Journal of Diabetes Science and Technology最新文献

This report represents the conclusions of 15 experts in nephrology and endocrinology, based on their knowledge of key studies and evidence in the field, on the role of continuous glucose monitors (CGMs) in patients with diabetes and chronic kidney disease (CKD), including those receiving dialysis. The experts discussed issues related to CGM accuracy, indications, education, clinical outcomes, quality of life, research gaps, and barriers to dissemination. Three main goals of management for patients with CKD and diabetes were identified: (1) greater use of CGMs for better glycemic monitoring and management, (2) further research evaluating the accuracy, feasibility, outcomes, and potential value of CGMs in patients with end-stage kidney disease (ESKD) on hemodialysis, and (3) equitable access to CGM technology for patients with CKD. The experts also developed 15 conclusions regarding the use of CGMs in this population related to CGMs' unique delivery of both real-time information that can guide monitoring and management of glycemia and continuous and predictive data in this population, which is at higher risk for hypoglycemia and hyperglycemia. The group noted three major clinical gaps: (1) CGMs are not routinely prescribed for patients with diabetes and CKD; (2) CGMs are not approved by the United States Food and Drug Administration (FDA) for patients with diabetes who are on dialysis; and (3) CGMs are not routinely available to all of those who need them because of structural barriers in the health care system. These gaps can be improved with greater stakeholder collaboration, education, and awareness brought to the use of CGM technology in CKD.

Background: The aim of this single-center observational study was to assess the real-world performance of first- and second-generation automated insulin delivery (AID) systems in a cohort of children and adolescents with type 1 diabetes over a one-year follow-up.

Methods: Demographic, anamnestic, and clinical data of the study cohort were collected at the start of automatic mode. Data on continuous glucose monitoring metrics, system settings, insulin requirements, and anthropometric parameters at three different time points (start period, six months, 12 months) were retrospectively gathered and statistically analyzed.

Results: Fifty-four individuals (55.6% of females) aged 7 to 18 years switching to AID therapy were included in the analysis. Two weeks after starting automatic mode, subjects using advanced hybrid closed-loop (AHCL) showed a better response than hybrid closed-loop (HCL) users in terms of time in range (P = .016), time above range 180 to 250 mg/dl (P = .022), sensor mean glucose (P = .047), and glycemia risk index (P = .012). After 12 months, AHCL group maintained better mean sensor glucose (P = .021) and glucose management indicator (P = .027). Noteworthy, both HCL and AHCL users achieved the recommended clinical targets over the entire study period. The second-generation AID system registered longer time spent with automatic mode activated and fewer shifts to manual mode at every time point (P < .001).

Conclusions: Both systems showed sustained and successful glycemic outcomes in the first year of use. However, AHCL users achieved tighter glycemic targets, without an increase of hypoglycemia risk. Improved usability of the device may also have contributed to optimal glycemic outcomes by ensuring better continuity of the automatic mode activation.

Background: Digital health solutions (DHS) are increasingly used to support people with diabetes (PwD) to help manage their diabetes and to gather and manage health and treatment data. There is a need for scientifically reliable and valid methods to measure the value and impact of DHS on outcomes that matter to PwD. Here, we describe the development of a survey questionnaire designed to assess the perceptions of PwD toward DHS and their prioritized outcomes for DHS evaluation.

Method: We applied a structured process for engagement of a total of nine PwD and representatives of diabetes advocacy organizations. Questionnaire development consisted of a scoping literature review, individual interviews, workshops, asynchronous virtual collaboration, and cognitive debriefing interviews.

Results: We identified three overarching categories of DHS, which were meaningful to PwD and crucial for the identification of relevant outcomes: (1) online/digital tools for information, education, support, motivation; (2) personal health monitoring to support self-management; (3) digital and telehealth solutions for engaging with health professionals. Overall outcome domains identified to be important were diabetes-related quality of life, distress, treatment burden, and confidence in self-management. Additional positive and negative outcomes specific to DHS were identified and corresponding questions were incorporated into the survey questionnaire.

Conclusion: We identified the need for self-reporting of quality of life, diabetes distress, treatment burden, and confidence in self-management, as well as specific positive and negative impacts of DHS. We designed a survey questionnaire to further assess the perceptions and perspectives of people with type 1 and 2 diabetes on outcomes relevant for DHS evaluations.

With increasing prevalence of obesity and cardiovascular diseases, there is a growing interest in the use of glucagon-like peptide-1 receptor agonists (GLP-1RAs) as an adjunct therapy in type 1 diabetes (T1D). The GLP-1RAs are currently not approved by the US Food and Drug Administration for the treatment of T1D in the absence of randomized controlled trials documenting efficacy and safety of these agents in this population. The Diabetes Technology Society convened a series of three consensus meetings of clinicians and researchers with expertise in diabetes technology, GLP-1RA therapy, and T1D management. The project was aimed at synthesizing current literature and providing conclusions on the use of GLP-1RA therapy as an adjunct to automated insulin delivery (AID) systems in adults with T1D. The expert panel members met virtually three times on January 17, 2024, and April 24, 2024, and August 14, 2024, to discuss topics ranging from physiology and outcomes of GLP-1RAs in T1D to limitations of current sensors, algorithms, and insulin for AID systems. The panelists also identified research gaps and future directions for research. The panelists voted to in favor of 31 recommendations. This report presents the consensus opinions of the participants that, in adults with T1D using AID systems, GLP-1RAs have the potential to (1) provide effective adjunct therapy and (2) improve glycemic and metabolic outcomes without increasing the risk of severe hypoglycemia or diabetic ketoacidosis.

The quality of clinician-patient relationship is integral to patient health and well-being. This article is a narrative review of published literature on concordance between clinician and patient perspectives on barriers to diabetes technology use. The goals of this manuscript were to review published literature on concordance and to provide practical recommendations for clinicians and researchers. In this review, we discuss the qualitative and quantitative methods that can be applied to measure clinician and patient concordance. There is variability in how concordance is defined, with some studies using questionnaires related to working alliance, while others use a dichotomous variable. We also explore the impact of concordance and discordance on diabetes care, barriers to technology adoption, and disparities in technology use. Published literature has emphasized that physicians may not be aware of their patients' perspectives and values. Discordance between clinicians and patients can be a barrier to diabetes management and technology use. Future directions for research in diabetes technology including strategies for recruiting and retaining representative samples, are discussed. Recommendations are given for clinical care, including shared decision-making frameworks, establishing social support groups optimizing clinician-patient communication, and using patient-reported outcomes to measure patient perspectives on outcomes of interest.

Background: Adverse events for continuous glucose monitors (CGMs) represent a significant issue for people with diabetes with 281 963 CGM adverse events occurring in 2022. The process to obtain adverse events and the US Food and Drug Administration (FDA) database that contains them are reviewed.

Methods: Tables were created in SQL Server for four CGM products (Dexcom G6, all versions of Abbott Libre, Medtronic Guardian 3, and Senseonics Eversense) containing either malfunction or injury adverse events sorted by the manufacturer's chosen product code. As the product code is not always clear (or appropriate), the causes of the events were determined from the text description of the adverse event. The resulting causes were listed in decreasing order in tables for each product and event type.

Results: A common effect of several event causes prevented the user from obtaining a result. Inaccuracy was also a frequent complaint. Other causes were specific to that device.

Conclusions: Creating tables based on manufacturer problem codes for their CGMs, followed by analysis of the adverse event text, facilitates the analysis of event causes. Analyzing adverse event data is the first step in trying to reduce the number of adverse events.