A Simplified Approach Using Rate of Change Arrows to Adjust Insulin With Real-Time Continuous Glucose Monitoring

A Proposal for the Clinical Characterization of Continuous Glucose Monitoring Trend Arrow Accuracy

The assessment and characterization of trend accuracy, that is, the ability of a continuous glucose monitoring (CGM) system to correctly indicate the direction and rate of change (RoC) of glucose levels, has received comparatively little attention in the overall evaluation of CGM performance. As such, only few approaches that examine the trend accuracy have been put forward. In this article, we review existing approaches and propose the clinical trend concurrence analysis (CTCA) which is an adaptation of the conventional trend concurrence analysis. The CTCA is intended to directly evaluate the trend arrows displayed by the CGM systems by characterizing their agreement to suitably categorized comparator RoCs. Here, we call on manufactures of CGM systems to provide the displayed trend arrows for retrospective analysis. The CTCA classifies any deviations between the CGM trend and comparator RoC according to their risk for an adverse clinical event arising from a possibly erroneous treatment decision. For that, the existing rate error grid analysis and a specific set of trend arrow-based insulin dosing recommendations were used. The results of the CTCA are presented in an accessible graphical display and exemplified on data from three CGM systems. With this article, we hope to increase the awareness for the importance and challenges of assessing the accuracy of trend information displayed by CGM systems.

drCORRECT: An Algorithm for the Preventive Administration of Postprandial Corrective Insulin Boluses in Type 1 Diabetes Management

BACKGROUND

In type 1 diabetes therapy, precise tuning of postprandial corrective insulin boluses (CIBs) is crucial to mitigate hyperglycemia without inducing dangerous hypoglycemic events. Several heuristic formulas accounting for continuous glucose monitoring (CGM) trend have been proposed in the literature. However, these formulas suggest a lot of quantized CIB adjustments, and they lack personalization.

METHOD

drCORRECT algorithm proposed in this work employs a patient-specific time parameter and the "dynamic risk" (DR) measure to determine postprandial CIB suggestion. The expected benefits include the reduction of time in hyperglycemia, thanks to the preventive action exploited through DR. drCORRECT has been assessed retrospectively vs the literature methods proposed by Aleppo et al (AL), Bruttomesso et al (BR), and Ziegler et al (ZI) using a data set of 49 CGM daily traces recorded in free-living conditions. Retrospective evaluation of the algorithms is made possible by the use of ReplayBG, a digital twin-based tool that allows assessing alternative insulin therapies on already collected glucose data. Efficacy in terms of glucose control was measured by temporal, risk indicators, and dedicated hyperglycemic/hypoglycemic events metrics.

RESULTS

drCORRECT significantly reduces time spent in hyperglycemia when compared with AL and BR (33.52 [24.16, 39.89]% vs 39.76 [22.54, 48.15]% and 36.32 [26.91, 45.93]%, respectively); significantly reduces daily injected insulin (5.97 [3.80, 8.06] U vs 7.5 [5.21, 10.34] U), glycemia risk index (38.78 [26.58, 55.39] vs 40.78 [27.95, 70.30]), and time spent in hypoglycemia (0.00 [0.00, 1.74]% vs 0.00 [0.00, 10.23]%) when compared with ZI, resulting overall in a safer strategy.

CONCLUSIONS

The proposed drCORRECT algorithm allows preventive actions thanks to the personalized timing configuration and the introduction of the innovative DR-based CIB threshold, proving to be a valid alternative to the available heuristic literature methods.

A Head-to-Head Comparison of Two Algorithms for Adjusting Mealtime Insulin Doses Based on CGM Trend Arrows in Adult Patients with Type 1 Diabetes: Results from an Exploratory Study

BACKGROUND

Continuous glucose monitoring (CGM) users are encouraged to consider trend arrows before injecting a meal bolus. We evaluated the efficacy and safety of two different algorithms for trend-informed bolus adjustments, the Diabetes Research in Children Network/Juvenile Diabetes Research Foundation (DirectNet/JDRF) and the Ziegler algorithm, in type 1 diabetes.

METHODS

We conducted a cross-over study of type 1 diabetes patients using Dexcom G6. Participants were randomly assigned to either the DirectNet/JDRF or the Ziegler algorithm for two weeks. After a 7-day wash-out period with no trend-informed bolus adjustments, they crossed to the alternative algorithm.

RESULTS

Twenty patients, with an average age of 36 ± 10 years, completed this study. Compared to the baseline and the DirectNet/JDRF algorithm, the Ziegler algorithm was associated with a significantly higher time in range (TIR) and lower time above range and mean glucose. A separate analysis of patients on CSII and MDI revealed that the Ziegler algorithm provides better glucose control and variability than DirectNet/JDRF in CSII-treated patients. The two algorithms were equally effective in increasing TIR in MDI-treated patients. No severe hypoglycemic or hyperglycemic episode occurred during the study.

CONCLUSIONS

The Ziegler algorithm is safe and may provide better glucose control and variability than the DirectNet/JDRF over a two-week period, especially in patients treated with CSII.

Methods for Insulin Bolus Adjustment Based on the Continuous Glucose Monitoring Trend Arrows in Type 1 Diabetes: Performance and Safety Assessment in an In Silico Clinical Trial

BACKGROUND

Providing real-time magnitude and direction of glucose rate-of-change (ROC) via trend arrows represents one of the major strengths of continuous glucose monitoring (CGM) sensors in managing type 1 diabetes (T1D). Several literature methods were proposed to adjust the standard formula (SF) used for insulin bolus calculation by accounting for glucose ROC, but each of them provides different suggestions, making it difficult to understand which should be applied in practice. This work aims at performing an extensive in-silico assessment of their performance and safety.

METHODS

The methods of Buckingham (BU), Scheiner (SC), Pettus/Edelman (PE), Klonoff/Kerr (KL), Aleppo/Laffel (AL), Ziegler (ZI), and Bruttomesso (BR) were evaluated using the UVa/Padova T1D simulator, in single-meal scenarios, where ROC and glucose at mealtime varied between [-2,+2] mg/dL/min and [80,200] mg/dL, respectively. Efficacy of postprandial glucose control was quantitatively assessed by time in, above and below range (TIR, TAR, and TBR, respectively).

RESULTS

For negative ROCs, all methods proved to increase TIR and decrease TAR and TBR vs SF, with KL, PE, and BR being the most effective. For positive ROCs, a general worsening of the performances is present, only BR improved the glycemic control when mealtime glucose was close to hypoglycemia, while SC resulted the safest in the other conditions.

CONCLUSIONS

Insulin bolus adjustment methods are effective for negative ROCs, but they generally appear to overdose for positive ROCs, calling for safer strategies in such a scenario. These results can be useful in outlining guidelines to identify which adjustment to apply based on the mealtime condition.

Evaluation of the usefulness of and satisfaction with the flash glucose monitoring system (FreeStyle Libre®) guide for use in patients with type 1 diabetes⋆

The Flash Guide (FG) for insulin dosing (A. Chico, C. González) was the first document intended for FreeStyle Libre® (FSL) user patients to help with decision-making depending on glucose level and trend. The objective of the study was to evaluate the usefulness of and the level of satisfaction with the recommendations given by the FG in a group of patients with type 1 diabetes (DM1) who were FSL users. It included 31 subjects (54% women; age 41 ± 15 years; DM duration 21 ± 14 years; 22 with FSL > 12 months) who were provided with the FG. They completed a questionnaire on decision-making depending on glucose trend in different situations (before and three months after using the FG), and a satisfaction questionnaire (ad hoc). Demographic, clinical and glycaemic control data were collected. The percentage of subjects who used glucose trend in decision-making after receiving the FG increased: for adjusting insulin (51 vs. 83; p = 0.016), action without insulin (51 vs. 90%; p = 0.001), and in special circumstances. The FG was evaluated as very useful (4.19/5). There were no significant changes in glycaemic control, although the percentage of data gathered increased significantly (89.07 vs. 94.46%; p = 0.042). In conclusion, the FG was evaluated well for managing glucose trends with FSL by the patients with DM1 analysed, increasing their use of trend in decision-making, with no changes in glycaemic control, but with more data gathered.

Automated Bolus Calculators and Connected Insulin Pens: A Smart Combination for Multiple Daily Injection Insulin Therapy

Although automated bolus calculators (ABCs) have become a mainstay in insulin pump therapy, they have not achieved similar levels of adoption by persons with diabetes (PWD) using multiple daily injections of insulin (MDI). Only a small number of blood glucose meters (BGMs) have incorporated ABC functionality and the proliferation of unregulated ABC smartphone apps raised safety concerns and eventually led to Food and Drug Administration (FDA)-mandated regulatory oversight for these types of apps. With the recent introduction of smartphone-connected insulin pens, manufacturer-supported companion ABC apps may offer an ideal solution for PWD and health care professionals that reduces errors of mental math when calculating bolus insulin dosing, increases the quality of diabetes data reporting, and improves glycemic outcomes.

Clinical Evaluation of a Novel CGM-Informed Bolus Calculator with Automatic Glucose Trend Adjustment

Background: Expert opinion guidelines and limited data from clinical trials recommend adjustment to bolus insulin doses based on continuous glucose monitor (CGM) trend data, yet minimal evidence exists to support this approach. We performed a clinical evaluation of a novel CGM-informed bolus calculator (CIBC) with automatic insulin bolus dose adjustment based on CGM trend used with sensor-augmented pump therapy. Materials and Methods: In this multicenter, outpatient study, participants 6-70 years of age with type 1 diabetes (T1D) used the Omnipod^® 5 System in Manual Mode, first for 7 days without a connected CGM (standard bolus calculator, SBC, phase 1) and then for 7 days with a connected CGM using the CIBC (CIBC phase 2). The integrated bolus calculator used stored pump settings plus user-estimated meal size and/or either a manually entered capillary glucose value (SBC phase) or an imported current CGM value and trend (CIBC phase) to recommend a bolus amount. The CIBC automatically increased or decreased the suggested bolus amount based on the CGM trend. Results: Twenty-five participants, (mean ± standard deviation) 27 ± 15 years of age, with T1D duration 12 ± 9 years and A1C 7.0% ± 0.9% completed the study. There were significantly fewer sensor readings <70 mg/dL 4 h postbolus with the CIBC compared to the SBC (2.1% ± 2.0% vs. 2.8 ± 2.7, P = 0.03), while percent of sensor readings >180 and 70-180 mg/dL remained the same. There was no difference in insulin use or number of boluses given between the two phases. Conclusion: The CIBC was safe when used with the Omnipod 5 System in Manual Mode, with fewer hypoglycemic readings in the postbolus period compared to the SBC. This trial was registered at ClinicalTrials.gov (NCT04320069).

Products for Monitoring Glucose Levels in the Human Body With Noninvasive Optical, Noninvasive Fluid Sampling, or Minimally Invasive Technologies

BACKGROUND

Conventional home blood glucose measurements require a sample of blood that is obtained by puncturing the skin at the fingertip. To avoid the pain associated with this procedure, there is high demand for medical products that allow glucose monitoring without blood sampling. In this review article, all such products are presented.

METHODS

In order to identify such products, four different sources were used: (1) PubMed, (2) Google Patents, (3) Diabetes Technology Meeting Startup Showcase participants, and (4) experts in the field of glucose monitoring. The information obtained were filtered by using two inclusion criteria: (1) regulatory clearance, and/or (2) significant coverage in Google News starting in the year 2016, unless the article indicated that the product had been discontinued. The identified bloodless monitoring products were classified into three categories: (1) noninvasive optical, (2) noninvasive fluid sampling, and (3) minimally invasive devices.

RESULTS

In total, 28 noninvasive optical, 6 noninvasive fluid sampling, and 31 minimally invasive glucose monitoring products were identified. Subsequently, these products were characterized according to their regulatory, technological, and consumer features. Products with regulatory clearance are described in greater detail according to their advantages and disadvantages, and with design images.

CONCLUSIONS

Based on favorable technological features, consumer features, and other advantages, several bloodless products are commercially available and promise to enhance diabetes management. Paths for future products are discussed with an emphasis on understanding existing barriers related to both technical and non-technical issues.

Practical Approach to Using Trend Arrows on Real-Time Continuous Glucose Monitoring System in Type 1 Diabetes Adolescents Living Camp Setting Treated With Multiple Daily Injection or Continuous Subcutaneous Insulin Infusion Insulin Therapy

BACKGROUND

The aim of the study was to determine the effect of an educational intervention on the use of trend arrows of a real-time continuous glucose monitoring (rt-CGM) to manage daily therapy decisions in a group of adolescents with type 1 diabetes attending a camp. The secondary aim was to evaluate the variations in total daily dose (TDD) of insulin requirement.

METHODS

Twenty patients (15-17 years) on multiple insulin injections (n = 8) or continuous subcutaneous insulin infusion (n = 12) attended a training session at the beginning of the camp to learn our algorithm for the management of therapy depending on trend arrows. TDD, time in range (TIR), time above range (TAR), and time below range (TBR) (in the 24 hours and in the three hours after breakfast) before the training session (run-in) and at the end of the camp (T1) were analyzed.

RESULTS

Data showed a reduction of TAR (run-in 42.6%, T1 32.05%, P = .036) and an increase in TIR (run-in 52.9%, T1 62.4%, P = .013). Reduction of TBR (run-in 42.5%, T1 37.5%, P = .05) and improvement in TIR (run-in 49.0%, T1 57.0%, P = .02) were also observed in the post-breakfast period. Data showed a significant reduction in the TDD (run-in 52.02 ± 17.44 U/die, T1 46.49 ± 12.39 U/die, P = .024).

CONCLUSIONS

Statistically significant improvement of glycemic control and reduction of TTD were observed in all patients regardless of therapy type. The improvement between run-in and T1 demonstrates the importance of patients' education on the correct use of rt-CGM with simple algorithms for the management of therapy.

Evaluation of the usefulness of and satisfaction with the flash glucose monitoring system (FreeStyle Libre®) guide for use in patients with type 1 diabetes

The Flash Guide (FG) for insulin dosing (A. Chico, C. González) was the first document intended for FreeStyle Libre® (FSL) user patients to help with decision-making depending on glucose level and trend. The objective of the study was to evaluate the usefulness of and the level of satisfaction with the recommendations given by the FG in a group of patients with type 1 diabetes (DM1) who were FSL users. It included 31 subjects (54% women; age 41±15 years; DM duration 21±14 years; 22 with FSL>12 months) who were provided with the FG. They completed a questionnaire on decision-making depending on glucose trend in different situations (before and three months after using the FG), and a satisfaction questionnaire (ad hoc). Demographic, clinical and glycaemic control data were collected. The percentage of subjects who used glucose trend in decision-making after receiving the FG increased: for adjusting insulin (51 vs. 83; P=.016), action without insulin (51 vs. 90%; P=.001), and in special circumstances. The FG was evaluated as very useful (4.19/5). There were no significant changes in glycaemic control, although the percentage of data gathered increased significantly (89.07 vs. 94.46%; P=.042). In conclusion, the FG was evaluated well for managing glucose trends with FSL by the patients with DM1 analysed, increasing their use of trend in decision-making, with no changes in glycaemic control, but with more data gathered.

Current treatment options and challenges in patients with Type 1 diabetes: Pharmacological, technical advances and future perspectives

Type 1 diabetes mellitus imposes a significant burden of complications and mortality, despite important advances in treatment: subjects affected by this disease have also a worse quality of life-related to disease management. To overcome these challenges, different new approaches have been proposed, such as new insulin formulations or innovative devices. The introduction of insulin pumps allows a more physiological insulin administration with a reduction of HbA1c level and hypoglycemic risk. New continuous glucose monitoring systems with better accuracy have allowed, not only better glucose control, but also the improvement of the quality of life. Integration of these devices with control algorithms brought to the creation of the first artificial pancreas, able to independently gain metabolic control without the risk of hypo- and hyperglycemic crisis. This approach has revolutionized the management of diabetes both in terms of quality of life and glucose control. However, complete independence from exogenous insulin will be obtained only by biological approaches that foresee the replacement of functional beta cells obtained from stem cells: this will be a major challenge but the biggest hope for the subjects with type 1 diabetes. In this review, we will outline the current scenario of innovative diabetes management both from a technological and biological point of view, and we will also forecast some cutting-edge approaches to reduce the challenges that hamper the definitive cure of diabetes.

A "Slide Rule" to Adjust Insulin Dose Using Trend Arrows in Adults with Type 1 Diabetes: Test in Silico and in Real Life

INTRODUCTION

In persons with type 1 diabetes (T1D) insulin dosing can be adjusted based on trend arrows derived from continuous glucose monitoring (CGM). We propose a slide rule with narrower blood glucose intervals and more classes of insulin sensitivity than are available in current models.

METHODS

The slide rule was tested in silico, in which a meal was simulated in 100 virtual subjects and the insulin bolus was calculated either in the standard way based on the insulin-to-carbohydrate ratio and the correction factor or according to the slide rule, following which the percentage time spent in range (70-180 mg/dl; %T_IR), hypoglycemia (< 70 mg/dl; %T_HYPO), and hyperglycemia (> 180 mg/dl; %T_HYPER) was compared between the methods during the 4 h after the meal. Slide rule performance was also tested in real life by analyzing the same variables at during the 4 h postprandial period in 27 individuals with T1D. Only meals starting while the rate of change was at least 1 mg/dl per minute (increasing or decreasing) were considered for analysis.

RESULTS

In silico, when the preprandial trend arrow was increasing, our slide rule reduced %T_HYPER and increased %T_IR (p < 0.05), whereas when the preprandial trend arrow was decreasing, it reduced %T_HYPO and slightly increased %T_HYPER (p < 0.05). In real life, our slide rule kept subjects on target for 70.8 and 91.6% of postprandial time when preprandial trend arrows were increasing or decreasing, respectively.

CONCLUSION

The proposed slide rule performed well both in silico and in real life, suggesting that it could be safely adopted by individuals with T1D to improve glucose control.

The effect of preceding glucose decline rate on low-dose glucagon efficacy in individuals with type 1 diabetes: A randomized crossover trial

Identifying determinants of low-dose glucagon efficacy is important to optimise its utilization for prevention and treatment of hypoglycaemia in individuals with type 1 diabetes. The study objective was to investigate whether the preceding glucose decline rate affects glucose response to low-dose glucagon administration. Ten adults with insulin pump-treated type 1 diabetes were included in this randomized, single-blind, two-way crossover study. Using a hyperinsulinaemic clamp technique, plasma glucose levels were reduced with either a rapid or slow decline rate while maintaining fixed insulin levels. When the plasma glucose level reached 3.9 mmoL/L, insulin and glucose infusions were discontinued and 150 μg subcutaneous glucagon was administered, followed by 120 minutes of plasma glucose monitoring. The positive incremental area under the glucose curve after administration of low-dose glucagon did not differ between the rapid-decline and slow-decline visits (mean ± SEM: 220 ± 49 vs. 174 ± 31 mmoL/L x min; P = 0.21). Similarly, no differences in total area under the glucose curve, peak plasma glucose, incremental peak plasma glucose, time-to-peak plasma glucose or end plasma glucose were observed. Thus, preceding glucose decline rate did not significantly affect the glucose response to low-dose glucagon.

Continuous Glucose Monitors and Automated Insulin Dosing Systems in the Hospital Consensus Guideline

This article is the work product of the Continuous Glucose Monitor and Automated Insulin Dosing Systems in the Hospital Consensus Guideline Panel, which was organized by Diabetes Technology Society and met virtually on April 23, 2020. The guideline panel consisted of 24 international experts in the use of continuous glucose monitors (CGMs) and automated insulin dosing (AID) systems representing adult endocrinology, pediatric endocrinology, obstetrics and gynecology, advanced practice nursing, diabetes care and education, clinical chemistry, bioengineering, and product liability law. The panelists reviewed the medical literature pertaining to five topics: (1) continuation of home CGMs after hospitalization, (2) initiation of CGMs in the hospital, (3) continuation of AID systems in the hospital, (4) logistics and hands-on care of hospitalized patients using CGMs and AID systems, and (5) data management of CGMs and AID systems in the hospital. The panelists then developed three types of recommendations for each topic, including clinical practice (to use the technology optimally), research (to improve the safety and effectiveness of the technology), and hospital policies (to build an environment for facilitating use of these devices) for each of the five topics. The panelists voted on 78 proposed recommendations. Based on the panel vote, 77 recommendations were classified as either strong or mild. One recommendation failed to reach consensus. Additional research is needed on CGMs and AID systems in the hospital setting regarding device accuracy, practices for deployment, data management, and achievable outcomes. This guideline is intended to support these technologies for the management of hospitalized patients with diabetes.

Diabetes Healthcare Professionals Use Multiple Continuous Glucose Monitoring Data Indicators to Assess Glucose Management

BACKGROUND

Continuous glucose monitoring (CGM) offers multiple data features that can be leveraged to assess glucose management. However, how diabetes healthcare professionals (HCPs) actually assess CGM data and the extent to which they agree in assessing glycemic management are not well understood.

METHODS

We asked HCPs to assess ten de-identified CGM datasets (each spanning seven days) and rank order each day by relative glycemic management (from "best" to "worst"). We also asked HCPs to endorse features of CGM data that were important in making such assessments.

RESULTS

In the study, 57 HCPs (29 endocrinologists; 28 diabetes educators) participated. Hypoglycemia and glycemic variance were endorsed by nearly all HCPs to be important (91% and 88%, respectively). Time in range and daily lows and highs were endorsed more frequently by educators (all Ps < .05). On average, HCPs endorsed 3.7 of eight data features. Overall, HCPs demonstrated agreement in ranking days by relative glycemic control (Kendall's W = .52, P < .001). Rankings were similar between endocrinologists and educators (R² = .90, Cohen's kappa = .95, mean absolute error = .4 [all Ps < .05]; Mann-Whitney U = 41, P = .53).

CONCLUSIONS

Consensus in the endorsement of certain data features and agreement in assessing glycemic management were observed. While some practice-specific differences in feature endorsement were found, no differences between educators and endocrinologists were observed in assessing glycemic management. Overall, HCPs tended to consider CGM data holistically, in alignment with published recommendations, and made converging assessments regardless of practice.

Diabetes Technology Use in Adults with Type 1 and Type 2 Diabetes

In the last 2 decades, diabetes technology has emerged as a branch of diabetes management thanks to the advent of continuous glucose monitoring (CGM) and increased availability of continuous subcutaneous insulin infusion systems, or insulin pumps. These tools have progressed from rudimentary instruments to sophisticated therapeutic options for advanced diabetes management. This article discusses the available CGM and insulin pump systems and the clinical benefits of their use in adults with type 1 diabetes, intensively insulin-treated type 2 diabetes, and pregnant patients with preexisting diabetes.

Benefits and limitations of continuous glucose monitoring in type 1 diabetes

Introduction: Type 1 diabetes (T1D) is a chronic condition characterized by a complete deficiency in insulin production. Optimal management requires constant knowledge of glucose levels for safe and effective insulin administration. Self-monitoring of blood glucose (SMBG) using capillary blood glucose meters is cumbersome and provides limited information to guide management. Continuous glucose monitoring (CGM) technology addresses many of these gaps, but itself has limitations which have prevented people with diabetes and their clinicians from fully embracing this technology. This review covers the benefits and limitations of CGM use, and looks toward future application of this technology in the management of T1D.Areas covered: Impact of CGM on physical and psychosocial outcomes in people with T1D. Barriers to CGM uptake. Integration with insulin pumps and other technologies. Opportunities for future application.Expert opinion: CGM technology will be utilized by the majority of people with T1D and increasing numbers of people with type 2 diabetes due to improved insurance coverage and easier-to-use systems. Its use as part of artificial pancreas systems will add further utility, as it will help to protect from both hypoglycemia and hyperglycemia. People with diabetes will spend more time in range and experience fewer acute and chronic complications.

Clinical Approach to Flash Glucose Monitoring: An Expert Recommendation

The flash glucose monitoring (FGM) system FreeStyle Libre® is a device that measures interstitial glucose in a very simple way and indicates direction and speed of glucose change. This allows persons with diabetes to prevent hypoglycemic and hyperglycemic events. Scientific evidence indicates that the system can improve glycemic control and quality of life. To obtain the maximum benefit, it is necessary to properly handle glucose values and trends. Due to the generalization of the system use, the purpose of the document is to provide recommendations for the optimal use of the device, not only in the management of glucose values and trends but also in the prevention of hypoglycemia, actuation in exercise, special situations, and retrospective analysis of the glucose data, among others.

Predictive Glucose Trends From Continuous Glucose Monitoring: Friend or Foe in Clinical Decision Making?

In this commentary, we briefly review the currently recommended approaches to interpretation and management of continuous glucose monitor (CGM) rate of change (ROC) trend arrows and discuss the inherent difficulty in incorporating practical recommendations for their application into routine clinical care. We have limited our review and discussion to the currently available Dexcom G5 and G6 CGM systems and Abbott's Freestyle Libre flash glucose monitor (FGM) system, as they are the most widely used and currently approved for nonadjunctive use in the United States.

Continuous Glucose Monitoring Integration in Clinical Practice: A Stepped Guide to Data Review and Interpretation

BACKGROUND

The advent of continuous glucose monitoring (CGM) technology has transformed the approach to diabetes care. Multiple CGM systems are commercially available and increased accuracy has allowed development of hybrid and automated insulin delivery systems. Evidence of CGM clinical benefits has also increased exponentially in the last decade.

METHODS

Literature search, review of professional guidelines, and consensus statements were used to guide the preparation of this article. The clinical benefits of both professional and personal CGM in clinical practice as well as barriers to wider adotpion were explored. A stepped approach to review and interpretation of CGM data is suggested for use in the clinician's office regardless of the software used.

RESULTS

Although increasing, the use of CGM in patients with diabetes is still not widespread; multiple barriers are still in place, despite the approval of CGM systems for patients above the age of 2 years old, the extension of coverage for Medicare beneficiaries and the integration of CGM with multiple insulin pump systems. Integration of CGM technology in clinical practice presents various challenges, from concerns relative to time constraints during office visits to lack of systematic approach to interpretation of the data.

CONCLUSIONS

Understanding the usefulness of personal and professional CGM, appropriate patient selection as well as patient and provider training are crucial for the expansion of CGM therapy use in clinical practice. Utilizing the proposed stepped approach to CGM review and interpretation may allow wider adoption of CGM with more effective and efficient office visits.

Therapy Adjustments Based on Trend Arrows Using Continuous Glucose Monitoring Systems

Continuous glucose monitoring (CGM) systems use trend arrows to accurately display the anticipated glucose curve for the user. These are used for both "real-time" glucose monitoring and for intermittent scanning glucose monitoring. Trend arrow data are used by people with diabetes to make corrections to their glucose control. It is essential that they are correctly interpreted when adjusting insulin doses and to ensure that appropriate treatment decisions are made. The aim of this article is to provide general treatment guidance for diabetes teams and for people with diabetes using CGM in the context of trend arrows. This is based on previous recommendations for interpreting trend arrows without losing sight of the need for individual therapy adjustment.

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

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

Analysis of "Performance of a Factory-Calibrated, Real-Time Continuous Glucose Monitoring System in Pediatric Participants With Type 1 Diabetes"

Accuracy of sensors play an important role in the acceptance and long-term use of CGM which is related to improved glycemic outcome. This has been lower in children and adolescents in the past for reasons such as size of the device, pain, and necessity to calibrate sensors but also inaccuracy and perceived nonreliability on alarms among others. In the study of Welsh et al, performance of a new, factory-calibrated sensor was assessed. The accuracy of the sensor, as measured in MARD, paired values within 20/20% or 15/15% and surveillance error grid analysis showed very good results, although less so in low value range <70 mg/dL, falling rate of change, and on first day of use. Accurate glucose measurements especially in these incidences are of utmost importance to people with diabetes as their treatment decisions are based on these, also in the beginning of sensor use.

Optimising use of rate-of-change trend arrows for insulin dosing decisions using the FreeStyle Libre flash glucose monitoring system

Continuous glucose monitoring and flash glucose monitoring systems are increasingly used by people with diabetes on multiple daily injections of insulin and continuous subcutaneous insulin infusion. Along with real-time updates on current glucose levels, these technologies also use trend arrows to provide information on the direction and rate of change of glucose. Two systems, the Dexcom G5 and the FreeStyle Libre, have recently been approved for use without the need for adjunct capillary blood glucose, and there is a need for practical guidance for insulin dosing which incorporates rate of change in the insulin dosing algorithm. Here, we review the integration of rate of change trend arrow information into daily glucose management, including rapid-acting insulin dosing decisions. Based on the FreeStyle Libre flash glucose monitoring system, we also review a practical decision-support tool for actions to take when using trend arrows in conjunction with current glucose readings.

Freestyle Libre trend arrows for the management of adults with insulin-treated diabetes: A practical approach

Freestyle Libre (FSL) system is a new method to detect glucose enabling a new paradigm in glucose monitoring and self-management. The sensor, reading the interstitial fluid glucose concentration, provides a numerical data of glucose level and a trend arrow that add context to static measurement of glucose level. Therefore, patients could easily follow the progression of their glucose levels over the time, allowing early detection and timely treatment of deviations from targeted glucose level range, thus preventing extreme fluctuations. In order to take full advantage of the system both the caregiver and the person with diabetes must appreciate the need of careful interpretation of the data generated by the FSL. To this purpose we have generated recommendations that are based on methods suggested for CGM, our clinical experience and discussion with experienced patients using FSL, to provide a pragmatic approach to use FSL trend arrow data for managing diabetes in adults.

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

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

Prediction Quality of Glucose Trend Indicators in Two Continuous Tissue Glucose Monitoring Systems

BACKGROUND

Continuous interstitial glucose monitoring (CGM) systems often provide glucose trend indicators (e.g., arrows) in addition to current glucose values. These indicators are recommended to be used in therapeutic decisions, because they are ascribed predictive qualities by CGM system manufacturers and expert committees. This study assessed how reliably trend indicators match future glucose change, because such information is missing.

METHODS

In a clinical trial, two different CGM systems were used by 20 participants, with two sensors of each system per patient. Participants used the systems for 14 days with three study site visits (48 h each). During study site visits, glucose trend indicators, as displayed by the CGM systems, were recorded at least once per hour during daytime and once at night in a diary. In addition, CGM data were downloaded from the devices. Trend indicators were compared with glucose change calculated from CGM data >30 min after recording the trend indicator.

RESULTS

Approximately 60% of trend indicators matched the glucose change calculated from CGM data. More than 10% of trend indicators differed by at least two trend indicator categories. Focusing on trend indicators recorded around carbohydrate (CHO) intake and insulin deliveries resulted in approximately half of trend indicators matching the calculated glucose change.

CONCLUSIONS

Trend indicators do not always match future glucose change, especially within the first few hours after CHO intake and insulin deliveries. Manufacturers' labeling and recommendations should reflect this, so that CGM users can make informed decisions.

A Practical Approach to Using Trend Arrows on the Dexcom G5 CGM System to Manage Children and Adolescents With Diabetes

After assessing previously published methods, we developed a practical approach to adjusting insulin doses using rtCGM trend arrows in pediatric patients with diabetes.