The Glycemia Risk Index Predicts Performance of Diabetes Self-Management Habits in Youth With Type 1 Diabetes Mellitus.

BACKGROUND: The Glycemia Risk Index (GRI) was developed in adults with diabetes and is a validated metric of quality of glycemia. Little is known about the relationship between GRI and type 1 diabetes (T1D) self-management habits, a validated assessment of youths' engagement in habits associated with glycemic outcomes. METHOD: We retrospectively examined the relationship between GRI and T1D self-management habits in youth with T1D who received care from a Midwest pediatric diabetes clinic network. The GRI was calculated using seven days of continuous glucose monitor (CGM) data, and T1D self-management habits were assessed ±seven days from the GRI score. A mixed-effects Poisson regression model was used to evaluate the total number of habits youth engaged in with GRI, glycated hemoglobin A1c (HbA1c), age, race, ethnicity, and insurance type as fixed effects and participant ID as a random effect to account for multiple clinic visits per individual. RESULTS: The cohort included 1182 youth aged 2.5 to 18.0 years (mean = 13.8, SD = 3.5) comprising 50.8% male, 84.6% non-Hispanic White, and 64.8% commercial insurance users across a total of 6029 clinic visits. Glycemia Risk Index scores decreased as total number of habits performed increased, suggesting youth who performed more self-management habits achieved a higher quality of glycemia. CONCLUSIONS: In youth using CGMs, GRI may serve as an easily obtainable metric to help identify youth with above target glycemia, and engagement/disengagement in the T1D self-management habits may inform clinicians with suitable interventions for improving glycemic outcomes.

Utilizing the Glucose and Insulin Response Shape of an Oral Glucose Tolerance Test to Predict Dysglycemia in Children with Overweight and Obesity, Ages 8-18 Years.

Common dysglycemia measurements including fasting plasma glucose (FPG), oral glucose tolerance test (OGTT)-derived 2 h plasma glucose, and hemoglobin A1c (HbA1c) have limitations for children. Dynamic OGTT glucose and insulin responses may better reflect underlying physiology. This analysis assessed glucose and insulin curve shapes utilizing classifications-biphasic, monophasic, or monotonically increasing-and functional principal components (FPCs) to predict future dysglycemia. The prospective cohort included 671 participants with no previous diabetes diagnosis (BMI percentile ≥ 85th, 8-18 years old); 193 returned for follow-up (median 14.5 months). Blood was collected every 30 min during the 2 h OGTT. Functional data analysis was performed on curves summarizing glucose and insulin responses. FPCs described variation in curve height (FPC1), time of peak (FPC2), and oscillation (FPC3). At baseline, both glucose and insulin FPC1 were significantly correlated with BMI percentile (Spearman correlation r = 0.22 and 0.48), triglycerides (r = 0.30 and 0.39), and HbA1c (r = 0.25 and 0.17). In longitudinal logistic regression analyses, glucose and insulin FPCs predicted future dysglycemia (AUC = 0.80) better than shape classifications (AUC = 0.69), HbA1c (AUC = 0.72), or FPG (AUC = 0.50). Further research should evaluate the utility of FPCs to predict metabolic diseases.

Association Between Psychosocial Acuity and Glycemic Control in a Pediatric Type 1 Diabetes Clinic.

PURPOSE: The purpose of this study was to describe the frequency of psychosocial risk and its associations with glycemic levels in youth with type 1 diabetes (T1D) seen by social work staff during regular clinical care. METHODS: A retrospective longitudinal analysis of observational clinical data was conducted. Individuals (1-26 years) with known T1D who were seen at a pediatric diabetes clinic in a US academic medical center between 2014 and 2021 were included. Variables included psychosocial acuity, A1C, and demographic characteristics. Chi-square tests, Wilcoxon rank sum tests, and mixed linear regressions were used to examine associations between demographic variables, psychosocial acuity, and A1C. RESULTS: Of 966 patients, 513 (53.1%) were male, 76 (7.9%) were non-Hispanic Black, and 804 (83.2%) were non-Hispanic White. There was a mean of 6.9 annual social work encounters per patient, with 3 psychosocial domains measured at each visit. Results showed that as psychosocial acuity level increased, glycemic control decreased. There were significant differences in A1C according to race/ethnicity, insurance, age, and psychosocial acuity. CONCLUSIONS: In a real-world clinical population, psychosocial acuity was associated with glycemic control. Presenting for psychosocial issues in their diabetes clinic was associated with reduced glycemic control among youth with T1D. There is an opportunity to connect pediatric patients with appropriate mental health services and psychosocial supports.

Associations between food insecurity and diabetes risk factors in US adolescents in the National Health and Nutrition Examination Survey (NHANES) 2007-2016.

OBJECTIVE: To evaluate the associations between household food insecurity and diabetes risk factors among lower-income US adolescents. DESIGN: Cross-sectional analysis. Household food security status was measured using the 18-item Food Security Survey Module. Simple and multivariable linear and logistic regressions were used to assess the association between food security status and fasting plasma glucose (FPG), oral glucose tolerance test (OGTT), HbA1C and homoeostatic model assessment - insulin resistance (HOMA-IR). The analyses were adjusted for household and adolescent demographic and health characteristics. SETTING: USA. PARTICIPANTS: 3412 US adolescents aged 12-19 years with household incomes ≤300 % of the federal poverty line from the National Health and Nutrition Examination Survey cycles 2007-2016. RESULTS: The weighted prevalence of marginal food security was 15·4 % and of food insecurity was 32·9 %. After multivariate adjustment, adolescents with food insecurity had a 0·04 % higher HbA1C (95 % CI 0·00, 0·09, P-value = 0·04) than adolescents with food security. There was also a significant overall trend between severity of food insecurity and higher HbA1C (Ptrend = 0·045). There were no significant mean differences in adolescents' FPG, OGTT or HOMA-IR by household food security. CONCLUSIONS: Food insecurity was associated with slightly higher HbA1c in a 10-year sample of lower-income US adolescents aged 12-19 years; however, other associations with diabetes risk factors were not significant. Overall, this suggests slight evidence for an association between food insecurity and diabetes risk in US adolescents. Further investigation is warranted to examine this association over time.

Weight Loss Treatment and Longitudinal Weight Change Among Primary Care Patients With Obesity.

Importance: Among individuals with obesity, 5% or greater weight loss can improve health. Weight management treatments (WMT) include nutrition counseling, very low-calorie meal replacement (MR), antiobesity medications (AOM), and bariatric surgery; however, little is known about how these WMT are associated with weight change among individual patients and populations. Objective: To characterize weight status and WMT use among primary care patients and assess associations between WMT and weight trajectories. Design, Setting, and Participants: Retrospective, population-based cohort study of primary care patients from 1 academic health system in Michigan between October 2015 and March 2020 using cross-sectional analysis to compare obesity prevalence and WMT utilization. For patients with obesity and WMT exposure or matched controls, a multistate Markov model assessing associations between WMT and longitudinal weight status trajectories was used. Data were analyzed from October 2021 to October 2023. Exposures: Cross-sectional exposure was year: 2017 or 2019. Trajectory analysis exposures were WMT: nutrition counseling, MR, AOM, and bariatric surgery. Main Outcomes and Measures: Cross-sectional analysis compared mean body mass index (BMI), obesity prevalence, and, among patients with obesity, prospective WMT use. The trajectory analysis examined longitudinal weight status using thresholds of ±5% and 10% of baseline weight with primary outcomes being the 1-year probabilities of 5% or greater weight loss for each WMT. Results: Adult patients (146 959 participants) consisted of 83 636 female participants (56.9%); 8940 (6.1%) were Asian, 14 560 (9.9%) were Black, and 116 664 (79.4%) were White. Patients had a mean (SD) age of 49.6 (17.7) years and mean (SD) BMI of 29.2 (7.2). Among 138 682 patients, prevalence of obesity increased from 39.2% in 2017 to 40.7% in 2019; WMT use among patients with obesity increased from 5.3% to 7.1% (difference: 1.7%; 95% CI, 1.3%-2.2%). In a multistate model (10 180 patients; 33 549 patient-years), the 1-year probability of 5% or greater weight loss without WMT exposure was 15.6% (95% CI, 14.3%-16.5%) at reference covariates. In contrast, the probability of 5% or greater weight loss was more likely with year-long exposures to any WMT (nutrition counseling: 23.1%; 95% CI, 21.3%-25.1%; MR: 54.6%; 95% CI, 46.5%-61.2%; AOM: 27.8%; 95% CI, 25.0%-30.5%; bariatric surgery: 93.0%; 95% CI, 89.7%-95.0%). Conclusions and Relevance: In this cohort study of primary-care patients with obesity, all WMT increased the patient-level probability of achieving 5% or greater weight loss, but current rates of utilization are low and insufficient to reduce weight at the population level.

Real-World Depression Screening Practices Among Primary Care Providers Across Patient-Level and Provider-Level Characteristics.

This study examined primary care provider (PCP) alignment with guideline-based care for adolescent depression screening and identified factors associated with post-screening responses. A retrospective chart review was conducted across 17 primary care clinics. Logistical regressions were estimated across provider specialties, sociodemographic factors, and patient clinical histories. Significant differences in follow-up and identification of depression were found among patients with more severe depression presentation. Follow-up screening was also more likely to be completed among patients with private insurance and less likely to occur among Black patients. Patients with significant mental health history of a mood concern, history of being prescribed psychotropic medication, were currently on medications at the time of the screening, or had a history of an internal mental health referral had a higher predicted probability of being identified as depressed on the patient problem list.

Institutional Barriers to the Successful Implementation of Telemedicine for Type 1 Diabetes Care.

The aim of this study was to describe rates of telemedicine use 18 months after the start of the coronavirus disease 2019 pandemic and to assess the institutional barriers to its implementation for type 1 diabetes care across centers of the T1D Exchange Quality Improvement Collaborative. Observational electronic health record data capturing telemedicine rates from 15 U.S. centers between September 2020 and September 2021 and a survey of 33 centers capturing telemedicine rates and key components of telemedicine were analyzed. A capacity score was developed and summed to a total capacity score and compared with overall telemedicine rates across centers. Telemedicine visits decreased by 17.4% from September 2020 to September 2021. Generally, it was observed that the lower the average telemedicine capacity score, the lower the rate of telemedicine visits. Despite a decline in the utilization of telemedicine 18 months after the start of the pandemic, visit rates were still 20% higher than in the pre-pandemic period. However, there is a need to improve structural components to ensure telemedicine capacity and robust telemedicine utilization.

The Design of the Electronic Health Record in Type 1 Diabetes Centers: Implications for Metrics and Data Availability for a Quality Collaborative.

BACKGROUND: Systematic and comprehensive data acquisition from the electronic health record (EHR) is critical to the quality of data used to improve patient care. We described EHR tools, workflows, and data elements that contribute to core quality metrics in the Type 1 Diabetes Exchange Quality Improvement Collaborative (T1DX-QI). METHOD: We conducted interviews with quality improvement (QI) representatives at 13 T1DX-QI centers about their EHR tools, clinic workflows, and data elements. RESULTS: All centers had access to structured data tools, nine had access to patient questionnaires and two had integration with a device platform. There was significant variability in EHR tools, workflows, and data elements, thus the number of available metrics per center ranged from four to 17 at each site. Thirteen centers had information about glycemic outcomes and diabetes technology use. Seven centers had measurements of additional self-management behaviors. Centers captured patient-reported outcomes including social determinants of health (n = 9), depression (n = 11), transition to adult care (n = 7), and diabetes distress (n = 3). Various stakeholders captured data including health care professionals, educators, medical assistants, and QI coordinators. Centers that had a paired staffing model in clinic encounters distributed the burden of data capture across the health care team and was associated with a higher number of available data elements. CONCLUSIONS: The lack of standardization in EHR tools, workflows, and data elements captured resulted in variability in available metrics across centers. Further work is needed to support measurement and subsequent improvement in quality of care for individuals with type 1 diabetes.

Clinician Experiences With Hybrid Closed Loop Insulin Delivery Systems in Veterans With Type 1 Diabetes: Qualitative Study.

BACKGROUND: Hybrid closed loop (HCL) insulin pumps adjust insulin delivery based on input from a continuous glucose monitor. Several systems are FDA approved and associated with improved time in range, reduction in hemoglobin A1c, and decreased incidence of hypoglycemia. Major diabetes guidelines differ in their strength of recommendations regarding the use of HCL systems. Overall, limited information about the factors that influence HCL pump clinical decision-making is available, especially among endocrinology clinicians. OBJECTIVE: The study objective is to describe the knowledge and attitudes, network support, and self-efficacy regarding HCL insulin delivery systems among endocrinology clinicians in one Veterans Affairs (VA) Healthcare System in the Midwest. METHODS: Following a descriptive approach, this qualitative study used semistructured interviews and inductive thematic analysis. All endocrinologists, endocrinology fellows, and nurses in the endocrinology and metabolism department at one VA Healthcare System in the Midwest were invited to participate in one-on-one phone interviews. Thematic analysis explored clinician perspectives on HCL insulin pump systems. RESULTS: Participants (n=11) had experience within VA and university health care system endocrinology clinics. From their experiences, 4 themes were identified involving the evaluation and assessment of insulin pump candidates, prescribing challenges, clinical benefits of HCL pumps, and overall clinician confidence. CONCLUSIONS: Findings suggest that clinicians believe HCL systems have significant glycemic benefits but are not appropriate for all patients, especially those with cognitive impairment. HCL pump initiation is a multi-step process requiring an interdisciplinary team of health care clinicians to ensure patient and pump success. Furthermore, HCL systems improve clinician confidence in overall diabetes management.

Point of Decision Design to Address Adolescent Overweight and Obesity.

OBJECTIVES: This study aims to utilize the point of decision design framework to understand how, where, and why adolescents and families make decisions about diet and physical activity and to explore how modifications to the environment can help to promote healthier choices and reduce obesity. BACKGROUND: Child and adolescent obesity is a critical public health problem. As environmental factors are a primary contributor, understanding the role of design in our surrounding environment highlights an important area of interdisciplinary study. Design strategies have been used successfully to increase stair use and reduce sedentary behavior and can be used to further promote healthier diet and activity choices among adolescents and families. METHODS: We leveraged the human-centered design-thinking process through (1) qualitative interviews and survey instruments, (2) persona and prompt development, and (3) a design workshop with multidisciplinary stakeholders. RESULTS: Five personas were developed from the qualitative data and used in a design-thinking workshop. During the workshop, participants generated 12 influential factors and nine points of decision which were used to generate 33 solutions spanning the design continuum (from information and policy design to the design of urban, architectural, and interior environments) aimed at improving nutrition and physical activity among adolescents. Additionally, a tool kit was prototyped, which includes interview guides, a persona framework, and a workshop facilitation guide. CONCLUSIONS: Our novel process led to the generation of design solutions that can be implemented to expand and improve upon existing interventions for childhood obesity and create environments that encourage positive health outcomes.

Prospective Test Performance of Nonfasting Biomarkers to Identify Dysglycemia in Children and Adolescents.

INTRODUCTION: Test performance screening measures for dysglycemia have not been evaluated prospectively in youth. This study evaluated the prospective test performance of random glucose (RG), 1-h nonfasting glucose challenge test (1-h GCT), hemoglobin A1c (HbA1c), fructosamine (FA), and 1,5-anhydroglucitol (1,5-AG) for identifying dysglycemia. METHODS: Youth ages 8-17 years with overweight or obesity (body mass index, BMI, ≥85th percentile) without known diabetes completed nonfasting tests at baseline (n = 176) and returned an average of 1.1 years later for two formal fasting 2-h oral glucose tolerance tests. Outcomes included glucose-defined dysglycemia (fasting plasma glucose ≥100 mg/dL or 2-h plasma glucose ≥140 mg/dL) or elevated HbA1c (≥5.7%). Longitudinal test performance was evaluated using receiver-operating characteristic (ROC) curves and calculation of area under the curve (AUC). RESULTS: Glucose-defined dysglycemia, elevated HbA1c, and either dysglycemia or elevated HbA1c were present in 15 (8.5%), 11 (6.3%), and 23 (13.1%) participants at baseline, and 16 (9.1%), 18 (10.3%), and 28 (15.9%) participants at follow-up. For prediction of glucose-defined dysglycemia at follow-up, RG, 1-h GCT, and HbA1c had similar performance (0.68 (95% CI: 0.55-0.80), 0.76 (95% CI: 0.64-0.89), and 0.70 (95% CI: 0.56-0.84)), while FA and 1,5-AG performed poorly. For prediction of HbA1c at follow-up, baseline HbA1c had strong performance (AUC 0.93 [95% CI: 0.88-0.98]), RG had moderate performance (AUC 0.67 [95% CI: 0.54-0.79]), while 1-h GCT, FA, and 1,5-AG performed poorly. CONCLUSION: HbA1c and nonfasting glucose tests had reasonable longitudinal discrimination identifying adolescents at risk for dysglycemia, but performance depended on outcome definition.

Impact of diabetes status and related factors on COVID-19-associated hospitalization: A nationwide retrospective cohort study of 116,370 adults with SARS-CoV-2 infection.

AIMS: We examined diabetes status (no diabetes; type 1 diabetes [T1D]; type 2 diabetes [T2D]) and other demographic and clinical factors as correlates of coronavirus disease 2019 (COVID-19)-related hospitalization. Further, we evaluated predictors of COVID-19-related hospitalization in T1D and T2D. METHODS: We analyzed electronic health record data from the de-identified COVID-19 database (December 2019 through mid-September 2020; 87 US health systems). Logistic mixed models were used to examine predictors of hospitalization at index encounters associated with confirmed SARS-CoV-2 infection. RESULTS: In 116,370 adults (>=18 years old) with COVID-19 (93,098 no diabetes; 802 T1D; 22,470 T2D), factors that independently increased risk for hospitalization included diabetes, male sex, public health insurance, decreased body mass index (BMI; <25.0-29.9 kg/m2), increased BMI (>25.0-29.9 kg/m2), vitamin D deficiency/insufficiency, and Elixhauser comorbidity score. After further adjustment for concurrent hyperglycemia and acidosis in those with diabetes, hospitalization risk was substantially higher in T1D than T2D and in those with low vitamin D and elevated hemoglobin A1c (HbA1c). CONCLUSIONS: The higher hospitalization risk in T1D versus T2D warrants further investigation. Modifiable risk factors such as vitamin D deficiency/insufficiency, BMI, and elevated HbA1c may serve as prognostic indicators for COVID-19-related hospitalization in adults with diabetes.

Self-Regulation as a Protective Factor for Diabetes Distress and Adherence in Youth with Type 1 Diabetes During the COVID-19 Pandemic.

OBJECTIVE: The COVID-19 pandemic increased economic, social, and health stressors for families, yet its impacts on families of youth with chronic conditions, such as type 1 diabetes (T1D), are not well understood. Self-regulation (SR)-or the capacities to control emotions, cognition, and behavior in response to challenge-is known to support T1D management and coping in the face of stress. Strong SR may have protected youth with T1D from the impacts of pandemic-related stressors. This study compared youth and parent emotional functioning and T1D management before and after the pandemic's onset in relation to family pandemic-related stress and youth SR. METHODS: Parents of youth with T1D (N = 88) and a subset of these youth (N = 43; Mean age 15.3 years [SD 2.2]) completed surveys regarding SR, stress, emotional functioning, and T1D-related functioning prior to and after March 2020. Outcomes were compared using mixed effects models adjusting for covariates. Family pandemic-related stress experiences and youth SR were tested as moderators of change. RESULTS: Parents' responsibility for T1D management increased across pandemic onset and their diabetes-related distress decreased. Family pandemic-related stress was associated with decreased emotional functioning over time. Youth SR, particularly emotional and behavioral aspects, predicted better emotional and T1D-related functioning. DISCUSSION: While youth with T1D whose families experienced higher pandemic-related stress had poorer adjustment, strong emotional and behavioral SR appeared to protect against worsening youth mood and adherence across pandemic onset. Both social-contextual and individual factors are important to consider when working with families managing T1D.

Increase in newly diagnosed type 1 diabetes in youth during the COVID-19 pandemic in the United States: A multi-center analysis.

BACKGROUND: An increase in newly diagnosed type 1 diabetes (T1D) has been posited during the COVID-19 pandemic, but data are conflicting. We aimed to determine trends in newly diagnosed T1D and severity of presentation at diagnosis for pediatric and adolescent patients during COVID-19 (2020) as compared to the previous year (2019) in a multi-center analysis across the United States. METHODS: This retrospective study from seven centers in the T1D Exchange Quality Improvement Collaborative (T1DX-QI) included data on new onset T1D diagnosis and proportion in DKA at diagnosis from January 1 to December 31, 2020, compared to the prior year. Chi-square tests were used to compare differences in patient characteristics during the pandemic period compared to the prior year. RESULTS: Across seven sites, there were 1399 newly diagnosed T1D patients in 2020, compared to 1277 in 2019 (p = 0.007). A greater proportion of newly diagnosed patients presented in DKA in 2020 compared to 2019 (599/1399(42.8%) vs. 493/1277(38.6%), p = 0.02), with a higher proportion presenting with severe DKA (p = 0.01) as characterized by a pH <7.1 and/or bicarbonate of <5 mmol/L. Monthly data trends demonstrated a higher number of new T1D diagnoses over the spring and summer months (March to September) of 2020 compared to 2019 (p < 0.001). CONCLUSIONS: We found an increase in newly diagnosed T1D and a greater proportion presenting in DKA at diagnosis during the COVID-19 pandemic compared to the prior year. Future longitudinal studies are needed to confirm these findings with population level data and determine the long-term impact of COVID-19 on diabetes trends.

Association Between Management of Continuous Subcutaneous Basal Insulin Administration and HbA1C.

BACKGROUND: While we expect that patients who adjust their insulin delivery algorithms between clinic visits to have better glucose control compared to those who do not, this effect has not been quantified. METHOD: This is a single-center retrospective cohort study including pediatric and adult patients with type 1 diabetes evaluating insulin pump self-management behaviors. Basal insulin dose information was obtained from the Glooko-Diasend database, and used to quantify the frequency and magnitude of basal insulin daily dose adjustments within the 90-day window preceding HbA1c measurement. We use a linear mixed-effects model to analyze associations between frequency/magnitude of daily basal insulin changes and HbA1c. RESULTS: We present data on 114 adult (44 ± 17 years, 60% female) and 212 pediatric (12 ± 4 years, 50% female) patients. Individuals changed their basal insulin dose on 72%-94% (interquartile range [IQR]) of observed days relative to the previous day. These changes varied 0.6%-2.4% IQR from the previous day's value. In pediatric patients, lower HbA1c was associated with more frequent daily profile adjustments, while controlling for rate of hypoglycemia (z = -3.2, P = .001). In adults, there was no relationship between HbA1c and magnitude or frequency of basal profile adjustments. CONCLUSIONS: Pediatric patients who frequently modify their basal insulin exhibit somewhat better clinical outcomes, although the magnitude by which their basal amount is changed does not contribute to this effect.

Baseline Quality Improvement Capacity of 33 Endocrinology Centers Participating in the T1D Exchange Quality Improvement Collaborative.

This article describes the evolution of the Type 1 Diabetes Exchange Quality Improvement Collaborative (T1DX-QI) and provides insight into the development and growth of a successful type 1 diabetes quality improvement (QI) program. Since its inception 8 years ago, the collaborative has expanded to include centers across the United States with varying levels of QI experience, while simultaneously achieving many tangible improvements in type 1 diabetes care. These successes underscore the importance of learning health systems, data-sharing, benchmarking, and peer collaboration as drivers for continuous QI. Future efforts will include recruiting additional small- to medium-sized centers focused on adult care and underserved communities to further the goal of improving care and outcomes for all people living with type 1 diabetes.

Feasibility of Electronic Health Record Assessment of 6 Pediatric Type 1 Diabetes Self-management Habits and Their Association With Glycemic Outcomes.

Importance: A low-burden electronic health record (EHR) workflow has been devised to systematize the collection and validation of 6 key diabetes self-management habits: (1) checks glucose at least 4 times/day or uses continuous glucose monitor (CGM); (2) gives at least 3 rapid-acting insulin boluses per day; (3) uses insulin pump; (4) delivers boluses before meals; (5) reviewed glucose data since last clinic visit, and (6) has changed insulin doses since the last clinic visit. Objective: To describe the performance of these habits and examine their association with hemoglobin A1c (HbA1c) levels and time in range (TIR). Design, Setting, and Participants: This cross-sectional study included individuals with known type 1 diabetes who were seen in a US pediatric diabetes clinic in 2019. Main Outcomes and Measures: Habit performance, total habit score (sum of 6 habits per person), HbA1c levels, and TIR. Results: Of 1344 patients, 1212 (609 [50.2%] males; 66 [5.4%] non-Hispanic Black; 1030 [85.0%] non-Hispanic White; mean [SD] age, 15.5 [4.5] years) were included, of whom 654 (54.0%) were using CGM and had a TIR. Only 105 patients (8.7%) performed all 6 habits. Habit performance was lower among older vs younger patients (age ≥18 years vs ≤12 years: 17 of 411 [4.1%] vs 57 of 330 [17.3%]; P < .001), Black vs White patients (3 [4.5%] vs 95 [9.2%]; P < .001), those with public vs private insurance (14 of 271 [5.2%] vs 91 of 941 [9.7%]; P < .001), and those with lower vs higher parental education levels (

Comparing the Fasting and Random-Fed Metabolome Response to an Oral Glucose Tolerance Test in Children and Adolescents: Implications of Sex, Obesity, and Insulin Resistance.

As the incidence of obesity and type 2 diabetes (T2D) is occurring at a younger age, studying adolescent nutrient metabolism can provide insights on the development of T2D. Metabolic challenges, including an oral glucose tolerance test (OGTT) can assess the effects of perturbations in nutrient metabolism. Here, we present alterations in the global metabolome in response to an OGTT, classifying the influence of obesity and insulin resistance (IR) in adolescents that arrived at the clinic fasted and in a random-fed state. Participants were recruited as lean (n = 55, aged 8-17 years, BMI percentile 5-85%) and overweight and obese (OVOB, n = 228, aged 8-17 years, BMI percentile ≥ 85%). Untargeted metabolomics profiled 246 annotated metabolites in plasma at t0 and t60 min during the OGTT. Our results suggest that obesity and IR influence the switch from fatty acid (FA) to glucose oxidation in response to the OGTT. Obesity was associated with a blunted decline of acylcarnitines and fatty acid oxidation intermediates. In females, metabolites from the Fasted and Random-Fed OGTT were associated with HOMA-IR, including diacylglycerols, leucine/isoleucine, acylcarnitines, and phosphocholines. Our results indicate that at an early age, obesity and IR may influence the metabolome dynamics in response to a glucose challenge.

Quality Improvement in Diabetes Care: A Review of Initiatives and Outcomes in the T1D Exchange Quality Improvement Collaborative.

Despite immense strides in therapeutic advances, clinical outcomes continue to be less than ideal for people with type 1 diabetes. This discrepancy has prompted an outpouring of quality improvement (QI) initiatives to address the medical, psychosocial, and health equity challenges that complicate ideal type 1 diabetes care and outcomes. This article reviews a framework for QI in diabetes care that guided the development of the T1D Exchange Quality Improvement Collaborative to improve care delivery and health outcomes in type 1 diabetes. Evaluation of the methodology, outcomes, and knowledge gained from these initiatives will highlight the importance of continued QI initiatives in diabetes care.

Increasing Insulin Pump Use Among 12- to 26-Year-Olds With Type 1 Diabetes: Results From the T1D Exchange Quality Improvement Collaborative.

Insulin pump therapy in pediatric type 1 diabetes has been associated with better glycemic control than multiple daily injections. However, insulin pump use remains limited. This article describes an initiative from the T1D Exchange Quality Improvement Collaborative aimed at increasing insulin pump use in patients aged 12-26 years with type 1 diabetes from a baseline of 45% in May 2018 to >50% by February 2020. Interventions developed by participating centers included increasing in-person and telehealth education about insulin pump technology, creating and distributing tools to assist in informed decision-making, facilitating insulin pump insurance approval and onboarding processes, and improving clinic staff knowledge about insulin pumps. These efforts yielded a 13% improvement in pump use among the five participating centers, from 45 to 58% over 22 months.