Institutional role conflict in the digital age: The case of diabetes management at school.

As the prevalence of pediatric diabetes grows and new technologies to manage diabetes emerge, there is increasing concern about consistency in health management across institutional settings, particularly in schools. While much is known about barriers at school, there are still gaps in understanding the institutional dynamics that shape health management in this setting. Using focus groups with 19 youth with type 1 diabetes (T1D) and applying institutional role theory, we find healthcare providers' recommendations conflict with school rules and norms, making it difficult to enact both the "sick role" and the "student role." These conflicts elicit negative responses from teachers and peers and stigmatize youth with T1D in school. Caregiver involvement often heightens rather than ameliorates conflict and teachers do not intervene in effective ways. Ultimately, youth must manage conflicts and stigma. By reframing challenges in health management as institutional role conflict, this paper contributes to sociological research by highlighting the importance of institutional roles, especially beyond healthcare. More broadly, the study suggests health research and policy should investigate how to better align institutional roles-rather than relying on youth and their families-to support health management of chronic illnesses across institutional settings.

Long-term Continuous Glucose Monitor Use in Very Young Children With Type 1 Diabetes: One-Year Results From the SENCE Study.

OBJECTIVES: Achieving optimal glycemic outcomes in young children with type 1 diabetes (T1D) is challenging. This study examined the durability of continuous glucose monitoring (CGM) coupled with a family behavioral intervention (FBI) to improve glycemia. STUDY DESIGN: This one-year study included an initial 26-week randomized controlled trial of CGM with FBI (CGM+FBI) and CGM alone (Standard-CGM) compared with blood glucose monitoring (BGM), followed by a 26-week extension phase wherein the BGM Group received the CGM+FBI (BGM-Crossover) and both original CGM groups continued this technology. RESULTS: Time in range (70-180 mg/dL) did not improve with CGM use (CGM+FBI: baseline 37%, 52 weeks 41%; Standard-CGM: baseline 41%, 52 weeks 44%; BGM-Crossover: 26 weeks 38%, 52 weeks 40%). All three groups sustained decreases in hypoglycemia (<70 mg/dL) with CGM use (CGM+FBI: baseline 3.4%, 52 weeks 2.0%; Standard-CGM: baseline 4.1%, 52 weeks 2.1%; BGM-Crossover: 26 weeks 4.5%, 52 weeks 1.7%, P-values <.001). Hemoglobin A1c was unchanged with CGM use (CGM+FBI: baseline 8.3%, 52 weeks 8.2%; Standard-CGM: baseline 8.2%, 52 weeks 8.0%; BGM-Crossover: 26 weeks 8.1%, 52 weeks 8.3%). Sensor use remained high (52-week study visit: CGM+FBI 91%, Standard-CGM 92%, BGM-Crossover 88%). CONCLUSION: Over 12 months young children with T1D using newer CGM technology sustained reductions in hypoglycemia and, in contrast to prior studies, persistently wore CGM. However, pervasive hyperglycemia remained unmitigated. This indicates an urgent need for further advances in diabetes technology, behavioral support, and diabetes management educational approaches to optimize glycemia in young children.

Real-Time Continuous Glucose Monitoring in Adolescents and Young Adults With Type 2 Diabetes Can Improve Quality of Life.

OBJECTIVE: Real-time continuous glucose monitoring (CGM) is effective for diabetes management in cases of type 1 diabetes and adults with type 2 diabetes (T2D) but has not been assessed in adolescents and young adults (AYAs) with T2D. The objective of this pilot interventional study was to assess the feasibility and acceptability of real-time CGM use in AYAs with T2D. METHODS: Adolescents and young adults (13-21 years old) with T2D for six months or more and hemoglobin A1c (A1c) greater than 7%, on any Food and Drug Administration-approved treatment regimen, were included. After a blinded run-in period, participants were given access to a real-time 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: Participants' (n = 9) median age was 19.1 (interquartile range [IQR] 16.8-20.5) years, 78% were female, 100% were people of color, and 67% were publicly insured. Baseline A1c was 11.9% (standard deviation ±2.8%), with median diabetes duration of 2.5 (IQR 1.4-6) years, and 67% were using insulin. Seven participants completed the study and demonstrated statistically significant improvement in diabetes-related quality of life, with the mean Pediatric Quality of Life inventory (PedsQL) diabetes score increasing from 70 to 75 after using CGM (P = .026). Focus group results supported survey results that CGM use among AYAs with T2D is feasible, can improve quality of life, and has the potential to modify behavior. CONCLUSION: Real-time CGM is feasible and acceptable for AYAs with T2D and may improve the quality of life of patients with diabetes. Larger randomized controlled trials are needed to assess the effects on glycemic control and healthy lifestyle changes.

Comorbidities increase COVID-19 hospitalization in young people with type 1 diabetes.

OBJECTIVES: We evaluated COVID-19 outcomes in children and young adults with type 1 diabetes (T1D) to determine if those with comorbidities are more likely to experience severe COVID-19 compared to those without. RESEARCH DESIGN AND METHODS: This cross-sectional study included questionnaire data on patients <25 years of age with established T1D and laboratory-confirmed COVID-19 from 52 sites across the US between April 2020 and October 2021. We examined patient factors and COVID-19 outcomes between those with and without comorbidities. Multivariate logistic regression analysis examined the odds of hospitalization among groups, adjusting for age, HbA1c, race and ethnicity, insurance type and duration of diabetes. RESULTS: Six hundred fifty-one individuals with T1D and COVID-19 were analyzed with mean age 15.8 (SD 4.1) years. At least one comorbidity was present in 31%, and more than one in 10%. Obesity and asthma were the most frequently reported comorbidities, present in 19% and 17%, respectively. Hospitalization occurred in 17% of patients and 52% of hospitalized patients required ICU level care. Patients with at least one comorbidity were almost twice as likely to be hospitalized with COVID-19 than patients with no comorbidities (Odds ratio 2.0, 95% CI: 1.3-3.1). This relationship persisted after adjusting for age, HbA1c, race and ethnicity (minority vs nonminority), insurance type (public vs. private), and duration of diabetes. CONCLUSIONS: Our findings show that comorbidities increase the risk for hospitalization with COVID-19 in children and young adults highlighting the need for tailored COVID-19 prevention and treatment strategies in T1D.

Improving the Patient Experience With Longer Wear Infusion Sets Symposium Report.

Continuous subcutaneous insulin infusion (CSII) therapy is becoming increasingly popular. CSII provides convenient insulin delivery, precise dosing, easy adjustments for physical activity, stress, or illness, and integration with continuous glucose monitors in hybrid or other closed-loop systems. However, even as insulin pump hardware and software have advanced, technology for insulin infusion sets (IISs) has stayed relatively stagnant over time and is often referred to as the "Achilles heel" of CSII. To discuss barriers to insulin pump therapy and present information about advancements in, and results from clinical trials of extended wear IISs, Diabetes Technology Society virtually hosted the "Improving the Patient Experience with Longer Wear Infusion Sets Symposium" on December 1, 2021. The symposium featured experts in the field of IISs, including representatives from Steno Diabetes Center Copenhagen, University of California San Francisco, Stanford University, Medtronic Diabetes, and Science Consulting in Diabetes. The webinar's seven speakers covered (1) advancements in insulin pump therapy, (2) efficacy of longer wear infusion sets, and (3) innovations to reduce plastics and insulin waste.

Youth with Type 1 Diabetes Had Improvement in Continuous Glucose Monitoring Metrics During the COVID-19 Pandemic.

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.

Diabetic ketoacidosis drives COVID-19 related hospitalizations in children with type 1 diabetes.

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 <19 years with COVID-19 were reported. Diabetic ketoacidosis (DKA) was the most common adverse outcome (n = 44, 72% of hospitalized patients). There were four hospitalizations for severe hypoglycemia, three hospitalizations requiring respiratory support (one of whom was intubated and mechanically ventilated), one case of multisystem inflammatory syndrome in children, and 10 patients who were hospitalized for reasons unrelated to COVID-19 or diabetes. Hospitalized patients (n = 61) were more likely than nonhospitalized patients (n = 205) to have minority race/ethnicity (67% vs 39%, P < 0.001), public insurance (64% vs 41%, P < 0.001), higher A1c (11% [97 mmol/mol] vs 8.2% [66 mmol/mol], P < 0.001), and lower insulin pump and lower continuous glucose monitoring use (26% vs 54%, P < 0.001; 39% vs 75%, P < 0.001). Age and gender were not associated with risk of hospitalization. Higher A1c was significantly associated with hospitalization, with an odds ratio of 1.56 (1.34-1.84) after adjusting for age, gender, insurance, and race/ethnicity. CONCLUSIONS: Higher A1c remained the only predictor for hospitalization with COVID-19. Diabetic ketoacidosis is the primary concern among this group.

Inequities in Diabetic Ketoacidosis Among Patients With Type 1 Diabetes and COVID-19: Data From 52 US Clinical Centers.

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 < 0.001, and 9.7 [3.1] vs 8.3 [2.4], P = 0.01, respectively). We found that more NH Black and Hispanic presented with DKA compared to Whites (55% and 33% vs 13%, P < 0.001 and P = 0.008, respectively). After adjusting for potential confounders, NH Black patients continued to have greater odds of presenting with DKA compared with NH Whites (OR [95% CI]: 3.7 [1.4, 10.6]). 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.

Comparison of Insulin Pump Bolus Calculators Reveals Wide Variation in Dose Recommendations.

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.

How organizations shape medical technology allocation: Insulin pumps and pediatric patients with type 1 diabetes.

Although guidelines for prescribing insulin pumps to patients with type 1 diabetes (T1D) focus on patient assessment, sociological research shows decision-making is influenced by the organizations within which actors are embedded. However, how organizational context shapes unequal resource allocation by race and class is less well understood. To investigate this, we compare two pediatric endocrinology centers differing in racial and socio-economic equity in pump use. Using over 400 h of observations and 16 provider interviews, we find allocation is shaped by how organizations use patient cultural health capital to determine pump eligibility, frame technology use, and structure decision-making processes. Overall, findings extend health inequalities research by describing how organizations shape technology resource allocation by race and class.

A Pilot Study of Use of a Software Platform for the Collection, Integration, and Visualization of Diabetes Device Data by Health Care Providers in a Multidisciplinary Pediatric Setting.

BACKGROUND: Diabetes 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 METHODS: Participating 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. RESULTS: The 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. CONCLUSIONS: The 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.

PedsQL 3.2 Diabetes Module for Children, Adolescents, and Young Adults: Reliability and Validity in Type 1 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.

Diabetes management mediating effects between diabetes symptoms and health-related quality of life in adolescents and young adults with type 1 diabetes.

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.

Diabetes symptoms predictors of health-related quality of life in adolescents and young adults with type 1 or type 2 diabetes.

OBJECTIVES: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Digital Diabetes Congress 2017.

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.

Pilot Study of a Novel Application for Data Visualization in Type 1 Diabetes.

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.

Evaluation of Pump Discontinuation and Associated Factors in the T1D Exchange Clinic Registry.

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 <13 and 13 and <18 years, participants who discontinued pump use were more likely to have higher HbA1c levels at baseline (adjusted P < .001 for both). The top participant-reported reasons for discontinuing the pump included problems with wearability (57%), disliking the pump or feeling anxious (44%), and problems with glycemic control (30%). 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.

Prevalence of cardiovascular risk factors in youth with type 1 diabetes and elevated body mass index.

AIM: 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. METHODS: We studied 11,348 children 2 to <18 years of age enrolled in T1D Exchange between September 2010 and August 2012 with type 1 diabetes for ≥1 year and BMI ≥ 5th age-/sex-adjusted percentile (mean age 12 years, 49 % female, 78 % non-Hispanic White). Overweight and obesity were defined based on Centers for Disease Control and Prevention criteria. Diagnoses of hypertension, dyslipidemia, and micro-/macroalbuminuria were obtained from medical records. Logistic and linear regression models were used to assess factors associated with weight status. RESULTS: Of the 11,348 participants, 22 % were overweight and 14 % obese. Hypertension and dyslipidemia were diagnosed in 1.0 % and 3.8 % of participants, respectively; micro-/macroalbuminuria was diagnosed in 3.8 % of participants with available data (n = 7,401). The odds of either hypertension or dyslipidemia were higher in obese than healthy weight participants [OR 3.5, 99 % confidence interval (CI) 2.0-6.1 and 2.2, 99 % CI 1.6-3.1, respectively]. Obese participants tended to be diagnosed with micro-/macroalbuminuria less often than healthy weight participants (OR 0.6, 99 % CI 0.4-1.0). CONCLUSIONS: Obese children with type 1 diabetes have a higher prevalence of hypertension and dyslipidemia than healthy weight children with type 1 diabetes. The possible association of obesity with lower micro-/macroalbuminuria rates warrants further investigation.

A Minority of Patients with Type 1 Diabetes Routinely Downloads and Retrospectively Reviews Device Data.

BACKGROUND: In 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 METHODS: A 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. RESULTS: Only 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. CONCLUSIONS: A 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.