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Z.R. is a 20-year-old White man with no prior relevant medical or surgical history. He presented to his pediatrician’s office in April 2020 with a 1-month history of thirst and polyuria and an unintentional weight loss of 25 lb. His weight was 167 lb, and he was 6 feet tall. He was not in distress, dehydrated, or hyperventilating. His vital signs and physical examination were normal, but point-of-care glucose levels were in the 300-mg/dL range, with urine positive for glucose and ketones. Z.R. is a college student majoring in sports medicine. He reports not smoking tobacco or drinking alcohol. At the time of his clinic visit, he was home from college and staying with parents during the coronavirus disease 2019 (COVID-19) pandemic lockdown. He had no family history of diabetes or autoimmune diseases. He is of Ashkenazi Jewish descent. The pediatrician contacted the endocrine service at 5:00 p.m. on a Thursday night. The pediatrician and endocrinologist mutually agreed that it would be in the best interests of the patient to avoid both an emergency department visit and a hospital stay. The COVID-19 outbreak was straining hospital resources and posing a potential nosocomial infection risk. Furthermore, telehealth resources were in place to safely and effectively manage Z.R.’s needs remotely. The endocrinologist contacted Z.R. and his parents and conducted an initial telehealth consultation by telephone that evening. The family was informed of the likely diagnosis of type 1 diabetes and agreed to initiate glucose monitoring and insulin administration that evening and that Z.R. would undergo laboratory testing the next morning. The value of blood glucose monitoring and continuous glucose monitoring (CGM) was discussed along with the requirement for insulin therapy. The endocrinologist also reviewed how to recognize and treat hypoglycemia, the basic nutrition principles of matching insulin to carbohydrates, and the potential …

OBJECTIVE To explore the effect of discontinuing continuous glucose monitoring (CGM) after 8 months of CGM use in adults with type 2 diabetes treated with basal without bolus insulin. RESEARCH DESIGN AND METHODS This multicenter trial had an initial randomization to either real-time CGM or blood glucose monitoring (BGM) for 8 months followed by 6 months in which the BGM group continued to use BGM (n = 57) and the CGM group was randomly reassigned either to continue CGM (n = 53) or discontinue CGM with resumption of BGM for glucose monitoring (n = 53). RESULTS In the group that discontinued CGM, mean time in range (TIR) 70–180 mg/dL, which improved from 38% before initiating CGM to 62% after 8 months of CGM, decreased after discontinuing CGM to 50% at 14 months (mean change from 8 to 14 months −12% [95% CI −21% to −3%], P = 0.01). In the group that continued CGM use, little change was found in TIR from 8 to 14 months (baseline 44%, 8 months 56%, 14 months 57%, mean change from 8 to 14 months 1% [95% CI −11% to 12%], P = 0.89). Comparing the two groups at 14 months, the adjusted treatment group difference in mean TIR was −6% (95% CI −16% to 4%, P = 0.20). CONCLUSIONS In adults with type 2 diabetes treated with basal insulin who had been using real-time CGM for 8 months, discontinuing CGM resulted in a loss of about one-half of the initial gain in TIR that had been achieved during CGM use.

Adolescents with type 1 diabetes are vulnerable to suboptimal glycemic control, generally due to insufficient self-care behaviors (1,2). Because they have some of the highest rates of mobile communication technology use (3), this modality may hold promise for providing reminders or encouragement to adolescents to engage in self-care. However, the effects of text messaging interventions on self-care and glycemic outcomes are mixed, with some reports favoring improvements in teen self-care behaviors such blood glucose monitoring frequency or medication adherence (4–7). In an alternative attempt to reach this high-risk age-group, researchers have explored the use of financial incentives to promote self-care behaviors, which yielded some glycemic benefit in the short term (8,9). However, there is limited research on the combination of a financial incentive and a mobile health intervention (10,11) and the potential benefits that could accrue from blending these approaches. Nonetheless, use of either a unimodal or a bimodal intervention requires that adolescent recipients remain engaged with the program. In this report, we describe adolescent engagement during a 6-month study of a psychoeducational text messaging intervention that incorporated financial incentives. The primary study included adolescents with type 1 diabetes in suboptimal control and showed a potential increase in self-reported self-care in those receiving the intervention as intended (10). This analysis of the primary study’s intervention group described patterns of adolescent engagement with the intervention and identified factors associated with responsiveness. We also evaluated the potential impact of engagement on glycemic outcomes and self-care. This study analyzed 6 months of data from teenagers with type 1 diabetes receiving an incentivized text messaging intervention aimed at increasing education and support for diabetes self-care. Youths were eligible for inclusion if they were 12–18 years of age, had a duration of type 1 diabetes of …

OBJECTIVE To explore associations between reductions in diabetes distress (DD) and improvements in glycemic outcomes among adults with type 1 diabetes (T1D) in the context of a DD randomized clinical trial. RESEARCH DESIGN AND METHODS Adults with T1D (N = 301) participated in a two-arm trial aimed at reducing DD (DD-focused OnTrack group vs. education-oriented KnowIt group). Mean age was 45.1 years; mean baseline HbA1c was 8.8% (73 mmol/mol). Individuals were assessed at baseline and 9 months later on DD, self-care, HbA1c, and frequency of hypoglycemia. Structural equation models evaluated hypothesized pathways among changes in DD, self-care, and glycemic outcomes in the total sample and by intervention group. RESULTS Reductions in DD were significantly and independently associated with better self-care, including fewer missed insulin boluses, more frequent insulin adjustment, improved problem-solving skills, more blood glucose monitoring, and greater adoption of continuous glucose monitoring (all P < 0.05). In turn, better self-care was linked with better glycemic outcomes, including fewer episodes of hypoglycemia and improved HbA1c over time. Fit indices indicated good fit of the model to the data (confirmatory fit index = 0.94, root mean square error of approximation = 0.05), with stronger and more meaningful associations for OnTrack than for KnowIt. CONCLUSIONS In the context of an intervention to reduce DD for adults with T1D, results indicate that reductions in DD do not affect glycemic outcomes directly but through improvements in self-care behavior. Findings support the importance of integrating disease management with DD interventions to maximize improvements in glycemic outcomes.

Comprehensive care of diabetes requires satisfactory stewardship of an underutilized prescription in diabetes management: the prescription for structured blood glucose monitoring (BGM). Structured BGM is a recommended schedule of actionable blood glucose measurements taken at specific times with the intent of using the data for individualized patient education and therapeutic intervention. The utility of different BGM protocols is logically dictated by a patient’s therapeutic regimen. This article reviews the prescription for structured BGM in the setting of intensive insulin, nonintensive basal insulin, and noninsulin treatment regimens. Evidence-based prescriptions of structured 5- to 7-point BGM profiles in diabetes provide essential information for productive clinician- and patient-directed therapeutic interventions. The effective implementation of structured BGM aids clinicians in achieving the desired goal of A1C reduction while bolstering patient education and empowering self-management.

The proliferation of smartphones over the past decade has led to the development of a seemingly endless number of digital applications (apps) designed to improve users’ health and fitness. This article addresses the regulation of these apps and provides details about the apps most commonly used by patients in the primary care and diabetes settings. Those described in detail include the American Diabetes Association’s Standards of Care app, apps for blood glucose monitoring and tracking and continuous glucose monitoring, lifestyle apps, a glucagon use app, prescription cost-saving apps, and apps for do-it-yourself automated insulin delivery.

The introduction of home blood glucose monitoring (BGM) 40 years ago revolutionized diabetes self-management, providing valuable glucose data that have helped many people with diabetes (PWD) improve their glycemic management. In the early 2000s, personal continuous glucose monitoring (CGM) systems also became available, raising questions regarding the future role of BGM. However, for some PWD, particularly many with type 2 diabetes who do not take medications associated with increased hypoglycemia risk, BGM remains more easily accessible and more affordable than CGM and can adequately meet their needs. In addition, PWD who use CGM still need to periodically use BGM. This publication reviews key issues related to the optimal and most cost-effective use of BGM. The authors address the accuracy of modern glucose meters and the recommended frequency of monitoring for people with different types of diabetes and therapeutic regimens. They suggest strategies for using glycemic data to inform therapy adjustments, as well as ways to overcome common barriers to BGM use. They then review the use of BGM in patients who also use CGM and describe the latest related technological innovations, including Cloud-based data management, mobile applications, insulin calculators, and remote and automated counseling systems. The authors conclude that BGM remains an important tool in diabetes management, even as diabetes management technologies continue to evolve.

BACKGROUND | Young adulthood is a vulnerable developmental period associated with increased risk for suboptimal health outcomes in youth with type 1 diabetes. Psychosocial factors have been associated with self-management and glycemic control in younger populations, but the extent to which these associations exist among young adults is poorly understood. This study aimed to examine the psychosocial functioning of young adults with type 1 diabetes and associated clinical outcomes. METHODS | Participants included young adults (n = 44) between the ages of 18 and 23 years in a pediatric setting who were preparing to transition to adult care. All participants completed self-report measures of psychosocial functioning at baseline as part of this longitudinal observational study. Outcome data included glycemic control, frequency of blood glucose monitoring, and self-management ratings at baseline and 1-year follow-up. RESULTS | Young adults with type 1 diabetes reported higher levels of depressive symptoms, lower self-efficacy, and more risk behaviors compared with previously published scores for adolescents. Young adults also reported greater resilience and transition readiness than their younger counterparts. Psychosocial variables were differentially related to glycemic control and frequency of blood glucose monitoring both cross-sectionally and longitudinally. CONCLUSION | This study provides key information about the psychosocial functioning of young adults with type 1 diabetes. It identifies relevant psychosocial factors that are associated with meaningful health outcomes during the transition preparation period. These findings may inform the development of clinical programs aimed at promoting transition preparation and health outcomes in young adults with type 1 diabetes.

Physical activity is an important element of type 1 diabetes management, and hypoglycemia is a known risk. There are few data on strategies adolescents use to mitigate this risk. We surveyed 66 adolescents with type 1 diabetes who were 12–18 years of age about blood glucose monitoring, carbohydrate intake, and insulin management before, during, and after exercise. The adolescents completed the International Physical Activity Questionnaire–Short Form and the Children’s Hypoglycemia Fear Survey. We found that adolescents with type 1 diabetes do not generally follow guidelines about glucose monitoring or about food and insulin adjustment around exercise. More targeted education and interventions are needed to improve adolescents’ uptake of recommended behaviors and improve outcomes.

Continuous glucose monitoring (CGM) technology has brought about a paradigm shift in defining glycemic control in diabetes management and research. A1C and blood glucose monitoring have been widely accepted measurements in diabetes care, yet each has limitations in its clinical utility. A1C is established as an indicator of population health and long-term risk for microvascular complications but is less useful in personalizing glycemic goals, guiding therapy changes, or understanding patterns of glycemic excursions (1). Furthermore, A1C has limitations in accuracy and reliability in the context of hemoglobinopathy, anemia, iron deficiency (2), pregnancy (3), and racial differences (4). With increasing evidence regarding the relationship of glycemic variability with micro- and macrovascular risks, the definition of diabetes “control” is changing, and that change is bringing opportunity to tailor therapy decisions that truly improve outcomes (5). Self-monitoring of blood glucose (SMBG) has been an important tool for calculating insulin doses and gaining an understanding of daily glucose patterns. SMBG provides the glucose level at a single point in time without the context of past or future directionality and carries a burden of pain and inconvenience for patients, further limiting the amount of data available to analyze (1). The accuracy of an SMBG reading is dependent on the user’s testing technique and on the accuracy of the glucose meter itself; many glucose meters do not meet accuracy standards (6). Although CGM provides a wealth of information that A1C testing and SMBG lack, adoption of and persistence with this technology have been limited (7). However, with the arrival of systems for personal use (real-time use for patients) and professional use (blinded for patients with retrospective analysis by clinicians) that are more affordable and user-friendly (i.e., that do not require SMBG calibration and are indicated as an alternative to SMBG for making treatment …

Despite evidence pointing to clinical benefits of CGM, access has been limited by many state Medicaid plans. We assessed the budget impact of providing flash CGM to members with type 1 (T1D) or type 2 diabetes (T2D) taking multiple daily injections of insulin (MDI). We included the total US Medicaid and CHIP population. Using published data, we estimated rates of severe hypoglycemic events (SHE), diabetic ketoacidosis and other severe hyperglycemic events (DKA) as well as risk reduction from use of flash CGM for the various types of events and for reduction in HbA1c. Blood glucose monitoring (BGM) frequency was sourced from clinical trials. Costs for BGM, flash CGM, and unit costs for SHE and DKA and impact of HbA1c reductions were obtained from published literature and inflated to 2019. Increased use of the flash CGM in T1D and T2D MDI populations is almost cost-neutral from a Medicaid perspective. Increasing the population proportion using flash CGM (and the remainder using BGM) from a hypothetical share of 23% to 33% was associated with a $23 million overall decrease to the budget in one year. The analysis illustrates that although the unit cost of CGM is greater than blood glucose monitoring, cost offsets due to reductions in complications can lead to overall cost savings. This finding is important because health inequities, such as access to diabetes technology, are associated with poorer outcomes. Disclosure J. Frank: None. R. Hellmund: Employee; Self; Abbott Diabetes. N. Virdi: Employee; Self; Abbott Diabetes, Stock/Shareholder; Self; Johnson & Johnson. D. B. Blissett: Consultant; Self; Abbott Diabetes, Consultant; Spouse/Partner; Abbott Diabetes.

People with T1D (PWT1D) use many strategies to avoid nocturnal hypoglycemia (NH), however, the current evidence on these strategies is limited. Technologies such as continuous subcutaneous insulin infusion (CSII) or continuous glucose monitors (CGM) could help reduce NH and possibly alter PWT1D’ management behaviors. Aim: To describe PWT1D’ preferred NH prevention strategies according to their use of technology. Methods: Self-reported data from an online registry of PWT1D were analyzed. To describe which NH prevention strategies are most often used, we ran a χ2 test with a post hoc pairwise comparison of the groups based on their mode of insulin delivery and glucose monitoring (CSII + self-monitoring of blood glucose (SMBG); CSII + CGM; multiple daily injections (MDI) + CGM; MDI + SMBG). Results: Among 767 adults (64% female, mean age 45 ± 15 years, T1D duration 25 ± 14 years) 42% used MDI + CGM, 40% CSII + CGM, 5% CSII + SMBG, and 13% MDI + SMBG. About 67% reported waking up ≥1 time in the past month due to NH symptoms. The most widely used strategies were verifying bedtime glycemia (71%), having an evening/bedtime snack (60%), and/or reducing nocturnal basal insulin (30%). PWT1D using CSII + CGM or CSII + SMBG relied more on basal insulin reduction (36% and 33.3%, respectively) compared to those using MDI + CGM (26%) or MDI + SMBG (19%). Less PWT1D using CSII + CGM reported having a snack to prevent NH (51%), compared to CSII + SBMG (61%), MDI + CGM (66%), and MDI + SBGM (67%) groups (p Conclusion: Results suggest that PWT1D using technology choose different strategies to avoid NH than non-users. CSII users relying on basal insulin adjustment was expected as CSII offers more flexibility for insulin delivery. Snacks remain a popular strategy to prevent NH but are less used by PWT1D on CSII + CGM. While our findings provide some real-life insight into the methods PWT1D use to avoid NH, the efficacy of these strategies still needs further investigation. Disclosure M. K. Talbo: None. V. Messier: Other Relationship; Self; Eli Lilly and Company. K. Desjardins: None. R. Rabasa-lhoret: Advisory Panel; Self; Bayer Inc., Covance Inc., Insulet Corporation, Pfizer Inc., Other Relationship; Self; Abbott, AstraZeneca, Boehringer Ingelheim (Canada) Ltd., Dexcom, Inc., Eli Lilly and Company, HLS Therapeutics Inc., Janssen Pharmaceuticals, Inc., Medtronic, Merck & Co., Inc., Novo Nordisk, Sanofi-Aventis, Research Support; Self; Canadian Institutes of Health Research, Cystic Fibrosis Canada, Diabetes Canada, JDRF, National Institutes of Health, Prometic, Société Francophone du Diabète, Speaker’s Bureau; Self; CMS Canadian Medical&Surgical Knowledge Translation Research Group, CPD Network. A. Brazeau: None. T. Peters: None. Funding Canadian Institutes of Health Research (JT1-157204); JDRF (4-SRA-2018-651-Q-R)

IN BRIEF Therapeutic inertia and suboptimal treatment adherence remain the key drivers of chronic poor diabetes control. Advances in mHealth technologies have spurred the development of a new generation of blood glucose monitoring systems that enable individuals with diabetes to automatically transfer glucose data and other information from their smartphones to their health care providers for analysis and interpretation via diabetes data-management software. This report discusses key lessons learned from two investigations that assessed the effects of interventions using the Accu-Chek Connect diabetes-management system (Roche Diabetes Care, Indianapolis, Ind.) within diverse diabetes populations.

OBJECTIVE This study evaluated the effects of continuous glucose monitoring (CGM) combined with family behavioral intervention (CGM+FBI) and CGM alone (Standard-CGM) on glycemic outcomes and parental quality of life compared with blood glucose monitoring (BGM) in children ages 2 to RESEARCH DESIGN AND METHODS This was a multicenter (N = 14), 6-month, randomized controlled trial including 143 youth 2 to RESULTS Approximately 90% of participants in the CGM groups used CGM ≥6 days/week at 6 months. Between-group TIR comparisons showed no significant changes: CGM+FBI vs. BGM 3.2% (95% CI −0.5, 7.0), Standard-CGM vs. BGM 0.5% (−2.6 to 3.6), CGM+FBI vs. Standard-CGM 2.7% (−0.6, 6.1). Mean time with glucose level CONCLUSIONS CGM used consistently over a 6-month period in young children with type 1 diabetes did not improve TIR but did significantly reduce time in hypoglycemia. The FBI benefited parental well-being.

OBJECTIVE To investigate glycemic and psychosocial outcomes with hybrid closed-loop (HCL) versus user-determined insulin dosing with multiple daily injections (MDI) or insulin pump (i.e., standard therapy for most adults with type 1 diabetes). RESEARCH DESIGN AND METHODS Adults with type 1 diabetes using MDI or insulin pump without continuous glucose monitoring (CGM) were randomized to 26 weeks of HCL (Medtronic 670G) or continuation of current therapy. The primary outcome was masked CGM time in range (TIR; 70–180 mg/dL) during the final 3 weeks. RESULTS Participants were randomized to HCL (n = 61) or control (n = 59). Baseline mean (SD) age was 44.2 (11.7) years, HbA1c was 7.4% (0.9%) (57 [10] mmol/mol), 53% were women, and 51% used MDI. HCL TIR increased from (baseline) 55% (13%) to (26 weeks) 70% (10%) with the control group unchanged: (baseline) 55% (12%) and (26 weeks) 55% (13%) (difference 15% [95% CI 11, 19]; P < 0.0001). For HCL, HbA1c was lower (median [95% CI] difference −0.4% [−0.6, −0.2]; −4 mmol/mol [−7, −2]; P < 0.0001) and diabetes-specific positive well-being was higher (difference 1.2 [95% CI 0.4, 1.9]; P < 0.0048) without a deterioration in diabetes distress, perceived sleep quality, or cognition. Seventeen (9 device-related) versus 13 serious adverse events occurred in the HCL and control groups, respectively. CONCLUSIONS In adults with type 1 diabetes, 26 weeks of HCL improved TIR, HbA1c, and their sense of satisfaction from managing their diabetes compared with those continuing with user-determined insulin dosing and self-monitoring of blood glucose. For most people living with type 1 diabetes globally, this trial demonstrates that HCL is feasible, acceptable, and advantageous.

Since 2016 more than 600,000 people have been utilizing the CONTOUR®DIABETES app (CDA) in combination with connected CONTOUR® Blood Glucose Monitoring Systems (BGMSs) worldwide. The aim of this analysis was to assess demographic data of CDA users from North America (NA) 42.6%, Europe (EU) 47.9% and Asian Pacific (APAC) region 4.5%. We examined the CDA database of patients that uploaded at least one blood glucose (BG) result during September 2019. BG results were automatically synched from a BGMS to CDA via BLE (Bluetooth Low Energy) or had the capability to enter manually in the app. All other data were self-reported and included age, gender, diabetes type, therapy mode, physical activities, carbs and location. From 625,837 users 19.9% of patients recorded at least one BG result during September 2019. In all three regions the proportion of patients above 60 years old was similar (NA 26.6%, EU 23.8%, APAC 26.5%). There were slightly fewer male users in U.S. than in EU and APAC (NA 49.3%, EU 52.6%, APAC 52.8%). The proportion of T1D and T2D users was as follows in NA: T1D 12.9%, T2D 48.6%, EU :T1D 23.2%, T2D 39.4% and APAC: T1D 15.9%, T2D 48.9%. Analysis of treatment mode demonstrated that T2D patients treated by insulin alone or in combination with other glucose lowering medications (OAM) differed from region to region (NA 28.0%, EU 38.1%, APAC 14.5%). Among them daily BG testing adherence also varied (NA 25.5%, EU 33.3%, APAC 23.9%). The daily BG testing in T1D patients was also different per region (NA 30.3%, EU 33.8%, APAC 26.3%). Around 20% of patients that registered with CDA since 2016 were actively using the app. The majority of them were T2D patients across all regions. The proportion of insulin use in this population varied by region. This analysis showed that real world BG testing frequency in T2D patients treated with insulin alone or in combination with OAM as well as in T1D patients appears lower than current recommendations. Further analysis is planned to identify the profile of patients who would mostly benefit from the use of CDA. Disclosure J.M. Richardson: Employee; Self; Ascensia Diabetes Care. Employee; Spouse/Partner; Ascensia Diabetes Care. S. Pardo: Employee; Self; Ascensia Diabetes Care. R. Shaginian: Employee; Self; Ascensia Diabetes Care.

The CGM Intervention in Teens and Young Adults (CITY) trial demonstrated reductions in hemoglobin A1c (HbA1c) and hypoglycemia using CGM compared with intermittent blood glucose monitoring over a 6-month period. To determine if this improvement would be sustained, we evaluated outcomes in participants who continued CGM use through 12 months. The study was completed by 70 of 74 (95%) in the CGM group (43% female, median age 17 yrs, 67% non-Hispanic white, and 47% insulin pump users). Central-lab measured HbA1c and CGM measured glycemic outcomes at 12 months were compared with baseline (CGM at baseline was masked). HbA1c decreased from 8.9% at baseline to 8.3% at 12 months (p Disclosure K. Miller: None. L. Kanapka: None. C. Bauza: None. L.M. Laffel: Advisory Panel; Self; Roche Diabetes Care. Consultant; Self; Boehringer Ingelheim Pharmaceuticals, Inc., ConvaTec Inc., Dexcom, Inc., Insulet Corporation, Insulogic LLC, Janssen Pharmaceuticals, Inc., Lilly Diabetes, Novo Nordisk Inc., Sanofi US. Funding The Leona M. and Harry B. Helmsley Charitable Trust; Dexcom, Inc.

Purpose: To provide a new system of in-hospital blood glucose team management combining with network blood glucose monitoring system, and analyze the effect on hyperglycemic patients’ blood glucose control lived in non-critical care units. Methods: Hyperglycemic patients admitted to non-critical care units were divided into two groups. They were intervened actively by the hospital’s blood glucose management team and routine consultation group, respectively. A better method with shorter hospital stay and inpatient diabetes cost could be selected by comparing the two blood glucose management methods. Results: Compared to routine consultation group, the team management group had higher detection rate of hyperglycemia (18.49% vs16.17%, P Conclusion: In-hospital blood glucose team management combined network blood glucose monitoring system effectively improved the blood glucose control and fluctuation level of patients, who admitted to non-critical care units, thereby reducing hospital stay and inpatient hyperglycemia cost. Disclosure Y. Zhu: None. M. Yang: None. H. Zhou: None. W. Xia: None. P. Li: None. Y. Yang: None.

Background: Pregnant women with pre-existing type 2 diabetes (T2DM) are at risk for poor maternal and neonatal outcomes. Previous systematic reviews in women with T2DM have focused on physical activity, blood glucose monitoring, and insulin injections. The purpose of this review was to examine the barriers and facilitators of diabetes self-management. Method: PubMed, CINAHL, and EMBASE databases were searched using PRISMA-ScR guidelines from January 1, 2009, to July 30, 2019. Inclusion criteria included manuscripts written in English and qualitative studies. Themes were compared and contrasted to identify areas of congruence and discrepancy. Results: The review included ten manuscripts with 241 pregnant women with pre-existing T2DM, and eight family members were enrolled with sample sizes ranging from 5-89. First, barriers to knowledge about diabetes in pregnancy, physical activity, dietary control, medication adherence, financial constraints, stress, lack of social support, and cultural beliefs. Second, stress related to the diagnosis, infant outcomes, and cultural expectations. Third, barriers to access to care and disrespect from health care providers. Fourth, a loss of self-control. Fifth, facilitators of diabetes self-management in pregnancy were related to support from family, financial support, support from health care providers. Discussion: Pregnant women with pre-existing T2DM have multiple barriers. Only one manuscript incorporated family members. Further qualitative research may need to seek the perspectives of family members about diabetes self-management in pregnancy and examine how they can provide support to the women. Conclusion: This supports an integrative model of maternity care to overcome critical barriers and optimize key facilitators to enhance diabetes self-management behaviors and improve maternal and neonatal health outcomes. Disclosure R. Phonyiam: None. D.C. Berry: None.

Aim: Teens with T1D often report negative emotions related to diabetes self-care. Affect tends to vary throughout the day and may provide an explanatory pathway to poor diabetes self-care and suboptimal glycemic control in teens. We used momentary sampling to examine associations between affect and BGM adherence in teens with T1D. Methods: Over 2 weeks, 32 teens (ages 14-18 years) used handheld computers to self-report positive (POS) and negative (NEG) affect (Positive and Negative Affect Schedule) and BGM adherence 4 times daily. Teens selected the times to receive the messages based on their usual BGM times. There were 225 paired affect and BG adherence reports. Z-scores were calculated for the NEG and POS subscales to reflect deviations from each teen’s overall affect. Separate logistic generalized estimating equations, adjusted for age, sex, T1D duration, and pump therapy assessed associations between POS and NEG affect and BGM adherence. Results: Teens (56% female) were (M±SD) 16.6±1.4 years old with T1D duration of 8.8±4.2 years; 63% were pump treated and A1c was 8.8±1.4%. Teens reported checking BG 59% of the time. In adjusted models, greater NEG affect was associated with lower odds of BGM (OR=0.5, 95% CI: 0.4-0.8, p=.001). POS affect was not significantly associated with BGM. Age, sex, T1D duration, and pump therapy were not significantly associated with BGM. Conclusions: In a sample of teens with T1D receiving multiple daily prompts to check BG, positive affect did not relate to BGM frequency; however, negative affect was associated with being half as likely to check BG. These findings suggest a need to provide teens with strategies for maintaining diabetes self-care behaviors when they are experiencing negative emotions. Disclosure A. Shapira: None. L.K. Volkening: None. J. Borus: None. L.M. Laffel: Advisory Panel; Self; Roche Diabetes Care. Consultant; Self; Boehringer Ingelheim Pharmaceuticals, Inc., ConvaTec Inc., Dexcom, Inc., Insulet Corporation, Insulogic LLC, Janssen Pharmaceuticals, Inc., Lilly Diabetes, Novo Nordisk Inc., Sanofi US. Funding JDRF International; National Institutes of Health (P30DK036836, K12DK094721)

Background: The production of YSI 2300 STAT (YSI 2300), a widely used Class II in-vitro diagnostics medical device for calibrating blood glucose monitoring systems, has been discontinued and replaced by new generation analyzers such as the YSI 2900D Biochemistry Analyzer (YSI 2900). The aim of this study was to evaluate the analytical performance of the YSI 2900D (YSI 2900) laboratory instrument using the validated YSI 2300 STAT Plus™ (YSI 2300) medical device as the reference method. Methods: Serum controls (YSI and NIST SRM 965b) and blood and plasma samples were used to assess precision, accuracy (bias) and linearity of both analyzers for glucose concentration measurements. Human blood (n= 4 subject) was collected to prepare blood and plasma samples with low (1-70 mg/dL), mid (70-125 mg/dL) and high (125-900 mg/dL) glucose concentrations. Both analyzers employed a glucose oxidase amperometric biosensor and were configured with the same parameters. Daily membrane integrity and linearity checks were performed prior to conducting sample analyses. Results: Both instruments passed the daily performance checks prior to sample analyses. The YSI 2900 analyzer demonstrated similar within-run precision as the YSI 2300 (CV < 2% for each analyzer and each serum control tested). A total of 80 blood samples (range: 3.7-766.3 mg/dL) and 80 plasma samples (range: 4.7-880.7 mg/dL) were analyzed in triplicate on both analyzers. Paired results from the YSI 2900 and YSI 2300 showed a high correlation coefficient (R2 > 0.99) and similar regression statistics for both blood and plasma samples. Both the YSI 2900 and the YSI 2300 analyzers met accuracy (bias) criteria and Clarke error grid analysis demonstrated clinical accuracy with 100% of blood and 100% of plasma results in zone A. Conclusion: Results from this study demonstrates that the YSI 2900 analyzer is analytically comparable to the YSI 2300 for a wide range of blood and plasma glucose concentrations. Disclosure M. Hernandez: None. C. Beysen: Employee; Self; ProSciento. M. Hompesch: Board Member; Self; ProSciento. Employee; Self; ProSciento. Stock/Shareholder; Self; ProSciento. L. Morrow: Employee; Spouse/Partner; Lilly Diabetes. Employee; Self; ProSciento. Funding YSI

Background: Few long-term RCTs compare Hybrid Closed Loop (HCL) insulin delivery to manual (non-HCL) insulin dosing in type 1 diabetes (T1D). Objective: To examine glycemic and psychosocial outcomes in adults with T1D using HCL vs. manual insulin dosing with self-monitoring of blood glucose (SMBG) for 6 months. Methods: Adults using multiple daily injections or pumps with SMBG were randomized 1:1 after insulin dose optimization to 26 weeks of HCL (Medtronic 670G) or continuation of current therapy. The primary outcome was time in target range (70-180mg/dL) with masked CGM during the final 3 weeks. Secondary outcomes included other CGM metrics, HbA1c, treatment satisfaction (DTSQs) and diabetes distress (PAID). Intention to treat analysis was performed with ANCOVA or rank sum test. Results: HCL and control groups were well balanced at baseline (Table). At 26 weeks, mean (95% CI) CGM time in range with HCL was greater by 14.8% (11.1, 18.5), with reduced high and low glucose time, and lower HbA1c. There were no between-group differences in treatment satisfaction or diabetes distress (Table). Conclusions: HCL provided a significant and sustained glycemic benefit compared with standard therapy. Results will inform potential users and health professionals and a cost-benefit analysis may facilitate HCL access. Disclosure S.A. McAuley: Advisory Panel; Self; Medtronic. Research Support; Self; Medtronic, Roche Diabetes Care. Speaker’s Bureau; Self; Lilly Diabetes, Roche Diabetes Care. M.H. Lee: Research Support; Self; Medtronic. Speaker’s Bureau; Self; AstraZeneca, Medtronic. B. Paldus: Research Support; Self; JDRF. Speaker’s Bureau; Self; Australian Diabetes Society, Medtronic. S. Vogrin: None. M.B. Abraham: Speaker’s Bureau; Self; Lilly Diabetes. L. Bach: None. M. Burt: None. N. Cohen: Advisory Panel; Self; Abbott, AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Lilly Diabetes. Research Support; Self; Ypsomed AG. Speaker’s Bureau; Self; Novo Nordisk A/S. P.G. Colman: None. E.A. Davis: None. C. Hendrieckx: None. M. de Bock: None. J. Holmes-Walker: None. J. Kaye: Advisory Panel; Self; Abbott. Speaker’s Bureau; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Eli Lilly and Company, Novo Nordisk Inc. K. Kumareswaran: None. R. MacIsaac: None. R.W. McCallum: None. C.M. Sims: Stock/Shareholder; Self; Medtronic. J. Speight: Research Support; Self; Abbott, AstraZeneca, Medtronic, Sanofi-Aventis. Speaker’s Bureau; Self; American Diabetes Association, Australian Diabetes Society, Roche Diabetes Care. S. Stranks: Advisory Panel; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Lilly Diabetes, Sanofi-Aventis. S. Trawley: None. V. Sundararajan: None. G. Ward: None. A.C. Keech: Advisory Panel; Self; Amgen, Kowa Research Institute, Inc. Consultant; Self; Sanofi-Aventis. Speaker’s Bureau; Self; Abbott, Amgen. A. Jenkins: Advisory Panel; Self; Abbott, Medtronic. Research Support; Self; Abbott, GlySens Incorporated, Medtronic, Sanofi-Aventis. T. Jones: Other Relationship; Self; Medtronic. D.N. ONeal: None.

A1C is a universally used blood test to assess glycemic control during the previous 2–3 months in patients with diabetes (1). It is used to monitor long-term glycemic control and assess patients’ response to therapy and is a quality-assessment tool for diabetes care in the United Kingdom and throughout the world (2). Hence, it is important that any condition that can affect the true value of A1C be considered in clinical practice. We report here a case series of patients attending our adult secondary care diabetes clinic, all of whom were noted to have considerably lower A1C levels than what would be expected from their daily blood glucose monitoring results. The cause for the falsely low A1C in each case was found to be drug-induced hemolysis, most commonly due to sulfasalazine use. When A1C is inaccurate, fructosamine levels can be another way of monitoring average glycemic control, particularly in patients taking drugs that cause drug-induced hemolysis (1,3). In some patients, A1C can be falsely low. Any condition that shortens the life span of red blood cells, and therefore the length of time hemoglobin is exposed to glucose in the bloodstream, can falsely lower A1C. Examples include hemolytic anemias, hemoglobinopathies, splenomegaly, blood loss, blood transfusions, chronic liver or kidney disease, and some drugs (4,5). Drugs that cause subtle hemolysis without anemia may interfere with the accuracy of A1C measurement (6). Reported examples of such drugs include dapsone, sulfasalazine, ribavirin, and antiretroviral drugs (4). There are few data from randomized, controlled studies on the subject of drug-induced hemolysis causing falsely low A1C levels; thus, there is little information about the prevalence of this phenomenon. There are, however, several case reports. The first, reported in 1979 from Kesson et al. (6), described a case of dapsone-induced hemolysis …

OBJECTIVE Our objective was to characterize diabetes-specific health-related quality of life (D-HRQOL) in a global sample of youth and young adults with type 1 diabetes (T1D) and to identify the main factors associated with quality of life. RESEARCH DESIGN AND METHODS The TEENs study was an international, cross-sectional study of youth, 8–25 years of age, with T1D. Participants (N = 5,887) were seen in clinical sites in 20 countries across 5 continents enrolled for 3 predetermined age groups: 8–12, 13–18, and 19–25 years of age. To assess D-HRQOL, participants completed the PedsQL Diabetes Module 3.0 and were interviewed about family-related factors. Specifics about treatment regimen and self-management behaviors were collected from medical records. RESULTS Across all age groups, females reported significantly lower D-HRQOL than did males. The 19–25-year age group reported the lowest D-HRQOL. Multivariate linear regression analyses revealed that D-HRQOL was significantly related to HbA1c; the lower the HbA1c, the better the D-HRQOL. Three diabetes-management behaviors were significantly related to better D-HRQOL: advanced methods used to measure food intake; more frequent daily blood glucose monitoring; and more days per week that youth had ≥30 min of physical activity. CONCLUSIONS In all three age groups, the lower the HbA1c, the better the D-HRQOL, underscoring the strong association between better D-HRQOL and optimal glycemic control in a global sample of youth and young adults. Three diabetes-management behaviors were also related to optimal glycemic control, which represent potentially modifiable factors for clinical interventions to improve D-HRQOL as well as glycemic control.

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 HbA1c ≤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.

High quality blood glucose monitoring systems are required for adequate self-monitoring of blood glucose (SMBG). In this study, system accuracy of 18 current-generation SMBG systems from different manufacturers was evaluated based on the international standard ISO 15197:2013 with 1 lot each against 2 comparison methods. Manufacturers were selected by their respective market share in Europe. Each lot was tested on 100 capillary blood samples from different subjects and compliance with accuracy criterion A stipulated in ISO 15197 (at least 95% of results within ±15% or ±15 mg/dL of the comparison method’s results for BG concentrations above or below 100 mg/dL, respectively) was assessed. Glucose oxidase (GOD) and hexokinase (HK) were used as comparison methods (GOD: YSI 2300 STAT Plus, YSI Incorporated, OH, U.S.A.; HK: Cobas Integra® 400 plus, Roche Instrument Center, Switzerland). In total, 14 of 18 systems had ≥95% of results within ±15% or ±15 mg/dL of the result obtained with the respective manufacturer’s measurement method. Individual systems showed 89 to 100% of results within these limits. Results within ±10% or ±10 mg/dL of the respective comparison method results ranged from 71 to 99.5% with 3 systems showing ≥95% of results within these more stringent limits. In this evaluation, 14 out of 18 systems met the minimum system accuracy criterion A of ISO 15197 with the tested lot. Although only current-generation systems available on the market were used, more than 20% of systems did not meet ISO 15197 accuracy criteria. Disclosure S. Pleus: None. A. Baumstark: None. N.R. Jendrike: None. J. Mende: None. C. Haug: None. G. Freckmann: Advisory Panel; Self; Abbott, Novo Nordisk Pharma GmbH, Sensile Medical AG. Consultant; Self; Metronom Health Europe, Roche Diabetes Care, Sanofi. Speaker’s Bureau; Self; Ascensia Diabetes Care, Dexcom, Inc., Ypsomed AG. Funding AgaMatrix Europe Limited; Ascensia Diabetes Care GmbH; Beurer GmbH: i-SENS GmbH; LifeScan Scotland Limited; Roche Diabetes Care GmbH

Diabetes is one of the biggest health problems in the U.S., affecting 9.4% of the population and 19.9% of people in southeastern Ohio. Despite the high prevalence of diabetes, it is understudied in this region. One critical outcome that has not been addressed is diabetes distress. The purpose of this study was to explore experiences of diabetes distress in adults with type 1 diabetes (T1D) and type 2 diabetes (T2D). A purposive sample of 36 adults participated in in-depth interviews (55.6% T2D, duration=13.9±13.6 years, A1C=7.6±1.9%, 58.3% on insulin; age=45.8±19.8 years; 58.3% female; 91.7% white). Two researchers independently coded the interviews, met to resolve discrepancies, and agreed on themes. Qualitative analysis revealed 4 themes: 1) Relentless Burden of Self-Care: Both T1D and T2D participants described how hard it was to manage the daily aspects of diabetes, with blood glucose monitoring reported as the most challenging behavior; 2) Perceived Lack of Support: The majority of T1D and T2D participants felt that family and friends did not understand how difficult it was to live with diabetes. Many of these participants chose to hide their diagnosis for fear of stigmatization; 3) Worry about the Inevitability of Complications: All of the participants addressed fears about developing complications, with several experiencing debilitating distress; and 4) Uncertainties about the Cost and Quality of Care: T2D participants voiced more concerns about the cost of care. With rising drug and diabetes supply costs, T2D participants expressed more unease about their future. Further, many T2D participants felt that their primary care providers did not know enough about diabetes to take care of them properly. T1D participants did not report these views. In conclusion, T1D and T2D shared more common experiences with diabetes distress than not. In southeastern Ohio, people with T1D and T2D diabetes may benefit from group interventions that incorporate problem-solving therapy and emotion regulation. Disclosure E.A. Beverly: None. R.G. Rennie: None. E.H. Guseman: None. A. Healy: None. Funding American Osteopathic Association (1291708718)

Purpose: Long-term injection of insulin preparations causes subcutaneous amyloid deposits called "insulin balls", leading to impaired blood glucose control due to delayed absorption of the drugs. In order to get therapeutic effects of insulin, proper selection of the injection site is quite essential. Subcutaneous amyloid deposition in abdominal wall can be detected by CT examination. The present study was conducted to establish a method for detection of insulin-derived amyloid deposits and the management of insulin injection site by the combination of continuous blood glucose monitoring (CGM) and abdominal wall CT examination. Methods: The present study included 120 T2DM patients who were treated with insulin preparations over 5 years. Two weeks CGM was performed using Free Style Libre Pro. In case of significant day-to-day variation in blood glucose control, abdominal wall CT was performed to detect amyloid deposition. Results: As shown in Figure, abdominal wall CT revealed that subcutaneous amyloid deposition is caused not by ultra-short acting insulin but by long-acting insulin. Blood glucose control was stabilized by insulin injection avoiding amyloid deposits detected by CGM and CT. Conclusion: CGM and abdominal wall CT examination are useful tools for early detection of amyloid deposition by insulin and optimization of injection site. Disclosure A. Hirai: None. K. Hirai: None. H. Nishihara: None. J. Sasaki: None. T. Sudo: None. K. Fujimura: None. T. Kageyama: None.

Background: Since the prevalence of diabetes mellitus has dramatically increased over the last decades, reliable non-invasive techniques for blood glucose monitoring are required to overcome problems and obstacles for regularly home-based blood glucose assessment. The aim of this study was the validation of the newly developed non-invasive blood glucose system NIRLUS® (Near Infra Red Light Ultra Sound, NIRLUS Engineering AG, Lübeck, Germany) under well standardized conditions. Methods: 17 healthy normal weight men (BMI: 22.4 ± 1.4 kg/m2) aged 18 to 45 years were enrolled in this study. During an intravenous glucose tolerance test (ivGTT), blood glucose profiles were measured simultaneously by two researchers with the NIRLUS® system (blinded for measured values) and a gold-standard laboratory reference system (reference, EKF-Diagnostics Biosen C-line, Barleben, Germany), respectively. During the course of ivGTT, blood glucose levels ranged from hyper- to mild hypoglycemia. Results:Correlation analysis revealed a strong association between NIRLUS and reference values (r=0.934; p Conclusion: This proof-of-concept study clearly demonstrates accuracy of blood glucose measures obtained by NIRLUS®as compared to a gold-standard laboratory reference system. Precise non-invasive glucose monitoring by NIRLUS®is feasible and might lower the burden of glucose control in patients with diabetes. Disclosure S. Meyhoefer: Research Support; Spouse/Partner; NIRLUS Engineering AG. B. Wilms: Research Support; Spouse/Partner; NIRLUS Engineering AG. F. Ihling: Research Support; Spouse/Partner; NIRLUS Engineering AG. A. Windjäger: Research Support; Spouse/Partner; NIRLUS Engineering AG. V. Herrmann: Research Support; Self; NIRLUS Engineering AG. A. Augustinov: Research Support; Self; NIRLUS Engineering AG. S.M. Schmid: Research Support; Self; NIRLUS AG. Funding NIRLUS Engineering AG

Background: Inpatients hypoglycemia has adverse impacts on patient outcomes and healthcare resources use. While recurrent hypoglycemia is largely preventable, limited studies were done within the Asia-Pacific context. We sought to determine whether temporal distributions of hypoglycemia exist between insulin and/or sulfonylureas (SU) treated patients and identify predictors of recurrent hypoglycemia at a tertiary medical center in Singapore. Methods: We analyzed data of 420 hypoglycemic episodes (capillary blood glucose (CBG) ≤ 70mg/dL) in 207 diabetes patients at general medical wards over a 2-month period from 1st May 2017. This was analyzed by 4 time frames coincided with blood glucose monitoring times. Time periods associated with hypoglycemia were compared using the Chi-square test. Multivariate logistic regression estimated risk factors of recurrent hypoglycemia. Results: Most frequent hypoglycemia episodes occurred between 04:00 and 09:59 (41.7%). Greater frequency was seen in insulin- and SU-treated than insulin-treated patients between 04:00 to 09:59 (58.3% vs.37.9% of readings for respective treatments, p 7% and repeated CBG checking > 30 minutes interval emerged as predictors of recurrent hypoglycemia with odds ratio of 1.07 (95% CI 1.03-1.11), 8.07 (95% CI 2.82-23.08), 3.71 (95% CI 1.59-8.65), 3.12 (95% CI 1.26-7.74) and 3.54 (95% CI 1.59-7.91), respectively. Conclusions: Hypoglycemic episodes were more frequent in the early hours of the day in insulin and SU-treated inpatients. This may have implications for the continuing use of SU at inpatients. Recurrent hypoglycemia can be prevented by developing strategies targeting the modifiable iatrogenic risk factors. Disclosure P. Lim: None. S. Goh: None. Y. Bee: None. X. Xin: None. L. Ang: None. N.A. Salleha: None. M.M. Teh: None.

This paper presents DiaBits, an iPhone application that allows patients with diabetes to efficiently monitor and manage their blood glucose levels in real time. Using current CGM data, smartphone sensor data, and user inputs, DiaBits takes advantage of modern machine learning techniques to predict future blood glucose fluctuations up to 60 minutes in advance. These predictions, which are over 95% clinically acceptable according to standard Error Grid Analysis methods, give the patients an opportunity to take corrective action in advance in order to keep their blood glucose values within normal range. Additionally, the presence of predictive alarms and statistical tools for analysis of past data makes it easier for the users to manage their condition and have better blood glucose control. The paper discusses some of the details of the predictive approach, provides accuracy results for 1.63 million predictions made for free-living users of the application, gives a detailed overview of the available features and the interface of DiaBits, and describes some challenges related to using machine learning for real-time predictions of blood glucose behavior. Disclosure A. Hayeri: Other Relationship; Self; Bio Conscious Technologies INC.

Deployment and maturation of computerized medical records has improved insight into the unintended variability of glucose management in hyperglycemic inpatients. We used expert panels and extensive field testing to design a Glycemic Management Program to simultaneously reduce mean glucose levels and the frequency of hypoglycemic events. Factors observed as contributing to glucose control variation included over-use of sliding scale insulin; inconsistencies in timing, type and dose of insulin; and the alignment of blood glucose testing with meal tray delivery. We designed our Glycemic Management Program to address these factors with four distinct components: 1) Change management via targeted education; 2) Standardization of the ordering process for nutrition, blood glucose monitoring frequency, and a single subcutaneous insulin order set with decision support; 3) Standardization of workflow, including the timing and coordination of glucose testing and meal tray delivery; and 4) Patient specific, customized ongoing insulin dosing recommendations through FDA-approved decision support software. We implemented our Glycemic Management Program pilot in a 325 bed community hospital in the southeastern United States. Since its launch, 2277 patients have been managed on the program. By six months post-implementation, the rate of severe hypoglycemia ( A comprehensive program that incorporates decision support with attention to workflow, provider engagement, and education can result in improved glucose management in an inpatient setting. Feedback has led to programmatic changes to maximize positive outcomes and ensure sustainability. Disclosure R. Freeman: None. W.E. Gay: None. T.L. Garthwaite: Advisory Panel; Self; Ondine Biomedical. L. Hollis: None. J. McCannon (Bush): None. C. Spencer-Smith: None. E.E. Samuelson: None. P. Mehta: None.

The study aimed to investigate the effect of 7-point or 5-point glucose monitoring on medical costs, glycemic control and the incidence of hypoglycemia in hospitalized patients with type 2 diabetes (T2DM). A total of 4002 patients with T2DM (1490 male and 2512 female cases) with complete medical records were included between 2012 and 2017. The average age was 61.5 years and the mean disease duration 8.68 years. According to the frequency of daily monitoring of blood glucose during hospitalization, patients were divided into 2 subgroups of 5-point group and 7-point group. Patients in 5-point group received fasting blood glucose (FBG), 2h blood glucose (2hBG) after breakfast, 2hBG after lunch, 2hBG after dinner and bedtime blood glucose tests. Patients in 7-point group received additional tests of pre-lunch glucose and pre-dinner blood glucose. Blood glucose monitoring was performed using Johnson & Johnson SureStep blood glucose meter. Comparison of two groups includes duration of in-hospital stay, medical costs, glycemic control and the incidence of hypoglycemia. Patients in 7-point glucose monitoring group had significantly shorter hospital stay (14.4 vs. 16.6 days, P0.05). At discharge, both fasting and 2-h glucose decreased significantly compared with baseline levels in either 5-point or 7-point group. In 7-point group, FPG decreased by 2.41mmol/L and 2hPG by 3.9mmol/L. In the 5-point group, the corresponding figures were 2.07mmol/L and 3.6mmol/L, respectively. The incidence of hypoglycemia were 24.2% in 7-point group and 33.1% in 5-point group (P Disclosure L. Zhang: None. Y. Gu: None. Y. Yang: None. N. Wang: None. W. Gao: None. J. Wang: None. X. Yin: None. Y. Dong: None.

The ADA’s recent release of the Standards of Medical Care in Diabetes recommends including technology-based methods for the delivery of effective diabetes self-management education and support. Self-management of diabetes involves meal planning, taking medications, blood glucose monitoring, physical activity, coordinating care, and others. The program developed by Pack Health addresses all of the tasks above and more through a structured 12-week program, evidence-based tools, and a non-prescriptive Health Advisor. The program has over 60 proactive outbound touchpoints that originate from the Health Advisor (via text messages, emails, and/or phone calls). The Pack Health program collects and utilizes patient-reported outcomes (PROs) along with clinical measures, self-reported by patients. All data is used for coaching sessions and evaluation purposes. This study examines the impact of Digital Health Coaching on a national diabetes population (n=198) and an African American sub-population (n=57) enrolled in the South (AL, GA, FL, MS) upon completion of the initial 12-weeks of engagement. The DDS is a 17-item scale that captures four critical dimensions of distress: emotional burden, regimen distress, interpersonal distress and physical distress. DDS score benchmarks are established at little to no diabetes distress ( National Diabetes Population: Baseline: 3.0; Post: 2.2; Improvement: 0.8 African Americans in the South: Baseline: 3.0; Post: 2.1; Improvement: 0.9 The data above emphasizes that digital coaching program can have a significant impact on Diabetes Distress for a general population and African American population in the South. Disclosure M. Allison: None. U. Srivastava: None. S.B. Burton: None. M. Rasulnia: None. D. Patel: None.

Objective: The majority of adolescents with type 1 diabetes have poor glycemic control, calling for an action to be taken. The aim of this study was to identify the determinants of poor glycemic control among adolescents with type 1 diabetes. Methods: Data were collected for all adolescents with type 1 diabetes (age < 20 years), who attended diabetes clinics at one hospital, and had at least one result of HbA1c performed during the study year. The average level of HbA1c was calculated from all the HbA1c results collected over one year. Glycemic control was defined as poor if the HbA1c was >8%. Variables studied were gender, age, age at diagnosis, diabetes duration, annual clinic attendance, frequency of blood glucose monitoring, healthy eating, medication adherence, and frequency of HbA1c performance over one year. Results: The study included 78 adolescents with type 1 diabetes (47.4% males). Mean age was 15.4+2.0 years, mean age at diagnosis was 9.0+3.6 years, and mean duration of diabetes was 6.6+3.8 years. The mean of the average level of HbA1c was 10.2+1.9%, and 84.6% had HbA1c >8%. Mean frequency of HbA1c performance was twice per year, and mean annual clinic attendance was three visits. Poor glycemic control was significantly associated with female gender (p 3 per year) were significantly associated (p Conclusions: The overall glycemic control in adolescents with type 1 diabetes was poor, putting them at high risk of developing diabetes complications at an early stage of life. Healthy behavior was a major determinant of glycemic control. Behavioral healthy intervention strategies should be integrated in the management plan of diabetes care to improve glycemic control and reduce diabetes complications in this vulnerable group. Disclosure A.M.A. Aladsani: None.

The purpose of this study was to evaluate the preliminary efficacy of a self-management group + mHealth program (Yo Puedo!) on clinical (A1C, BP, BMI), self-management (diet, exercise, blood glucose monitoring), depressive symptom, and self-efficacy outcomes in adults with type 2 diabetes (T2D) at Seguro Popular clinics in Mexico City. Participants were randomly assigned to treatment (n=26) or wait-list control groups (n=21) with data collected at 3 and 6 months. The Yo Puedo! Program included 7 weekly sessions and 6 months of daily text messages. Descriptive statistics and generalized linear mixed model (GLMM) with random intercept were calculated. Adults with T2D were 55.5 years of age (±8.6), 68% female, 59% married/partnered, 88.6% overweight/obese, 50% lived in moderate/severe food insecure households, 35.7% had increased depressive symptoms, and 80% had A1C above 7.0%. Mean duration of T2D since diagnosis was 11.5 years (±7.1). There were no between-group differences on baseline characteristics. There was 89% attendance at sessions and 6% attrition at 6 months. Group by time effects were seen in blood glucose monitoring (p Disclosure R. Whittemore: None. M. Vilar-Compte: None. S. De La Cerda: None. R. Delvy: None. S. Jeon: None. S.I. Burrola-Méndez: None. A.A. Lozano-Marrufo: None. R. Perez-Escamilla: None. Funding National Institute of Nursing Research

Time in-range blood glucose level (70-140 mg/dl) is one of the greatest challenges when managing diabetes. Digital engagement can play a pivotal role in the care of patients with diabetes and other chronical conditions, potentially improving patient’s compliance. In this study DarioTM Blood Glucose Monitoring System (BGMS) users were evaluated to examine whether higher App engagement contributes to better diabetes management. Method: A retrospective data evaluation study was performed on the DarioTM cloud database. A population of active type 2 diabetic (T2D) users (>15 measurements per month on average) was evaluated. The study assessed the ratio of in-range blood glucose readings (70-140 mg/dL) as a function of App engagement level for 6 months as recorded in the database compared to first 30 days as a starting point of analysis. Results: A population of 4917 T2D non-insulin users measuring more than 15 times per month on average during 6 months in a row was evaluated. The ratio of in-range (70-140 mg/dL) readings was increased following 3 months in correlation to the level of tagging meal reference/carbs/physical activity occurrences (4.0%, 9.1% and 11.9% for tagging 0-1, 1-2 and >2 times per day on average, respectively) and sustained for 6 months (3.1%, 7.0% and 12.2%, respectively). In subgroup analysis focusing on users entering their meal reference, high correlation was observed following 3 months with an increase of in-range measurements in 4.6%, 8.4% and 12.0% for 0-1, 1-2 and >2 meal reference tagging per day on average, respectively, and maintained stability over 6 months period (3.2%, 7.4%, and 12.5%, respectively). Conclusion: The combination of a glucose meter, an App and engaged user may promote better behavioral modification which enhance and sustain adherence to diabetes management. Disclosure Y. Hershcovitz: Employee; Self; DarioHealth. S. Dar: Employee; Self; DarioHealth. E. Feniger: Employee; Self; DarioHealth.

Objectives: It is now well documented that adolescents with T1D are at greater risk for elevated anxiety than young people without diabetes. In addition, higher levels of state anxiety are associated with higher haemoglobin A1c (HbA1c), less frequent blood glucose monitoring, and more poorly controlled diabetes. Anxiety is also predictive of poor glycaemic control as far as 12 months into the future. To better understand how stress and anxiety may be related to moment-to-moment fluctuations in blood glucose levels, we used a novel method of measuring changes in emotional state in real time, known as experience sampling methodology (ESM), in combination with continuous glucose monitoring (CGM) technology. Methods: ESM is an ambulatory research method whereby participants respond to questions sent via a smartphone ‘app’ at multiple times throughout the day. In this study, adolescents (n= 53) diagnosed with T1D (aged 12-18 years) responded to questions regarding their current emotional state 10 times a day, over a 10-day period. Results: Preliminary analysis, using multilevel regression modelling, explored the relationships between anxiety and measures of glycaemic control. The following measures of glycaemic control were examined: concurrent sensor glucose (SGL), mean sensor glucose in the previous 60 minutes, and standard deviation (SD) of sensor glucose in the previous 60 minutes. The results of the model indicated that a quadratic term for concurrent SGL (p < 0.001) and SD of sensor glucose (p = 0.005) were significant independent predictors of anxiety. The relationship between concurrent SGL and anxiety was U-shaped, with the vertex (minimum) of 7.8 mmol/L. Conclusions: These novel findings confirm that elevated anxiety is associated with sub-optimal blood glucose levels in the preceding hour. Further analysis of this data will explore this relationship in greater detail, including possible inter-individual variation in this pattern. Disclosure K. Bebbington: None. D. Rudaizky: None. G.J. Smith: None. A.M. Hunt: None. E.A. Davis: None. T. Jones: Research Support; Self; Dexcom, Inc., Medtronic MiniMed, Inc. Speaker's Bureau; Self; Eli Lilly and Company, Roche Diabetes Care. A. Lin: None.

Background: Adolescence is associated with suboptimal diabetes control, with average HbA1C levels of 9.0%. Adolescents are highly engaged in mobile technology; over half report sending text messages at least daily. Text messaging (TM) is most commonly used technology in adolescents with type 1 diabetes (T1D). Pilot studies have demonstrated TM to be a useful tool in diabetes education. MyDiaText™ is a website and TM platform created to support behavior change in adolescents with T1DM. Enrollment in a randomized controlled trial (RCT) using MyDiaText™ began in August 2018. Objective: To report the baseline characteristics, self-care behaviors, and engagement in a TM intervention for T1D education and support in a diverse population. Methods: Subjects were recruited from the CHOP Diabetes Center. Enrollment criteria for the trial included: 12-18 years, >1 year from diagnosis and point-of-care HbA1C > 8%. Adolescents selected an AADE7™ Self-Care Behavior (SCB) goal on which to focus. Those in the intervention group received daily educational and motivational text messages. Self-Care Inventory (SCI), 14 questions scored 1-5, and HbA1C were obtained at baseline. Engagement index, defined as number of responses/total messages received, was calculated by the application. Results: There were 107 subjects (average age = 15.8 years {45.8% M, 52.3% F, 1.9% other; 60 (56.1%) W, 33 (30.8%) B, 10 (9.3%) mixed race and 4 (3.7%) other; 11 (10.2%) identified as Hispanic}) enrolled. “Monitoring” was most common SCB selected, 45 subjects (42.4%). Mean (range) baseline HbA1C was 10.0% (8.0-14.1). Mean baseline SCI score was 3.36 (1.07-5.0). Engagement was 60% or greater for 74% of subjects in treatment arm. Conclusions: A diverse population of adolescents with T1D and suboptimal control preferred text messaging support for blood glucose monitoring and demonstrated high engagement in MyDiaText™. Further analyses will determine the efficacy of MyDiaText™ on diabetes outcomes. Disclosure T. Kaushal: None. L.E. Katz: None. M.E. Marowitz: None. J. Joseph: None. D.P. Ritter: None. T.H. Lipman: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (2T32DK063688-11-12 to L.E.K.)

Background: It is critical that Blood Glucose Monitoring System’s (BGMS) are easy to use since they are an important tool in the management of diabetes mellitus, including the prevention of micro and macrovascular complications. The GLUCOCARD® W BGMS is intended for consumer use and is an aid in monitoring the effectiveness of diabetes management. The “Ease of Use” consumer study is typically evaluated as part of the FDA 510(k) approval process for BGMS. Purpose: The objective of this study was to evaluate the Ease of Use for the GLUCOCARD® W BGMS. Methods: A total of 148 untrained consumers with diabetes performed a fingerstick self-test and answered a questionnaire directed at Ease of Use of the device and test strip. The topics in the questionnaire included, “Inserting a Test Strip into Meter to Turn it On”; “Blood Draw into Test Strip (Capillary Action)”; “Reading the Meter Display”; “Removing Test Strip from Meter” and “Performing a Blood Glucose Test from your Fingertip.” The subjects were asked to rate the topics as Very Easy, Easy, Ok, Difficult or Very Difficult. For evaluation purposes, these topics were grouped as Positive (Very Easy/Ease/Ok) and Negative (Difficult/Very Difficult). Results: The topics in the questionnaire received the following positive ratings (%): “Inserting a Test Strip into Meter to Turn it On”, 97.3% (144/148); “Blood Draw into Test Strip (Capillary Action)”, 100.0% (147/147, one subject did not rate this topic); “Reading the Meter Display” received a 99.3% (147/148); “Removing Test Strip from Meter”, 100.0% (148/148) and “Performing a Blood Glucose Test from your Fingertip”, 100.0% (148/148). Conclusion: The GLUCOCARD® W BGMS scored an overall positive rating of 99.3% (average of the ratings) from the untrained consumers with diabetes evaluating the BGMS as Very Easy to Ok to use. Disclosure J. Walker: Employee; Self; Arkray, Inc. P. Gill: Employee; Self; Arkray, Inc. D. Maher: Employee; Self; Arkray, Inc. J.M. Gleisner: Employee; Self; Arkray, Inc..

Adequate frequency of self-monitoring of blood glucose (SMBG) is important to maintain glycemic control. Real-time sharing of adolescent SMBG data with parents and providers is possible, however, adolescents may be reluctant to adopt this technology. The objective of this research was to determine patient-centered outcomes of adolescent-parent research participant pairs who were randomized to utilize: (1) a glucometer that shared blood glucose data among patients, parent, and providers, and allowed for communication; (2) family-centered goal setting; and (3) a combination of (1) and (2). We evaluated data from 97 adolescent-parent pairs in the form of 10 validated surveys; we modeled longitudinal changes in survey responses from baseline to 6 months. Differences between treatment groups were evaluated using ANOVAs and changes within patients over time were evaluated using paired t-tests. Patient and parent satisfaction was high at the onset of the intervention; 4.31 out of 5 and 4.55 out of 5, respectively. Parent Satisfaction Survey (p = 0.04) and Parental Environment Questionnaire (p = 0.006) results decreased over time; there was no significant change for any other surveys. Our data suggest that it is important to individualize therapy to meet patient-centered goals and acknowledge this when designing interventions to improve health outcomes in adolescents with T1D. Disclosure J.B. Halper: None. T. Hannon: Consultant; Self; Eli Lilly and Company. L. Yazel-Smith: None.

By 2034, the number of U.S. individuals with diabetes is predicted to increase from 23.7 to 44.1 million, and annual diabetes-related spending is expected to grow from $113 to $336 billion. Current healthcare systems are often not equipped to support the growing diabetes population, and many individuals are not achieving clinical targets necessary for preventing diabetes complications and for improving long-term survival. To address this need, an innovative, Chronic Care Model (CCM)-based care management program was developed that used clinical risk stratification, standardized decision support tools, RN + health coach + PCP team-based care, and a depression care manager. N=236 T1D and T2D (96%) patients (M age = 61.9 ± 11.4 years; 51% male) were enrolled at a San Diego clinic that includes diverse payors and an integrated PCP group. This care management program was previously shown to achieve significant improvements in cardiometabolic outcomes (HbA1c, LDL-c) and health care costs relative to usual care at 1-year. The present analysis evaluated effects on diabetes self-management (Summary of Diabetes Self Care Activities) and distress (Diabetes Distress Scale), and patients’ experience with CCM-based healthcare delivery components (Patient Assessment of Chronic Illness Care). Statistically significant improvements were observed in healthful eating (5 vs. 4 days/week), exercise (5 vs. 3), blood glucose monitoring (5 vs. 4), foot-checking (5 vs. 3), and diabetes distress (14% vs. 24% with moderate distress) over 12 months (ps < .05). Patients’ perceptions of follow-up/care coordination, support for patient activation and self-management, and delivery design also improved over this period (ps < .05). Taken together, this population-based care management program represents an approach that can improve clinical, behavioral, psychosocial and cost outcomes, and health care delivery experience for people with diabetes in the primary care environment. Disclosure A.L. Fortmann: None. J.L. Preciado: None. C. Walker: None. R. Morrisey: None. K. Barger: None. D. Mills: None. M. Robacker: None. A. Philis-Tsimikas: Research Support; Self; Dexcom, Inc.. Advisory Panel; Self; Dexcom, Inc., Eli Lilly and Company, Merck & Co., Inc., Novo Nordisk A/S, Sanofi. Research Support; Self; Novo Nordisk A/S, Sanofi, Mylan. Stock/Shareholder; Spouse/Partner; Novo Nordisk A/S. Employee; Spouse/Partner; Ionis Pharmaceuticals, Inc.. Stock/Shareholder; Spouse/Partner; Esperion Therapeutics, Ionis Pharmaceuticals, Inc.. Advisory Panel; Self; AstraZeneca.

No studies have reported changes in self-care behavior, and it remains unclear whether Free Style Libre (Libre) differs from conventional blood glucose self-monitoring devices in this regard. Therefore, we instructed diabetes patients using conventional self-monitoring blood glucose (SMBG) devices to use the Libre and prospectively examined the effect of this new device on self-care behavior and patient treatment satisfaction. The subjects comprised 41 outpatients with diabetes who were using conventional SMBG devices. The subjects were randomly assigned to group A, which comprised patients using Libre for ≥2 weeks (n = 21), or group B, which comprised patients who continued using conventional SMBG devices (n = 20). All patients received 30 minutes of diet and exercise therapy instruction from a registered dietitian and nurse (or clinical laboratory technologists). The Summary of Diabetes Self-Care Activities measure (SDSCA) was administered at baseline, 1, 3, and 6 months. Changes in the SDSCA, glycated hemoglobin (HbA1c), glycated albumin (GA), and body weight from baseline to 1 month were analyzed (UMIN000029016). At baseline, the two groups did not differ significantly in terms of the HbA1c, GA, body weight, or 17 SDSCA items. At 1 month, the numbers of days involving eating five or more servings of fruits and vegetables were 5.0 (3.3, 6.8) in group A and 3.0 (1.0, 6.0) in group B, the numbers of days involving exercise for at least 30 minutes were 5.0 (2.0, 6.0) in group A and 2.0 (0, 3.0) in group B, and the number of days involving specific exercise were 3.0 (2.0, 6.0) in group A and 1.5 (0, 2.3) in group B; both of these values were significantly higher in group A than in group B (p = 0.033, 0.037 and 0.041, respectively). These results suggest that the use of the Libre may improve the self-care behaviors of diabetes patients regarding diet and exercise, compared with the use of conventional SMBG devices. Disclosure A. Kudara: None. T. Tosaki: Other Relationship; Self; Eli Lilly and Company, Takeda Development Center Asia, Pte. Ltd., MSD K.K., Mitsubishi Tanabe Pharma Corporation. S. Sato: None. A. Inagaki: None. M. Kondo: None. S. Tsunekawa: None. Y. Kato: Speaker's Bureau; Self; Merck Sharp & Dohme Corp., Sanofi, Takeda Pharmaceutical Company, Eli Lilly Japan. H. Kamiya: Other Relationship; Self; MSD K.K., Ono Pharmaceutical Co., Ltd., Sanofi K.K., AstraZeneca, Astellas Pharma KK, Eli Lilly and Company, Novartis Pharma K.K., Dainippon Sumitomo Pharma Co., Ltd, Boehringer Ingelheim Pharmaceuticals, Inc., Takeda Pharmaceutical Co., Ltd, Ono Pharmaceutical Co., Ltd. J. Nakamura: Other Relationship; Self; Astellas Pharma US, Inc., AstraZeneca, Ono Pharmaceutical Co., Ltd., MSD K.K., Kyowa Hakko Kirin Co., Ltd., Kowa Pharmaceuticals America, Inc., Sanofi K.K., Taisho Pharmaceutical Co., Ltd., Takeda Development Center Asia, Pte. Ltd., Mitsubishi Tanabe Pharma Corporation, Eli Lilly and Company, Novartis Pharma K.K., Pfizer Inc..

One of the goals of a digital diabetes management system is to improve the patient’s self-management and control of their condition. Blood glucose level reduction and sustainment of lower levels of blood glucose is one of the greatest challenges in managing diabetes. Digital engagement can play a pivotal role in the care of patients with diabetes and other chronical conditions, potentially improving patient’s compliance. The DarioTM Blood Glucose Monitoring System (BGMS) connects physically to a smart mobile device and automatically logs blood glucose measurements into a designated application (App). Data is transmitted to the Dario cloud. Method: A retrospective data evaluation study was performed on the DarioTM cloud data base. A population of all active type 2 diabetic (T2D) users that took measurements with DarioTM BGMS on average of 20 measurements per month during 2017. The study assessed the ratio of all high blood glucose readings (180-400 mg/dL) and the ratio of all normal blood glucose readings (80-120 mg/dL) in their first month of use to their last month of use during 2017 as recorded in the database. Results: For 17,156 T2D users activated during 2017 the average ratio of high events (180-400 mg/dL) was reduced by 19.3% (from 28.4% to 22.9% of the entire measurements). While at the same time, the ratio of normal range readings (80-120 mg/dL) was increased in 11.3% (from 25.6% to 28.5% of the entire measurements). The most significant shift occurred after one month of usage (14% decrease) and maintained stability over the following months throughout the full year. Conclusion: The combination of a glucose meter and an App may promote behavioral modification and enhanced adherence to diabetes management, demonstrating improvement in glycemic outcomes and sustainment for a long period of time. Disclosure Y. Hershcovitz: Employee; Self; DarioHealth. E. Feniger: Employee; Self; DarioHealth. S. Dar: Employee; Self; DarioHealth.

One of the goals of a digital diabetes management system is to improve patient’s self-management and control of their condition. High blood glucose level is defined as 180-400 mg/dL while severe hyperglycemia (above 400 mg/dL) is considered a medical emergency. Digital engagement can play a pivotal role in the care of patients with diabetes and other chronical conditions, assisting patients to enhance their compliance. The DarioTM Blood Glucose Monitoring System (BGMS) connects physically to a smart mobile device and automatically logs blood glucose measurements into designated App. Data is transmitted to the Dario cloud. Method: A retrospective data evaluation study was performed on the DarioTM cloud database. A population of active type 2 diabetic (T2D) users that continuously measured their blood glucose using DarioTM BGMS during the full year of 2017 was evaluated. The study assessed the ratio of high (180-400 mg/dL) and hyperglycemic (>400mg/dL) blood glucose readings during full year of 2017 as recorded in the database. The average of high and hyperglycemic glucose readings were calculated in periods of 30-60, 60-90, 90-120, 120-150, 150-180, 180-210, 210-240, 240-270, 270-300, 300-330, 330-360 days and compared to first 30 days as a starting point of analysis. Results: For 225 T2D active users the ratio of high events (180-400 mg/dL) was reduced gradually in 19.6% (from 23.4% to 18.8% of the entire measurements) from baseline compared to the 12th month of the year. Moreover, the ratio of severe hyperglycemia events (>400 mg/dL) was decreased in 57.8% (from 0.90% to 0.38% of the entire measurements) at the same period. Conclusion: By means of glucose meter and App patients have the potential to promote behavioral modification and enhance adherence to diabetes management, demonstrating better glycemic control. Disclosure Y. Hershcovitz: Employee; Self; DarioHealth. S. Dar: Employee; Self; DarioHealth. E. Feniger: Employee; Self; DarioHealth.