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Optimizing postprandial glucose control in persons with type 1 diabetes (T1D) is challenging. We hypothesized that in free-living individuals, meal composition (high and low glycemic index [HGI and LGI], high and low fat [HF and LF]) may impact insulin requirements. Adults ( N = 25) with T1D using open-loop insulin and continuous glucose monitoring were provided a meal-tagging app and prepackaged meals with defined macronutrient content. Data from 463 meals were analyzed. LGI meals required significantly more insulin than HGI meals ( P = 0.01). Furthermore, the mean (±standard deviation) carbohydrate-to-insulin ratio (CIR) was significantly different overall among the LGI-LF (5.5 ± 3.4), LGI-HF (4.5 ± 3.8), HGI-LF (7.6 ± 5.1), and HGI-HF (8.7 ± 5.8) meals ( P = 0.001). The risk of nocturnal hypoglycemia is associated with daytime hypoglycemia and amount of insulin administered prior to the evening and exercise. This exploratory study designed to examine the impact of different meal types on insulin dosing requirements in free-living adults with T1D emphasizes the need for individualized adjustment of the CIR depending on meal composition.

Background: Recent advancements in diabetes technology have significantly improved Type 1 diabetes (T1D) management, but disparities persist, particularly in the adoption of automated insulin delivery (AID) systems within minoritized communities. We aimed to improve patient access to AID system training and overcome clinical inertia to referral., Methods: We report on a transformative program implemented at Boston Medical Center, the largest safety-net hospital in New England, aimed at reducing disparities in AID system utilization. We employed a multidisciplinary team and quality improvement principles to identify barriers and develop solutions. Strategies included increasing access to diabetes educators, creating a referral system, and developing telemedicine education classes. We also made efforts to raise clinician awareness and confidence in recommending AID therapy., Results: At baseline, 13.5% of our clinic T1D population was using an insulin pump. The population referred included 97 people with T1D (49% female, mean A1c 8.7%, 68% public insurance beneficiaries, 25% Hispanic and 25% non-Hispanic Black). Results from the first year showed a 166% increase in AID system use rates, with 64% of referred patients starting on AID. Notably, 78% of patients with A1c >8.5% adopted AID systems, addressing a gap in representation observed in clinical efficacy trials. The initiative successfully narrowed disparities in AID use among minoritized populations., Conclusions: The program's success among minoritized patients underscores the significance of tailored, collaborative, team-based care and targeted educational initiatives. Our experience provides a foundation for future efforts to ensure equitable access to diabetes technologies, emphasizing the potential of local quality improvement interventions., Competing Interests: Disclosure The authors have no multiplicity of interest to disclose., (Copyright © 2024 AACE. Published by Elsevier Inc. All rights reserved.)

Background: A composite metric for the quality of glycemia from continuous glucose monitor (CGM) tracings could be useful for assisting with basic clinical interpretation of CGM data., Methods: We assembled a data set of 14-day CGM tracings from 225 insulin-treated adults with diabetes. Using a balanced incomplete block design, 330 clinicians who were highly experienced with CGM analysis and interpretation ranked the CGM tracings from best to worst quality of glycemia. We used principal component analysis and multiple regressions to develop a model to predict the clinician ranking based on seven standard metrics in an Ambulatory Glucose Profile: very low-glucose and low-glucose hypoglycemia; very high-glucose and high-glucose hyperglycemia; time in range; mean glucose; and coefficient of variation., Results: The analysis showed that clinician rankings depend on two components, one related to hypoglycemia that gives more weight to very low-glucose than to low-glucose and the other related to hyperglycemia that likewise gives greater weight to very high-glucose than to high-glucose. These two components should be calculated and displayed separately, but they can also be combined into a single Glycemia Risk Index (GRI) that corresponds closely to the clinician rankings of the overall quality of glycemia (r = 0.95). The GRI can be displayed graphically on a GRI Grid with the hypoglycemia component on the horizontal axis and the hyperglycemia component on the vertical axis. Diagonal lines divide the graph into five zones (quintiles) corresponding to the best (0th to 20th percentile) to worst (81st to 100th percentile) overall quality of glycemia. The GRI Grid enables users to track sequential changes within an individual over time and compare groups of individuals., Conclusion: The GRI is a single-number summary of the quality of glycemia. Its hypoglycemia and hyperglycemia components provide actionable scores and a graphical display (the GRI Grid) that can be used by clinicians and researchers to determine the glycemic effects of prescribed and investigational treatments.

Diabetes Technology Society hosted its annual Diabetes Technology Meeting from November 3 to November 5, 2022. Meeting topics included (1) the measurement of glucose, insulin, and ketones; (2) virtual diabetes care; (3) metrics for managing diabetes and predicting outcomes; (4) integration of continuous glucose monitor data into the electronic health record; (5) regulation of diabetes technology; (6) digital health to nudge behavior; (7) estimating carbohydrates; (8) fully automated insulin delivery systems; (9) hypoglycemia; (10) novel insulins; (11) insulin delivery; (12) on-body sensors; (13) continuous glucose monitoring; (14) diabetic foot ulcers; (15) the environmental impact of diabetes technology; and (16) spinal cord stimulation for painful diabetic neuropathy. A live demonstration of a device that can allow for the recycling of used insulin pens was also presented.

Diabetes mellitus remains the leading cause of end-stage kidney disease worldwide. Inadequate glucose monitoring has been identified as one of the gaps in care for hemodialysis patients with diabetes, and lack of reliable methods to assess glycemia has contributed to uncertainty regarding the benefit of glycemic control in these individuals. Hemoglobin A1c, the standard metric to evaluate glycemic control, is inaccurate in patients with kidney failure, and does not capture the full range of glucose values for patients with diabetes. Recent advances in continuous glucose monitoring have established this technology as the new gold standard for glucose management in diabetes. Glucose fluctuations are uniquely challenging in patients dependent on intermittent hemodialysis, and lead to clinically significant glycemic variability. This review evaluates continuous glucose monitoring technology, its validity in the setting of kidney failure, and interpretation of glucose monitoring results for the nephrologist. Continuous glucose monitoring targets for patients on dialysis have yet to be established. While continuous glucose monitoring provides a more complete picture of the glycemic profile than hemoglobin A1c and can mitigate high-risk hypoglycemia and hyperglycemia in the context of the hemodialysis procedure itself, whether the technology can improve clinical outcomes merits further investigation., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Williams, Steenkamp and Wolpert.)

Maintaining blood glucose levels in the target range during exercise can be onerous for people with type 1 diabetes (T1D). Using evidence-based research and consensus guidelines, we developed an exercise advisor app to reduce some of the burden associated with diabetes management during exercise. The app will guide the user on carbohydrate feeding strategies and insulin management strategies before, during, and after exercise and provide targeted and individualized recommendations. As a basis for the recommendations, the decision trees for the app use various factors including the type of insulin regimen, time of activity, previous insulin boluses, and current glucose level. The app is designed to meet the various needs of people with T1D for different activities to promote safe exercise practices.

Objective: This study used connected pen to determine missed bolus dose (MBD) frequency during masked and unmasked continuous glucose monitoring (CGM) periods and examined its link with time-in-range (TIR), time-above-range (TAR), time-below-range (TBR), and key participant characteristics in people with diabetes. Methods: This was a 12-week, single-arm, exploratory, two-period study for people with type 1 diabetes (T1D) or type 2 diabetes (T2D). The primary objective was to estimate the average number of MBD during masked and real-time CGM use. The secondary objective was to estimate the average percent TIR and its relationship to MBD. An exploratory objective was to investigate the participant characteristics that were associated with MBD. Data were analyzed for differences in MBD by diabetes type and other participant characteristics, by CGM period, and by hypoglycemic fear scores. Results: Participants ( n  = 64; T1D, n  = 38; T2D, n  = 26) were 48 ± 11.9 years old and 44% were female. From the masked to the unmasked period, MBD, %TAR, %TBR, and glycated hemoglobin decreased significantly (0.74 MBD/day to 0.62 MBD/day, P  = 0.008; 53.6%-48.1%, P  = 0.004; 4.49%-2.93%, P  < 0.001; mean 8.8%-8.4%, P  < 0.001, respectively), while %TIR increased significantly (41.9%-49.0%, P  < 0.001). MBD/day was negatively associated with TIR ( P  = 0.016) and positively associated with TAR ( P  = 0.015) for T1D and positively associated with TBR ( P  = 0.024) for T2D in the masked period only. MBD was significantly associated with fear of hypoglycemia for T2D, but not T1D. Conclusions: MBD is associated with reduced TIR when CGM is masked and tailored therapeutic approaches are needed for T1D and T2D populations.

Current guidelines recommend 15-20 g of carbohydrate (CHO) for treatment of mild to moderate hypoglycemia. However, these guidelines do not account for reduced insulin during suspensions with predictive low-glucose suspend (PLGS). We assessed insulin suspensions, hypoglycemic events, and CHO treatment during a 20-h inpatient evaluation of an investigational system with a PLGS feature, including an overnight basal up-titration period to activate the PLGS. Among 10 adults with type 1 diabetes, there were 59 suspensions; 7 suspensions were associated with rescue CHO and 5 with hypoglycemia. Rescue treatment consisted of median 9 g CHO (range: 5-16 g), with no events requiring repeat CHO. No rescue CHO were given during or after insulin suspension for the overnight basal up-titration. To minimize rebound hyperglycemia and needless calorie intake from hypoglycemia overtreatment, updated guidance for PLGS systems should reflect possible need to reduce CHO amounts for hypoglycemia rescue associated with an insulin suspension. The clinical trial was registered with ClinicalTrials.gov (NCT03890003).

The advent of connected insulin pens will generate an avalanche of digital insulin data, especially in the context of prandial- and multiple daily injection-insulin regimens. There is a need for the diabetes community to develop standards for such data, analogous to what has been achieved using the ambulatory glucose profile and associated metrics for glucose, permitting harmonization of data reporting for multiple devices and facilitating integration of glucose, insulin, food intake, and physical activity data. Several studies have estimated the timing of meals by analyses of glucose excursions but using diverse criteria. There is need for uniform criteria for multiple types of insulin boluses, including premeal, perimeal, delayed, missed, and correction boluses to facilitate research studies and patient care. This article contains a first preliminary proposal for standards regarding reporting of insulin dosing data. Clinical usage of these reports will require sensitive communication between health care providers and patients.

Background: Automated insulin delivery (AID) systems have demonstrated improvements in time-in-range (TIR, blood glucose 70-180 mg/dL) without increasing hypoglycemia. Testing a closed-loop system in an inpatient environment with supervised challenges allows for initial evaluation of performance and safety of the system. Methods: Adults with type 1 diabetes (T1D) were enrolled into two similar studies ( n  = 10 per study), with 3-day inpatient analysis periods. Participants tested a Lilly hybrid closed-loop (HCL) system comprising an investigational insulin pump, insulin lispro, a pump-embedded model predictive control algorithm, a continuous glucose monitor (CGM), and an external dedicated controller. Each protocol included meal-related and exercise challenges to simulate real-world diabetes self-management errors. Only study staff interacted with the HCL system. Performance was assessed using standard CGM metrics overall and within prespecified periods. Results: Participants (25% male) had mean ± standard deviation (SD) age 44.7 ± 14.2 years, T1D duration 30.2 ± 11.1 years, A1C 7.2% ± 0.8%, and insulin usage 0.53 ± 0.21 U/(kg·day). Percentage TIR 70-180 mg/dL (mean ± SD) was 81.2 ± 8.4 overall, 85.2 ± 8.1 outside of challenge periods, 97.3 ± 5.3 during the nocturnal periods, and 74.5 ± 16.2 for the postprandial periods. During challenge periods, percentage TIR for the overbolus challenge was 65.4 ± 29.2 and that for the delayed bolus challenge was 57.1 ± 25.1. No adverse events (AEs), serious AEs, or unanticipated adverse device events occurred while participants were using the HCL system. Conclusions: In participants with T1D, Lilly AID system demonstrated expected algorithm performance and safety with satisfactory glycemic outcomes overall and in response to simulated diabetes management challenges. Additional studies in less supervised conditions and with broader patient populations are warranted. ClinicalTrials.gov Registration number NCT03743285, NCT03849612.

This study examined whether daily stressors and continuously monitored glucose levels and glucose variability predict daily diabetes symptoms. Fifty Latinos with type 2 diabetes were randomized to either diabetes education (DE-only; N = 23) or DE plus stress management and relaxation training (DE + SMR; N = 32). After treatment, for 7 days they wore 'blinded' continuous glucose monitors and reported common stressors and diabetes symptoms twice daily. Between individuals, participants with more numerous overall stressors and more time in hyperglycemia reported higher symptoms. Within individuals, symptoms were higher during intervals of greater than usual stressors. Yet, diabetes symptoms did not covary with changes in glucose levels or glucose variability. The within-person stressor-symptom association was stronger among older individuals and non-significant for participants in DE + SMR condition. Diabetes symptoms were associated with recent stressor exposure, but not recent glucose level or changes in glucose. CLINICAL TRIAL NUMBER: ClinicalTrials.gov Identifier (No. NCT01578096).

Background: Adults with type 1 diabetes (PWDs) face challenging self-management regimens including monitoring their glucose values multiple times a day to assist with achieving glycemic targets and reduce the risk of long-term diabetes complications. Recent advances in diabetes technology have reportedly improved glycemia, but little is known about how PWDs utilize mobile technology to make positive changes in their diabetes self-management., Objective: The aim of this qualitative study was to explore PWDs' experiences using Sugar Sleuth, a glucose sensor-based mobile app and Web-based reporting system, integrated with the FreeStyle Libre glucose monitor that provides feedback about glycemic variability., Methods: We used a qualitative descriptive research design and conducted semistructured interviews with 10 PWDs (baseline mean glycated hemoglobin, HbA 1c ) 8.0%, (SD 0.45); 6 males and 4 females, aged 52 years (SD 15), type 1 diabetes (T1D) duration 31 years (SD 13), 40% (4/10, insulin pump) following a 14-week intervention during which they received clinical support and used Sugar Sleuth to evaluate and understand their glucose data. Audio-recorded interviews were transcribed, coded, and analyzed using thematic analysis and NVivo 11 (QSR International Pty Ltd)., Results: A total of 4 main themes emerged from the data. Participants perceived Sugar Sleuth as an Empowering Tool that served to inform lifestyle choices and diabetes self-management tasks, promoted preemptive self-care actions, and improved discussions with clinicians. They also described Sugar Sleuth as providing a Source of Psychosocial Support and offering relief from worry, reducing glycemic uncertainty, and supporting positive feelings about everyday life with diabetes. Participants varied in their Approaches to Glycemic Data: 40% (4/10) described using Sugar Sleuth to review data, understand glycemic cause and effect, and plan for future self-care. On the contrary, 60% (6/10) were reluctant to review past data; they described receiving benefits from the immediate numbers and trend arrows, but the app still prompted them to enter in the suspected causes of glucose excursions within hours of their occurrence. Finally, only 2 participants voiced Concerns About Use of Sugar Sleuth; they perceived the app as sometimes too demanding of information or as not attuned to the socioeconomic backgrounds of PWDs from diverse populations., Conclusions: Results suggest that Sugar Sleuth can be an effective educational tool to enhance both patient-clinician collaboration and diabetes self-management. Findings also highlight the importance of exploring psychosocial and socioeconomic factors that may advance the understanding of PWDs' individual differences when using glycemic technology and may promote the development of customized mobile tools to improve diabetes self-management., (©Marilyn D Ritholz, Owen Henn, Astrid Atakov Castillo, Howard Wolpert, Stephanie Edwards, Lawrence Fisher, Elena Toschi. Originally published in JMIR Diabetes (http://diabetes.jmir.org), 08.07.2019.)

Background: The goal of this uncontrolled pilot study was to assess the feasibility of a self-care management mobile app, called Sugar Sleuth, which incorporates the FreeStyle Libre™ glucose sensor, to help clinicians and people with type 1 diabetes (PWD) identify and mitigate self-care behaviors that contribute to glucose variability., Methods: PWDs with a baseline A1c between 7.5 and 9.0% used the mobile app for 14 weeks. The app prompted the PWD to enter the suspected cause of detected glycemic excursions, and to record food and insulin information. PWDs met with clinicians to collaboratively review data, identify challenges, and devise a specific self-care plan. Outcome measures included a single glycemic outcome score (SGOS) and attitude rating scales to better understand how participant attitudes could affect glycemic outcome., Results: Thirty enrolled PWDs had a mean age of 55 ± 2.6 years, and a mean diabetes duration of 32 ± 2.9 years. A significant average reduction in A1c of 0.5 ± 0.07% ( P < .01) and in mean daily carbohydrate intake of 43 ± 21 grams ( P = .05) was found. No statistically significant change in glycemic metrics, body weight, or total daily insulin dose was found. A significant negative association occurred between SGOS and "hypoglycemia tolerance" ( P = .04), and a positive correlation occurred that approached significance with "motivation to change behavior" ( P = .06)., Conclusions: These findings suggest that this mobile app system, in conjunction with CGM, provides a useful platform for helping clinicians and adults with T1D improve self-management skills to improve glycemic control.

Objective: Patients with type 1 diabetes who do aerobic exercise often experience a drop in blood glucose concentration that can result in hypoglycemia. Current approaches to prevent exercise-induced hypoglycemia include reduction in insulin dose or ingestion of carbohydrates, but these strategies may still result in hypoglycemia or hyperglycemia. We sought to determine whether mini-dose glucagon (MDG) given subcutaneously before exercise could prevent subsequent glucose lowering and to compare the glycemic response to current approaches for mitigating exercise-associated hypoglycemia., Research Design and Methods: We conducted a four-session, randomized crossover trial involving 15 adults with type 1 diabetes treated with continuous subcutaneous insulin infusion who exercised fasting in the morning at ∼55% VO 2max for 45 min under conditions of no intervention (control), 50% basal insulin reduction, 40-g oral glucose tablets, or 150-μg subcutaneous glucagon (MDG)., Results: During exercise and early recovery from exercise, plasma glucose increased slightly with MDG compared with a decrease with control and insulin reduction and a greater increase with glucose tablets ( P < 0.001). Insulin levels were not different among sessions, whereas glucagon increased with MDG administration ( P < 0.001). Hypoglycemia (plasma glucose <70 mg/dL) was experienced by six subjects during control, five subjects during insulin reduction, and none with glucose tablets or MDG; five subjects experienced hyperglycemia (plasma glucose ≥250 mg/dL) with glucose tablets and one with MDG., Conclusions: MDG may be more effective than insulin reduction for preventing exercise-induced hypoglycemia and may result in less postintervention hyperglycemia than ingestion of carbohydrate., (© 2018 by the American Diabetes Association.)

Introduction: The application of digital monitoring biomarkers in health, wellness and disease management is reviewed. Harnessing the near limitless capacity of these approaches in the managed healthcare continuum will benefit from a systems-based architecture which presents data quality, quantity, and ease of capture within a decision-making dashboard., Methods: A framework was developed which stratifies key components and advances the concept of contextualized biomarkers. The framework codifies how direct, indirect, composite, and contextualized composite data can drive innovation for the application of digital biomarkers in healthcare., Results: The de novo framework implies consideration of physiological, behavioral, and environmental factors in the context of biomarker capture and analysis. Application in disease and wellness is highlighted, and incorporation in clinical feedback loops and closed-loop systems is illustrated., Conclusions: The study of contextualized biomarkers has the potential to offer rich and insightful data for clinical decision making. Moreover, advancement of the field will benefit from innovation at the intersection of medicine, engineering, and science. Technological developments in this dynamic field will thus fuel its logical evolution guided by inputs from patients, physicians, healthcare providers, end-payors, actuarists, medical device manufacturers, and drug companies.

Objective: This study investigated between- and within-person associations among mean levels and variability in affect, diabetes self-care behaviors, and continuously monitored glucose in Latinos with type 2 diabetes., Methods: Fifty participants (M [SD] age = 57.8 [11.7] years, 74% women, mean [SD] glycosylated hemoglobin A1c = 8.3% [1.5%]) wore a "blinded" continuous glucose monitor for 7 days, and they responded to twice daily automated phone surveys regarding positive affect, negative affect, and self-care behaviors., Results: Higher mean levels of NA were associated with higher mean glucose (r = .30), greater percent hyperglycemia (r = .34) and greater percentage of out-of-range glucose (r = .34). Higher NA variability was also related to higher mean glucose (r = .34), greater percent of hyperglycemia (r = .44) and greater percentage of out-of-range glucose (r = .43). Higher positive affect variability was related to lower percentage of hypoglycemia (r = -.33). Higher mean levels of self-care behaviors were related to lower glucose variability (r = -.35). Finally, higher self-care behavior variability was related to greater percentage of hyperglycemia (r = .31) and greater percentage of out-of-range glucose (r = -.28). In multilevel regression models, within-person increases from mean levels of self-care were associated with lower mean levels of glucose (b = -7.4, 95% confidence interval [CI] = -12.8 to -1.9), lower percentage of hyperglycemia (b = -0.04, 95% CI = -0.07 to -0.01), and higher percentage of hypoglycemia (b = 0.02, 95% CI = 0.01 to 0.03) in the subsequent 10-hour period., Conclusions: Near-to-real time sampling documented associations of glucose with affect and diabetes self-care that are not detectable with traditional measures.

Context: Standard treatment of hypoglycemia is oral carbohydrate, but it often results in hyperglycemia and entails extra caloric intake., Objective: To evaluate low-dose glucagon to treat mild hypoglycemia in ambulatory adults with type 1 diabetes (T1D)., Design: Randomized crossover trial (two 3-week periods)., Setting: Five U.S. diabetes clinics., Patients: Twenty adults with T1D using an insulin pump and continuous glucose monitor (CGM) and experiencing frequent mild hypoglycemia., Intervention: Nonaqueous mini-dose glucagon (MDG) (150 µg) to treat nonsevere hypoglycemia., Main Outcome Measures: Successful treatment was defined as blood glucose (BG) ≥50 mg/dL 15 minutes and ≥70 mg/dL 30 minutes after intervention, on the study meter. Two authors, blinded to treatment arm, independently judged each event as a clinical success or failure., Results: Sixteen participants (mean age 39 years, 75% female, mean diabetes duration 23 years, mean hemoglobin A1c 7.2%) had 118 analyzable events with initial BG of 50 to 69 mg/dL. Successful treatment criteria were met for 58 (94%) of 62 events during the MDG period and 53 (95%) of 56 events during the glucose tablets (TABS) period (adjusted P = 0.99). Clinical assessments of success for these events were 97% and 96%, respectively. CGM-measured time in range did not differ between treatment groups during the 2 hours after events, but TABS resulted in higher maximum glucose (116 vs 102 mg/dL; P = 0.01) over the first hour., Conclusions: Low-dose glucagon can successfully treat mild hypoglycemia and may be a useful alternative to treatment with oral carbohydrate when trying to avoid unnecessary caloric intake., (Copyright © 2017 Endocrine Society)

Importance: Previous clinical trials showing the benefit of continuous glucose monitoring (CGM) in the management of type 1 diabetes predominantly have included adults using insulin pumps, even though the majority of adults with type 1 diabetes administer insulin by injection., Objective: To determine the effectiveness of CGM in adults with type 1 diabetes treated with insulin injections., Design, Setting, and Participants: Randomized clinical trial conducted between October 2014 and May 2016 at 24 endocrinology practices in the United States that included 158 adults with type 1 diabetes who were using multiple daily insulin injections and had hemoglobin A1c (HbA1c) levels of 7.5% to 9.9%., Interventions: Random assignment 2:1 to CGM (n = 105) or usual care (control group; n = 53)., Main Outcomes and Measures: Primary outcome measure was the difference in change in central-laboratory-measured HbA1c level from baseline to 24 weeks. There were 18 secondary or exploratory end points, of which 15 are reported in this article, including duration of hypoglycemia at less than 70 mg/dL, measured with CGM for 7 days at 12 and 24 weeks., Results: Among the 158 randomized participants (mean age, 48 years [SD, 13]; 44% women; mean baseline HbA1c level, 8.6% [SD, 0.6%]; and median diabetes duration, 19 years [interquartile range, 10-31 years]), 155 (98%) completed the study. In the CGM group, 93% used CGM 6 d/wk or more in month 6. Mean HbA1c reduction from baseline was 1.1% at 12 weeks and 1.0% at 24 weeks in the CGM group and 0.5% and 0.4%, respectively, in the control group (repeated-measures model P < .001). At 24 weeks, the adjusted treatment-group difference in mean change in HbA1c level from baseline was -0.6% (95% CI, -0.8% to -0.3%; P < .001). Median duration of hypoglycemia at less than <70 mg/dL was 43 min/d (IQR, 27-69) in the CGM group vs 80 min/d (IQR, 36-111) in the control group (P = .002). Severe hypoglycemia events occurred in 2 participants in each group., Conclusions and Relevance: Among adults with type 1 diabetes who used multiple daily insulin injections, the use of CGM compared with usual care resulted in a greater decrease in HbA1c level during 24 weeks. Further research is needed to assess longer-term effectiveness, as well as clinical outcomes and adverse effects., Trial Registration: clinicaltrials.gov Identifier: NCT02282397.

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., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Objective: To formulate clinical practice guidelines for the use of continuous glucose monitoring and continuous subcutaneous insulin infusion in adults with diabetes., Participants: The participants include an Endocrine Society-appointed Task Force of seven experts, a methodologist, and a medical writer. The American Association for Clinical Chemistry, the American Association of Diabetes Educators, and the European Society of Endocrinology co-sponsored this guideline., Evidence: The Task Force developed this evidence-based guideline using the Grading of Recommendations, Assessment, Development, and Evaluation system to describe the strength of recommendations and the quality of evidence. The Task Force commissioned one systematic review and used the best available evidence from other published systematic reviews and individual studies., Consensus Process: One group meeting, several conference calls, and e-mail communications enabled consensus. Committees and members of the Endocrine Society, the American Association for Clinical Chemistry, the American Association of Diabetes Educators, and the European Society of Endocrinology reviewed and commented on preliminary drafts of these guidelines., Conclusions: Continuous subcutaneous insulin infusion and continuous glucose monitoring have an important role in the treatment of diabetes. Data from randomized controlled trials are limited on the use of medical devices, but existing studies support the use of diabetes technology for a wide variety of indications. This guideline presents a review of the literature and practice recommendations for appropriate device use.

Aims: Artificial pancreas systems show benefit in closely monitored at-home studies, but may not have sufficient power to assess safety during infrequent, but expected, system or user errors. The aim of this study was to assess the safety of an artificial pancreas system emulating the β-cell when the glucose value used for control is improperly calibrated and participants forget to administer pre-meal insulin boluses., Methods: Artificial pancreas control was performed in a clinic research centre on three separate occasions each lasting from 10 p.m. to 2 p.m. Sensor glucose values normally used for artificial pancreas control were replaced with scaled blood glucose values calculated to be 20% lower than, equal to or 33% higher than the true blood glucose. Safe control was defined as blood glucose between 3.9 and 8.3 mmol/l., Results: Artificial pancreas control resulted in fasting scaled blood glucose values not different from target (6.67 mmol/l) at any scaling factor. Meal control with scaled blood glucose 33% higher than blood glucose resulted in supplemental carbohydrate to prevent hypoglycaemia in four of six participants during breakfast, and one participant during the night. In all instances, scaled blood glucose reported blood glucose as safe., Conclusions: Outpatient trials evaluating artificial pancreas performance based on sensor glucose may not detect hypoglycaemia when sensor glucose reads higher than blood glucose. Because these errors are expected to occur, in-hospital artificial pancreas studies using supplemental carbohydrate in anticipation of hypoglycaemia, which allow safety to be assessed in a controlled non-significant environment should be considered as an alternative. Inpatient studies provide a definitive alternative to model-based computer simulations and can be conducted in parallel with closely monitored outpatient artificial pancreas studies used to assess benefit., (© 2015 The Authors. Diabetic Medicine published by John Wiley & Sons Ltd on behalf of Diabetes UK.)

Background: Traditionally, insulin bolus calculations for managing postprandial glucose levels in individuals with type 1 diabetes rely solely on the carbohydrate content of a meal. However, recent studies have reported that other macronutrients in a meal can alter the insulin required for good postprandial control. Specifically, studies have shown that high-fat (HF) meals require more insulin than low-fat (LF) meals with identical carbohydrate content. Our objective was to assess the mechanisms underlying the higher insulin requirement observed in one of these studies., Materials and Methods: We used a combination of previously validated metabolic models to fit data from a study comparing HF and LF dinners with identical carbohydrate content in seven subjects with type 1 diabetes. For each subject and dinner type, we estimated the model parameters representing the time of peak meal-glucose appearance (τ(m)), insulin sensitivity (S(I)), the net hepatic glucose balance, and the glucose effect at zero insulin in four time windows (dinner, early night, late night, and breakfast) and assessed the differences in model parameters via paired Wilcoxon signed-rank tests., Results: During the HF meal, the τ(m) was significantly delayed (mean and standard error [SE]: 102 [14] min vs. 71 [4] min; P = 0.02), and S(I) was significantly lower (7.25 × 10(-4) [1.29 × 10(-4)] mL/μU/min vs. 8.72 × 10(-4) [1.08 × 10(-4)] mL/μU/min; P = 0.02)., Conclusions: In addition to considering the putative delay in gastric emptying associated with HF meals, we suggest that clinicians reviewing patient records consider that the fat content of these meals may alter S(I).

Purpose: The purpose of this study was to explore perceptions that emerging adults with type 1 diabetes (T1D) have of their patient-provider relationships across the transition from pediatric to adult care., Methods: Twenty-six emerging adults with T1D (mean age 26.2 ± 2.5 years) participated in 5 focus groups stratified by current level of glycemic control (A1C). Coded audio-recorded data were analyzed using thematic analysis and aided by NVivo software., Results: Three major themes emerged from the analysis: (1) loss and gain in provider relationships across the transition-patients expressed 3 key responses to leaving pediatric providers that differed by A1C levels: sad reluctance and "natural progression" (mean A1C ± SD 7.4% ± 0.6%) and wanting to go (mean A1C ± SD 9.8% ± 1.0%); (2) partners in care versus on one's own-patients valued how adult providers' collaborative conversations promoted their involvement and accountability compared to "parent-centric" interactions with pediatric providers, but they also expressed ambivalence over increased independence in adult care; (3) improving provider approaches to transition-patients recommended that pediatric providers actively promote emerging adults' autonomy while maintaining parental support, communication with adult providers, and follow-up with transitioning patients., Conclusions: Findings highlight the importance of enhanced provider awareness of T1D emerging adults' complex feelings about the transition in care. Improved integration of individual- and family-centered approaches to developmentally tailored diabetes care is needed to augment patient and provider relationships.

Objective: Continuous glucose monitoring (CGM) systems collect and store glucose data in an ongoing fashion for several days at a time. The main advantage of CGM is that it can help identify fluctuations and trends that would otherwise go unnoticed with other glucose measures. Here, we provide a review of CGM for behavioral researchers., Methods: We begin with a brief review of diabetes and glucose measurement and then describe what CGM is and reference the commercial CGM systems currently available. We discuss the challenges involved in using CGM in behavioral research. We then present a broad overview of CGM in behavioral research, including data from ours and others' research programs. Finally, we cover some practical issues to be considered when using CGM, suggest reporting guidelines for the behavioral researcher, and offer suggestions for future research., Results: Only a handful of behavioral researchers are using CGM, although its use is increasing. The main ways that CGM is being used in behavioral research is to investigate basic biobehavioral processes, to assess the effects of behavioral interventions on diabetes control, and to use CGM itself as a behavior modification and teaching tool in diabetes self-management interventions., Conclusions: Continuous glucose monitoring holds promise to help behavioral researchers unravel the complex relationships among glucose and intrapersonal, interpersonal, and contextual factors. However, the uptake of CGM for this purpose is limited, and the possibilities for its use are largely unmet. We encourage behavioral researchers to implement CGM in their protocols and to do so in a way that maximizes its explanatory power.

Objective: The aim was to formulate practice guidelines for determining settings where patients are most likely to benefit from the use of continuous glucose monitoring (CGM)., Participants: The Endocrine Society appointed a Task Force of experts, a methodologist, and a medical writer., Evidence: This evidence-based guideline was developed using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) system to describe both the strength of recommendations and the quality of evidence., Consensus Process: One group meeting, several conference calls, and e-mail communications enabled consensus. Committees and members of The Endocrine Society, the Diabetes Technology Society, and the European Society of Endocrinology reviewed and commented on preliminary drafts of these guidelines., Conclusions: The Task Force evaluated three potential uses of CGM: 1) real-time CGM in adult hospital settings; 2) real-time CGM in children and adolescent outpatients; and 3) real-time CGM in adult outpatients. The Task Force used the best available data to develop evidence-based recommendations about where CGM can be beneficial in maintaining target levels of glycemia and limiting the risk of hypoglycemia. Both strength of recommendations and quality of evidence were accounted for in the guidelines.

Objective: To determine the individual persistence of the relationship between mean sensor glucose (MG) concentrations and hemoglobin A(1c) (A1C) from the Juvenile Diabetes Research Foundation Continuous Glucose Monitoring (CGM) Randomized Trial., Research Design and Methods: MG was calculated using CGM data for 3 months before A1C measurements at 3, 6, 9, and 12 months for the CGM group and at 9 and 12 months for the control group. An MG-to-A1C ratio was included in analysis for subjects who averaged ≥4 days/week of CGM use., Results: Spearman correlations of the MG-to-A1C ratio between consecutive visits 3 months apart ranged from 0.70 to 0.79. The correlations for children and youth were slightly smaller than those for adults. No meaningful differences were observed by device type or change in A1C., Conclusions: Individual variations in the rate of hemoglobin glycation are persistent and contribute to the inaccuracy in estimating MGs calculated from A1C levels.

Objective: Identify factors predictive of severe hypoglycemia (SH) and assess the clinical utility of continuous glucose monitoring (CGM) to warn of impending SH., Research Design and Methods: In a multicenter randomized clinical trial, 436 children and adults with type 1 diabetes were randomized to a treatment group that used CGM (N = 224), or a control group that used standard home blood glucose monitoring (N = 212) and completed 12 months of follow-up. After 6 months, the original control group initiated CGM while the treatment group continued use of CGM for 6 months. Baseline risk factors for SH were evaluated over 12 months of follow-up using proportional hazards regression. CGM-derived indices of hypoglycemia were used to predict episodes of SH over a 24-h time horizon., Results: The SH rate was 17.9 per 100 person-years, and a higher rate was associated with the occurrence of SH in the prior 6 months and female sex. SH frequency increased eightfold when 30% of CGM values were ≤ 70 mg/dL on the prior day (4.5 vs. 0.5%; P < 0.001), but the positive predictive value (PPV) was low (<5%). Results were similar for hypoglycemic area under the curve and the low blood glucose index calculated by CGM., Conclusions: SH in the 6 months prior to the study was the strongest predictor of SH during the study. CGM-measured hypoglycemia over a 24-h span is highly associated with SH the following day (P < 0.001), but the PPV is low.

Aims: To identify psychosocial factors associated with the use of continuous glucose monitoring by adults with Type 1 diabetes., Methods: Twenty adult patients (aged 45 +/- 15 years, diabetes duration 25 +/- 19 years, 50% female) followed at our site in the multi-centre Juvenile Diabetes Research Foundation continuous glucose monitoring trial were divided into three groups: Glycated haemoglobin (HbA(1c)) Responders who demonstrated an improvement in glycaemic control with continuous glucose monitoring (baseline HbA(1c)> or = 7.0%, HbA(1c) reduction greater than or equal to 0.5%), Hypoglycaemia Responders (baseline HbA(1c) < 7.0%) who demonstrated decreased time < 3.9 mmol/l while remaining within target HbA(1c), and HbA(1c) Non-Responders (baseline HbA(1c)> or = 7.0%, HbA(1c) reduction less than 0.5%). Subjects participated in semi-structured interviews focusing on their psychosocial experiences with continuous glucose monitoring., Results: Three major themes were identified that differentiated Responders (including both the HbA(1c) and Hypoglycaemia groups) from Non-Responders: (i) coping with frustrations-Responders used self-controlled rather than emotions-based coping when faced with continuous glucose monitoring frustrations; (ii) use of information-Responders used retrospective pattern analysis, not just minute-by-minute data analysis, in glycaemic management; (iii) 'significant other'/spousal involvement-Responders endorsed interest, encouragement and participation by their loved ones. Both Responders and Non-Responders expressed body image concerns when wearing continuous glucose monitoring devices., Conclusions: This qualitative study points to the importance of coping skills, retrospective review of data, and 'significant other' involvement in the effective use of continuous glucose monitoring. These findings will inform clinical initiatives to improve patient selection and training in the use of this new technology and have served as the basis for development of quantitative surveys to be used in clinical practice.

In recent years continuous subcutaneous insulin infusion pumps have become widely adopted in many parts of the world in the treatment of type 1 diabetes in adults. A comprehensive summary of all aspects of pump therapy is beyond the scope of this article, and in this review we will focus on several practical issues that in our experience are of clinical importance in the care of patients using insulin pumps. These include: benefits and risks of pump therapy, including the use of pumps to limit hypoglycemia; individual patient considerations in choosing between pump therapy and multiple daily injections; common pump-specific etiologies of erratic glucose control, including routine clinical practices that can assist with the detection of these problems; and the use of different pump bolus types for prandial insulin coverage.

Objective: To evaluate long-term effects of continuous glucose monitoring (CGM) in intensively treated adults with type 1 diabetes., Research Design and Methods: We studied 83 of 86 individuals >or=25 years of age with type 1 diabetes who used CGM as part of a 6-month randomized clinical trial in a subsequent 6-month extension study. RESULTS After 12 months, median CGM use was 6.8 days per week. Mean change in A1C level from baseline to 12 months was -0.4 +/- 0.6% (P < 0.001) in subjects with baseline A1C >or=7.0%. A1C remained stable at 6.4% in those with baseline A1C <7.0%. The incidence rate of severe hypoglycemia was 21.8 and 7.1 events per 100 person-years in the first and last 6 months, respectively. Time per day with glucose levels in the range of 71-180 mg/dl increased significantly (P = 0.02) from baseline to 12 months., Conclusions: In intensively treated adults with type 1 diabetes, CGM use and benefit can be sustained for 12 months.

Objective: To evaluate factors associated with successful use of continuous glucose monitoring (CGM) among participants with intensively treated type 1 diabetes in the Juvenile Diabetes Research Foundation Continuous Glucose Monitoring Randomized Clinical Trial., Research Design and Methods: The 232 participants randomly assigned to the CGM group (165 with baseline A1C >or=7.0% and 67 with A1C <7.0%) were asked to use CGM on a daily basis. The associations of baseline factors and early CGM use with CGM use >or=6 days/week in the 6th month and with change in A1C from baseline to 6 months were evaluated in regression models., Results: The only baseline factors found to be associated with greater CGM use in month 6 were age >or=25 years (P < 0.001) and more frequent self-reported prestudy blood glucose meter measurements per day (P < 0.001). CGM use and the percentage of CGM glucose values between 71 and 180 mg/dl during the 1st month were predictive of CGM use in month 6 (P < 0.001 and P = 0.002, respectively). More frequent CGM use was associated with a greater reduction in A1C from baseline to 6 months (P < 0.001), a finding present in all age-groups., Conclusions: After 6 months, near-daily CGM use is more frequent in intensively treated adults with type 1 diabetes than in children and adolescents, although in all age-groups near-daily CGM use is associated with a similar reduction in A1C. Frequency of blood glucose meter monitoring and initial CGM use may help predict the likelihood of long-term CGM benefit in intensively treated patients with type 1 diabetes of all ages.

OBJECTIVE The potential benefits of continuous glucose monitoring (CGM) in the management of adults and children with well-controlled type 1 diabetes have not been examined. RESEARCH DESIGN AND METHODS A total of 129 adults and children with intensively treated type 1 diabetes (age range 8-69 years) and A1C <7.0% were randomly assigned to either continuous or standard glucose monitoring for 26 weeks. The main study outcomes were time with glucose level < or =70 mg/dl, A1C level, and severe hypoglycemic events. RESULTS At 26 weeks, biochemical hypoglycemia (< or =70 mg/dl) was less frequent in the CGM group than in the control group (median 54 vs. 91 min/day), but the difference was not statistically significant (P = 0.16). Median time with a glucose level < or =60 mg/dl was 18 versus 35 min/day, respectively (P = 0.05). Time out of range (< or =70 or >180 mg/dl) was significantly lower in the CGM group than in the control group (377 vs. 491 min/day, P = 0.003). There was a significant treatment group difference favoring the CGM group in mean A1C at 26 weeks adjusted for baseline (P < 0.001). One or more severe hypoglycemic events occurred in 10 and 11% of the two groups, respectively (P = 1.0). Four outcome measures combining A1C and hypoglycemia data favored the CGM group in comparison with the control group (P < 0.001, 0.007, 0.005, and 0.003). CONCLUSIONS Most outcomes, including those combining A1C and hypoglycemia, favored the CGM group. The weight of evidence suggests that CGM is beneficial for individuals with type 1 diabetes who have already achieved excellent control with A1C <7.0%.

Background: The value of continuous glucose monitoring in the management of type 1 diabetes mellitus has not been determined., Methods: In a multicenter clinical trial, we randomly assigned 322 adults and children who were already receiving intensive therapy for type 1 diabetes to a group with continuous glucose monitoring or to a control group performing home monitoring with a blood glucose meter. All the patients were stratified into three groups according to age and had a glycated hemoglobin level of 7.0 to 10.0%. The primary outcome was the change in the glycated hemoglobin level at 26 weeks., Results: The changes in glycated hemoglobin levels in the two study groups varied markedly according to age group (P=0.003), with a significant difference among patients 25 years of age or older that favored the continuous-monitoring group (mean difference in change, -0.53%; 95% confidence interval [CI], -0.71 to -0.35; P<0.001). The between-group difference was not significant among those who were 15 to 24 years of age (mean difference, 0.08; 95% CI, -0.17 to 0.33; P=0.52) or among those who were 8 to 14 years of age (mean difference, -0.13; 95% CI, -0.38 to 0.11; P=0.29). Secondary glycated hemoglobin outcomes were better in the continuous-monitoring group than in the control group among the oldest and youngest patients but not among those who were 15 to 24 years of age. The use of continuous glucose monitoring averaged 6.0 or more days per week for 83% of patients 25 years of age or older, 30% of those 15 to 24 years of age, and 50% of those 8 to 14 years of age. The rate of severe hypoglycemia was low and did not differ between the two study groups; however, the trial was not powered to detect such a difference., Conclusions: Continuous glucose monitoring can be associated with improved glycemic control in adults with type 1 diabetes. Further work is needed to identify barriers to effectiveness of continuous monitoring in children and adolescents. (ClinicalTrials.gov number, NCT00406133.), (2008 Massachusetts Medical Society)

Continuous glucose monitoring (CGM) is an evolving technology poised to redefine current concepts of glycemic control and optimal diabetes management. To date, there are few randomized studies examining how to most effectively use this new tool. Therefore, a group of eight diabetes specialists heard presentations on continuous glucose sensor technology and then discussed their experience with CGM in order to identify fundamental considerations, objectives, and methods for applying this technology in clinical practice. The group concluded that routine use of CGM, with real-time data showing the rate and direction of glucose change, could revolutionize current approaches to evaluating and managing glycemia. The need for such progress is indicated by the growing prevalence of inadequately treated hyperglycemia. Coordinating financial and educational resources and developing clear protocols for using glucose sensor technology are urgent priorities in promoting wide adoption of CGM by patients and health care providers. Finally, researchers, manufacturers, payers, and advocacy groups must join forces on the policy level to create an environment conducive to managing continuous data, measuring outcomes, and formalizing best practices.

Real-time continuous glucose monitoring (RT-CGM) devices provide detailed information on glucose patterns and trends, and alarms that alert the patient to both hyper- and hypoglycemia. This technology can dramatically improve the day-to-day management of patients with diabetes and promises to be a major advance in diabetes care. The safe and effective use of RT-CGM in diabetes management rests on an understanding of several physiological as well as technological issues. This article outlines the key issues that should be addressed in the training curriculum for patients starting on RT-CGM: (1) physiologic lag between interstitial and blood glucose levels and the implications for device calibration, and interpretation and use of data in diabetes management; (2) practical considerations with the use of sensor alarms and caveats in the setting of alarm thresholds; and (3) potential risk for hypoglycemia related to excessive postprandial bolusing by RT-CGM users, and the practical implications for patient training.

Objective: The purpose of this study was to identify psychosocial issues related to diabetes, approaches to self-care, self-perceptions, and social interactions among insulin pump users with type 1 diabetes., Research Design and Methods: Adult insulin pump users participated in focus groups loosely formed on the basis of A1C level. Transcripts of focus group meetings were coded into themes by five reviewers using NVivo2 qualitative software., Results: Thirty adults with long-term diabetes participated in five focus groups: two with low mean +/-SD A1C (6.8 +/- 0.4%), one with mid A1C (7.80 +/- 0.3%), and two with high A1C (9.1 +/- 0.5%). Three major themes were identified: impact on diabetes self-care, emotional reactions to the insulin pump, body image, and social acceptance. Participants who described the pump as a tool to meet glycemic goals also described a more active approach to diabetes and had better glycemic control; those who discussed the pump as a panacea described more passive self-care and had poorer glycemic control. Low A1C groups reported that starting the insulin pump reminded them of feelings they experienced at their initial diabetes diagnosis, whereas the high A1C groups did not report these feelings. Women were more concerned than men about body image and social acceptance with pump use., Conclusions: Active participation in self-care, realistic expectations of pump use, and emotional recall of diabetes diagnosis were associated with better glycemic control. Interventions to improve diabetes management with pump use should include evaluation and discussion of active versus passive approaches to self-care, recall of diabetes diagnosis, expectations of the pump, and pump-related self-consciousness and body image concerns. The roles of these factors in optimal diabetes management warrant further investigation.

Past cross-sectional studies have suggested that young adults with insulin-dependent (Type 1) diabetes mellitus (IDDM) may experience problems in their close peer relationships. For 10 years, we have followed an onset cohort of children and adolescents with IDDM (n = 57) and an age-matched group who were originally recruited after an acute illness, accident, or injury (n = 54). Now aged 19-26 years, these two groups were compared in terms of their friendship patterns, dating and love experiences, and sense of loneliness. All subjects in both groups had at least one friend. However, the IDDM group reported fewer friendships overall. The difference was accounted for by the number of less intimate friends. The two groups had similar frequencies of current romantic partners (IDDM = 63%; comparison group = 64%). While dating attitude and dating assertiveness did not differ between groups, some differences were found in terms of experiences of a primary love relationship. IDDM patients experienced less trust and sense of intimate friendship in these love relationships. No differences in loneliness were found. The preponderance of our findings indicate that the two groups had similar patterns and experiences of close peer relationships. Thus, the study does not suggest that IDDM leads to serious problems in forming social relationships for these patients during the transition to young adulthood. On the other hand, the IDDM patients' lower level of trust and intimacy within love relationships are consistent with other findings from this study suggesting specific areas of lowered self-worth that appear in social relationships.