Screening for diabetes distress and depression in routine clinical care for youth with type 1 diabetes.

OBJECTIVE: The purpose of this study is to examine diabetes distress as a potential mediator of the relationship between depression symptoms and diabetes outcomes, including hemoglobin A1c (hemoglobin A1c [HbA1c]) and diabetes management behaviors in a clinical sample of adolescents and young adults. METHODS: In a pediatric diabetes clinic, 716 youth (ages 12-21 years) completed measures of diabetes distress (Problem Areas in Diabetes-Teen [PAID-T]), a single-item of diabetes distress, and depression (Patient Health Questionnaire [PHQ-9]) as part of standard care. Electronic health records were extracted for the "Six Habits" and glycemic management (HbA1c). RESULTS: Overall, 3.6% (n = 26) of adolescents had clinically elevated diabetes distress and depression symptoms, 5.0% had diabetes distress alone, 8.7% had depression symptoms alone, and 82.7% had neither clinical elevation of diabetes distress nor depression symptoms. Results of mediation analysis demonstrated diabetes distress (both full and single-item measures) fully mediated the relationship between depression symptoms and HbA1c (p < .001). Also, mediation analysis results showcase incomplete mediation of the effect of the Six Habits score on HbA1c appears by PAID-T Diabetes Distress. CONCLUSIONS: In a clinical sample of youth with type 1 diabetes, both depressive symptoms and diabetes distress are associated with HbA1c. Furthermore, diabetes distress fully mediates the relationship between depressive symptoms and HbA1c. As part of standard clinical care, the single-item screener for diabetes distress captured similar results as the full-scaled PAID-T. With limited clinical resources, providers may consider focusing assessment and interventions on the psychological factor of diabetes distress within the diabetes clinic to maximize the impact on glycemic control and consider the use of single-item screening to identify distress.

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.

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.

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.

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.

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 (

Racial differences in prediabetes prevalence by test type for the US pediatric and adult population: NHANES 1999-2016.

BACKGROUND: Previous studies have shown that US estimates of prediabetes or diabetes differ depending on test type, fasting plasma glucose (FPG) vs hemoglobin A1c (HbA1c). Given age, race, and test differences reported in the literature, we sought to further examine these differences in prediabetes detection using a nationally representative sample. METHODS: Using the National Health and Nutrition Examination Survey (NHANES) 1999-2016, individuals were identified as having prediabetes with an HbA1c of 5.7% to 6.4% or a FPG of 100 to 125 mg/dL. We excluded individuals with measurements in the diabetic range. We ran generalized estimating equation logistic regressions to examine the relationship between age, race, and test type with interactions, controlling for sex and body mass index. We compared the difference in predicted prediabetes prevalence detected by impaired fasting glycemia (IFG) vs HbA1c by race/ethnicity among children and adults separately using adjusted Wald tests. RESULTS: The absolute difference in predicted prediabetes detected by IFG vs HbA1c was 19.9% for white adolescents, 0% for black adolescents, and 20.1% for Hispanic adolescents; 21.4% for white adults, -1.2% for black adults, and 19.2% for Hispanic adults. Using adjusted Wald tests, we found the absolute differences between black vs white and black vs Hispanic individuals to be significant, but, not between Hispanic and white individuals among children and adults separately. CONCLUSIONS: These observations highlight differences in test performance among racial/ethnic groups. Our findings corroborate the need for further studies to determine appropriate HbA1c cutoff levels for diagnosis of prediabetes by age group and race.

Enhanced Myeloid Leukocytes in Obese Children and Adolescents at Risk for Metabolic Impairment.

Objective: We aimed to examine if myeloid leukocyte profiles are associated with metabolic impairment in children and adolescents with obesity, and if sex, age, or race influence this relationship. Methods: 282 children ages 8-17 were evaluated. Predictor measures were absolute neutrophil counts (ANC), absolute monocyte count, monocyte subtypes and C reactive protein (CRP). Outcome variables were waist circumference, fasting glucose and insulin, HOMA-IR, HbA1c (%) and lipid profiles. Pearson correlation coefficients were used to determine associations between predictor and outcome variables. Wilcoxon two-sample tests were used to evaluate differences by sex. Results: CRP (p < 0.0001), ANC (p < 0.0018), and classical monocytes (p = 0.05) were significantly higher in children with obesity. CRP, ANC and classical monocytes showed positive correlations with waist circumference, insulin, HOMA-IR and triglycerides. CRP was positively associated with ANC overall (p = 0.05). ANC demonstrated positive correlation with monocytes (p < 0.001). The associations between predictor and outcome variables were influenced by sex, race, and age. Conclusions: CRP and myeloid leukocyte populations, specifically classical monocytes and neutrophils associate with both body composition and metabolic parameters in children with obesity suggesting that these cells may play a critical role in metabolic impairment. Race, gender and age interactions between monocytes and metabolic parameters were significant.

Evolution of Do-It-Yourself Remote Monitoring Technology for Type 1 Diabetes.

BACKGROUND: The Nightscout Project is a leading example of patient-designed, do-it-yourself (DIY), open-source technology innovations to support type 1 diabetes management. We are unaware of studies that have described the evolution of patient-driven innovations from the Nightscout Project to date. METHODS: We identified patient-driven, DIY innovations from posts and comments in the "CGM in the Cloud" private Facebook group as well as data from Twitter, GitHub, and the Nightscout website. For each innovation, we described its intent or its unaddressed need as well as the associated features and improvements. We conducted a thematic analysis to identify overarching patterns among the innovations, features, and improvements, and compared the timeline of innovations in the DIY space with the timing of similar innovations in the commercial space. RESULTS: We identified and categorized innovations in Nightscout with the most commonly appearing themes of: visualization improvements, equipment improvements, and user experience improvements. Other emerging themes included: Care Portal support, safety, remote monitoring, decision support, international support, artificial pancreas, pushover notifications, and open-source collaboration. CONCLUSIONS: This rapid development of patient-designed DIY innovations driven by unmet needs in the type 1 diabetes community reflects a revolutionary, bottom-up approach to medical innovation. Nightscout users accessed features earlier than if they had waited for commercial products, and they also personalized their tools and devices, empowering them to become the experts of their own care.

Peer Support Through a Diabetes Social Media Community.

BACKGROUND: Caregivers and individuals living with type 1 diabetes (T1D) who are members of CGM in the Cloud, a Facebook group associated with the Nightscout Project, were interviewed to assess how the online community impacted peer support. METHODS: Semistructured qualitative interviews were conducted with caregivers and patients who are part of CGM in the Cloud Facebook group. Interview transcripts were analyzed to identify various themes related to peer support in the online group. RESULTS: Members of the CGM in the Cloud Facebook group identified peer support through giving and receiving technical, emotional, and medical support, as well as giving back to the larger community by paying it forward. Peer support also extended beyond the online forum, connecting people in person, whether they were local or across the country. CONCLUSIONS: An online community can provide many avenues for peer support through emotional and technical support, as well as serve as a tool of empowerment. The community as a whole also had a spirit of altruism that bolstered confidence in others as well as those who paid it forward.

Motivations for Participation in an Online Social Media Community for Diabetes.

BACKGROUND: Our objectives were to describe individuals' motivations for participation in an online social media community and to assess their level of trust in medical information provided by medical professionals and community members. METHODS: A purposive survey was delivered to participants recruited through posts on the CGM in the Cloud group, Twitter, and blogs. Individuals were asked a series of demographic and social media use questions. RESULTS: A total of 1268 members of the CGM in the Cloud community responded to the survey. The majority were non-Hispanic White (92.1%) and caregivers of an individual with diabetes (80.9%). Mean age was 41 years old, and 74.8% were female. Primary goals of the Facebook group were to learn more about Nightscout technology and to receive technological assistance. Individuals provided assistance to the community through spreading awareness, technical assistance, support, and donation. Respondents put a high level of trust in their peers versus health professionals in many health situations with nearly 40% of individuals reported to be helped by following advice found in the Facebook group, and 99% reported no harm. CONCLUSIONS: Our findings suggest that patients with diabetes and their caregivers use social media for many health-related purposes including medical recommendations and technical support for medical devices and systems as well as emotional support.

Real-World Use and Self-Reported Health Outcomes of a Patient-Designed Do-it-Yourself Mobile Technology System for Diabetes: Lessons for Mobile Health.

BACKGROUND: The aim of this study is to compare demographic/disease characteristics of users versus nonusers of a do-it-yourself (DIY) mobile technology system for diabetes (Nightscout), to describe its uses and personalization, and to evaluate associated changes in health behaviors and outcomes. METHODS: A cross-sectional, household-level online survey was used. Of 1268 household respondents who were members of the CGM in the Cloud Facebook group, there were 1157 individuals with diabetes who provided information about Nightscout use. RESULTS: The majority of individuals with diabetes in the household sample were 6-12 years old (followed by 18 years and above, and 13-17 years), non-Hispanic whites (90.2%), with type 1 diabetes (99.4%). The majority used an insulin pump (85.6%) and CGM (97.0%) and had private health insurance (83.8%). Nightscout use was more prevalent among children compared with adolescents and adults. Children used Nightscout for nighttime, school, sporting events, and travel; adults used it for nighttime, work, travel, and sporting events. Whereas the majority of adults viewed their own data without assistance from others, among pediatric users, a median of three individuals (range: 0-8) viewed Nightscout, with a median of three devices per viewer (range: 0-7). Individuals reported that after Nightscout adoption, they checked blood glucose values with a meter less often; bolused more frequently; gave more boluses without checking first with a blood glucose meter; and experienced significant improvements in HbA1c and quality of life. CONCLUSIONS: The Nightscout Project is a patient-driven mobile technology for health and may have beneficial effects on glycemic control and quality of life.