HOW PATIENTS WITH TYPE 1 DIABETES TRANSLATE CONTINUOUS GLUCOSE MONITORING DATA INTO DIABETES MANAGEMENT DECISIONS

Development of a three-dimensional scoring model for the assessment of continuous glucose monitoring data in type 1 diabetes

INTRODUCTION

Despite the improvements in diabetes management by continuous glucose monitoring (CGM) it is difficult to capture the complexity of CGM data in one metric. We aimed to develop a clinically relevant multidimensional scoring model with the capacity to identify the most alarming CGM episodes and/or patients from a large cohort.

RESEARCH DESIGN AND METHODS

Retrospective CGM data from 2017 to 2020 available in electronic medical records were collected from n=613 individuals with type 1 diabetes (total 82 114 days). A scoring model was developed based on three metrics; glycemic variability percentage, low blood glucose index and high blood glucose index. Values for each dimension were normalized to a numeric score between 0-100. To identify the most representative score for an extended time period, multiple ways to combine the mean score of each dimension were evaluated. Correlations of the scoring model with CGM metrics were computed. The scoring model was compared with interpretations of a clinical expert board (CEB).

RESULTS

The dimension of hypoglycemia must be weighted to be representative, whereas the other two can be represented by their overall mean. The scoring model correlated well with established CGM metrics. Applying a score of ≥80 as the cut-off for identifying time periods with a 'true' target fulfillment (ie, reaching all targets for CGM metrics) resulted in an accuracy of 93.4% and a specificity of 97.1%. The accuracy of the scoring model when compared with the CEB was high for identifying the most alarming CGM curves within each dimension of glucose control (overall 86.5%).

CONCLUSIONS

Our scoring model captures the complexity of CGM data and can identify both the most alarming dimension of glycemia and the individuals in most urgent need of assistance. This could become a valuable tool for population management at diabetes clinics to enable healthcare providers to stratify care to the patients in greatest need of clinical attention.

Covid 19 and diabetes in children: advances and strategies

BACKGROUND

Throughout the COVID-19 pandemic, there has been a notable increase in the incidence of new-onset diabetes and diabetic ketoacidosis (DKA). Simultaneously, children diagnosed with type 1 diabetes (T1D) have encountered difficulties in maintaining optimal blood glucose levels. The mechanisms underpinning these correlations still remain a puzzle. We reviewed the studies that examined changes in incidence during the pandemic. These studies utilized various metrics for comparison, which encompassed the timing of data collection, diagnostic criteria, as well as the numbers and incidence rates of diabetes and DKA. We found the incidence of diabetes and DKA was higher during the pandemic. As to mechanisms, the invivo and invitro study revealed the factors such as direct viral damage, metabolic dysfunction, and immune responses all attribute to the process of T1D after suffering from COVID-19. Furthermore, we provide some useful strategies to prevent and treat children suffering from diabetes and COVID-19.

CONCLUSIONS

Strong correlations have been observed between new-onset diabetes and COVID-19. Insights gleaned from clinical descriptions and basic research can offer valuable experience and recommendations for the treatment and prevention of diabetes during future pandemics.

Perceptions of Continuous Glucose Monitoring Systems in the T1D Exchange Diabetes Registry: Satisfaction, Concerns, and Areas for Future Improvement

Manufacturers continue to improve performance and usability of continuous glucose monitoring (CGM) systems. As CGM becomes a standard of care, especially for people on insulin therapy, it is important to routinely gauge how satisfied people with diabetes are with this technology. This article describes survey feedback from a large cohort of people with diabetes using older and current CGM systems and highlights areas of current satisfaction, concern, and future system improvement.

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.

Diabetes Device Downloading: Benefits and Barriers Among Youth With Type 1 Diabetes

BACKGROUND

The majority of youth with type 1 diabetes (T1D) fail to meet glycemic targets despite increasing continuous glucose monitoring (CGM) use. We therefore aimed to determine the proportion of caregivers who review recent glycemic trends ("retrospective review") and make ensuant insulin adjustments based on this data ("retroactive insulin adjustments"). We additionally considered that fear of hypoglycemia and frequency of severe hypoglycemia would be associated with performing retrospective review.

METHODS

We conducted a cross-sectional survey of caregivers of youth with T1D, collecting demographics, diabetes technology usage, patterns of glucose data review/insulin dose self-adjustment, and Hypoglycemia Fear Survey (HFS).

RESULTS

Nineteen percent of eligible caregivers (191/1003) responded. Performing retrospective review was associated with younger child age (12.2 versus 15.4, P = .0001) and CGM use (92% versus 73%, P = .004), but was not associated with a significant improvement in child's HbA1c (7.89 versus 8.04, P = .65). Retrospective reviewers had significantly higher HFS-behavior scores (31.9 versus 27.7, P = .0002), which remained significantly higher when adjusted for child's age and CGM use (P = .005). Linear regression identified a significant negative association between HbA1c (%) and number of retroactive insulin adjustments (0.24 percent lower mean HbA1c per additional adjustment made, P = .02).

CONCLUSIONS

Retrospective glucose data review is associated with improved HbA1c when coupled with data-driven retroactive insulin adjustments. Barriers to data downloading existed even in this cohort of predominantly CGM-using T1D families.

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.

Optimal Prandial Timing of Insulin Bolus in Youths with Type 1 Diabetes: A Systematic Review

The aim of this systematic review was to report the evidence on optimal prandial timing of insulin bolus in youths with type 1 diabetes. A systematic search was performed including studies published in the last 20 years (2002-2022). A PICOS framework was used in the selection process and evidence was assessed using the GRADE system. Up to one third of children and adolescents with type 1 diabetes injected rapid-acting insulin analogues after a meal. Moderate-high level quality studies showed that a pre-meal bolus compared with a bolus given at the start or after the meal was associated with a lower peak blood glucose after one to two hours, particularly after breakfast, as well as with reduced HbA1c, without any difference in the frequency of hypoglycemia. There were no differences related to the timing of bolus in total daily insulin and BMI, although these results were based on a single study. Data on individuals' treatment satisfaction were limited but did not show any effect of timing of bolus on quality of life. In addition, post-prandial administration of fast-acting analogues was superior to rapid-acting analogues on post-prandial glycemia. There was no evidence for any difference in outcomes related to the timing of insulin bolus across age groups in the two studies. In conclusion, prandial insulin injected before a meal, particularly at breakfast, provides better post-prandial glycemia and HbA1c without increasing the risk of hypoglycemia, and without affecting total daily insulin dose and BMI. For young children who often have variable eating behaviors, fast-acting analogues administered at mealtime or post-meal could provide an additional advantage.

The Role of Retrospective Data Review in the Personal Use of Real-Time Continuous Glucose Monitoring: Perceived Impact on Quality of Life and Health Outcomes

Background: To explore whether regularly reviewing one's own retrospective continuous glucose monitoring (CGM) data might be linked with perceived quality of life (QoL) and glycemic benefits. Methods: Adults with type 1 diabetes (N = 300) or insulin-using type 2 diabetes (N = 198) using the Dexcom G5 Mobile or G6 Real-Time CGM (RT-CGM) system and receiving the weekly CLARITY summary report of their glucose data completed a survey exploring their use of the report and its perceived value and impact on QoL and glycemic outcomes. Regression analyses examined whether personal use of the report was associated with QoL, perceived glycemic outcomes, and RT-CGM metrics. Results: The majority reported that receiving and viewing the report contributed to improved hypoglycemic confidence (75.9%) and overall well-being (50.0%), reduced diabetes distress (59.3%-74.1%), and helped to improve A1C (73.1%) and reduce problems with hypoglycemia (61.8%) and chronic hyperglycemia (73.1%). Regularly reviewing the report with family or friends (positive predictor) and doing nothing with the report's information (negative predictor) were independently associated with QoL and perceived glycemic outcomes. Surprisingly, both predictors were also associated with poorer glycemic control (e.g., greater % time above range >180). Conclusions: These findings suggest that receiving a weekly RT-CGM summary report may contribute to QoL and health benefits, especially if the individual chooses to actively review and make use of the report's findings and openly reviews the findings with family or friends. Prospective studies are needed to more precisely determine how retrospective RT-CGM data summaries can best be presented and utilized effectively by adults with diabetes to enhance health outcomes.

Capturing the real-world benefit of residual β-cell function during clinically important time-periods in established Type 1 diabetes

AIMS

Many individuals with type 1 diabetes retain residual β-cell function, with increased endogenous insulin secretion associated with reduced hyperglycaemia, hypoglycaemia and glycaemic variability. However, it is unknown when these improvements occur during the day. Dysglycaemia is common in overnight and postprandial periods and associated with diabetes complications. Therefore, this study aimed to determine the influence of residual β-cell function upon nocturnal and postprandial glycaemic control in established type 1 diabetes.

METHODS

Under free-living conditions, 66 participants wore a blinded continuous glucose monitor (CGM), kept a food diary, and completed a stimulated urine C-peptide creatinine (UCPCR) test. Nocturnal, and postprandial CGM outcomes (participant means and discrete event analysis) were compared between UCPCR groups: undetectable (Cpep_und ), low (Cpep_low : 0.001-0.19 nmol/mmol) and high (Cpep_high : ≥0.2 nmol/mmol).

RESULTS

Greater β-cell function was associated with incremental improvements in glycaemia. Cpep_high spent significantly greater time in normoglycaemia than Cpep_und overnight (76 ± 20% vs. 58 ± 20%, p = 0.005) and 0-300 mins postprandially (68 ± 22% vs. 51 ± 22%, p = 0.045), while also having reducing nocturnal variability (SD 1.12 ± 0.41 vs. 1.52 ± 0.43 mmol/L, p = 0.010). Analysis of individual events, controlling for diabetes duration, BMI, basal insulin, use of a continuous or flash glucose monitor and (for postprandial) meal type, carbohydrate and bolus insulin intake, replicated the group findings, additionally demonstrating Cpep_und had increased hyperglycaemia versus Cpep_low overnight and increased postprandial hypoglycaemic events compared with Cpep_high . For all participants, breakfast had a significantly higher incremental area under the curve than lunch and dinner.

CONCLUSIONS

Residual β-cell function is associated with improved nocturnal and postprandial glycaemic control. These data may be of clinical importance for identifying specific periods and individuals where further glycaemic management strategies would be beneficial.

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.

Magnitude of Glycemic Improvement in Patients with Type 2 Diabetes Treated with Basal Insulin: Subgroup Analyses from the MOBILE Study

Objective: To determine if type 2 diabetes patients using basal insulin without prandial insulin with worse glycemic control at baseline would have the greatest benefit from using real-time continuous glucose monitoring (CGM). Methods: We conducted a post hoc analysis of the MOBILE Study, a multicenter trial examining the impact of CGM versus self-monitoring with a blood glucose meter (BGM) in patients with type 2 diabetes treated with basal insulin without prandial insulin. Participants were divided into subgroups based on baseline hemoglobin A1c (HbA1c) and baseline time-in-range 70-180 mg/dL (TIR). Change in TIR from baseline was calculated within each subgroup. Results: In subgroups based on baseline HbA1c, compared with the BGM group, the CGM group had 14% greater increase in TIR for participants with baseline HbA1c ≥8.5%, 14% greater increase for baseline HbA1c ≥9.0%, 22% greater increase for baseline HbA1c ≥9.5%, and 32% greater increase for baseline HbA1c ≥10.0% (P-value for interaction = 0.27). The time spent with glucose >250 mg/dL was significantly lower with CGM compared with BGM among participants with higher HbA1c values (P for interaction = 0.004). Results in subgroups based on baseline TIR paralleled the results in subgroups based on baseline HbA1c. Conclusion: While the benefit of CGM on TIR among patients with type 2 diabetes treated with basal insulin is apparent across the range of baseline glycemic control, the greatest impact of CGM is in those with the worst baseline glycemic control, particularly among those with HbA1c ≥10%. Clinical Trial Registration number: NCT03566693.

COVID-19-Induced New-Onset Diabetes: Trends and Technologies

The coronavirus disease 2019 (COVID-19) global pandemic continues to spread worldwide with approximately 216 million confirmed cases and 4.49 million deaths to date. Intensive efforts are ongoing to combat this disease by suppressing viral transmission, understanding its pathogenesis, developing vaccination strategies, and identifying effective therapeutic targets. Individuals with preexisting diabetes also show higher incidence of COVID-19 illness and poorer prognosis upon infection. Likewise, an increased frequency of diabetes onset and diabetes complications has been reported in patients following COVID-19 diagnosis. COVID-19 may elevate the risk of hyperglycemia and other complications in patients with and without prior diabetes history. It is unclear whether the virus induces type 1 or type 2 diabetes or instead causes a novel atypical form of diabetes. Moreover, it remains unknown if recovering COVID-19 patients exhibit a higher risk of developing new-onset diabetes or its complications going forward. The aim of this review is to summarize what is currently known about the epidemiology and mechanisms of this bidirectional relationship between COVID-19 and diabetes. We highlight major challenges that hinder the study of COVID-19-induced new-onset of diabetes and propose a potential framework for overcoming these obstacles. We also review state-of-the-art wearables and microsampling technologies that can further study diabetes management and progression in new-onset diabetes cases. We conclude by outlining current research initiatives investigating the bidirectional relationship between COVID-19 and diabetes, some with emphasis on wearable technology.

Continuous Glucose Monitoring (CGM) Is a Tool, Not a Reward: Unjustified Insurance Coverage Criteria Limit Access to CGM

Recent studies have demonstrated the clinical utility of continuous glucose monitoring (CGM) use in type 2 diabetes (T2D) patients who are treated with intensive insulin management. Large retrospective database analyses of T2D patients treated with less-intensive therapies have also shown that CGM use was associated with significant reductions in hemoglobin A1c levels and health resource utilization, including diabetes-related hospitalizations and emergency room care. Despite the growing body of evidence supporting CGM use in the broader T2D population, current eligibility criteria required by public and many private insurers are denying millions of individuals with T2D access to this valuable technology. In this article, we discuss an evidence-based rationale for modifying current eligibility requirements for CGM coverage.

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.

An algorithm mimicking pancreas pulsatile behavior improves artificial pancreas performance

BACKGROUND

Artificial pancreas design using subcutaneous insulin infusion without pre-meal feed-forward boluses often induces an over-response leading to hypoglycemia due to the increase of blood insulin concentration sustained in time. The objective of this work was to create an algorithm for controlling the function of insulin pumps in closed-loop systems to improve blood glucose management in type 1 diabetic patients by mimicking the pulsatile behaviour of the pancreas.

METHODS

A controller tuned in a pulsatile way promotes damped oscillations of blood insulin concentration injected through an insulin pump. We tested it in a simulated environment, using nine 'in silica' subjects. The control algorithm is founded on feedback linearization where through a change of variables, the nonlinear system turns into an equivalent linear system, suitable for implementing through a PID controller. We compared the results obtained 'in silica' with the volume injected by an insulin pump controlled by this algorithm.

RESULTS

The use of this algorithm resulted in a pulsatile control of postprandial blood glucose concentration, avoiding hypoglycaemic episodes. The results obtained 'in silica' were replicated in a real pump 'in vitro'.

CONCLUSIONS

With this proposed linear system, an appropriate control input can be designed. The controller works with a damped pulsatile pattern making the insulin infusion from the pump and blood insulin concentration pulsatile. This operational would improve the performance of an artificial pancreas.

Glycemic Outcome Associated With Insulin Pump and Glucose Sensor Use in Children and Adolescents With Type 1 Diabetes. Data From the International Pediatric Registry SWEET

OBJECTIVE

Insulin delivery methods, glucose-monitoring modalities, and related outcomes were examined in a large, international, diverse cohort of children and adolescents with type 1 diabetes from the Better Control in Pediatric and Adolescent Diabetes: Working to Create Centers of Reference (SWEET) -Registry.

RESEARCH DESIGN AND METHODS

Participants with type 1 diabetes of ≥1 year, aged ≤18 years, and who had documented pump or sensor usage during the period August 2017-July 2019 were stratified into four categories: injections-no sensor (referent); injections + sensor; pump-no sensor; and pump + sensor. HbA_1c and proportion of patients with diabetic ketoacidosis (DKA) or severe hypoglycemia (SH) were analyzed; linear and logistic regression models adjusted for demographics, region, and gross domestic product per capita were applied.

RESULTS

Data of 25,654 participants were analyzed. The proportions of participants (adjusted HbA_1c data) by study group were as follows: injections-no sensor group, 37.44% (8.72; 95% CI 8.68-8.75); injections + sensor group, 14.98% (8.30; 95% CI 8.25-8.35); pump-no sensor group, 17.22% (8.07; 95% CI 8.03-8.12); and pump + sensor group, 30.35% (7.81; 95% CI 7.77-7.84). HbA_1c was lower in all categories of participants who used a pump and/or sensor compared with the injections-no sensor treatment method (P < 0.001). The proportion of DKA episodes was lower in participants in the pump + sensor (1.98%; 95% CI 1.64-2.48; P < 0.001) and the pump-no sensor (2.02%; 95% CI 1.64-2.48; P < 0.05) groups when compared with those in the injections-no sensor group (2.91%; 95% CI 2.59-3.31). The proportion of participants experiencing SH was lower in pump-no sensor group (1.10%; 95% CI 0.85-1.43; P < 0.001) but higher in the injections + sensor group (4.25%; 95% CI 3.65-4.95; P < 0.001) compared with the injections-no sensor group (2.35%; 95% CI 2.04-2.71).

CONCLUSIONS

Lower HbA_1c and fewer DKA episodes were observed in participants using either a pump or continuous glucose monitoring (CGM) or both. Pump use was associated with a lower rate of SH. Across SWEET centers, use of pumps and CGM is increasing. The concomitant use of pump and CGM was associated with an additive benefit.

Therapy adjustments in people with type 1 diabetes with impaired hypoglycemia awareness on multiple daily injections using real-time continuous glucose monitoring: a mechanistic analysis of the HypoDE study

INTRODUCTION

Studies have shown beneficial effects of real-time continuous glucose monitoring (rtCGM) usage on clinical outcomes. The objective of this analysis was to identify which therapy adjustments were made by people with type 1 diabetes with impaired hypoglycemia awareness during rtCGM usage enabling reductions in the number of low glucose events observed in the HypoDE (Hypoglycemia in Deutschland) study.

RESEARCH DESIGN AND METHODS

In the multicenter randomized controlled trial in people with type 1 diabetes on multiple daily injections with impaired hypoglycemia awareness, participants recorded their diabetes therapy in 7-day logbooks at baseline and at 6-month follow-up. They used rtCGM or self-monitoring of blood glucose for therapy adjustments. This mechanistic analysis looked at changes in various aspects of therapy.

RESULTS

Logbooks were completed by 70 participants in the rtCGM group and 65 participants in the control group. Participants in the rtCGM group kept their total carbohydrate consumption, daily insulin doses and distribution constant during the study. However, they reported an increased intake of rescue carbohydrates (0.8±0.6 (mean±SD) vs 1.0±0.8 intake/day; baseline-adjusted between-group difference 0.3 intake (0.1-0.5), p=0.031). The glucose threshold at which rescue carbohydrate intake was initiated was elevated from 71±13 mg/dL (3.9±0.7 mmol/L) to 79±14 mg/dL (4.4±0.8 mmol/L) (adjusted between-group difference +7.6 mg/dL (2.4-12.8) (+0.4 mmol/L (0.1-0.7)); p=0.005) in the rtCGM group. Regression analysis showed that follow-up low glucose events were associated with group allocation (p<0.001), low glucose events at baseline (p=0.016) and rescue threshold (p=0.001).

CONCLUSIONS

No major adjustments in insulin therapy were made by study participants with impaired hypoglycemia awareness; however, they were more active in preventing hypoglycemia by taking rescue carbohydrates earlier and more often.

TRIAL REGISTRATION NUMBER

NCT02671968.

Self-Management Behaviors of Patients with Type 1 Diabetes: Comparing Two Sources of Patient-Generated Data

OBJECTIVES

This article aims to evaluate adult type 1 diabetes mellitus (T1DM) self-management behaviors (SMBs) related to exercise and alcohol on a survey versus a smartphone app to compare self-reported and self-tracked SMBs, and examine inter- and intrapatient variability.

METHODS

Adults with T1DM on insulin pump therapy were surveyed about their alcohol, meal, and exercise SMBs. For 4 weeks, participants self-tracked their alcohol, meal, and exercise events, and their SMBs corresponding with these events via an investigator-developed app. Descriptive statistics and generalized linear mixed-effect models were used to analyze the data RESULTS:  Thirty-five participants self-tracked over 5,000 interactions using the app. Variability in how participants perceived the effects of exercise and alcohol on their blood glucose was observed. The congruity between SMBs self-reported on the survey and those self-tracked with the app was measured as mean (SD). The lowest congruity was for alcohol and exercise with 61.9% (22.7) and 66.4% (20.2), respectively. Congruity was higher for meals with 80.9% (21.0). There was significant daily intra- and interpatient variability in SMBs related to preprandial bolusing: recommended bolus, p < 0.05; own bolus choice, p < 0.01; and recommended basal adjustment, p < 0.01.

CONCLUSION

This study highlights the variability in intra- and interpatient SMBs obtained through the use of a survey and app. The outcomes of this study indicate that clinicians could use both one-time and every-day assessment tools to assess SMBs related to meals. For alcohol and exercise, further research is needed to understand the best assessment method for SMBs. Given this degree of patient variability, there is a need for an educational intervention that goes beyond the traditional "one-size-fits-all" approach of diabetes management to target individualized treatment barriers.

Data-Driven Diabetes Education Guided by a Personalized Report for Patients on Insulin Pump Therapy

Objective

It is difficult to assess self-management behaviors (SMBs) and incorporate them into a personalized self-care plan. We aimed to develop and apply SMB phenotyping algorithms from data collected by diabetes devices and a mobile health (mHealth) application to create patient-specific SMBs reports to guide individualized interventions. Follow-up interventions aimed to understand patient's reasoning behind discovered SMB choices.

Methods

This study deals with adults on continuous subcutaneous insulin infusion using a continuous glucose monitor (CGM) who self-tracked SMBs with an mHealth application for 1 month. Patient-generated data were quantified and an SMB report was designed and populated for each participant. A diabetes educator used the report to conduct personalized, data-driven educational interventions. Thematic analysis of the intervention was conducted.

Results

Twenty-two participants recorded 118 alcohol, 251 exercise, 2,661 meal events, and 1,900 photos. A patient-specific SMB report was created from this data and used to conduct the educational intervention. High variability of SMB was observed between patients. There was variability in the percentage of alcohol events accompanied by a blood glucose check, median 79% (38-100% range), and frequency of changing the bolus waveform, median 11 (7-95 range). Interventions confirmed variability of SMBs. Main emerging themes from thematic analysis were: challenges and barriers, motivators, current SMB techniques, and future plans to improve glycemic control.

Conclusion

The ability to quantify SMBs and understand patients' rationale may help improve diabetes self-care and related outcomes. This study describes our first steps in piloting a patient-specific diabetes educational intervention, as opposed to the current "one size fits all" approach.

Continuous Glucose Monitoring Sensors for Diabetes Management: A Review of Technologies and Applications

By providing blood glucose (BG) concentration measurements in an almost continuous-time fashion for several consecutive days, wearable minimally-invasive continuous glucose monitoring (CGM) sensors are revolutionizing diabetes management, and are becoming an increasingly adopted technology especially for diabetic individuals requiring insulin administrations. Indeed, by providing glucose real-time insights of BG dynamics and trend, and being equipped with visual and acoustic alarms for hypo- and hyperglycemia, CGM devices have been proved to improve safety and effectiveness of diabetes therapy, reduce hypoglycemia incidence and duration, and decrease glycemic variability. Furthermore, the real-time availability of BG values has been stimulating the realization of new tools to provide patients with decision support to improve insulin dosage tuning and infusion. The aim of this paper is to offer an overview of current literature and future possible developments regarding CGM technologies and applications. In particular, first, we outline the technological evolution of CGM devices through the last 20 years. Then, we discuss about the current use of CGM sensors from patients affected by diabetes, and, we report some works proving the beneficial impact provided by the adoption of CGM. Finally, we review some recent advanced applications for diabetes treatment based on CGM sensors.

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.

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.

Baseline Glycated Hemoglobin Values Predict the Magnitude of Glycemic Improvement in Patients with Type 1 and Type 2 Diabetes: Subgroup Analyses from the DIAMOND Study Program

The DIAMOND study demonstrated that the addition of real-time continuous glucose monitoring (rtCGM) effectively lowers glycated hemoglobin (HbA_1c) in patients with type 1 (T1D) and type 2 diabetes (T2D), treated with multiple daily injections (MDI). This post hoc analysis investigated whether DIAMOND study participants at progressively higher baseline HbA_1c levels benefit from using rtCGM. We examined outcomes data from a large, randomized, controlled trial of MDI-treated participants with T1D (N = 158) and T2D (N = 158), comparing monitoring by rtCGM versus self-monitoring of blood glucose (SMBG). The primary outcome was the magnitude of HbA_1c reductions among study participants within elevated baseline HbA_1c levels (≥8.0%-10.0%, ≥8.5%-10.0%, and ≥9.0%-10.0%). Analyses were performed on three subgroups: T1D, T2D, and combined T1D/T2D. The full T1D analysis population had a mean baseline HbA_1c value of 8.6 ± 0.6% (range 7.5%-9.9%), randomized to rtCGM (n = 105) or control (n = 53). The full T2D analysis population had a mean baseline HbA_1c value of 8.5 ± 0.6% (range 7.5%-9.9%), randomized to rtCGM (n = 79) or control (n = 79). Participants had improvements in glycemic status regardless of monitoring method. In the three subgroups, the change in HbA_1c was significantly greater in rtCGM participants compared to SMBG at all predefined baseline HbA_1c levels at 12 and 24 weeks. Among the rtCGM participants, the change in HbA_1c was numerically greatest at the highest baseline HbA_1c subgroup (≥9.0%). Participants with elevated baseline HbA_1c had improvements in glycemic status regardless of monitoring method. However, the magnitudes of improvements appeared greater among participants using rtCGM.

The Effect of Reduced Self-Monitored Blood Glucose Testing After Adoption of Continuous Glucose Monitoring on Hemoglobin A1c and Time in Range

The effectiveness of real-time continuous glucose monitoring (rtCGM) in adults with diabetes treated with insulin injections was evaluated in the 24-week DIAMOND clinical trial comparing rtCGM users to a control group using self-monitored blood glucose (SMBG) testing ( Clinicaltrials.gov : NCT02282397). All participants were instructed to use SMBG results for diabetes management decisions; however, SMBG testing frequency varied within the rtCGM group. This brief report evaluated how SMBG frequency changes in the rtCGM group were correlated with glycemic outcomes in the same trial. Baseline and end-of-study hemoglobin A1c (HbA1c) levels, percentages of CGM values in the 70-180 mg/dL target range (time in range [TIR]), mean of daily differences (MODD), and glycemic coefficients of variation (CVs) were compared. The rtCGM group analyzed included 175 participants-99 with type 1 diabetes (T1D) and 76 with type 2 diabetes (T2D). When comparing participants whose SMBG testing frequency decreased by >1/day versus ≤1/day, mean change in HbA1c was similar (-0.9 ± 0.7 percentage points in both groups, P = 0.59), as was change in TIR (+3.9 ± 14.3 vs. +5.7 ± 13.7 percentage points, respectively, P = 0.39). Likewise, when comparing participants in the highest and lowest quartiles of SMBG frequency reduction (≥2.2 vs. ≤0.4 fewer tests/day, respectively), changes in HbA1c (-0.8 ± 0.6 vs. -0.9 ± 0.6 percentage points, respectively, P = 0.52) and TIR (+4.8 ± 13.2 vs. +5.6 ± 12.7 percentage points, respectively, P = 0.98) were similar. The mean (standard deviation [SD]) change in MODD was -8.3 mg/dL (14.8) and -5.5 mg/dL (14.7) for participants who reduced their SMBG frequency by >1 test/day and ≤1 test/day, respectively; the mean (SD) change in CV was -3.6% (5.0) and -1.6% (5.1) for participants who reduced their SMBG frequency by >1 test/day and ≤1 test/day, respectively. These findings suggest that individuals who decrease the frequency of SMBG testing can effectively base some of their diabetes-related treatment decisions on glucose concentrations, trend information, and alarms provided by their rtCGM systems.

Continuous Glucose Monitoring (CGM) or Blood Glucose Monitoring (BGM): Interactions and Implications

At the 2017 10th annual International Conference on Advanced Technologies and Treatments for Diabetes (ATTD) in Paris, France, four speakers presented their perspectives on the roles of continuous glucose monitoring (CGM) and of blood glucose monitoring (BGM) in patient management within one symposium. These presentations included discussions of the differences in the accuracy of CGM and BGM, a clinical perspective on the physiological reasons behind differences in CGM and BGM values, and an overview of the impact of variations in device accuracy on patients with diabetes. Subsequently a short summary of these presentations is given, highlighting the value of good accuracy of BGM or CGM systems and the ongoing need for standardization. The important role of both BGM and CGM in patient management was a theme across all presentations.

First Experiences With a Wearable Multisensor Device in a Noninvasive Continuous Glucose Monitoring Study at Home, Part II: The Investigators' View

BACKGROUND

Extensive past work showed that noninvasive continuous glucose monitoring with a wearable multisensor device worn on the upper arm provides useful information about glucose trends to improve diabetes therapy in controlled and semicontrolled conditions.

METHOD

To test previous findings also in uncontrolled conditions, a long term at home study has been organized to collect multisensor and reference glucose data in a population of 20 type 1 diabetes subjects. A total of 1072 study days were collected and a fully on-line compatible algorithmic routine linking multisensor data to glucose applied to estimate glucose levels noninvasively.

RESULTS

The algorithm used here calculates glucose values from sensor data and adds a constant obtained by a daily calibration. It provides point inaccuracy measured by a MARD of 35.4 mg/dL on test data. This is higher than current state-of-the-art minimally invasive devices, but still 86.9% of glucose rate points fall within the zone AR+BR.

CONCLUSIONS

The multisensor device and the algorithmic routine used earlier in controlled conditions tracks glucose changes also in uncontrolled conditions, although with lower accuracy. The examination of learning curves suggests that obtaining more data would not improve the results. Therefore, further efforts would focus on the development of more complex algorithmic routines able to compensate for environmental and physiological confounders better.

Hypoglycaemia in type 1 diabetes: technological treatments, their limitations and the place of psychology

Advances in technology allowing improved insulin delivery and glucose monitoring can significantly reduce the burden of hypoglycaemia when used appropriately. However, limitations of the current technology, and the skills, commitment and motivation required to use them, mean that it does not work for all people. Education and informed professional support are key to success. In the context of problematic hypoglycaemia, data suggest that newer technology has lower efficacy and uptake in those with most need. Identifying the causes of hypoglycaemia and understanding some of the underlying behavioural drivers may prove useful and psycho-educational strategies may be effective in selected individuals. Ultimately, as in many spheres of medicine, successful management of problematic hypoglycaemia depends upon matching the right treatment to the right individual.

Best friend or spy: a qualitative meta-synthesis on the impact of continuous glucose monitoring on life with Type 1 diabetes

AIMS

This is a meta-synthesis of extant qualitative literature related to impact of continuous glucose monitoring (CGM). CGM has been available for a decade for the management of Type 1 diabetes and is the lynchpin of future artificial pancreas technologies. Clinical uptake of CGM is an important area of inquiry. The purpose of this meta-synthesis is to understand the impact of CGM on individuals with Type 1 diabetes and others (parents, significant others, providers) in order to design appropriate clinical interventions for adherence.

METHODS

Studies published in English between 2007 and 2017 were included, reflecting commercial CGM availability. PubMed, PsychINFO, CINALH, Web of Science and EMBASE databases were queried using search terms related to CGM, qualitative, experience and Type 1 diabetes. Included articles contained original qualitative or mixed-method research on CGM, sensor-augmented pump or closed-loop therapies. Articles underwent quality appraisal and thematic interpretive integration by a multidisciplinary team.

RESULTS

Nine articles (343 participants) met the inclusion criteria and were included in the synthesis. Six novel themes emerged: interacting with CGM, burden of living with CGM, feeling different from others, feeling empowered, interacting with glucose information and impact on relationships.

CONCLUSION

CGM affects physical, emotional and relational aspects of life. Clinicians can help minimize the burden of CGM with carefully delivered education and expectation-setting with individuals. Empowerment and relational partnerships in diabetes care can be explored to maximize satisfaction with CGM. Systematic interpretive synthesis of qualitative studies provides a comprehensive, contextual understanding of the impact of CGM on daily life and relationships.

Self-Reported Compensation Techniques for Carbohydrate, Exercise, and Alcohol Behaviors in Patients With Type 1 Diabetes on Insulin Pump Therapy

Studies have found variability in self-care behaviors in patients with type 1 diabetes, particularly when incorporating exercise and alcohol consumption. The objective of this study was to provide results from a survey to understand (1) insulin pump behaviors, (2) reported self-management behaviors for exercise and alcohol, and (3) perceptions of the effects of exercise and alcohol on blood glucose (BG) control. Fourteen participants from an outpatient endocrinology practice were recruited and administered an electronic survey. Compensation techniques for exercise and alcohol, along with reasons for employing the techniques were identified. Also identified were factors that participants said affected BG control with regard to exercise and alcohol. These results confirm the considerable inconsistency patients have about incorporating exercise and alcohol into decisions about self-management behaviors.

Patients' and caregivers' experiences of using continuous glucose monitoring to support diabetes self-management: qualitative study

BACKGROUND

Continuous glucose monitoring (CGM) enables users to view real-time interstitial glucose readings and provides information on the direction and rate of change of blood glucose levels. Users can also access historical data to inform treatment decisions. While the clinical and psychological benefits of CGM are well established, little is known about how individuals use CGM to inform diabetes self-management. We explored participants' experiences of using CGM in order to provide recommendations for supporting individuals to make optimal use of this technology.

METHODS

In-depth interviews (n = 24) with adults, adolescents and parents who had used CGM for ≥4 weeks; data were analysed thematically.

RESULTS

Participants found CGM an empowering tool because they could access blood glucose data effortlessly, and trend arrows enabled them to see whether blood glucose was rising or dropping and at what speed. This predicative information aided short-term lifestyle planning and enabled individuals to take action to prevent hypoglycaemia and hyperglycaemia. Having easy access to blood glucose data on a continuous basis also allowed participants to develop a better understanding of how insulin, activity and food impacted on blood glucose. This understanding was described as motivating individuals to make dietary changes and break cycles of over-treating hypoglycaemia and hyperglycaemia. Participants also described how historical CGM data provided a more nuanced picture of blood glucose control than was possible with blood glucose self-monitoring and, hence, better information to inform changes to background insulin doses and mealtime ratios. However, while participants expressed confidence making immediate adjustments to insulin and lifestyle to address impending hypoglycaemia and hypoglycaemia, most described needing and expecting health professionals to interpret historical CGM data and determine changes to background insulin doses and mealtime ratios. While alarms could reinforce a sense of hypoglycaemic safety, some individuals expressed ambivalent views, especially those who perceived alarms as signalling personal failure to achieve optimal glycaemic control.

CONCLUSIONS

CGM can be an empowering and motivational tool which enables participants to fine-tune and optimize their blood glucose control. However, individuals may benefit from psycho-social education, training and/or technological support to make optimal use of CGM data and use alarms appropriately.

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.

Retrospective Analysis of Continuous Glucose Monitoring Data With the Surveillance Error Grid Supports Nonadjunctive Dosing Decisions

OBJECTIVE

The objective was to assess clinical risks of inaccurate continuous glucose monitoring (CGM) system readings as estimated by the surveillance error grid (SEG).

METHODS

Values from Dexcom G4 Platinum system with an advanced algorithm (Software 505) were plotted on the SEG with temporally matched reference venous (YSI) values collected during clinic visits on days 1, 4, and 7 of sensor wear. Data from a pediatric study (N = 79, age [mean ± SD] 12.2 ± 4.6 years, all with type 1 diabetes) and an adult study (N = 51, age 46.7 ± 15.8 years, 44 with type 1 diabetes and 7 with type 2 diabetes) were used.

RESULTS

Pediatric data included 2262 paired points, of which 1990 (88.0%) were in the "no risk" zone. Adult data included 2263 paired points, of which 2056 (90.9%) were in the "no risk" zone. Performance was best on Day 4, when 92.7% and 93.3% of points from the pediatric and adult studies, respectively, were in the "no risk" zone. Nine of the 4525 points (<0.2%) from 5 different sensors were in zones representing moderate risk, and none were in zones representing great or extreme risk.

CONCLUSIONS

SEG analysis suggests that in pediatric and adult subjects with diabetes, using CGM values for diabetes management poses minimal risk to the user. CGM users also benefit from glucose trends and alerts.

Effect of real-time continuous glucose monitoring on hypoglycemia in adult type 1 diabetes patients

In this manuscript, the application of CGM in hypoglycemia management in adult type 1 diabetes was commented and discussed.

Commentary Regarding Shapiro, "Nonadjunctive Use of Continuous Glucose Monitors for Insulin Dosing: Is It Safe?"

The FDA recently expanded the approved use of Dexcom's G5 Mobile continuous glucose monitoring (CGM) system to allow for diabetes treatment decisions. This decision is expected to reduce the burden of SMBG testing and increase the adoption and persistent use of CGM. The safety of nonadjunctive CGM use was questioned because of sporadic large discrepancies between CGM and SMBG values. These data were viewed in the context of complaints found in the FDA MAUDE database and social media postings. This commentary provides additional perspective on the inferences that can be drawn from these reports and the risk of nonadjunctive use of CGM data.

Practical Considerations on the Use of Continuous Glucose Monitoring in Pediatrics and Older Adults and Nonadjunctive Use

Clinical use of continuous glucose monitoring (CGM) devices has grown over the past 15 years from a niche concept to becoming standard of care for patients with type 1 diabetes (T1D). With the December 2016 Food and Drug Administration approval for diabetes treatment decisions directly from CGM values (nonadjunctive use) without finger-stick confirmation, the uptake and scope of CGM use will likely further expand. With this expansion, it is important to consider the role and impact of CGM technology in specific settings and high-risk populations, such as the young and the elderly. In pediatric patients, CGM concerns include limited body surface area, difficulty keeping sensors adhered, and the role of nonadjunctive use in the school setting. In older adults, Medicare did not, until very recently, cover CGM devices and as such, their use had been limited by lack of reimbursement. As CGM use will likely expand in clinical practice given the nonadjunctive indication, guidelines and recommendations for clinical practice are warranted. In this article, we discuss recent research on CGM use in the special populations of children and older adults and provide initial guidelines for nonadjunctive use in clinical practice.

Continuous Glucose Monitoring Use in Type 1 Diabetes: Longitudinal Analysis Demonstrates Meaningful Improvements in HbA1c and Reductions in Health Care Utilization

BACKGROUND

Real-time continuous glucose monitoring (rtCGM) improves glycemic control in type 1 diabetes (T1D) patients treated with continuous subcutaneous insulin infusion (CSII). However, the benefits of rtCGM in T1D patients treated with multiple daily insulin injection (MDI) therapy has not been well studied. We explored the effects of rtCGM versus self-monitoring of blood glucose (SMBG) on clinical outcomes within a large T1D population treated with either CSII or MDI therapy.

METHODS

This retrospective, longitudinal analysis utilized datasets from T1D patients enrolled in a commercial health plan to assess changes in HbA1c in 187 naïve to rtCGM users and 6260 SMBG users. Propensity score modeling was used to assess inpatient admissions, emergency room (ER) visits in 1130 patients (565 rtCGM, 565 SMBG). Differences in HbA1c reduction (rtCGM+MDI vs rtCGM+CSII) were evaluated.

RESULTS

Larger, clinically meaningful HbA1c reductions were seen among rtCGM versus SMBG users: -0.5% ( P = .004) versus -0.2% ( P < .0001); 0.3% diff in diff, P = .03. All-cause inpatient admissions were lower for rtCGM users: -42%, P = .013. Emergency room visits coded for diabetic ketoacidosis (DKA) were four times higher for SMBG patients than rtCGM patients: 17 versus 4, P = .0318. HbA1c reductions were most notable with rtCGM+MDI versus rtCGM+CSII treatment: -0.6% ( P = .01) versus -0.3% ( P = .16).

CONCLUSIONS

Use of rtCGM in T1D patients facilitates greater HbA1c improvements and reduced health care system utilization compared with traditional SMBG use regardless of insulin administration method. Treatment with rtCGM in conjunction with MDI confers similar or greater glycemic benefits without the additional costs associated with CSII therapy.

REPLACE-BG: A Randomized Trial Comparing Continuous Glucose Monitoring With and Without Routine Blood Glucose Monitoring in Adults With Well-Controlled Type 1 Diabetes

OBJECTIVE

To determine whether the use of continuous glucose monitoring (CGM) without confirmatory blood glucose monitoring (BGM) measurements is as safe and effective as using CGM adjunctive to BGM in adults with well-controlled type 1 diabetes (T1D).

RESEARCH DESIGN AND METHODS

A randomized noninferiority clinical trial was conducted at 14 sites in the T1D Exchange Clinic Network. Participants were ≥18 years of age (mean 44 ± 14 years), had T1D for ≥1 year (mean duration 24 ± 12 years), used an insulin pump, and had an HbA_1c ≤9.0% (≤75 mmol/mL) (mean 7.0 ± 0.7% [53 ± 7.7 mmol/mol]); prestudy, 47% were CGM users. Participants were randomly assigned 2:1 to the CGM-only (n = 149) or CGM+BGM (n = 77) group. The primary outcome was time in range (70-180 mg/dL) over the 26-week trial, with a prespecified noninferiority limit of 7.5%.

RESULTS

CGM use averaged 6.7 ± 0.5 and 6.8 ± 0.4 days/week in the CGM-only and CGM+BGM groups, respectively, over the 26-week trial. BGM tests per day (including the two required daily for CGM calibration) averaged 2.8 ± 0.9 and 5.4 ± 1.4 in the two groups, respectively (P < 0.001). Mean time in 70-180 mg/dL was 63 ± 13% at both baseline and 26 weeks in the CGM-only group and 65 ± 13% and 65 ± 11% in the CGM+BGM group (adjusted difference 0%; one-sided 95% CI -2%). No severe hypoglycemic events occurred in the CGM-only group, and one occurred in the CGM+BGM group.

CONCLUSIONS

Use of CGM without regular use of confirmatory BGM is as safe and effective as using CGM with BGM in adults with well-controlled T1D at low risk for severe hypoglycemia.

Characterization of Exercise and Alcohol Self-Management Behaviors of Type 1 Diabetes Patients on Insulin Pump Therapy

BACKGROUND

There is a lack of systematic ways to analyze how diabetes patients use their insulin pumps to self-manage blood glucose to compensate for alcohol ingestion and exercise. The objective was to analyze "real-life" insulin dosing decisions occurring in conjunction with alcohol intake and exercise among patients using insulin pumps.

METHODS

We recruited adult type 1 diabetes (T1D) patients on insulin pump therapy. Participants were asked to maintain their daily routines, including those related to exercising and consuming alcohol, and keep a 30-day journal on exercise performed and alcohol consumed. Thirty days of insulin pump data were downloaded. Participants' actual insulin dosing behaviors were compared against their self-reported behaviors in the setting of exercise and alcohol.

RESULTS

Nineteen T1D patients were recruited and over 4000 interactions with the insulin pump were analyzed. The analysis exposed variability in how subjects perceived the effects of exercise/alcohol on their blood glucose, inconsistencies between self-reported and observed behaviors, and higher rates of blood glucose control behaviors for exercise versus alcohol.

CONCLUSION

Compensation techniques and perceptions on how exercise and alcohol affect their blood glucose levels vary between patients. Improved individualized educational techniques that take into consideration a patient's unique life style are needed to help patients effectively apply alcohol and exercise compensation techniques.

Recommendations for Using Real-Time Continuous Glucose Monitoring (rtCGM) Data for Insulin Adjustments in Type 1 Diabetes

The clinical benefits of real time continuous glucose monitoring (rtCGM) use have been well demonstrated in both CSII- and MDI-treated individuals in large clinical trials. However, recommendations for patient use of rtCGM in everyday life situations are lacking. This article provides guidance to clinicians and patients with type 1 diabetes (T1D) in effective use of rtCGM data, including glucose rate of change (ROC) arrows, for insulin dosing adjustments and other treatment decisions. The recommendations presented here are based on our own clinical experiences as endocrinologists, our personal experiences living with T1D using rtCGM, and findings from a recent survey of T1D patients who have successfully used rtCGM in their self-management. It is important that both clinicians and people with diabetes understand the utility and limitations of rtCGM. Maintaining a collaborative clinician-user relationship remains an important factor in safe, successful rtCGM use.

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

A consensus conference of the American Association of Clinical Endocrinologists and American College of Endocrinology held in February 2016 advocated expanding the use of continuous glucose monitoring (CGM) in the management of diabetes. Based on the data described in this paper, CGM use is shown to improve glucose control and reduce hypoglycemic events, and therefore has the potential to reduce the risk of acute and chronic complications of diabetes. Likely, all of the above would not only improve the quality of life and life expectancy of people with diabetes, but would also have a positive impact on health-related cost.

Patient decision-making of CGM sensor driven insulin therapies in type 1 diabetes: In silico assessment

In type 1 diabetes (T1D) therapy, continuous glucose monitoring (CGM) sensors, which provide glucose concentration in the subcutis every 1-5 min for 7 consecutive days, should allow in principle a more efficient insulin dosing than that based on the conventional 3-4 self-monitoring of blood glucose (SMBG) measurements per day. However, CGM, at variance with SMBG, is still not approved for insulin dosing in T1D management because regulatory agencies, e.g. FDA, are looking for more factual evidence on its safety. An in silico assessment of SMBG- vs CGM-driven insulin therapy can be a first step. Here we present a simulation model of T1D patient decision-making obtained by interconnecting models of glucose-insulin dynamics, SMBG and CGM measurement errors, carbohydrates-counting errors, insulin boluses time variability and forgetfulness, and subcutaneous insulin pump delivery. Inter- and intra- patient variability of model parameters are considered. The T1D patient decision-making model allows to run realistic multi-day simulations scenarios in a population of virtual subjects. We present the first results of simulations run in 20 virtual subjects over a 7-day period, which demonstrates that additional information brought by CGM (trend and hypo/hyperglycemic warnings) with respect to SMBG produces a statistically significant increment (about of 9%) of time spent by the patient in the euglycemic range (70-180 mg/dl).

Differences in Use of Glucose Rate of Change (ROC) Arrows to Adjust Insulin Therapy Among Individuals With Type 1 and Type 2 Diabetes Who Use Continuous Glucose Monitoring (CGM)

OBJECTIVE

To understand differences between individuals with type 1 diabetes (T1D) and type 2 diabetes (T2D) in utilization of continuous glucose monitoring (CGM) data to adjust insulin therapy, either continuous subcutaneous insulin infusion (CSII) or multiple daily insulin injections (MDI).

METHODS

We surveyed 300 individuals who regularly used real-time CGM, using 70 questions to obtain information about general CGM use and response to glucose rate of change (ROC) arrows.

RESULTS

The survey was completed by 222 T1D and 78 T2D respondents treated with intensive insulin therapy. T1D respondents included CSII (n = 166) and MDI (n = 56) users. T2D respondents were more balanced: 34 (44%) versus 44 (56%), respectively. A larger percentage of T1D then T2D respondents reported a constant use of CGM (85% vs 61%, P < .001). T1D and T2D respondents reported similar substantial increases in correction dosages in response to rapidly increasing glucose (>3 mg/dL/min; 2 arrows up): +140% versus +136%, P = .4534. However, T1D respondents reported making smaller correction dosage reductions than T2D respondents in response to rapidly decreasing glucose (-42% vs -80%, P < .001). Differences between T1D and T2D respondents were also observed in mealtime dosage adjustments in response to rapidly increasing glucose compared to when glucose is stable (flat arrow) at 110 mg/dl: +81% versus +108%, respectively (P = .003). Although these adjustments are statistically different, both are large.

CONCLUSIONS

CGM users often rely on ROC information when determining insulin doses and tend to be more aggressive in their insulin adjustments despite differences in type of diabetes.

Nonadjunctive Use of Continuous Glucose Monitoring for Diabetes Treatment Decisions

While self-monitoring of blood glucose (SMBG) is the current standard used by people with diabetes to manage glucose levels, recent improvements in accuracy of continuous glucose monitoring (CGM) technology are making it very likely that diabetes-related treatment decisions will soon be made based on CGM values alone. Nonadjunctive use of CGM will lead to a paradigm shift in how patients manage their glucose levels and will require substantial changes in how care providers educate their patients, monitor their progress, and provide feedback to help them manage their diabetes. The approval to use CGM nonadjunctively is also a critical step in the pathway toward FDA approval of an artificial pancreas system, which is further expected to transform diabetes care for people with type 1 diabetes. In this article, we discuss how nonadjunctive CGM is expected to soon replace routine SMBG and how this new usage scenario is expected to transform health outcomes and patient care.

Unblinded CGM Should Replace Blinded CGM in the Clinical Management of Diabetes

The original continuous glucose monitors (CGMs) were limited to 3-day, blinded observation periods where glucose data was hidden from patients and later retrospectively analyzed by a provider to help guide the management of diabetes. Unblinded CGM, released several years later, allows patients to view their glucose data in real-time amidst their daily routines, enabling them to better understand how variables such as activity, nutrition, and medications affect glucose levels. Research studies consistently demonstrate improved glycemic control and reduced hypoglycemia in children and adults with type 1 and type 2 diabetes while using unblinded CGM.(1-4) As such, we believe that all CGM usage in clinical practice should be in real-time, unblinded mode for short-term and long-term wear periods.

The Rationale for Continuous Glucose Monitoring-based Diabetes Treatment Decisions and Non-adjunctive Continuous Glucose Monitoring Use

Self-monitoring of blood glucose (SMBG) is now recognised as a core component of diabetes self-management. However, there are many limitations to SMBG use in individuals with diabetes who are treated with intensive insulin regimens. Many individuals do not test at the recommended frequencies. Additionally, because SMBG only provides a blood glucose reading at a single point in time, hypoglycaemia and hyperglycaemia can easily go undetected, limiting the user's ability to take corrective action. Inaccuracies due to user error, environmental factors and weaknesses in SMBG system integrity further limit the utility of SMBG. Real-time continuous glucose monitoring (CGM) displays the current glucose, direction and velocity of glucose change and provides programmable alarms. This trending information and 'around-the-clock' vigilance provides a significant safety advantage relative to SMBG. No published clinical studies have evaluated outcomes when CGM is used as a replacement for SMBG; however, recent in silico studies support this indication. This article reviews the limitations of SMBG and discusses recent evidence that supports CGM-based decisions as an effective approach to managing insulin-treated diabetes.

Continuous Glucose Monitoring, Future Products, and Update on Worldwide Artificial Pancreas Projects

The development of accurate and easy-to-use continuous glucose monitoring (CGM) improved diabetes treatment by providing additional temporal information on glycemia and glucose trends to patient and physician. Although CGM enables users to lower their average glucose level without an increased incidence of hypoglycemia, this comes at the price of additional patient effort. Automation of insulin administration, also known as closed-loop (CL) or artificial pancreas treatment, has the promise to reduce patient effort and improve glycemic control. CGM data serve as the conditional input for insulin automation devices. The first commercial product for partial automation of insulin administration used insulin delivery shutoff at a predefined glucose level. These systems showed a reduction in hypoglycemia. Insulin-only CL devices show increased time spent in euglycemia and a reduction of hypo- and hyperglycemia. Improved glycemic control, coinciding with a minor decrease in hemoglobin A1c level, was confirmed in recent long-term home studies investigating these devices, paving the way for pivotal studies for commercialization of the artificial pancreas. Although the first results from dual-hormone CL systems are promising, because of increased cost of consumables of these systems, long-term head-to-head studies will have to prove superiority over insulin-only approaches. Now CL glucose control for daily use might finally become reality. Improved continuous glucose sensing technology, miniaturization of electrical devices, and development of algorithms were key in making this possible. Clinical adoption challenges, including device usability and reimbursement, need to be addressed. Time will tell for which patient groups CL systems will be reimbursed and whether these devices can deliver the promise that they hold.