Diabetes Spectrum最新文献

Objective: Sleep is critically important to children's well-being, and inadequate sleep duration significantly increases the risk for poor health outcomes. Insufficient sleep is a common finding in the pediatric population, specifically among individuals with type 1 diabetes. The aim of this study is to determine whether there are differences in sleep and glycemic outcomes between the summer and the school year among school-aged children with type 1 diabetes.

Research design and methods: School-aged children with type 1 diabetes enrolled in a hybrid closed-loop (HCL) automated insulin delivery (AID) and sleep study wore actigraphy watches and completed sleep diaries and surveys to assess their sleep quality and duration. Glycemic outcomes and sleep data were analyzed to determine variability between the summer and school year.

Results: On average, children (6-17 years of age) with type 1 diabetes using an HCL AID system slept more during the school year than in the summer, although this difference did not achieve statistical significance (442.2 vs. 483.3 minutes, P = 0.053). There was also no statistically significant difference in glycemic control between summer and the school year.

Conclusion: School-aged children with type 1 diabetes using a hybrid closed-loop AID system did not experience statistically significant differences in sleep or glycemic outcomes between summer and the school year. Use of a hybrid closed-loop AID system may play a role in eliminating variations in sleep and glycemic outcomes between summer and the school year. Sleep is a crucial factor in the management of type 1 diabetes, and further research is needed to identify interventions to improve sleep among school-aged children.

Objective: This study examined how structural and contextual barriers, including social needs and gender, influence diabetes self-management (DSM) through psychosocial pathways, particularly diabetes distress (DD) and self-efficacy (SE). Although these barriers are well documented, their interactions with psychosocial factors remain underexplored.

Research design and methods: We analyzed cross-sectional baseline data from the REAL-T (Resilient, Empowered, Active Living-Telehealth) study (n = 198). Using hierarchical regression, we assessed factors influencing DSM. Structural predictors included unmet social needs and limited insulin access; contextual predictors included gender and ethnicity. Hypothesized mediators were the scores on the Diabetes Distress Scale, the Diabetes Empowerment Scale, and the Audit of Diabetes Dependent Quality of Life. After identifying significant predictors and potential mediators through hierarchical multivariate regression analysis, separate path models were tested for each hypothesized mediator.

Results: Unmet social needs, as well as female and nonconforming genders, were found likely to increase DSM challenges. All selected predictors became nonsignificant when accounting for all psychosocial variables. DD mediated all tested relationships, and SE partially mediated the relationship between unmet social needs and DSM.

Conclusion: The proposed model suggests the need for targeted interventions addressing psychosocial pathways, particularly DD and SE, to mitigate the downstream effects of structural barriers to DSM. Inclusive gender-specific care models and systemic reforms to reduce social inequities are crucial for improving DSM outcomes and overall well-being.

Objective: This study evaluated the effectiveness of mindfulness-based interventions (MBIs) in managing comorbid depression and diabetes by assessing their efficacy in reducing depressive symptoms and improving glycemic control, while addressing inconsistencies in existing research.

Research design and methods: A systematic review and meta-analysis were conducted of 17 randomized controlled trials published between 2013 and 2024 and involving 1,336 participants with diabetes and depressive symptoms. Effect sizes were calculated using Hedges' g and random-effects models, with heterogeneity assessed using I ² statistics.

Results: MBIs significantly reduced depressive symptoms (standardized mean difference [SMD] -0.88, 95% CI -1.34 to -0.42) with high heterogeneity (I ² = 90%) and improved A1C levels (SMD -0.23, 95% CI -0.38 to -0.08). Among intervention types, mindfulness-based stress reduction (SMD -1.02, 95% CI -1.57 to -0.48) and mindfulness-based cognitive therapy (SMD -0.92, 95% CI -1.45 to -0.39) showed strong effects. Effects varied by region, with Asian studies showing greater benefits (SMD -1.44) compared with North American studies (SMD -0.61).

Conclusion: MBIs are effective in reducing depressive symptoms and improving glycemic control in individuals with comorbid diabetes and depression. These findings highlight the importance of culturally adapted approaches and call for further research to refine MBI applications in diabetes care.

Objective: To assess the feasibility and efficacy of a novel use of continuous glucose monitoring (CGM) in prediabetes to promote behavioral change and improve glycemia.

Research design and methods: We conducted a single-arm prospective study in a pediatric obesity clinic to evaluate the feasibility and acceptability of wearing a CGM sensor in children aged 10-17 years with obesity (BMI ≥95th percentile for age) and prediabetes. Feasibility was determined through participant recruitment. We analyzed differences in A1C, glucose variability, BMI, and dietary intake at 12 weeks.

Results: Of 22 participants recruited, 14 completed the study. Over 12 weeks, the mean BMI percentage of the 95th percentile decreased from 153.4 to 150.1% (P = 0.006), daily estimated carbohydrate consumption decreased by 41.4% (P = 0.009), and A1C decreased by 0.2% (P = 0.03).

Conclusion: CGM in an adolescent population with prediabetes and obesity may be a helpful adjunct to therapy to improve A1C, support dietary changes, reduce the rate of weight gain, and attenuate diabetes risk.

Objective: Uncontrolled diabetes in pregnancy is associated with maternal and fetal complications. Individuals with pregestational diabetes require frequent glucose monitoring and insulin adjustments to meet glycemic targets. The purpose of the study was to provide improved management of diabetes during pregnancy and up to 6 weeks postpartum, improve patient understanding of diabetes and diabetes self-management, and develop a multidisciplinary obstetrics workflow model for women with diabetes that is both replicable and self-sustaining.

Research design and methods: Fifty participants who were pregnant, diagnosed with type 1 or type 2 diabetes, and ≥18 years of age comprised two groups: a historical group who received traditional diabetes education and an intervention group who received traditional diabetes education enhanced with a cellular-enabled glucose meter, both alongside their prenatal medical appointments. In the intervention group, glucose levels were monitored daily via a cloud-based portal in addition to traditional weekly review, and outreach was initiated when glucose levels met thresholds. Diabetes medications were adjusted as needed in both groups. Practice, clinical, and glycemic data were extracted from the electronic medical record and cloud portal.

Results: Neonatal hypoglycemia was reduced (P = 0.047) and more participants used continuous glucose monitoring (P = 0.01) in the intervention group. Communication by text and telephone occurred more frequently in the intervention group (P = 0.007 and P = 0.011, respectively). The intervention group also received more diabetes education (4.44 vs. 2.89 hours, P = 0.030). Differences in other clinical, practice, or glycemic outcomes did not differ significantly.

Conclusion: Enhanced care with a cellular-enabled glucose meter facilitated remote patient monitoring with accurate glucose data. The intervention group received more hours of diabetes education and more text and telephone contact. Review of glucose data via the cloud-based portal increased the identification of hypoglycemic and hyperglycemic events, informing delivery decisions. Delivery was earlier for the intervention group, yet rates of neonatal hypoglycemia were reduced.

Objective: Diabetes affects nearly 25% of the Veterans Health Administration population, and a diagnosis of diabetes has been reported to increase distress in patients. This study aimed to assess the feasibility of incorporating a diabetes distress (DD) screening program in a Veterans Administration (VA) diabetes clinic and identifying opportunities for intervention.

Research design and methods: Veterans diagnosed with diabetes attending appointments with the clinical pharmacist practitioner in the endocrinology diabetes clinic were asked to participate. Veterans diagnosed with cognitive impairment and/or unable to answer multi-part questions were excluded. Veterans who agreed to participate were asked to complete the two-question Diabetes Distress Scale (DDS2) screening tool and then complete the Type 1 Diabetes Distress Scale (T1-DDS) or the Type 2 Diabetes Distress Assessment System (T2-DDAS), if indicated.

Results: Eighty-seven veterans were identified to complete the DD2S, and 58 (67%) agreed. The mean DDS2 score was 3.2 ± 1.3. Twenty of the 32 participants (67%) who were then offered the T1-DDS or T2-DDAS completed it. A majority of those with a score indicating at least moderate distress accepted a referral to a Whole Health health coach for follow-up.

Conclusion: Veterans were interested in completing the DD2S and the T1-DDS or T2-DDAS. This feasibility study was conducted to develop a foundation for larger trials to identify the optimal approach to identifying DD and providing proper referrals for interventions to address it. Successful integration of DD screening into daily clinical practice in VA clinics could improve diabetes care for veterans.

Objective: The purpose of this study was to evaluate insulin dose requirements after the addition of the dual glucose-dependent insulinotropic polypeptide/glucagon-like peptide 1 (GLP-1) receptor agonist tirzepatide compared with the GLP-1 receptor agonists injectable semaglutide and dulaglutide in people with type 2 diabetes.

Research design and methods: This was a retrospective cohort study using chart review of electronic health records to identify patients from a single academic medical center with type 2 diabetes who were initiated on tirzepatide, injectable semaglutide, or dulaglutide from 1 July 2021 to 31 May 2023 while on concomitant insulin therapy (basal with or without bolus or premixed insulin).

Results: A total of 135 patients were included in the study. The median percentage change in insulin requirement was 0% at 4-6 weeks (P = 0.286), -16.67% at 3 months (P <0.001), -51.03% at 6 months (P <0.001), and -58.33% at 12 months (P = 0.013) for the tirzepatide group (n = 45) and 0% at 4-6 weeks, 3 months, and 6 months and -12.50% at 12 months in the combined dulaglutide and semaglutide group (n = 90). Mean change in weight at 6 months was -8.5813 kg in the tirzepatide group and -3.4111 kg in the dulaglutide and semaglutide group (P <0.001). The most commonly reported adverse events in the tirzepatide group were decreased appetite, nausea, and vomiting.

Conclusion: In patients with type 2 diabetes who were also on insulin, tirzepatide led to significantly lower insulin requirements after 3, 6, and 12 months of use compared with dulaglutide and semaglutide. Tirzepatide also led to significantly more weight loss compared with dulaglutide and semaglutide and yielded a larger decrease in A1C overall without increasing side effects.

Diabetes and depression have a bidirectional relationship, with negative impacts on glycemia, self-care, long-term complications, quality of life, and mortality. This review highlights key aspects of the interconnected and complex relationship between diabetes and depression, including how it affects health outcomes, depression duration and recurrence, age-specific manifestations, and recommendations for screening and nonpharmacological treatment.

Diabetes is a major cause of end-stage kidney disease (ESKD). Glycemic management is challenging in this population, and A1C, commonly used for monitoring glycemic control, is unreliable. Continuous glucose monitoring indices can be used for glycemic monitoring in people with ESKD. Dipeptidyl peptidase 4 inhibitors, incretin mimetic agents (glucagon-like peptide 1 and glucose-dependent insulinotropic peptide receptor agonists), and insulin using an automated insulin delivery system are preferred to manage diabetes in people with ESKD on hemodialysis.

This article discusses the implementation and impact of autonomous artificial intelligence (AI) systems for diabetic eye disease testing at the Johns Hopkins Medicine health system, highlighting improvements in screening rates, access to care, and health equity for underserved populations. The AI technology has been effective in both adult and pediatric populations and has reduced disparities and increased follow-up with eye care professionals. While considering the challenges and successes of this approach, this article also highlights the potential long-term impact of AI systems in improving visual health outcomes for people with diabetes in diverse health care settings.