Search

Background: The impact of the coronavirus disease-2019 (COVID-19) pandemic on glycemic metrics in children is uncertain. This study evaluates the effect of the shelter-in-place (SIP) mandate on glycemic metrics in youth with type 1 diabetes (T1D) using continuous glucose monitoring (CGM) in Northern California, United States. Methods: CGM and insulin pump metrics in youth 3-21 years old with T1D at an academic pediatric diabetes center were analyzed retrospectively. Data 2-4 months before (distant pre-SIP), 1 month before (immediate pre-SIP), 1 month after (immediate post-SIP), and 2-4 months after (distant post-SIP) the SIP mandate were compared using paired t-tests, linear regression, and longitudinal analysis using a mixed effects model. Results: Participants (n = 85) had reduced mean glucose (-10.3 ± 4.4 mg/dL, P = 0.009), standard deviation (SD) (-5.0 ± 1.3 mg/dL, P = 0.003), glucose management indicator (-0.2% ± 0.03%, P = 0.004), time above range (TAR) >250 mg/dL (-3.5% ± 1.7%, P = 0.01), and increased time in range (TIR) (+4.7% ± 1.7%, P = 0.0025) between the distant pre-SIP and distant post-SIP periods. Relationships were maintained using a mixed effects model, when controlling for other demographic variables. There was improvement in SD, TAR 180-250 mg/dL, and TIR for participants with private insurance, but changes in the opposite direction for participants with public insurance. Conclusions: Improvement in CGM metrics in youth with T1D during the COVID-19 pandemic suggests that diabetes management can be maintained in the face of sudden changes to daily living. Youth with public insurance deserve more attention in research and clinical practice.

Background Diabetes is a risk factor for poor COVID‐19 outcomes, but pediatric patients with type 1 diabetes are poorly represented in current studies. Methods T1D Exchange coordinated a US type 1 diabetes COVID‐19 registry. Forty‐six diabetes centers submitted pediatric cases for patients with laboratory confirmed COVID‐19. Associations between clinical factors and hospitalization were tested with Fisher's Exact Test. Logistic regression was used to calculate odds ratios for hospitalization. Results Data from 266 patients with previously established type 1 diabetes aged, Highlights Outcomes for children with type 1 diabetes who experience COVID‐19 are currently unknown. We report 266 cases from US diabetes clinics of children with type 1 diabetes who had COVID‐19. Diabetic ketoacidosis was the major adverse outcome, and it was associated with higher A1c.

Background: The introduction of insulin pumps with bolus calculators (BCs) has improved glycemic outcomes and quality of life for those with type 1 diabetes. Despite the increased reliance on BCs, the formulas used to derive recommended boluses are not standardized. Our objective was to examine whether recommendations from different pump BCs vary significantly for identical clinical scenarios. Methods: Three commercially available insulin pump BCs were programmed with identical settings and then presented with combinations of blood glucose (BG) and carbohydrates (CHOs) to generate a 4-unit bolus. At one- and two-hour time points, while there was insulin-on-board (IOB) present, we simulated various BG and CHO scenarios in order to compare BC-recommended doses. Results: Differences in suggested doses were noted between BCs, as well as within the same brand. The greatest variation was apparent when BG was below target. Doses suggested by one BC varied depending on whether the IOB resulted from a previous dose given for BG or CHO, while the other two BCs adjusted for total IOB regardless of the source. Conclusions: In this simulation study, there were large differences in recommended doses between BCs due to the unique way each manufacturer incorporates IOB into their formulas as well as the pharmacokinetics used to derive the IOB amount. Providers should be aware that identical pump settings will result in a different dose recommendation for each pump brand and advise patients accordingly.

Objective: Real-time continuous glucose monitoring (CGM) is effective for diabetes management in T1D and adults with T2D, but has not been assessed in youth with T2D. The objective of this study was to assess the feasibility and acceptability of CGM use in youth with T2D. Methods: Youth (13- 21 years old) with T2D ≥ 6 months and A1c > 7%, on any FDA approved treatment regimen were included. After a blinded run-in period, participants were given a Dexcom G6 CGM system for 12 weeks. The use and acceptability of the real-time CGM were evaluated by sensor usage, surveys, and focus group qualitative data. Results: Youth (n=8) had median age 19.4 (IQR 15.5-20.6) years, were 75% female, 50% hispanic/latino ethnicity, 50% non-English speaking at home, and 91% had public insurance. Baseline A1c was 11.7 (±2.8)% with mean diabetes duration of 2.5 (IQR 1.4 - 5.1) years and 75% were on basal insulin. Of the 7 participants who have completed the CGM intervention, all reported CGM was a positive experience (50% very positive, 50% slightly positive), easy to use (50% very easy, 50% easy), and useful (83% useful, 17% useful). All participants desired to continue to use real-time CGM in the future. 85% were “extremely” likely to recommend real-time CGM to friends. 67% of participants self-reported eating fewer meals while using CGM. All participants used sensors for the duration of the study. Conclusion: Real-time CGM is feasible and acceptable for youth with type 2 diabetes. Larger randomized controlled trials are needed to assess effects on glycemic control, healthy lifestyle changes, and diabetes distress. Disclosure H. Chesser: None. S. Srinivasan: None. J. C. Wong: Advisory Panel; Self; Provention Bio, Inc., Research Support; Self; Dexcom, Inc., Tandem Diabetes Care.

Hypoglycemia occurs frequently in children with type 1 diabetes (T1D). However, the relationship between fear of hypoglycemia (FOH) and use of diabetes technology with different insulin delivery systems has not been well studied. Similarly, little is known about the relationship of diabetes treatment satisfaction with advances in diabetes technology in the pediatric population. Caregivers of children 6-17 years with T1D (n=104, 84% female caregivers, median T1D duration 5.3 years, mean GMI 7.5 ± 0.7%, 93% insulin pump users, 92% CGM users) using any insulin delivery system (8% MDI, 0.05% pump alone, 31% sensor augmented pump, 23% predictive low glucose suspend, 38% hybrid closed loop) completed the Hypoglycemia Fear Survey - Parent (HFS-P) and the Diabetes Treatment Satisfaction Questionnaire - Parent (DTSQ-P). Youth 13-17 years (n=35, 56% males) also completed the HFS - Child (HFS-C) and DTSQ - Child (DTSQ-C). Linear regression was used to look for associations between HFS and DTSQ scores and clinical factors, and paired t-tests were used to compare scores between caregivers and youth. Female caregivers had higher mean HFS Worry and Behavior scores than male caregivers (Worry 1.4 ± 0.18 vs. 0.88 ± 0.16, p=0.004; Behavior 4.9 ± 0.39 vs. 3.9 ± 0.3, p=0.008). Longer duration of diabetes, duration of pump use, and duration of CGM use were all associated with higher mean HFS-C Worry scores, but not with HFS-P Worry scores. The use of different insulin delivery systems was not associated with any HFS scores. Caregivers had a higher mean HFS Behavior score (4.8 ± 0.29) than youth (2.2 ± 0.078) (p Disclosure F. Abdulhussein: None. J. C. Wong: Advisory Panel; Self; Provention Bio, Inc., Research Support; Self; Dexcom, Inc., Tandem Diabetes Care.

People with diabetes (PWD) benefit from continuous glucose monitoring (CGM), yet CGM uptake in the US remains low. While diabetes care providers are key facilitators of CGM provision, data on provider behavior related to CGM use and CGM generated data is limited. In March 2020, we conducted a national survey of providers caring for PWD on CGM-related opinions, facilitators and barriers to CGM prescription, data review practices, and reimbursement. Descriptive statistics were used to report prevalence of Likert scale answers to a 55-question survey. Of 182 survey respondents caring for PWD using CGM, 75% were at academic medical centers, 66% were endocrinologists, and 70% practiced in urban settings. Nearly 70% of providers reported CGM use in a majority of their patients with type 1 diabetes. CGM use in patients with type 2 diabetes was low, with half the providers reporting Despite uniform support for CGM by providers, inadequate time and inefficient data review processes are ongoing challenges. Improvements in data access and integration, supportive clinical infrastructure, and decreased administrative burden to obtain CGM, are facilitators of effective use of CGM-data by providers and necessitate ongoing attention. Disclosure T. Kompala: Consultant; Self; Eli Lilly and Company, Employee; Self; Livongo. J. C. Wong: Advisory Panel; Self; Provention Bio, Inc., Research Support; Self; Dexcom, Inc., Tandem Diabetes Care. A. B. Neinstein: Consultant; Self; Eli Lilly and Company, Intuity Medical , Medtronic, Roche Diabetes Care, Steady Health.

Objective We examined whether diabetic ketoacidosis (DKA), a serious complication of type 1 diabetes (T1D) was more prevalent among Non-Hispanic (NH) Black and Hispanic patients with T1D and laboratory-confirmed coronavirus disease 2019 (COVID-19) compared with NH Whites. Method This is a cross-sectional study of patients with T1D and laboratory-confirmed COVID-19 from 52 clinical sites in the United States, data were collected from April to August 2020. We examined the distribution of patient factors and DKA events across NH White, NH Black, and Hispanic race/ethnicity groups. Multivariable logistic regression analysis was performed to examine the odds of DKA among NH Black and Hispanic patients with T1D as compared with NH White patients, adjusting for potential confounders, such as age, sex, insurance, and last glycated hemoglobin A1c (HbA1c) level. Results We included 180 patients with T1D and laboratory-confirmed COVID-19 in the analysis. Forty-four percent (n = 79) were NH White, 31% (n = 55) NH Black, 26% (n = 46) Hispanic. NH Blacks and Hispanics had higher median HbA1c than Whites (%-points [IQR]: 11.7 [4.7], P Conclusion We found that among T1D patients with COVID-19 infection, NH Black patients were more likely to present in DKA compared with NH White patients. Our findings demonstrate additional risk among NH Black patients with T1D and COVID-19.

Background: Patient-driven innovation has led to the development of do-it-yourself artificial pancreas systems (DIYAPS) for the management of type 1 diabetes (T1D). There have been few studies comparing glycemic outcomes for DIYAPS compared to conventional sensor-augmented pump (SAP) therapy. Methods: A retrospective double cohort study was performed. The DIY group consisted of people with T1D using DIYAPS (OpenAPS, Loop, and AndroidAPS) who contributed data to the OpenAPS Data Commons. The SAP group included age-matched SAP users whose sensor data was obtained through the Tidepool Big Data Donation Project. The primary outcome of percent of sensor glucoses (SG) in low glucose range (=15-minute hypoglycemic episodes (=180 mg/dL) and in target range (70-180 mg/dL). Results: The DIY group included 90 days of data from 74 individuals with mean age of 36 ± 15 years and 24 ± 16 years since T1D diagnosis. The SAP group had 98 individuals with mean age of 35 ± 14 years and 20 ± 13 years since diagnosis. There was no significant difference in percent of SG =180 mg/dL was lower (16.9% for DIY vs. 26.1% for SAP, p Conclusion: Users of DIYAPS had a comparable amount of hypoglycemia to those using SAP and had less hyperglycemia. This study suggests that the glycemic benefit of DIYAPS is in reducing hyperglycemia without compromising the low occurrence of hypoglycemia. Disclosure J. Zabinsky: None. H. Howell: None. A. Ghezavati: None. D.M. Lewis: Research Support; Self; JDRF. A. Nguyen: None. J.C. Wong: Consultant; Self; pH Pharma. Research Support; Self; Dexcom, Inc. Funding JDRF

Previous studies have shown adolescents with T1D diagnosed prior to menarche have an older age of menarche compared with those diagnosed after menarche and to the general population, and menstrual irregularity in women with T1D is more common than in those without T1D, suggesting that T1D may be associated with reproductive abnormalities. In this study, multiple regression models were used to explore the relationship between clinical factors and markers of reproductive health in 3528 women >18 years (mean age 39±17 years) in the T1D Exchange Clinic Registry who had a 5-year follow-up. Average age of menarche was 13±2 years, and 13% reported irregular menstrual periods unrelated to pregnancy or menopause. Younger age at T1D diagnosis was significantly associated with older age at menarche (p=0.001) after adjustment for race/ethnicity, current BMI, and report of severe hypoglycemia (SH). Having an evaluation for infertility was reported by 6% of participants and was associated with lower mean hemoglobin A1c (A1c; OR 0.79, 95% CI 0.67-0.91 for a 1% increase in A1c) and current use of continuous glucose monitoring (CGM, OR 1.58, 95% CI 1.16-2.16). Seeking an infertility evaluation was not significantly associated with age at T1D diagnosis, autoantibody status, or current menstrual regularity. Additionally, having an abnormal infertility evaluation was not associated with mean A1c (OR 0.85, 95% CI 0.62-1.17) or current use of CGM (OR 1.62, 95% CI 0.91-2.91). There were also no factors that were both clinically and statistically significantly associated with miscarriage or problems conceiving a child. These results suggest that women with T1D who are likely to seek infertility evaluations may be more determined to maintain optimal glycemic control with technology such as CGM, or that concern about fertility may drive the decision to use CGM and lower A1c. This study highlights the need for prospective studies to assess the impact of T1D on fertility in women. Disclosure A. Erkin-Cakmak: None. R. Bailey: None. P. Calhoun: Stock/Shareholder; Self; Dexcom, Inc. H. Cakmak: None. J.C. Wong: Consultant; Self; pH Pharma. Research Support; Self; Dexcom, Inc. Funding The Leona M. and Harry B. Helmsley Charitable Trust (G-2016PG-T1D053)

The use of real-time continuous glucose monitoring (CGM) is on the rise in children with type 1 diabetes (T1D), but little is known about how caregivers respond to high and low sensor glucose (SG) values in a real-world setting. We previously reported results from a cross-sectional survey, distributed throughout the United States, of 169 caregivers of children with T1D using CGM. In the current study, 21 of these participants, who were also using insulin pumps, voluntarily contributed their device data anonymously through the Tidepool platform. Up to 90 days of CGM and pump data per participant were analyzed to determine how caregivers respond to SG levels below and above target range. The children had a mean age of 8.8 ± 3.0 years, were 60% female, were 15% ethnic minority or mixed ethnicity, and had an average hemoglobin A1c of 7.2% ± 0.8%. For these participants in a 90-day period, there were a total of 453,908 CGM values, or a mean of 7205 values per 30 days per participant (mean 2263 to 14,323 values per 30 days for each participant). The average SG was 171.7 ± 29.9 mg/dL, with 57.8% of sensor values between 70-180 mg/dL. The percentage of values in hypoglycemic range (180 mg/dL) was 39.3%. Per 30 days, participants had means of 26.6 ± 30.3 hypoglycemic and 73.7 ± 28.6 hyperglycemic events lasting at least 15 minutes. Glucose values were rarely entered into pumps within 5 minutes of having SG values outside of target range for at least 15 minutes and were entered for 2.7% ± 5.3% of hypoglycemic and 3.0% ± 3.5% of hyperglycemic episodes. In response to high SG lasting at least 15 minutes, an insulin bolus was given 4.7% ± 4.0% of the time within 5 minutes and 59.3% ± 36.8% of the time within 60 minutes. The variable response to hypo- and hyperglycemia suggests further interventions that decrease the need for caregivers to perform active tasks in response to CGM data may help ease management burden and improve time in target range. Disclosure H. Howell: None. B.J. Yeung: None. A. Nguyen: None. J.C. Wong: Consultant; Self; pH Pharma. Research Support; Self; Dexcom, Inc. Funding Dexcom, Inc. (IIS-2017-048)

AIM: To assess the associations between demographic and clinical characteristics and sensor glucose metrics in young children with type 1 diabetes, using masked, continuous glucose monitoring data from children aged 2 to < 8 years. RESEARCH DESIGN AND METHODS: The analysis included 143 children across 14 sites in the USA, enrolled in a separate clinical trial. Eligibility criteria were: age 2 to 10.0 mmol/l) and a median of ~1 h/day in hypoglycaemia (

BackgroundDiabetes devices provide data for health care providers (HCPs) and people with type 1 diabetes to make management decisions. Extracting and viewing the data require separate, proprietary software applications for each device. In this pilot study, we examined the feasibility of using a single software platform (Tidepool) that integrates data from multiple devices.Materials and methodsParticipating HCPs (n = 15) used the software with compatible devices in all patient visits for 6 months. Samples of registration desk activity and office visits were observed before and after introducing the software, and HCPs provided feedback by survey and focus groups.ResultsThe time required to upload data and the length of the office visit did not change. However, the number of times the HCP referred to the device data with patients increased from a mean of 2.8 (±1.2) to 6.1 (±3.1) times per visit (P = 0.0002). A significantly larger proportion of children looked at the device data with the new application (baseline: 61% vs. study end: 94%, P = 0.015). HCPs liked the web-based user interface, integration of the data from multiple devices, the ability to remotely access data, and use of the application to initiate patient education. Challenges included the need for automated data upload and integration with electronic medical records.ConclusionsThe software did not add to the time needed to upload data or the length of clinic visits and promoted discussions with patients about data. Future studies of HCP use of the application will evaluate clinical outcomes and effects on patient engagement and self-management.

OBJECTIVES: The primary objective was to investigate the mediating effects of diabetes management in the relationship between diabetes symptoms and generic health-related quality of life (HRQOL) in adolescents and young adults (AYAs) with type 1 diabetes. The secondary objective explored patient health communication and perceived treatment adherence barriers as mediators in a serial multiple mediator model. METHODS: The PedsQL 3.2 Diabetes Module 15-item diabetes symptoms summary score, 18-item diabetes management summary score, and PedsQL 4.0 generic core scales were completed in a 10-site national field test study by 418 AYA aged 13 to 25 years with type 1 diabetes. Diabetes symptoms and diabetes management were tested for bivariate and multivariate linear associations with overall generic HRQOL. Mediational analyses were conducted to test the hypothesized mediating effects of diabetes management as an intervening variable between diabetes symptoms and generic HRQOL. RESULTS: The predictive effects of diabetes symptoms on HRQOL were mediated in part by diabetes management. In predictive analytics models utilizing multiple regression analyses, demographic and clinical covariates, diabetes symptoms, and diabetes management significantly accounted for 53% of the variance in generic HRQOL (P < 0.001), demonstrating a large effect size. Patient health communication and perceived treatment adherence barriers were significant mediators in an exploratory serial multiple mediator model. CONCLUSIONS: Diabetes management explains in part the effects of diabetes symptoms on HRQOL in AYA with type 1 diabetes. Patient health communication to healthcare providers and perceived treatment adherence barriers further explain the mechanism in the relationship between diabetes symptoms and overall HRQOL.

The objective was to investigate the patient-reported diabetes symptoms predictors of generic health-related quality of life (HRQOL) in adolescents and young adults (AYA) with type 1 or type 2 diabetes. The 15-item PedsQL™ 3.2 Diabetes Module Diabetes Symptoms Summary Score and PedsQL™ 4.0 Generic Core Scales were completed in a 10-site national field test study by 513 AYA ages 13–25 years with type 1 (n = 424) or type 2 (n = 89) diabetes. Diabetes symptoms were tested for bivariate and multivariate linear associations with generic HRQOL. Diabetes symptoms were associated with decreased HRQOL in bivariate analyses. In predictive analytics models utilizing hierarchical multiple regression analyses controlling for relevant demographic and clinical covariates, diabetes symptoms accounted for 38 and 39% of the variance in patient-reported generic HRQOL for type 1 and type 2 diabetes, respectively, reflecting large effect sizes. The diabetes symptoms facets hyperglycemia symptoms, hypoglycemia symptoms, and nonspecific diabetes symptoms individually accounted for a significant percentage of the variance in separate exploratory predictive analytics models after controlling for demographic and clinical covariates, with small-to-large effect sizes. Diabetes symptoms are potentially modifiable predictors of generic HRQOL in AYA with diabetes. Identifying specific diabetes symptoms or symptoms facets that are the most important predictors from the patient perspective facilitates a patient-centered approach in clinical research, clinical trials, and practice designed to enhance overall generic HRQOL in AYA with diabetes.

© 2016 Diabetes Technology Society. The purpose of developing mobile applications for diabetes is generally to: (1) provide enhanced access to timely information for patients, health care professionals, and researchers; (2) facilitate remote monitoring and diagnosis of patients, often based on information delivered by wearable devices; (3) provide decision support to assist patients in selecting treatment; or (4) deliver timely recommendations for treatment to increase adherence to prescribed therapy. There is a perception that mobile applications can provide meaningful clinical benefits, however, there is only sparse convincing evidence to support this belief at the present time. Compounding this problem is the short life span of digital software, such that if a traditional type of randomized controlled trial is conducted on a product, by the time the study has been designed, approved by an IRB, conducted, and analyzed, the product might have significantly changed to a next generation system. Because of great interest in establishing what are the potential benefits, metrics of success, and appropriate components of mobile applications for diabetes, Diabetes Technology Society and William Sansum Diabetes Center launched the Digital Diabetes Congress, March 7-8, 2017, in San Francisco. This report contains summaries of the meeting's 12 sessions. Each summary was written by the session's moderator who helped develop the session prior to the event and keep it on track during the event. This meeting report presents a summary of how 57 panelists, speakers, and moderators, who are leaders in digital health, see the current and future landscape of digital health tools applied to diabetes.

Continuous glucose monitoring (CGM) improves glycemic outcomes in children with type 1 diabetes (T1D) and is recommended for regular use. However, it is unclear how families use CGM and if they are using it to its greatest potential. In this study, 193 caregivers of children with T1D using CGM (mean age 9.3±2.8 years, 44% female, 10% ethnic minority, 92% using insulin pump) were recruited throughout the United States by social media to complete a cross-sectional survey about their real-time CGM use. Many children (70%) wore the sensor “all of the time,” with 77% using CGM ≥22 of the last 30 days. Most caregivers (93%) had a CGM feature to see their child’s data remotely in real time; 87% of those who used this feature viewed their child’s data at least once a day when their child was not with them. Though nearly all knew about CGM alert functions, only 73% set alerts for hyperglycemia and 80% for hypoglycemia “all the time.” Frequent retrospective review of CGM data was less common, with only 64% uploading and reviewing data at least monthly. Since starting CGM, most caregivers reported a decrease in their child’s glycated hemoglobin (A1c) (64%) and reduced frequency and severity of hypoglycemia (78%) and hyperglycemia (72%). In regression analysis (adjusted for age, duration of T1D, gender, minority status, caregiver education, geographic region, and pump use), younger age was associated with decrease in A1c (OR 0.78, 95% CI 0.67, 0.92) and decrease in hyperglycemia (OR 0.70, 95% CI 0.58, 0.84). Longer duration of CGM use was associated with decrease in hypoglycemia (OR 2.0, 95% CI 1.0, 4.1). Seventy-two percent reported CGM is “essential,” and 53% felt the greatest benefit is seeing data in real time. In summary, caregivers utilize real-time CGM functions (remote monitoring, alerts) more frequently than they retrospectively review data. Future studies should focus on how caregivers use real-time and retrospective CGM data to make T1D management decisions in order to optimize use of the technology. Disclosure J.C. Wong: Advisory Panel; Self; Tidepool Project. Research Support; Self; Dexcom, Inc. F. Abdulhussein: None. B.J. Yeung: None. E.J. Velazquez: None. Funding Dexcom, Inc.

Background: A novel software application, Blip, was created to combine and display diabetes data from multiple devices in a uniform, user-friendly manner. The objective of this study was to test the usability of this application by adults and caregivers of children with type 1 diabetes (T1D). Methods: Patients (n = 35) and caregivers of children with T1D (n = 30) using an insulin pump for >1 year ± CGM were given access to the software for 3 months. Diabetes management practices and the use of diabetes data were assessed at baseline and at study end, and feedback was gathered in a concluding questionnaire. Results: At baseline, 97% of participants agreed it was important for patients to know how to interpret glucose data. Most felt that clinicians and patients should share the tasks of reviewing data, finding patterns, and making changes to their insulin plans. However, despite valuing shared responsibility, at baseline, 43% of participants never downloaded pump data, and only 9% did so at least once per month. At study end, 72% downloaded data at least once during the 3-month study, and 38% downloaded at least once per month. Regarding the software application, participants liked the central repository of data and the user interface. Suggestions included providing tools for understanding and interpreting glucose patterns, an easier uploading process, and access with mobile devices. Conclusions: Collaboration between developers and researchers prompted iterative, rapid development of data visualization software and improvements in the uploading process and user interface, which facilitates clinical integration and future clinical studies.

Aim To test the measurement properties of the revised and updated Pediatric Quality of Life Inventory (PedsQL) 3.2 Diabetes Module originally developed in Type 1 diabetes in youth with Type 2 diabetes. Methods The PedsQL 3.2 Diabetes Module and PedsQL Generic Core Scales were administered in a field test study to 100 young people aged 9-25 years with Type 2 diabetes. Factor analysis was conducted to determine the factor structure of the items. Results The 15-item Diabetes Symptoms Summary Score and 12-item Type 2-specific Diabetes Management Summary Score were empirically derived through factor analysis. The Diabetes Symptoms and Type 2-specific Diabetes Management Summary Scores showed acceptable to excellent reliability across the age groups tested (α = 0.85-0.94). The Diabetes Symptoms and Type 2-specific Diabetes Management Summary Scores evidenced construct validity through large effect size correlations with the Generic Core Scales Total Scale Score (r = 0.67 and 0.57, respectively). HbA1c was correlated with the Diabetes Symptoms and Type 2-specific Diabetes Management Summary Scores (r = -0.13 and -0.22). Minimal clinically important difference (MCID) scores were 5.91 and 7.39 for the Diabetes Symptoms and Type 2-specific Diabetes Management Summary Scores. Conclusions The PedsQL 3.2 Diabetes Module Diabetes Symptoms Summary Score and Type 2-specific Diabetes Management Summary Score exhibited satisfactory measurement properties for use as youth self-reported diabetes symptoms and diabetes management outcomes for clinical research and clinical practice for young people with Type 2 diabetes.

OBJECTIVE The objective of the study was to report on the measurement properties of the revised and updated Pediatric Quality of Life Inventory (PedsQL) 3.2 Diabetes Module for children, adolescents, and young adults with type 1 diabetes. RESEARCH DESIGN AND METHODS The 33-item PedsQL 3.2 Diabetes Module and PedsQL Generic Core Scales were completed in a 10-site national field test study by 656 families of patients ages 2–25 years with type 1 diabetes. RESULTS The 15-item Diabetes Symptoms Summary Score and 18-item Diabetes Management Summary Score were derived from the factor analysis of the items. The Diabetes Symptoms and Diabetes Management Summary Scores evidenced excellent reliability (patient self-report α = 0.88–0.90; parent proxy report α = 0.89–0.90). The Diabetes Symptoms and Diabetes Management Summary Scores demonstrated construct validity through medium to large effect size correlations with the Generic Core Scales Total Scale Score (r = 0.43–0.67, P < 0.001). HbA1c was significantly correlated with the Diabetes Symptoms and Diabetes Management Summary Scores (r = −0.21 to −0.29, P < 0.001). Minimal clinically important difference scores ranged from 5.05 to 5.55. CONCLUSIONS The PedsQL 3.2 Diabetes Module Diabetes Symptoms and Diabetes Management Summary Scores demonstrated excellent measurement properties and may be useful as standardized patient-reported outcomes of diabetes symptoms and diabetes management in clinical research, clinical trials, and practice in children, adolescents, and young adults with type 1 diabetes.

Glucose meters, insulin pumps, and continuous glucose monitoring systems provide data needed for people with type 1 diabetes to modify insulin regimens, evaluate lifestyle changes, or troubleshoot unexpected glucose levels. Health care providers (HCPs) can use device-specific software to review data at patient visits, often using separate, proprietary applications for each device. Using mixed qualitative and quantitative methods, we examined the feasibility of using the Tidepool platform and web application to view diabetes data from multiple devices together, in a multidisciplinary pediatric diabetes center where it was standard practice to upload and view data using device-specific software for each patient visit. Participating HCPs (n=15) used the software with compatible devices in all patient visits for 6 months. To evaluate the effect of the application on workflow, registration desk activity and office visits were observed before and after introducing the software, and HCPs provided feedback by survey and focus groups. The time required to upload device data and the length of the office visit did not change. However, the number of times the provider referred to the device data with patients increased from a mean of 2.8 (±1.2) to 6.1 (±3.1) times per observed visit (p=0.0002). A significantly larger proportion of the children looked at the device data with the new application (61% at baseline vs. 94% at study end, p=0.015). HCPs liked the use of color to indicate glucose levels, the graphical web-based user interface, integration of the data in one application, and the ability to remotely access data via the web for telehealth. They found the application most useful for initiating patient conversations and education. Remaining challenges include the need for automated data upload and integration with electronic medical records. Future studies of HCP use of the application will focus on clinical outcomes and effects on patient engagement and self-management. Disclosure J.C. Wong: Research Support; Self; Dexcom, Inc.. Other Relationship; Self; Tidepool Project. Z. Izadi: None. S.M. Schroeder: None. M. Nader: None. H.J. Min: None. A.B. Neinstein: None. S. Adi: Stock/Shareholder; Spouse/Partner; Dexcom, Inc.. Speaker's Bureau; Self; Dexcom, Inc.. Board Member; Self; Tidepool Project. Other Relationship; Self; Novo Nordisk Inc..

The American Association of Clinical Endocrinologists/American College of Endocrinology and Endocrine Society guidelines on insulin pump use emphasize patient assessment to determine pump readiness for patients with type 1 diabetes (T1D). While guidelines mention the importance of the clinical practice context, such as the presence of a comprehensive pump management program and prescribing provider expertise in pump therapy, primary emphasis is placed on the measurement of patient knowledge of diabetes management, their mental and psychological status, and adherence to self-care. But how clinics define and assess “pump readiness” is not standardized, and the extent to which this process is linked to systematic differences in the allocation of healthcare technologies by race and class is unclear. In this comparative qualitative study, we describe how two ADA recognized pediatric endocrinology centers with different prevalences of patient pump use (32% vs. 77% of patients with T1D) also differ in how they determine pump readiness. In the clinic with higher overall pump use, there are no differences in frequency of pump use between non-Hispanic white and ethnic minority patients, and differences by insurance status are small. In contrast, in the clinic with lower overall pump use, there are large differences in pump use by race and insurance status. To explore these trends, we conducted over 400 hours of observations of clinical encounters and decision-making processes and fifteen 30-minute interviews with pediatric endocrinologists, nurses, certified diabetes educators, and other staff and coded the data using Atlas.ti. Findings suggest pump allocation is shaped by how: 1) providers respond to patient “cultural capital” or interaction styles, 2) clinics frame and engage with medical technologies (e.g., “pro-tech” practices such as ongoing provider and patient education to support new devices), and 3) clinics organize provider care and decision making processes (e.g., professional opinion vs. use of metrics). Disclosure C. Puckett: None. J.C. Wong: Research Support; Self; Dexcom, Inc.. Other Relationship; Self; Tidepool Project.

Objective Develop a device-agnostic cloud platform to host diabetes device data and catalyze an ecosystem of software innovation for type 1 diabetes (T1D) management. Materials and Methods An interdisciplinary team decided to establish a nonprofit company, Tidepool, and build open-source software. Results Through a user-centered design process, the authors created a software platform, the Tidepool Platform, to upload and host T1D device data in an integrated, device-agnostic fashion, as well as an application (“app”), Blip, to visualize the data. Tidepool’s software utilizes the principles of modular components, modern web design including REST APIs and JavaScript, cloud computing, agile development methodology, and robust privacy and security. Discussion By consolidating the currently scattered and siloed T1D device data ecosystem into one open platform, Tidepool can improve access to the data and enable new possibilities and efficiencies in T1D clinical care and research. The Tidepool Platform decouples diabetes apps from diabetes devices, allowing software developers to build innovative apps without requiring them to design a unique back-end (e.g., database and security) or unique ways of ingesting device data. It allows people with T1D to choose to use any preferred app regardless of which device(s) they use. Conclusion The authors believe that the Tidepool Platform can solve two current problems in the T1D device landscape: 1) limited access to T1D device data and 2) poor interoperability of data from different devices. If proven effective, Tidepool’s open source, cloud model for health data interoperability is applicable to other healthcare use cases.

The prevalence of cardiovascular risk factors in children with type 1 diabetes and elevated BMI in the USA is poorly defined. We aimed to test the hypothesis that children with type 1 diabetes who are overweight or obese have increased frequencies of hypertension, dyslipidemia, and micro-/macroalbuminuria compared to their healthy weight peers. We studied 11,348 children 2 to

Few studies have explored durability of insulin pump use, and none have explored the link between depression and pump discontinuation. To examine the relationship between depressive symptoms [measured by the Children's Depression Inventory (CDI)], method of insulin delivery, and hemoglobin A1c (A1c), mixed models were used with data from 150 adolescents with type 1 diabetes (T1D) and visits every 6 months for 2 years. Of the 63% who used a pump, compared with multiple daily injections (MDI) at baseline, there were higher proportions who were non-minorities, had caregivers with a college degree, private insurance, and two caregivers in the home (p ≤ 0.01). After adjusting for time, sex, age, T1D duration, frequency of blood glucose monitoring, ethnicity, insurance, and caregiver number and education, baseline pump use was associated with -0.79% lower mean A1c [95% confidence interval (CI): -1.48, -0.096; p = 0.03]. For those using a pump at baseline, but switching to MDI during the study (n = 9), mean A1c was 1.38% higher (95% CI: 0.68, 2.08; p < 0.001) than that for those who did not switch method of delivery. A 10-point increase in CDI was associated with a 0.39% increase in A1c (95% CI: 0.16, 0.61; p = 0.001), independent of pump use. Regarding the temporal relationship between CDI score and changing method of insulin delivery, prior higher CDI score was associated with switching from pump to MDI (odds ratio = 1.21; 95% CI: 1.05, 1.39; p = 0.007). Clinicians should be aware of the associations between depressive symptoms, change in insulin delivery method, and the effect on glycemic control.

OBJECTIVE To assess the frequency of continuous glucose monitoring (CGM) device use, factors associated with its use, and the relationship of CGM with diabetes outcomes (HbA1c, severe hypoglycemia [SH], and diabetic ketoacidosis [DKA]). RESEARCH DESIGN AND METHODS Survey questions related to CGM device use 1 year after enrollment in the T1D Exchange clinic registry were completed by 17,317 participants. Participants were defined as CGM users if they indicated using real-time CGM during the prior 30 days. RESULTS Nine percent of participants used CGM (6% of children CONCLUSIONS CGM use is uncommon but associated with lower HbA1c in some age-groups, especially when used more frequently. Factors associated with discontinuation and infrequent use of retrospective analysis of CGM data should be considered in developing next-generation devices and education on CGM use.

Objectives Optimizing glycemic control in pediatric type 1 diabetes (T1D) is essential to minimizing long-term risk of complications. We used the T1D Exchange database from 58 US diabetes clinics to identify differences in diabetes management characteristics among children categorized as having excellent vs. poor glycemic control.

Objective Severe hypoglycemia (SH) and diabetic ketoacidosis (DKA) are common serious acute complications of type 1 diabetes (T1D). The aim of this study was to determine the frequency of SH and DKA and identify factors related to their occurrence in the T1D Exchange pediatric and young adult cohort. Research design and methods The analysis included 13 487 participants in the T1D Exchange clinic registry aged 2 to

Background: The objectives of this study were to examine factors associated with insulin pump discontinuation among children and adults followed longitudinally for 1 year in the multicenter T1D Exchange clinic registry, and to provide participant-reported reasons for stopping pump therapy. Methods: We longitudinally followed 8935 participants of all ages using an insulin pump at the time of registry enrollment. Logistic regressions were used to identify demographic and clinical factors associated with pump discontinuation. Pump discontinuation was self-reported by participants on a first annual follow-up survey. Results: The overall frequency of pump discontinuation was 3%. Discontinuation was higher in adolescents (4%) and young adults (4%) than in younger children (3%) or older adults (1%). In multivariate analysis of children between 6 and Conclusions: In T1D Exchange registry participants, insulin pump discontinuation is uncommon, but more prevalent among adolescents and young adults, and youth with poor glycemic control. Given the known benefits of pump therapy, these populations should be targeted for support and education on troubleshooting pump use. Common reasons for discontinuation should also be considered in future device design and technological improvement.

BackgroundIn type 1 diabetes (T1D), periodic review of blood glucose and insulin dosing should be performed, but it is not known how often patients review these data on their own. We describe the proportion of patients with T1D who routinely downloaded and reviewed their data at home.Materials and methodsA cross-sectional survey of 155 adults and 185 caregivers of children with T1D at a single academic institution was performed. "Routine Downloaders" (downloaded four or more times in the past year) were also considered "Routine Reviewers" if they reviewed their data most of the time they downloaded from devices. Logistic regression was used to identify factors associated with being a Routine Reviewer.ResultsOnly 31% of adults and 56% of caregivers reported ever downloading data from one or more devices, whereas 20% and 40%, respectively, were considered Routine Downloaders. Only 12% of adults and 27% of caregivers were Routine Reviewers. Mean hemoglobin A1c was lower in Routine Reviewers compared with non-Routine Reviewers (7.2±1.0% vs. 8.1±1.6% [P=0.03] in adults and 7.8±1.4% vs. 8.6±1.7% [P=0.001] in children). In adjusted analysis of adults, the odds ratio of being a Routine Reviewer of one or more devices for every 10-year increase in age was 1.5 (95% confidence interval, 1.1, 2.1 [P=0.02]). For every 10 years since diabetes diagnosis, the odds ratio of being a Routine Reviewer was 1.7 (95% confidence interval, 1.2, 2.4 [P=0.01]). For caregivers, there were no statistically significant factors associated with being a Routine Reviewer.ConclusionsA minority of T1D patients routinely downloads and reviews data from their devices on their own. Further research is needed to understand obstacles, provide better education and tools for self-review, and determine if patient self-review is associated with improved glycemic control.

The impressive progress achieved in recent years in diabetes technologies has made diabetes technological devices such as continuous subcutaneous insulin infusion (CSII) and continuous glucose monitoring (CGM) a significant part of diabetes treatment. Many studies conducted in recent years emphasized the advantages of using these technologies. The concept of the “human factor” in diabetes technologies as discussed in this chapter has several different aspects. First, it can refer to the way patients are satisfied with the use of the device and whether it is perceived convenient or inconvenient. For example, is the device perceived as “user friendly” (easy to learn and to operate, comfortable, does not cause many hassles). Second, there is the issue of effectiveness of the technology as it relates to their day-to-day diabetes management. For example, there is an improvement in glycemic control when one diabetes treatment regimen is compared to another (i.e., CSII vs. multiple daily injections (MDI)). Those two fundamental aspects may have different meanings for different groups. For example, different age groups (toddlers, children, adolescents, young adults, adults, and older people) can see different advantages and disadvantages in technological devices. The feasibility and utility of technological devices also need to fit the environments in which they will be used, such as school, the work place, and/or home. Specific subgroups such as diabetic youth with eating disorders can have unique interactions with diabetes technologies. In addition, diabetes technologies can be used as a measurement device, providing more rich and accurate data about patients' self-care that can contribute to our understanding of concepts such as adherence and satisfaction, and they can provide measurement tools to assess how glycemic control can effect cognition and intelligence. The present chapter will review articles published in the last year that have studied some of these issues.

We thank Price et al. (1) for their comments on our recent article exploring use of continuous glucose monitoring (CGM) in the T1D Exchange Clinic Network registry (2). We acknowledge, as we did in the original article, that the experience of participants included in our study was based on older generations of CGM devices and agree with Price et al. that newer generations …