US Fourth-Year Medical Students: Diabetes Knowledge and Confidence Dissonance.

Introduction: Self-assessed confidence is not a reliable indicator of knowledge levels, as multiple studies have shown; however, it is often used as a measure of knowledge. The purpose of this study is to identify whether the confidence of graduating students in a US medical school to diagnose and treat diabetes is correlated with their diabetes-related knowledge. Methods: We developed a 38-question survey, targeting students' external experiences, knowledge, and confidence related to the diagnosis, treatment, and prevention of diabetes. The survey includes six self-reported confidence questions and 15 multiple choice-style questions, to test diabetes knowledge. The survey was administered electronically using REDCap to the graduating medical school class (n=176) at Upstate Medical University. We calculated mean knowledge scores and confidence scores were calculated. We used Pearson correlation and t tests to assess for correlations and differences in the collected data. We also reviewed diabetes content in the current curriculum. Results: The response rate was 38%. The mean confidence score was 19.97 out of 30 (SD=3.92) and the mean knowledge score was 9.63 out of 15 (SD=2.09). Total knowledge and confidence scores were not correlated. A positive correlation between confidence in prescribing/adjusting medications to treat patients with type 1 diabetes and knowledge levels was found (R=.325, P=.007). Academic electives, external experiences with diabetes, and demographics did not correlate with knowledge and confidence differences. Conclusions: Students overestimated their ability to adequately manage people with diabetes. Better approaches are needed to prepare future physicians to diagnose and treat diabetes.

Predictors of readmission and mortality in adults with diabetes or stress hyperglycemia after initial hospitalization for COVID-19.

INTRODUCTION: We previously reported predictors of mortality in 1786 adults with diabetes or stress hyperglycemia (glucose>180 mg/dL twice in 24 hours) admitted with COVID-19 from March 2020 to February 2021 to five university hospitals. Here, we examine predictors of readmission. RESEARCH DESIGN AND METHODS: Data were collected locally through retrospective reviews of electronic medical records from 1786 adults with diabetes or stress hyperglycemia who had a hemoglobin A1c (HbA1c) test on initial admission with COVID-19 infection or within 3 months prior to initial admission. Data were entered into a Research Electronic Data Capture (REDCap) web-based repository, and de-identified. Descriptive data are shown as mean±SD, per cent (%) or median (IQR). Student's t-test was used for comparing continuous variables with normal distribution and Mann-Whitney U test was used for data not normally distributed. X2 test was used for categorical variable. RESULTS: Of 1502 patients who were alive after initial hospitalization, 19.4% were readmitted; 90.3% within 30 days (median (IQR) 4 (0-14) days). Older age, lower estimated glomerular filtration rate (eGFR), comorbidities, intensive care unit (ICU) admission, mechanical ventilation, diabetic ketoacidosis (DKA), and longer length of stay (LOS) during the initial hospitalization were associated with readmission. Higher HbA1c, glycemic gap, or body mass index (BMI) were not associated with readmission. Mortality during readmission was 8.0% (n=23). Those who died were older than those who survived (74.9±9.5 vs 65.2±14.4 years, p=0.002) and more likely had DKA during the first hospitalization (p<0.001). Shorter LOS during the initial admission was associated with ICU stay during readmission, suggesting that a subset of patients may have been initially discharged prematurely. CONCLUSIONS: Understanding predictors of readmission after initial hospitalization for COVID-19, including older age, lower eGFR, comorbidities, ICU admission, mechanical ventilation, statin use and DKA but not HbA1c, glycemic gap or BMI, can help guide treatment approaches and future research in adults with diabetes.

Barriers and Facilitators of Self-Management in Older People with Type 1 Diabetes: A Narrative Review Focusing on Cognitive Impairment.

Over the past decades, life expectancy of people with type 1 diabetes has increased considerably, which brings potential challenges due to the process of aging. Cognitive aging and dementia, as well as reductions in visual acuity, hearing and dexterity, can influence the frequency and quality of daily self-management activities, including medication taking and insulin dosing, glucose self-monitoring, and healthy eating. This can increase the risk for hypo- and hyperglycemic events, which, in turn, may contribute to cognitive decline. Because there is a gap in understanding the barriers and facilitators of self-management in older adults with type 1 diabetes and the relationship to cognitive functioning, the authors 1) review the available literature on cognitive aging and type 1 diabetes, 2) describe what self-management in later adulthood entails and the cognitive functions required for effective self-management behaviors, 3) analyze the interaction between type 1 diabetes, cognition, aging, and self-management behaviors, and 4) describe the barriers and facilitators for self-management throughout the life span and how they may differ for older people. Potential evidence-based practices that could be developed for older adults with type 1 diabetes are discussed. There is need for further studies that clarify the impact of aging on T1D self-management, ultimately to improve diabetes care and quality of life.

Receipt of Diabetes Specialty Care and Management Services by Older Adults With Diabetes in the U.S., 2015-2019: An Analysis of Medicare Fee-for-Service Claims.

OBJECTIVE: We characterized the receipt of diabetes specialty care and management services among older adults with diabetes. RESEARCH DESIGN AND METHODS: Using a 20% random sample of fee-for-service Medicare beneficiaries aged ≥65 years, we analyzed cohorts of type 1 diabetes (T1D) or type 2 diabetes (T2D) with history of severe hypoglycemia (HoH), and all other T2D annually from 2015 to 2019. Outcomes were receipt of office-based endocrinology care, diabetes education, outpatient diabetes health services, excluding those provided in primary care, and any of the aforementioned services. RESULTS: In the T1D cohort, receipt of endocrinology care and any service increased from 25.9% and 29.2% in 2015 to 32.7% and 37.4% in 2019, respectively. In the T2D with HoH cohort, receipt of endocrinology care and any service was 13.9% and 16.4% in 2015, with minimal increases. Age, race/ethnicity, residential setting, and income were associated with receiving care. CONCLUSIONS: These findings suggest that many older adults may not receive specialty diabetes care and underscore health disparities.

Expert Panel Recommendations for a Standardized Ambulatory Glucose Profile Report for Connected Insulin Pens.

Background: Connected insulin pens capture data on insulin dosing/timing and can integrate with continuous glucose monitoring (CGM) devices with essential insulin and glucose metrics combined into a single platform. Standardization of connected insulin pen reports is desirable to enhance clinical utility with a single report. Methods: An international expert panel was convened to develop a standardized connected insulin pen report incorporating insulin and glucose metrics into a single report containing clinically useful information. An extensive literature review and identification of examples of current connected insulin pen reports were performed serving as the basis for creation of a draft of a standardized connected insulin pen report. The expert panel participated in three virtual standardization meetings and online surveys. Results: The Ambulatory Glucose Profile (AGP) Report: Connected Insulin Pen brings all clinically relevant CGM-derived glucose and connected insulin pen metrics into a single simplified two-page report. The first page contains the time in ranges bar, summary of key insulin and glucose metrics, the AGP curve, and detailed basal (long-acting) insulin assessment. The second page contains the bolus (mealtime and correction) insulin assessment periods with information on meal timing, insulin-to-carbohydrate ratio, average bolus insulin dose, and number of days with bolus doses recorded. The report's second page contains daily glucose profiles with an overlay of the timing and amount of basal and bolus insulin administered. Conclusion: The AGP Report: Connected Insulin Pen is a standardized clinically useful report that should be considered by companies developing connected pen technology as part of their system reporting/output.

Psychosocial Factors and Glycemic Control in Young Adults With Youth-Onset Type 2 Diabetes.

Importance: Youth-onset type 2 diabetes is associated with poor glycemic control and early onset of complications. Identification of psychosocial factors associated with poor glycemic control is needed to inform efficacious interventions. Objective: To identify psychosocial factors associated with glycated hemoglobin (HbA1c) levels in young adults with youth-onset type 2 diabetes. Design, Setting, and Participants: For the iCount cohort study, HbA1c levels were measured twice (at baseline [T1] and at 1 year [T2]) during the last years (2017-2019) of the observational phase of the multicenter Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY2) study. Participants were young adults who had been diagnosed with type 2 diabetes during childhood or adolescence. Data were analyzed from December 2021 to September 2023. Main Outcomes and Measures: Glycemic control was examined categorically (high [≥8.0%] vs low [<8.0%] HbA1c), continuously (HbA1c level), and over time (change in HbA1c: decreased ≥0.5%, remained stable, or increased ≥0.5%). Psychosocial measures included beliefs about medicines, depression and anxiety symptoms, diabetes distress, diabetes self-efficacy, self-management support, and unmet material needs. Multivariable logistic and linear regression models evaluated the association of each psychosocial factor with the probability of T2 HbA1c of 8.0% or greater, T2 HbA1c level, and change in HbA1c. Results: Of the 411 TODAY2 participants approached, 381 enrolled in the iCount study, and 348 with T1 and T2 HbA1c data comprised the analysis group. The 348 participants had a mean (SD) age of 26.1 (2.5) years and a mean (SD) HbA1c of 9.4% (2.8%). Most participants (229 [65.8%]) were women. In adjusted multivariable regressions, greater beliefs that diabetes medicines are necessary (odds ratio [OR], 1.19 [95% CI, 1.03-1.37]; P = .02), concerns about medicines (OR, 1.20 [95% CI, 1.00-1.45]; P = .049), diabetes distress (OR, 1.08 [95% CI, 1.02-1.15]; P = .006), and high distress (OR, 2.18 [95% CI, 1.15-4.13]; P = .02) increased the odds of high HbA1c at T2. Greater support (OR, 0.67 [95% CI, 0.46-0.97]; P = .04) and diabetes self-efficacy (OR, 0.91 [95% CI, 0.84-0.99]; P = .02) decreased the odds of high HbA1c at T2. Diabetes distress was associated with higher HbA1c level at T2 (coefficient, 0.08 [95% CI, 0.02-0.13]; P = .01). Beliefs that diabetes medicines are necessary (OR, 1.20 [95% CI, 1.03-1.39]; P = .02) and concerns about medicines (OR, 1.22 [95% CI, 1.00-1.47]; P = .048) increased the odds of an HbA1c decrease of at least 0.5% over 1 year. Conclusions and Relevance: In this cohort study of young adults with youth-onset type 2 diabetes, beliefs about medicines, high diabetes distress, low diabetes self-efficacy, and self-management support were associated with high HbA1c over time. Future research should assess whether interventions that address these factors result in improved glycemic control in this at-risk group.

Risk factors associated with cognitive performance and cognitive impairment in older adults with type 1 diabetes: Data from the Wireless Innovation for Seniors with Diabetes Mellitus (WISDM) study.

BACKGROUND: Adults with type 1 diabetes (T1D) are considered at increased risk for cognitive impairment and accelerated brain aging. However, longitudinal data on cognitive impairment and dementia in this population are scarce. OBJECTIVE: To identify risk factors associated with cognitive performance and cognitive impairment in a longitudinal sample of older adults with T1D. METHODS: We analyzed data collected as part of the Wireless Innovation for Seniors with Diabetes Mellitus (WISDM) Study, in which 22 endocrinology practices participated. Randomized participants with T1D ≥60 years of age who completed at least one cognitive assessment were included in this study (n = 203). Cognitive impairment was classified using published recommendations. RESULTS: Older age, male sex, non-private health insurance, worse daily functioning, diagnosis of neuropathy, and longer duration of diabetes were associated with worse cognitive performance, but not cognitive impairment. 49 % and 39 % of the sample met criteria for cognitive impairment at baseline and 52 weeks respectively. Of the participants that had data at both time points, 10 % were normal at baseline and impaired at 52 weeks and 22 % of participants (44 % of those classified with cognitive impairment at baseline) reverted to normal over 52 weeks. CONCLUSION: This study indicated that several demographic and clinical characteristics are associated with worse cognitive performance in older adults with T1D, but there were no associations between these characteristics and cognitive impairment defined by NIH Toolbox cognitive impairment criteria. Caution is warranted when assessing cognition in older adults with T1D, as a large percentage of those identified as having cognitive impairment at baseline reverted to normal after 52 weeks. There is need for future studies on the interrelationship of cognition and aging to better understand the effects of T1D on cognitive health, to improve clinical monitoring and help mitigate the risk of dementia in this population.

Diabetes Management in Detention Facilities: A Statement of the American Diabetes Association.

This statement provides guidance for diabetes care in detention facilities. It focuses on areas where the processes for delivery of care to people with diabetes in detention facilities may differ from those in the community, and key points are made at the end of each section. Areas of emphasis, which inform multiple aspects discussed in this statement, include 1) timely identification or diagnosis of diabetes treatment needs and continuity of care (at reception/intake, during transfers, and upon discharge), 2) nutrition and physical activity, 3) timely access to diabetes management tools (insulin, blood glucose monitoring, tracking data, current diabetes management technologies, etc.), and 4) treatment of the whole person with diabetes (self-management education, mental health support, monitoring and addressing long-term complications, specialty care, etc.).

Effects of ADHD and ADHD treatment on glycemic management in type 1 diabetes: A systematic review and meta-analysis of observational studies.

AIMS: Studies suggested a higher prevalence of Attention-deficit/hyperactivity disorder (ADHD) in individuals with Type 1 Diabetes Mellitus (T1D). However, it is unclear how ADHD impacts glycemia and diabetes-related complications. This systematic review and meta-analysis aimed to investigate the effect of ADHD and ADHD medications on HbA1c and acute complications in T1D. METHODS: A literature search was conducted in PubMed, EMBASE, CINAHL, Scopus, PsycINFO, CENTRAL, and Web of Science collections up to November 22, 2023. Seventeen studies were selected for the systematic review by independent reviewers, with twelve included in the meta-analysis. RESULTS: Mean HbA1c levels were significantly higher in T1D individuals with ADHD compared to those without ADHD (MD = 0.60; 95 % CI: 0.41, 0.79; I2 = 90.1 %; p-value < 0.001). The rates of suboptimal HbA1c levels, hospitalization, diabetic ketoacidosis, and hypoglycemia were all substantially higher in T1D individuals with ADHD than those without ADHD. No difference was found in mean HbA1c between those who received ADHD treatment and those who did not (mean difference = -0.52; 95 % confidence interval: -1.16, 0.13; I2 = 78.6 %; p-value = 0.12). CONCLUSIONS: ADHD is associated with higher HbA1c and increased acute diabetes-related complications. More research is needed to assess the effects of ADHD treatments on T1D management.

Nocturnal hypoglycemia is associated with next day cognitive performance in adults with type 1 diabetes: Pilot data from the GluCog study.

OBJECTIVE:  Individuals with type 1 diabetes (T1D) have increased risk for cognitive dysfunction and high rates of sleep disturbance. Despite associations between glycemia and cognitive performance using cross-sectional and experimental methods few studies have evaluated this relationship in a naturalistic setting, or the impact of nocturnal versus daytime hypoglycemia. Ecological Momentary Assessment (EMA) may provide insight into the dynamic associations between cognition, affective, and physiological states. The current study couples EMA data with continuous glucose monitoring (CGM) to examine the within-person impact of nocturnal glycemia on next day cognitive performance in adults with T1D. Due to high rates of sleep disturbance and emotional distress in people with T1D, the potential impacts of sleep characteristics and negative affect were also evaluated. METHODS:  This pilot study utilized EMA in 18 adults with T1D to examine the impact of glycemic excursions, measured using CGM, on cognitive performance, measured via mobile cognitive assessment using the TestMyBrain platform. Multilevel modeling was used to test the within-person effects of nocturnal hypoglycemia and hyperglycemia on next day cognition. RESULTS:  Results indicated that increases in nocturnal hypoglycemia were associated with slower next day processing speed. This association was not significantly attenuated by negative affect, sleepiness, or sleep quality. CONCLUSIONS:  These results, while preliminary due to small sample size, showcase the power of intensive longitudinal designs using ambulatory cognitive assessment to uncover novel determinants of cognitive fluctuation in real world settings, an approach that may be utilized in other populations. Findings suggest reducing nocturnal hypoglycemia may improve cognition in adults with T1D.

Use of machine learning to identify characteristics associated with severe hypoglycemia in older adults with type 1 diabetes: a post-hoc analysis of a case-control study.

INTRODUCTION: Severe hypoglycemia (SH) in older adults (OAs) with type 1 diabetes is associated with profound morbidity and mortality, yet its etiology can be complex and multifactorial. Enhanced tools to identify OAs who are at high risk for SH are needed. This study used machine learning to identify characteristics that distinguish those with and without recent SH, selecting from a range of demographic and clinical, behavioral and lifestyle, and neurocognitive characteristics, along with continuous glucose monitoring (CGM) measures. RESEARCH DESIGN AND METHODS: Data from a case-control study involving OAs recruited from the T1D Exchange Clinical Network were analyzed. The random forest machine learning algorithm was used to elucidate the characteristics associated with case versus control status and their relative importance. Models with successively rich characteristic sets were examined to systematically incorporate each domain of possible risk characteristics. RESULTS: Data from 191 OAs with type 1 diabetes (47.1% female, 92.1% non-Hispanic white) were analyzed. Across models, hypoglycemia unawareness was the top characteristic associated with SH history. For the model with the richest input data, the most important characteristics, in descending order, were hypoglycemia unawareness, hypoglycemia fear, coefficient of variation from CGM, % time blood glucose below 70 mg/dL, and trail making test B score. CONCLUSIONS: Machine learning may augment risk stratification for OAs by identifying key characteristics associated with SH. Prospective studies are needed to identify the predictive performance of these risk characteristics.

Understanding Providers' Readiness and Attitudes Toward Autoantibody Screening: A Mixed-Methods Study.

Screening for autoantibodies associated with type 1 diabetes can identify people most at risk for progressing to clinical type 1 diabetes and provide an opportunity for early intervention. Drawbacks and barriers to screening exist, and concerns arise, as methods for disease prevention are limited and no cure exists today. The availability of novel treatment options such as teplizumab to delay progression to clinical type 1 diabetes in high-risk individuals has led to the reassessment of screening programs. This study explored awareness, readiness, and attitudes of endocrinology providers toward type 1 diabetes autoantibody screening.

Two Years with a Tubeless Automated Insulin Delivery System: A Single-Arm Multicenter Trial in Children, Adolescents, and Adults with Type 1 Diabetes.

Background: The Omnipod® 5 Automated Insulin Delivery (AID) System was shown to be safe and effective following 3 months of use in people with type 1 diabetes (T1D); however, data on the durability of these results are limited. This study evaluated the long-term safety and effectiveness of Omnipod 5 use in people with T1D during up to 2 years of use. Materials and Methods: After a 3-month single-arm, multicenter, pivotal trial in children (6-13.9 years) and adolescents/adults (14-70 years), participants could continue system use in an extension phase. HbA1c was measured every 3 months for up to 15 months; continuous glucose monitor metrics were collected for up to 2 years. Results: Participants (N = 224) completed median (interquartile range) 22.3 (21.7, 22.7) months of AID. HbA1c was reduced in the pivotal trial from 7.7% ± 0.9% in children and 7.2% ± 0.9% in adolescents/adults to 7.0% ± 0.6% and 6.8% ± 0.7%, respectively, (P < 0.0001), and was maintained at 7.2% ± 0.7% and 6.9% ± 0.6% after 15 months (P < 0.0001 from baseline). Time in target range (70-180 mg/dL) increased from 52.4% ± 15.6% in children and 63.6% ± 16.5% in adolescents/adults at baseline to 67.9% ± 8.0% and 73.8% ± 10.8%, respectively, during the pivotal trial (P < 0.0001) and was maintained at 65.9% ± 8.9% and 72.9% ± 11.3% during the extension (P < 0.0001 from baseline). One episode of diabetic ketoacidosis and seven episodes of severe hypoglycemia occurred during the extension. Children and adolescents/adults spent median 96.1% and 96.3% of time in Automated Mode, respectively. Conclusion: Our study supports that long-term use of the Omnipod 5 AID System can safely maintain improvements in glycemic outcomes for up to 2 years of use in people with T1D. Clinical Trials Registration Number: NCT04196140.

Supporting the 'lived expertise' of older adults with type 1 diabetes: An applied focus group analysis to characterize barriers, facilitators, and strategies for self-management in a growing and understudied population.

INTRODUCTION: There is a growing number of older adults (≥65 years) who live with type 1 diabetes. We qualitatively explored experiences and perspectives regarding type 1 diabetes self-management and treatment decisions among older adults, focusing on adopting care advances such as continuous glucose monitoring (CGM). METHODS: Among a clinic-based sample of older adults ≥65 years with type 1 diabetes, we conducted a series of literature and expert informed focus groups with structured discussion activities. Groups were transcribed followed by inductive coding, theme identification, and inference verification. Medical records and surveys added clinical information. RESULTS: Twenty nine older adults (age 73.4 ± 4.5 years; 86% CGM users) and four caregivers (age 73.3 ± 2.9 years) participated. Participants were 58% female and 82% non-Hispanic White. Analysis revealed themes related to attitudes, behaviours, and experiences, as well as interpersonal and contextual factors that shape self-management and outcomes. These factors and their interactions drive variability in diabetes outcomes and optimal treatment strategies between individuals as well as within individuals over time (i.e. with ageing). Participants proposed strategies to address these factors: regular, holistic needs assessments to match people with effective self-care approaches and adapt them over the lifespan; longitudinal support (e.g., education, tactical help, sharing and validating experiences); tailored education and skills training; and leveraging of caregivers, family, and peers as resources. CONCLUSIONS: Our study of what influences self-management decisions and technology adoption among older adults with type 1 diabetes underscores the importance of ongoing assessments to address dynamic age-specific needs, as well as individualized multi-faceted support that integrates peers and caregivers.

Antihypertensive and Lipid-Lowering Medication Adherence in Young Adults With Youth-Onset Type 2 Diabetes.

Importance: Youth-onset type 2 diabetes is associated with early development of chronic complications. Treatment of elevated blood pressure (BP), nephropathy, and dyslipidemia are critical to reduce morbidity. Data are needed on adherence to BP- and lipid-lowering medications in young adults with youth-onset diabetes. Objective: To assess adherence and factors associated with adherence to BP- and lipid-lowering medications in young adults with youth-onset type 2 diabetes and diagnoses of hypertension, nephropathy, or dyslipidemia. Design, Setting, and Participants: This cohort study measured medication adherence with 3 monthly unannounced pill counts at 2 time points 1 year apart during iCount, conducted during the last years (2017-2019) of the observational phase of the Treatment Options for Type 2 Diabetes in Adolescents and Youth study. Psychosocial factors associated with medication adherence were examined. Participants included individuals with youth-onset type 2 diabetes with hypertension, nephropathy, or dyslipidemia receiving diabetes care in their communities. Data were analyzed from September 2022 to September 2023. Main Outcomes and Measures: The main outcome was BP- and lipid-lowering medication adherence, with low adherence defined as using less than 80% of pills and high adherence, at least 80% of pills. Psychosocial factors were measured using the Beliefs about Medicines Questionnaire and Material Needs Insecurities Survey. Results: Of 381 participants in iCount, 243 participants (mean [SD] age, 26.12 [2.51] years; 159 [65.43%] women) with hypertension, nephropathy, or dyslipidemia were included in analysis. Among 196 participants with hypertension or nephropathy, 157 (80.1%) had low adherence. Participants with low adherence, compared with those with high adherence, were younger (mean [SD] age, 25.99 [2.41] vs 27.26 [2.41] years; P = .005), had higher glycated hemoglobin A1c (mean [SD], 10.33% [2.66 percentage points] vs 8.85% [2.39 percentage points]; P = .001), shorter diabetes duration (mean [SD], 12.32 [1.49] vs 12.90 [1.46] years; P = .03), and less education (eg, 17 participants [10.83%] vs 0 participants with no high school diploma; P = .004). Of 146 participants with dyslipidemia, 137 (93.8%) had low adherence and only 9 participants (6.2%) had high adherence. Of 103 participants with low adherence to BP-lowering medications and using oral hypoglycemic agents, 83 (80.58%) had low adherence to oral hypoglycemic agents. Beliefs that medications are necessary were higher for participants with high adherence to BP-lowering medications than those with low adherence in unadjusted analyses (mean [SD] necessity score, 16.87 [6.78] vs 13.89 [9.15]; P = .03). In adjusted multivariable analyses of participants with hypertension or nephropathy, having at least 1 unmet social need (odds ratio [OR], 0.20; 95% CI, 0.05-0.65; P = .04) and medication concerns (OR, 0.63; 95% CI, 0.40-0.96; P = .01) were associated with worse medication adherence 1 year follow-up. Diabetes distress, self-efficacy, depressive and anxiety symptoms, and self-management support were not associated with 1-year medication adherence. Conclusions and Relevance: These findings suggest that adherence to BP- and lipid-lowering medications was very poor in this cohort. To improve medication adherence and prevent early vascular events, approaches that identify and address medication concerns and unmet social needs are needed.

Comprehensive Telehealth Model to Support Diabetes Self-Management.

Importance: As the number of patients with diabetes continues to increase in the United States, novel approaches to clinical care access should be considered to meet the care needs for this population, including support for diabetes-related technology. Objective: To evaluate a virtual clinic to facilitate comprehensive diabetes care, support continuous glucose monitoring (CGM) integration into diabetes self-management, and provide behavioral health support for diabetes-related issues. Design, Setting, and Participants: This cohort study was a prospective, single-arm, remote study involving adult participants with type 1 or type 2 diabetes who were referred through community resources. The study was conducted virtually from August 24, 2020, to May 26, 2022; analysis was conducted at the clinical coordinating center. Intervention: Training and education led by a Certified Diabetes Care and Education Specialist for CGM use through a virtual endocrinology clinic structure, which included endocrinologists and behavioral health team members. Main Outcomes and Measures: Main outcomes included CGM-measured mean glucose level, coefficient of variation, and time in range (TIR) of 70 to 180 mg/dL, time with values greater than 180 mg/dL or 250 mg/dL, and time with values less than 70 mg/dL or 54 mg/dL. Hemoglobin A1c was measured at baseline and at 12 and 24 weeks. Results: Among the 234 participants, 160 had type 1 diabetes and 74 had type 2 diabetes. The mean (SD) age was 47 (14) years, 123 (53%) were female, and median diabetes duration was 20 years. Median (IQR) CGM use over 6 months was 96% (91%-98%) for participants with type 1 diabetes and 94% (85%-97%) for those with type 2 diabetes. Mean (SD) hemoglobin A1c (HbA1c) in those with type 1 diabetes decreased from 7.8% (1.6%) at baseline to 7.1% (1.0%) at 3 months and 7.1% (1.0%) at 6 months (mean change from baseline to 6 months, -0.6%, 95% CI, -0.8% to -0.5%; P < .001), with an 11% mean TIR increase over 6 months (95% CI, 9% to 14%; P < .001). Mean HbA1c in participants with type 2 diabetes decreased from 8.1% (1.7%) at baseline to 7.1% (1.0%) at 3 months and 7.1% (0.9%) at 6 months (mean change from baseline to 6 months, -1.0%; 95% CI, -1.4% to -0.7%; P < .001), with an 18% TIR increase over 6 months (95% CI, 13% to 24%; P < .001). In participants with type 1 diabetes, mean percentage of time with values less than 70 mg/dL and less than 54 mg/dL decreased over 6 months by 0.8% (95% CI, -1.2% to -0.4%; P = .001) and by 0.3% (95% CI, -0.5% to -0.2%, P < .001), respectively. In the type 2 diabetes group, hypoglycemia was rare (mean [SD] percentage of time <70 mg/dL, 0.5% [0.6%]; and <54 mg/dL, 0.07% [0.14%], over 6 months). Conclusions and Relevance: Results from this cohort study demonstrated clinical benefits associated with implementation of a comprehensive care model that included diabetes education. This model of care has potential to reach a large portion of patients with diabetes, facilitate diabetes technology adoption, and improve glucose control.

Longitudinal Trends in Glycemic Outcomes and Technology Use for Over 48,000 People with Type 1 Diabetes (2016-2022) from the T1D Exchange Quality Improvement Collaborative.

Objective: Previous studies revealed that hemoglobin A1c (HbA1c) increased overall in the United States in the past decade. In addition, health inequities in type 1 diabetes (T1D) outcomes by race/ethnicity and insurance type persist. This study examines the trends in HbA1c from 2016 to 2022 stratified by race/ethnicity and insurance in a large multicenter national database. Research Design and Methods: We analyzed glycemic outcomes and diabetes device use trends for >48,000 people living with type 1 diabetes (PwT1D) from 3 adult and 12 pediatric centers in the T1D Exchange Quality Improvement Collaborative (T1DX-QI), comparing data from 2016 to 2017 with data from 2021 to 2022. Results: The mean HbA1c in 2021-2022 was lower at 8.4% compared with the mean HbA1c in 2016-2017 of 8.7% (0.3% improvement; P < 0.01). Over the same period, the percentage of PwT1D using a continuous glucose monitor (CGM), insulin pump, or hybrid closed-loop system increased (45%, 12%, and 33%, respectively). However, these improvements were not equitably demonstrated across racial/ethnic groups or insurance types. Racial/ethnic and insurance-based inequities persisted over all 7 years across all outcomes; comparing non-Hispanic White and non-Hispanic Black PwT1D, disparate gaps in HbA1c (1.2%-1.6%), CGM (30%), pump (25%-35%), and hybrid-closed loop system (up to 20%) are illuminated. Conclusion: Population-level data on outcomes, including HbA1c, can provide trends and insights into strategies to improve health for PwT1D. The T1DX-QI cohort showed a significant improvement in HbA1c from 2016 to 2022. Improvements in diabetes device use are also demonstrated. However, these increases were inconsistent across all racial/ethnic groups or insurance types, an important focus for future T1D population health improvement work.

The Growing Role of Technology in the Care of Older Adults With Diabetes.

The integration of technologies such as continuous glucose monitors, insulin pumps, and smart pens into diabetes management has the potential to support the transformation of health care services that provide a higher quality of diabetes care, lower costs and administrative burdens, and greater empowerment for people with diabetes and their caregivers. Among people with diabetes, older adults are a distinct subpopulation in terms of their clinical heterogeneity, care priorities, and technology integration. The scientific evidence and clinical experience with these technologies among older adults are growing but are still modest. In this review, we describe the current knowledge regarding the impact of technology in older adults with diabetes, identify major barriers to the use of existing and emerging technologies, describe areas of care that could be optimized by technology, and identify areas for future research to fulfill the potential promise of evidence-based technology integrated into care for this important population.