testing QoL benefit.

CONCLUSIONS

Over patient lifetimes, rt-CGM was associated with improved clinical outcomes and is highly likely to be cost effective versus SMBG in people with T2D on insulin therapy in the UK.

Long-term cost-effectiveness of Dexcom G6 real-time continuous glucose monitoring system in people with type 1 diabetes in Australia

INTRODUCTION

Real-time continuous glucose monitoring (rt-CGM) allows patients with diabetes to adjust insulin dosing, potentially improving glucose control. This study aimed to compare the long-term cost-effectiveness of the Dexcom G6 rt-CGM device versus self-monitoring of blood glucose (SMBG) and flash glucose monitoring (FGM) in Australia in people with type 1 diabetes (T1D).

METHODS

Long-term costs and clinical outcomes were estimated using the CORE Diabetes Model. Clinical input data for the analysis of rt-CGM versus SMBG and FGM were sourced from the DIAMOND study and a network meta-analysis, respectively. Rt-CGM and FGM were associated with quality of life (QoL) benefits due to reduced fear of hypoglycaemia (FoH) and fingerstick testing. Analyses were performed over a lifetime time horizon from an Australian healthcare payer perspective, including direct costs from published data. Future costs and clinical outcomes were discounted at 5% per annum.

RESULTS

Rt-CGM was associated with an increased quality-adjusted life expectancy of 1.199 quality-adjusted life years (QALYs), increased mean total lifetime costs of AUD 21,596 and an incremental cost-effectiveness ratio (ICER) of AUD 18,020 per QALY gained compared with SMBG. Compared with FGM, rt-CGM was associated with an increased quality-adjusted life expectancy of 0.569 QALYs, increased mean total lifetime costs of AUD 11,064 and an ICER of AUD 19,455 per QALY gained. Key drivers of outcomes included HbA_1c benefits and QoL benefits associated with reduced FoH and fingerstick testing.

CONCLUSIONS

Due to improved clinical outcomes and QoL gains rt-CGM is highly cost-effective compared with SMBG and FGM in people with T1D in Australia.

Mitigation of Rebound Hyperglycemia With Real-Time Continuous Glucose Monitoring Data and Predictive Alerts

BACKGROUND

Excess carbohydrate intake during hypoglycemia can lead to rebound hyperglycemia (RH). We investigated associations between RH and use of real-time continuous glucose monitoring (rtCGM) and an rtCGM system's predictive alert.

METHODS

RH events were series of sensor glucose values (SGVs) >180 mg/dL starting within two hours of an antecedent SGV <70 mg/dL. Events were characterized by their frequency, duration (consecutive SGVs >180 mg/dL × five minutes), and severity (area under the glucose concentration-time curve). To assess the impact of rtCGM, data gathered during the four-week baseline phase (without rtCGM) and four-week follow-up phase (with rtCGM) from 75 participants in the HypoDE clinical trial (NCT02671968) of hypoglycemia-unaware individuals were compared. To assess the impact of predictive alerts, we identified a convenience sample of 24 518 users of an rtCGM system without predictive alerts who transitioned to a system whose predictive alert signals an SGV ≤55 mg/dL within 20 minutes (Dexcom G5 and G6, respectively). RH events from periods of blinded versus unblinded rtCGM wear and from periods of G5 and G6 wear were compared with paired t tests.

RESULTS

Compared to RH events in the HypoDE baseline phase, the mean frequency, duration, and severity of events fell by 14%, 12%, and 23%, respectively, in the follow-up phase (all P < .05). Compared to RH events during G5 use, the mean frequency, duration, and severity of events fell by 7%, 8%, and 13%, respectively, during G6 use (all P < .001).

CONCLUSIONS

Rebound hypreglycemia can be objectively quantified and mitigated with rtCGM and rtCGM-based predictive alerts.

Non-adjunctive continuous glucose monitoring for control of hypoglycaemia (COACH): Results of a post-approval observational study

OBJECTIVE

Prior to the Continuous Monitoring and Control of Hypoglycaemia (COACH) study described herein, no study had been powered to evaluate the impact of non-adjunctive RT-CGM use on the rate of debilitating moderate or severe hypoglycaemic events.

RESEARCH DESIGN AND METHODS

In this 12-month observational study, adults with insulin-requiring diabetes who were new to RT-CGM participated in a 6-month control phase where insulin dosing decisions were based on self monitoring of blood glucose values, followed by a 6-month phase where decisions were based on RT-CGM data (i.e. non-adjunctive RT-CGM use); recommendations for RT-CGM use were made according to sites' usual care. The primary outcome was change in debilitating moderate (requiring second-party assistance) and severe (resulting in seizures or loss of consciousness) hypoglycaemic event frequency. Secondary outcomes included changes in HbA1c and diabetic ketoacidosis (DKA) frequency.

RESULTS

A total of 519 participants with mean (SD) age 50.3 (16.1) years and baseline HbA1c 8.0% (1.4%) completed the study, of whom 32.8% had impaired hypoglycaemia awareness and 33.5% had type 2 diabetes (T2D). The mean (SE) per-patient frequency of hypoglycaemic events decreased by 63% from 0.08 (0.016) during the SMBG phase to 0.03 (0.010) during the RT-CGM phase (p = 0.005). HbA1c decreased during the RT-CGM phase both for participants with type 1 diabetes (T1D) and T2D and there was a trend towards larger reductions among individuals with higher baseline HbA1c.

CONCLUSIONS

Among adults with insulin-requiring diabetes, non-adjunctive use of RT-CGM data is safe, resulting in significantly fewer debilitating hypoglycaemic events than management using SMBG.

Effect of Nutritional Habits on the Glycemic Response to Different Carbohydrate Diet in Children with Type 1 Diabetes Mellitus

Unhealthy eating habits are associated with obesity, metabolic syndrome, and increased insulin resistance in young patients with type 1 diabetes mellitus (T1DM), and may impact the possible benefit from dietary interventions on glycaemic control. This study determines how nutritional patterns influence the quality of dietary intervention with a 30% or 50% carbohydrate diet in terms of glycaemic control measured with continuous glucose monitoring (CGM). Eating habits were obtained with a frequency-of-consumption questionnaire (FFQ-6) before the diet assessment. Altogether, we collected CGM and FFQ-6 data from 30 children (16 boys and 14 girls aged 10-17 years) with T1DM subjected to two consecutive 3-day nutritional plans. From these, 23 patients met the CGM data quality criteria for further analysis. Furthermore, high accuracy achieved in training (95.65%) and V-fold cross-validation (81.67%) suggest a significant impact of food habits in response to introduced nutritional changes. Patients who consumed more vegetables or grains (>4 times per day), more wheat products (>once per day), fewer fats (<1.5 times per day), and ranked fruit juice as the most common selection in the drinks category achieved glycaemic control more often after the introduction of a 30% carbohydrate diet, as opposed to those with different dietary patterns, whose glycaemic control was negatively impacted after switching to this diet. Additionally, the 50% carbohydrate diet was safe for all patients in the context of glycaemic control.

Hypoglycaemia detection and prediction techniques: A systematic review on the latest developments

The main objective of diabetes control is to correct hyperglycaemia while avoiding hypoglycaemia, especially in insulin-treated patients. Fear of hypoglycaemia is a hurdle to effective correction of hyperglycaemia because it promotes under-dosing of insulin. Strategies to minimise hypoglycaemia include education and training for improved hypoglycaemia awareness and the development of technologies to allow their early detection and thus minimise their occurrence. Patients with impaired hypoglycaemia awareness would benefit the most from these technologies. The purpose of this systematic review is to review currently available or in-development technologies that support detection of hypoglycaemia or hypoglycaemia risk, and identify gaps in the research. Nanomaterial use in sensors is a promising strategy to increase the accuracy of continuous glucose monitoring devices for low glucose values. Hypoglycaemia is associated with changes on vital signs, so electrocardiogram and encephalogram could also be used to detect hypoglycaemia. Accuracy improvements through multivariable measures can make already marketed galvanic skin response devices a good noninvasive alternative. Breath volatile organic compounds can be detected by dogs and devices and alert patients at hypoglycaemia onset, while near-infrared spectroscopy can also be used as a hypoglycaemia alarms. Finally, one of the main directions of research are deep learning algorithms to analyse continuous glucose monitoring data and provide earlier and more accurate prediction of hypoglycaemia. Current developments for early identification of hypoglycaemia risk combine improvements of available 'needle-type' enzymatic glucose sensors and noninvasive alternatives. Patient usability will be essential to demonstrate to allow their implementation for daily use in diabetes management.

Use of Continuous Glucose Monitor in Critically Ill COVID-19 Patients Requiring Insulin Infusion: An Observational Study

CONTEXT

The coronavirus disease 2019 (COVID-19) pandemic has created a need for remote blood glucose (BG) monitoring in the intensive care unit (ICU).

OBJECTIVE

To evaluate feasibility and patient safety of a hybrid monitoring strategy of point-of-care (POC) BG plus continuous glucose monitor (CGM) in the ICU.

DESIGN

Retrospective analysis.

SETTING

ICU of an academic medical center.

PATIENTS

Patients with COVID-19 on IV insulin.

INTERVENTION

After meeting initial validation criteria, CGM was used for IV insulin titration and POC BG was performed every 6 hours or as needed.

MAIN OUTCOME MEASURES

Outcomes included frequency of POC BG, workflow, safety, and accuracy measures.

RESULTS

The study included 19 patients, 18 with CGM data, mean age 58 years, 89% on mechanical ventilation, 37% on vasopressors, and 42% on dialysis. The median time to CGM validation was 137 minutes (interquartile range [IQR] 114-206). During IV insulin, the median number of POC values was 7 (IQR 6-16) on day 1, and declined slightly thereafter (71% reduction compared with standard of 24/day). The median number of CGM values used nonadjunctively to titrate IV insulin was 11.5 (IQR 0, 15) on day 1 and increased thereafter. Time in range 70 to 180 mg/dL was 64 ± 23% on day 1 and 72 ± 16% on days 2 through 7, whereas time <70 mg/dL was 1.5 ± 4.1% on day 1 and <1% on days 2 through 7.

CONCLUSIONS

This study provides data to support that CGM using a hybrid protocol is feasible, accurate, safe, and has potential to reduce nursing and staff workload.

Integrating Continuous Glucose Monitoring Into Clinical Practices and Patients' Lives

Numerous studies have demonstrated the clinical benefits of continuous glucose monitoring (CGM) in individuals with diabetes. Within ongoing innovations in CGM technology, individuals now have an expanding array of options that allow them to select the device that meets their individual needs and preferences. Although demand for CGM in primary care continues to grow, many clinicians are reluctant to prescribe this technology due to their unfamiliarity with the various devices, uncertainty about which devices are best suited to each patient and the feasibility of using CGM. This article reviews the features and functionality of the most recent commercially available CGM devices and provides guidance for integrating CGM use into clinical practices.

Evaluation of the Long-Term Cost-Effectiveness of the Dexcom G6 Continuous Glucose Monitor versus Self-Monitoring of Blood Glucose in People with Type 1 Diabetes in Canada

BACKGROUND

The Dexcom G6 real-time continuous glucose monitoring (RT-CGM) system is one of the most sophisticated RT-CGM systems developed to date and became available in Canada in 2019. A health economic analysis was performed to determine the long-term cost-effectiveness of the Dexcom G6 RT-CGM system versus SMBG in adults with type 1 diabetes (T1D) in Canada.

METHODS

The analysis was performed using the IQVIA Core Diabetes Model. Based on clinical trial data, patients with mean baseline HbA1c of 8.6% were assumed to have a HbA1c reduction of 1.0% with RT-CGM versus 0.4% reduction with SMBG. RT-CGM was also associated with a quality of life (QoL) benefit owing to reduced incidence of hypoglycemia, reduced fear of hypoglycemia (FoH) and elimination of fingerstick testing. Direct medical costs were sourced from published literature, and inflated to 2019 Canadian dollars (CAD).

RESULTS

Dexcom G6 RT-CGM was projected to improve mean quality-adjusted life expectancy by 2.09 quality-adjusted life years (QALYs) relative to SMBG (15.52 versus 13.43 QALYs) but mean total lifetime cots were CAD 35,353 higher with RT-CGM (CAD 227,357 versus CAD 192,004) resulting in an incremental cost-effectiveness ratio (ICER) of CAD 16,931 per QALY gained. Sensitivity analyses revealed that assumptions relating to the QoL benefit associated with reduced FoH and the elimination of fingerstick testing with RT-CGM as well as SMBG usage and change in HbA1c were the key drivers of cost-effectiveness.

CONCLUSION

For adults with T1D in Canada, RT-CGM is associated with improved glycemic control and QoL benefits owing to a reduced FoH and elimination of the requirement for fingerstick testing and over a lifetime time horizon is cost-effective relative to SMBG.

Sustainable Use of a Real-Time Continuous Glucose Monitoring System from 2018 to 2020

We aimed to describe patterns of continuous glucose monitoring (CGM) system use and glycemic outcomes from 2018 to 2020 in a large real-world cohort by analyzing anonymized data from US-based CGM users who transitioned from the G5 to the G6 System (Dexcom) in 2018. The main end points were persistent use, within-day and between-day utilization, hypoglycemia, time in range (TIR, 70-180 mg/dL [3.9-10 mmol/L]), and use of the optional calibration feature in 2019 and 2020. In a cohort of 31,034 individuals, rates of persistent use were high, with 27,932 (90.0%) and 26,861 (86.6%) continuing to upload data in 2019 and 2020, respectively. Compared with G5 use, G6 use was associated with higher device utilization, less hypoglycemia, higher TIR (in 2020), and >80% fewer calibrations in both 2019 and 2020 (P's < 0.001). High persistence and utilization of the G6 system may contribute to sustainable glycemic outcomes and decreased user burden.

Standardized Hybrid Closed-Loop System Reporting

The hybrid closed-loop (HCL) system has been shown to improve glycemic control and reduce hypoglycemia. Optimization of HCL settings requires interpretation of the glucose, insulin, and factors affecting glucose such as food intake and exercise. To the best of our knowledge, there is no published guidance on the standardized reporting of HCL systems. Standardization of HCL reporting would make interpretation of data easy across different systems. We reviewed the literature on patient and provider perspectives on downloading and reporting glucose metric preferences. We also incorporated international consensus on standardized reporting for glucose metrics. We describe a single-page HCL data reporting, referred to here as "artificial pancreas (AP) Dashboard." We propose seven components in the AP Dashboard that can provide detailed information and visualization of glucose, insulin, and HCL-specific metrics. The seven components include (A) glucose metrics, (B) hypoglycemia, (C) insulin, (D) user experience, (E) hyperglycemia, (F) glucose modal-day profile, and (G) insight. A single-page report similar to an electrocardiogram can help providers and patients interpret HCL data easily and take the necessary steps to improve glycemic outcomes. We also describe the optimal sampling duration for HCL data download and color coding for visualization ease. We believe that this is a first step in creating a standardized HCL reporting, which may result in better uptake of the systems. For increased adoption, standardized reporting will require input from providers, patients, diabetes device manufacturers, and regulators.

Change in Hemoglobin A1c and Quality of Life with Real-Time Continuous Glucose Monitoring Use by People with Insulin-Treated Diabetes in the Landmark Study

Background: Initiating continuous glucose monitoring (CGM) can affect hemoglobin A1c (HbA1c) levels and patients' relationship with their diabetes. We used real-world HbA1c data to quantify short-term changes in glycemia and validated psychosocial questionnaires to assess changes in quality-of-life indicators in people during their first few months of CGM use. Methods: Eligibility was assessed during calls to Dexcom sales regarding its G6 CGM System. Eligibility criteria included ages 25-65 years, type 1 (T1D) or type 2 diabetes (T2D) on intensive insulin therapy (IIT), and no prior CGM use. Participants used a web-based portal to complete the 17-item Diabetes Distress Scale (DDS) and the 14-item Hypoglycemia Attitudes and Behavior Scale (HABS); provided validated HbA1c measurements; and shared their CGM data pre- and 3-5 months post-CGM initiation. Satisfaction and ease of use with the G6 System were also assessed. Results: Data were available from 248 patients (182 with T1D, 66 with T2D; 57% male, 88% non-Hispanic white). Mean (standard deviation) HbA1c fell significantly from 8.2% (1.9%) at baseline to 7.1% (1.1%) at the end of the study (P < 0.001); more than half (54.4%) of those with initial HbA1c values >7% experienced absolute HbA1c reductions of >1%. Significant reductions in diabetes distress (DDS) and hypoglycemic concerns (HABS) were observed (P < 0.001). Most (93%) participants were satisfied or very satisfied with the G6 System and 73% found it very easy to use. Conclusions: The first 3 months of CGM use was correlated with improvements in psychosocial outcomes and improved HbA1c levels for people with T1D or T2D who use IIT.

Real-World Evidence and Glycemic Improvement Using Dexcom G6 Features

Background: Optional features of continuous glucose monitoring (CGM) systems empower patients and caregivers to understand and manage diabetes in new ways. We examined associations between use of optional features, demographics, and glycemic outcomes. Methods: Retrospective cohort studies were performed with data from US-based users of the G6 CGM System (Dexcom, Inc.). For all cohorts, data included sensor glucose values (SGVs). In separate cohorts, use of alert features (for hyperglycemia, existing hypoglycemia, and impending hypoglycemia), remote data sharing feature (Share), software for retrospective pattern analysis (CLARITY), "virtual assistant" feature that announces the current SGV and trend in response to a spoken request were assessed. Descriptive statistics were used to summarize feature set utilization patterns and relate them to glycemic outcomes. Results: Most individual features were consistently adopted by high proportions of G6 users. Threshold SGVs chosen for activating hyperglycemia and hypoglycemia alerts varied with age and were higher among the youngest and oldest patients. Use of the Share feature was more common among young patients and those with type 1 diabetes. Individuals who used more of the alert and notification features had more favorable glycemic outcomes, including time in range (TIR), than those who used fewer. More extensive engagement with CLARITY notifications was associated with higher TIR. Frequent use of the virtual assistant feature was associated with higher TIR and lower mean SGV. Conclusions: Optional features of the G6 CGM system are acceptable to and appear to benefit patients who use them. Different levels of engagement suggest that demographics and personal circumstances play a role in how patients and caregivers use CGM features to help manage diabetes.

Facilitators and Barriers to Nursing Implementation of Continuous Glucose Monitoring (CGM) in Critically Ill Patients With COVID-19

OBJECTIVE

We describe our implementation of a continuous glucose monitoring (CGM) guideline to support intravenous insulin administration and reduce point of care (POC) glucose monitoring frequency in the coronavirus disease 2019 medical intensive care unit (MICU) and evaluate nurses' experience with implementation of CGM and hybrid POC + CGM protocol using the Promoting Action on Research in Health Services framework.

METHODS

A multidisciplinary team created a guideline providing criteria for establishing initial sensor-meter agreement within each individual patient followed by hybrid use of CGM and POC. POC measures were obtained hourly during initial validation, then every 6 hours. We conducted a focus group among MICU nurses to evaluate initial implementation efforts with content areas focused on initial assessment of evidence, context, and facilitation to identify barriers and facilitators. The focus group was analyzed using a qualitative descriptive approach.

RESULTS

The protocol was integrated through a rapid cycle review process and ultimately disseminated nationally. The Diabetes Consult Service performed device set-up and nurses received just-in-time training. The majority of barriers centered on contextual factors, including limitations of the physical environment, complex device set-up, hospital firewalls, need for training, and CGM documentation. Nurses' perceived device accuracy and utility were exceptionally high. Solutions were devised to maximize facilitation and sustainability for nurses while maintaining patient safety.

CONCLUSION

Outpatient CGM systems can be implemented in the MICU using a hybrid protocol implementation science approach. These efforts hold tremendous potential to reduce healthcare worker exposure while maintaining glucose control during the COVID-19 pandemic.

Responses to Low- and High-Intensity Exercise in Adolescents with Type 1 Diabetes in Relation to Their Level of VO2 Max

The purpose of this study was to investigate the influence of maximal oxygen uptake (VO₂ max) on the glycemic changes during low and high intensity exercises in young type 1 diabetic patients. Twenty boys (age: 14.3 ± 1.6 years; height: 171.0 ± 11.3 cm; weight; 59.5 ± 12.8 kg) were divided into low-fit group (LFG, n = 10) and high-fit group (HFG, n = 10). According to the experimental design, participants performed three physical efforts (VO₂ max test, mixed aerobic-anaerobic effort and aerobic effort) on the cycloergometer, during which real-time glycemia was measured. Mixed aerobic-anaerobic exercise demanded significantly smaller carbohydrate supplementation (0.2 ± 0.2 g/kg during exercise) than the aerobic test session (0.4 ± 0.3 g/kg during exercise). Moreover, patients with higher VO₂ max had lower tendency for glycemic changes during the aerobic effort. The results of the current study suggest that young type 1 diabetic patients should perform different intensity activities using continuous glycemic monitoring system to avoid acute and chronic complications of the disease.

Long-Term Cost-Effectiveness the Dexcom G6 Real-Time Continuous Glucose Monitoring System Compared with Self-Monitoring of Blood Glucose in People with Type 1 Diabetes in France

INTRODUCTION

The aim was to determine the long-term cost-effectiveness of the Dexcom G6 real-time continuous glucose monitoring (RT-CGM) system versus self-monitoring of blood glucose (SMBG) in adults with type 1 diabetes (T1D) in France.

METHODS

The analysis was performed using the IQVIA Core Diabetes Model and utilized clinical input data from the DIAMOND clinical trial in adults with T1D. Simulated patients were assumed to have a mean baseline HbA1c of 8.6%, and those in the RT-CGM arm were assumed to have a HbA1c reduction of 1.0% compared with 0.4% in the SMBG arm. A quality of life (QoL) benefit associated with a reduced fear of hypoglycemia (FoH) and elimination of the requirement for fingerstick testing in the RT-CGM arm was also applied.

RESULTS

The G6 RT-CGM system was associated with an incremental gain in quality-adjusted life expectancy of 1.38 quality-adjusted life years (QALYs) compared with SMBG (10.64 QALYs versus 9.23 QALYs). Total mean lifetime costs were 21,087 euros higher with RT-CGM (148,077 euros versus 126,990 euros), resulting in an incremental cost-effectiveness ratio of 15,285 euros per QALY gained.

CONCLUSIONS

In France, based on a willingness-to-pay threshold of 50,000 euros per QALY gained, the use of the G6 RT-CGM system is cost-effective relative to SMBG for adults with long-standing T1D, driven primarily by improved glycemic control and the QoL benefit associated with reduced FoH and elimination of the requirement for fingerstick testing.

Continuous glucose monitoring: The achievement of 100 years of innovation in diabetes technology

Monitoring of glucose levels is essential to effective diabetes management. Over the past 100 years, there have been numerous innovations in glucose monitoring methods. The most recent advances have centered on continuous glucose monitoring (CGM) technologies. Numerous studies have demonstrated that use of continuous glucose monitoring confers significant glycemic benefits on individuals with type 1 diabetes (T1DM) and type 2 diabetes (T2DM). Ongoing improvements in accuracy and convenience of CGM devices have prompted increasing adoption of this technology. The development of standardized metrics for assessing CGM data has greatly improved and streamlined analysis and interpretation, enabling clinicians and patients to make more informed therapy modifications. However, many clinicians many be unfamiliar with current CGM and how use of these devices may help individuals with T1DM and T2DM achieve their glycemic targets. The purpose of this review is to present an overview of current CGM systems and provide guidance to clinicians for initiating and utilizing CGM in their practice settings.

Long-term Cost-Effectiveness of Dexcom G6 Real-time Continuous Glucose Monitoring Versus Self-Monitoring of Blood Glucose in Patients With Type 1 Diabetes in the U.K

OBJECTIVE

A long-term health economic analysis was performed to establish the cost-effectiveness of real-time continuous glucose monitoring (RT-CGM) (Dexcom G6) versus self-monitoring of blood glucose (SMBG) alone in U.K.-based patients with type 1 diabetes (T1D).

RESEARCH DESIGN AND METHODS

The analysis used the IQVIA CORE Diabetes Model. Clinical input data were sourced from the DIAMOND trial in adults with T1D. Simulations were performed separately in the overall population of patients with baseline HbA_1c ≥7.5% (58 mmol/mol), and a secondary analysis was performed in patients with baseline HbA_1c ≥8.5% (69 mmol/mol). The analysis was performed from the National Health Service health care payer perspective over a lifetime time horizon.

RESULTS

In the overall population, G6 RT-CGM was associated with a mean incremental gain in quality-adjusted life expectancy of 1.49 quality-adjusted life years (QALYs) versus SMBG (mean [SD] 11.47 [2.04] QALYs versus 9.99 [1.84] QALYs). Total mean (SD) lifetime costs were also pounds sterling (GBP) 14,234 higher with RT-CGM (GBP 102,468 [35,681] versus GBP 88,234 [39,027]) resulting in an incremental cost-effectiveness ratio of GBP 9,558 per QALY gained. Sensitivity analyses revealed that the findings were sensitive to changes in the quality-of-life benefit associated with reduced fear of hypoglycemia and avoidance of fingerstick testing as well as the HbA_1c benefit associated with RT-CGM use.

CONCLUSIONS

For U.K.-based T1D patients, the G6 RT-CGM device is associated with significant improvements in clinical outcomes and, over patient lifetimes, is a cost-effective disease management option relative to SMBG on the basis of a willingness-to-pay threshold of GBP 20,000 per QALY gained.

Continuous glucose monitoring for hypoglycaemia in children: Perspectives in 2020

Hypoglycaemia in children is a major risk factor for adverse neurodevelopment with rates as high as 50% in hyperinsulinaemic hypoglycaemia (HH). A key part of management relies upon timely identification and treatment of hypoglycaemia. The current standard of care for glucose monitoring is by infrequent fingerprick plasma glucose testing but this carries a high risk of missed hypoglycaemia identification. High-frequency Continuous Glucose Monitoring (CGM) offers an attractive alternative for glucose trend monitoring and glycaemic phenotyping but its utility remains largely unestablished in disorders of hypoglycaemia. Attempts to determine accuracy through correlation with plasma glucose measurements using conventional methods such as Mean Absolute Relative Difference (MARD) overestimate accuracy at hypoglycaemia. The inaccuracy of CGM in true hypoglycaemia is amplified by calibration algorithms that prioritize hyperglycaemia over hypoglycaemia with minimal objective evidence of efficacy in HH. Conversely, alternative algorithm design has significant potential for predicting hypoglycaemia to prevent neuroglycopaenia and consequent brain dysfunction in childhood disorders. Delays in the detection of hypoglycaemia, alarm fatigue, device calibration and current high cost are all barriers to the wider adoption of CGM in disorders of hypoglycaemia. However, machine learning, artificial intelligence and other computer-generated algorithms now offer significant potential for further improvement in CGM device technology and widespread application in childhood hypoglycaemia.

Longitudinal Analysis of Real-World Performance of an Implantable Continuous Glucose Sensor over Multiple Sensor Insertion and Removal Cycles

The Eversense® Continuous Glucose Monitoring (CGM) System, with the first long-term, implantable glucose sensor, has been commercially available in Europe and South Africa since 2016 for adults with diabetes. The performance of the sensor over multiple, sequential 90- or 180-day cycles from either real-world experience or clinical studies has not been previously published. The Eversense Data Management System (DMS) was used to evaluate the accuracy of General Data Protection Regulation (GDPR)-compliant sensor glucose (SG) values against self-monitoring of blood glucose (SMBG) from June 2016 through August 2019 among patients with at least four sensor cycles from European and South African health care practices. Mean SG and associated measures of variability, glucose management indicator (GMI), and percent and time in various hypoglycemic, euglycemic, and hyperglycemic ranges were calculated for the 24-h time period over each cycle. In addition, transmitter wear time was evaluated across each sensor wear cycle. Among the 945 users included in the analysis, the mean absolute relative difference (standard deviation [SD]) using 152,206, 174,645, 206,024, and 172,587 calibration matched pairs against SMBG was 11.9% (3.6%), 11.5% (4.0%), 11.8% (4.7%), and 11.5% (4.1%) during the first four sensor cycles, respectively. Mean values of the CGM metrics over the first sensor cycle were 156.5 mg/dL for SG, 54.7 mg/dL for SD, 0.35 for coefficient of variation, and 7.04% for GMI. Percent SG at different glycemic ranges was as follows: <54 mg/dL was 1.1% (16 min), <70 mg/dL was 4.6% (66 min), ≥70-180 mg/dL (time in range) was 64.5% (929 min), >180-250 mg/dL was 22.8% (328 min), and >250 mg/dL was 8.1% (117 min). The median transmitter wear time over the first cycle was 83.2%. CGM metrics and wear time were similar over the subsequent three cycles. This real-world evaluation of adult patients with diabetes using the Eversense CGM System in the home setting demonstrated that the implantable sensor provides consistent stable accuracy and CGM metrics over multiple, sequential sensor cycles with no indication of degradation of sensor performance.

Real-World Data from the First U.S. Commercial Users of an Implantable Continuous Glucose Sensor

Background: The Eversense^® Continuous Glucose Monitoring (CGM) System, with the first 90-day implantable sensor, received FDA (Food and Drug Administration) approval in June 2018. No real-world experience has been published. Methods: Deidentified sensor glucose (SG) data from August 1, 2018 to May 11, 2019 in the Eversense Data Management System (DMS) were analyzed for the first 205 patients who reached a 90-day wear period on the Eversense CGM system. The mean SG, standard deviation (SD), median interquartile range, coefficient of variation (CV), glucose measurement index (GMI), and percent and time in minutes across glucose ranges were computed for the 24-h time period, the nighttime (00:00-06:00), and by 30-day wear periods. Sensor accuracy, sensor reinsertion rate, transmitter wear time, and safety data were assessed. Results: Of the 205 patients, 129 identified as type 1, 18 as type 2, and 58 were unreported. Fifty were CGM naive, 112 had prior CGM experience, and 43 were unreported. The mean SG was 161.8 mg/dL, SD was 57.4 mg/dL, CV was 0.35, and GMI was 7.18%. Percent SG at <54 mg/dL was 1.2% (18 min), <70 mg/dL was 4.1% (59.7 min), time in range (≥70-180 mg/dL) was 62.3% (897.7 min), >180-250 mg/dL was 21.9% (315.8 min), and >250 mg/dL was 11.6% (166.7 min). Nighttime values were similar. The glucometric values were similar over 30-day time periods of the sensor wear. The mean absolute relative difference (SD) using 27,708 calibration paired points against home blood glucose meters was 11.2% (11.3%). The sensor reinsertion rate was 78.5%. The median transmitter wear time was 83.6%. There were no related serious adverse events. Conclusion: The Eversense real-world data showed promising glycemic results, sensor accuracy, and safety. These data suggest that the Eversense CGM system is a valuable tool for diabetes management.

Reducing Hypoglycemia in the Real World: A Retrospective Analysis of Predictive Low-Glucose Suspend Technology in an Ambulatory Insulin-Dependent Cohort

Objective: Analyze real-world usage and impact of a predictive low-glucose suspend (PLGS) insulin delivery system for maintenance of euglycemia and prevention of hypoglycemic events in people with insulin-dependent diabetes. Methods: Retrospective analysis of Tandem Basal-IQ users who uploaded at least 21 days of PLGS usage data between August 31, 2018, and March 14, 2019 (N = 8132). Insulin delivery and sensor-glucose concentrations were analyzed. The times spent below 70 mg/dL, between 70 and 180 mg/dL, and above 180 mg/dL were assessed. Subgroup analyses were conducted to examine matched pre-/postoutcomes with experienced users (n = 1371) and performance over time for a mixed subgroup with >9 weeks of data (n = 3563). Results: The mean age of patients was 32.4 years, 52% were female, 96% had type 1 diabetes, and 4% had type 2 diabetes. Mean duration on PLGS was 65 days. Algorithm introduction led to a 45% median relative risk reduction in sensor time <70 mg/dL, pre/post (% <70:2.0, 1.1), while the mean glucose remained stable (168 and 168 mg/dL). Mean frequency of hypoglycemic events decreased from one every 9 days to one every 30 days. Total daily insulin dose decreased from 43.4 to 42.3 U in the pre/post subgroup. Manual override of the system was low (4.5%). The number of daily suspensions remained stable (4.9). Conclusions: Introduction of PLGS resulted in effective and sustained prevention of hypoglycemia without a significant increase in mean blood glucose and may be considered for people with type 1 diabetes at risk for hypoglycemia.

Carbohydrate Restriction in Type 1 Diabetes: A Realistic Therapy for Improved Glycaemic Control and Athletic Performance?

Around 80% of individuals with Type 1 diabetes (T1D) in the United States do not achieve glycaemic targets and the prevalence of comorbidities suggests that novel therapeutic strategies, including lifestyle modification, are needed. Current nutrition guidelines suggest a flexible approach to carbohydrate intake matched with intensive insulin therapy. These guidelines are designed to facilitate greater freedom around nutritional choices but they may lead to higher caloric intakes and potentially unhealthy eating patterns that are contributing to the high prevalence of obesity and metabolic syndrome in people with T1D. Low carbohydrate diets (LCD; <130 g/day) may represent a means to improve glycaemic control and metabolic health in people with T1D. Regular recreational exercise or achieving a high level of athletic performance is important for many living with T1D. Research conducted on people without T1D suggests that training with reduced carbohydrate availability (often termed "train low") enhances metabolic adaptation compared to training with normal or high carbohydrate availability. However, these "train low" practices have not been tested in athletes with T1D. This review aims to investigate the known pros and cons of LCDs as a potentially effective, achievable, and safe therapy to improve glycaemic control and metabolic health in people with T1D. Secondly, we discuss the potential for low, restricted, or periodised carbohydrate diets in athletes with T1D.