Journal of Diabetes Science and Technology最新文献

{"title":"Methodology for Safe and Secure AI in Diabetes Management.","authors":"Remco Jan Geukes Foppen, Vincenzo Gioia, Shreya Gupta, Curtis L Johnson, John Giantsidis, Maria Papademetris","doi":"10.1177/19322968241304434","DOIUrl":"10.1177/19322968241304434","url":null,"abstract":"<p><p>The use of artificial intelligence (AI) in diabetes management is emerging as a promising solution to improve the monitoring and personalization of therapies. However, the integration of such technologies in the clinical setting poses significant challenges related to safety, security, and compliance with sensitive patient data, as well as the potential direct consequences on patient health. This article provides guidance for developers and researchers on identifying and addressing these safety, security, and compliance challenges in AI systems for diabetes management. We emphasize the role of explainable AI (xAI) systems as the foundational strategy for ensuring security and compliance, fostering user trust, and informed clinical decision-making which is paramount in diabetes care solutions. The article examines both the technical and regulatory dimensions essential for developing explainable applications in this field. Technically, we demonstrate how understanding the lifecycle phases of AI systems aids in constructing xAI frameworks while addressing security concerns and implementing risk mitigation strategies at each stage. In addition, from a regulatory perspective, we analyze key Governance, Risk, and Compliance (GRC) standards established by entities, such as the Food and Drug Administration (FDA), providing specific guidelines to ensure safety, efficacy, and ethical integrity in AI-enabled diabetes care applications. By addressing these interconnected aspects, this article aims to deliver actionable insights and methodologies for developing trustworthy AI-enabled diabetes care solutions while ensuring safety, efficacy, and compliance with ethical standards to enhance patient engagement and improve clinical outcomes.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968241304434"},"PeriodicalIF":4.1,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11672366/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142894881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How Might We Tell if Advances in Diabetes Care and Technology are Helping People to Feel Less Constrained? Introducing the Diabetes Constraints Scale.","authors":"William H Polonsky, Emily C Soriano, Lisa A Strycker, Lawrence Fisher","doi":"10.1177/19322968241308269","DOIUrl":"10.1177/19322968241308269","url":null,"abstract":"<p><strong>Background: </strong>Recent advances in diabetes care and technology, such as real-time continuous glucose monitoring, can help people live more freely, with more flexibility and fewer constraints, thereby enhancing quality of life (QOL). To date, there has been no validated means for measuring this key psychological dimension. We developed the Diabetes Constraints Scale (DCS) to assess perceived constraints pertaining to diabetes self-management.</p><p><strong>Methods: </strong>Six items were developed from qualitative interviews (20 adults with type 2 diabetes [T2D], 8 adults with type 1 diabetes [T1D]). Items were included in one study with T2D adults (N = 458) and one with T1D adults (N = 574). Scale reliability was analyzed for each study using exploratory factor analyses. Associations between DCS and key psychosocial and glycemic variables were assessed.</p><p><strong>Results: </strong>In both studies, factor analyses revealed a single factor, with adequate internal reliability (Cronbach's alpha >.80). Both studies demonstrated significant associations in the expected direction between DCS and overall well-being, diabetes-specific QOL, and diabetes distress (all <i>P</i> < .001). In both studies, DCS was positively linked with the number of missed insulin boluses and the frequency of severe hypoglycemic episodes (T1D both <i>P</i> < .001; T2D both <i>P</i> < .005) and-in the T1D group only-with HbA_1c (<i>P</i> < .001).</p><p><strong>Conclusions: </strong>The DCS is a reliable and valid method to determine the degree to which adults with diabetes feel constrained or limited by the disease. It may serve as a useful tool for assessing how new interventions can help individuals feel freer in the face of the demands of diabetes.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968241308269"},"PeriodicalIF":4.1,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11672359/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142894876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Determinants of Liraglutide Treatment Discontinuation in Type 1 Diabetes: A Post Hoc Analysis of ADJUNCT ONE and ADJUNCT TWO Randomized Placebo-Controlled Clinical Studies.","authors":"Viral N Shah, Rikke M Agesen, Lars Bardtrum, Erik Christiansen, Jennifer Snaith, Jerry R Greenfield","doi":"10.1177/19322968241305647","DOIUrl":"10.1177/19322968241305647","url":null,"abstract":"<p><strong>Introduction: </strong>Two phase 3 randomized controlled studies (ADJUNCT ONE (Clinicaltrials.gov: NCT01836523), ADJUNCT TWO (Clinicaltrials.gov: NCT02098395)) evaluated liraglutide (1.8, 1.2 or 0.6 mg) vs placebo in participants with type 1 diabetes (T1D) as an adjunct to insulin therapy. This paper aims to improve our understanding of the potential mechanisms leading to premature discontinuation of this treatment regimen.</p><p><strong>Methods: </strong>Post hoc comparisons were conducted on baseline characteristics and adverse event (AE) rates of participants completing and not completing the ADJUNCT studies due to AEs/lack of tolerance using summary tables and variance analysis.</p><p><strong>Results: </strong>Non-completers (liraglutide and placebo combined) had lower baseline body mass index (BMI) (ADJUNCT ONE: 27.8 kg/m² vs 29.8 kg/m², <i>P</i> < .0001; ADJUNCT TWO: 26.3 kg/m² vs 29.2 kg/m², <i>P</i> < .0001), longer duration of T1D (25.8 years vs 21.0 years, <i>P</i> < .0001; 24.1 years vs 21.0 years, <i>P</i> = .04), lower daily insulin doses by continuous infusion (46.4 U vs 57.3 U, <i>P</i> = .01; 40.9 U vs 57.4 U, <i>P</i> = .12) or multiple injections (58.4 U vs 68.5 U, <i>P</i> = .006; 56.0 U vs 65.8 U, <i>P</i> =.03) and a higher proportion of participants with undetectable C-peptide (91.5% vs 81.3%; 87.0% vs 84.9%) compared to completers. When analyzed by treatment group, only duration of T1D and C-peptide differed between completers and non-completers among liraglutide (and not placebo) participants. The AE rates were higher for non-completers.</p><p><strong>Conclusion: </strong>Individuals with longer-standing T1D and low levels of C-peptide at baseline were more likely to discontinue adjunctive liraglutide treatment due to AEs/lack of tolerance than individuals with residual insulin production. Lower BMI predicted a greater likelihood of non-completion for the included participants, regardless of treatment. These new findings may be relevant for clinical practice.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968241305647"},"PeriodicalIF":4.1,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11669135/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142882228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Addressing Disparities Using Continuous Glucose Monitors and Remote Patient Monitoring for Youth With Type 1 Diabetes.","authors":"Ming Yeh Lee, Victor Ritter, Blake Shaw, Johannes O Ferstad, Ramesh Johari, David Scheinker, Franziska Bishop, Manisha Desai, David M Maahs, Priya Prahalad","doi":"10.1177/19322968241305612","DOIUrl":"10.1177/19322968241305612","url":null,"abstract":"<p><strong>Background: </strong>Youth with type 1 diabetes (T1D) and public insurance have lower diabetes technology use. This pilot study assessed the feasibility of a program to support continuous glucose monitor (CGM) use with remote patient monitoring (RPM) to improve glycemia for youth with established T1D and public insurance.</p><p><strong>Methods: </strong>From August 2020 to June 2023, we provided CGM with RPM support via patient portal messaging for youth with established T1D on public insurance with challenges obtaining consistent CGM supplies. We prospectively collected hemoglobin A_1c (HbA_1c), standard CGM metrics, and diabetes technology use over 12 months.</p><p><strong>Results: </strong>The cohort included 91 youths with median age at enrollment 14.7 years, duration of diabetes 4.4 years, 33% non-English speakers, and 44% Hispanic. Continuous glucose monitor data were consistently available (≥70%) in 23% of the participants. For the 64% of participants with paired HbA_1c values at enrollment and study end, the median HbA_1c decreased from 9.8% to 9.0% (<i>P</i> < .001). Insulin pump users increased from 31 to 48 and automated insulin delivery users increased from 11 to 38.</p><p><strong>Conclusions: </strong>We established a program to support CGM use in youth with T1D and barriers to consistent CGM supplies, offering lessons for other clinics to address disparities with team-based, algorithm-enabled, remote T1D care. This real-world pilot and feasibility study noted challenges with low levels of protocol adherence and obtaining complete data in this cohort. Future iterations of the program should explore RPM communication methods that better align with this population's preferences to increase participant engagement.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968241305612"},"PeriodicalIF":4.1,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11664559/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142877339","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adherence Monitor for Measurement of Removable Cast Walker Wear-Time: Multiple Sensors and Predictive Analytics Improve Accuracy.","authors":"Robert M Havey, Avinash G Patwardhan, Rodney M Stuck, Stephanie A Keen, Muturi G Muriuki","doi":"10.1177/19322968241304751","DOIUrl":"10.1177/19322968241304751","url":null,"abstract":"<p><strong>Background: </strong>Treatment of diabetes and its complications is a primary health care expense. Up to 25% of people with diabetes will develop diabetic foot ulcers (DFUs). Removable cast walker (RCW) boots commonly prescribed for DFU treatment, promote healing, and provide offloading and wound protection. Patient RCW removal for hygiene and wound care can lead to decreased adherence and treatment effectiveness. This study evaluated a new system for wear-time adherence measurement using multiple sensor types.</p><p><strong>Methods: </strong>An electronic wear-time monitor was developed, which included internal and external temperature sensors, an accelerometer, and capacitive proximity foot and ankle sensors. Time-stamped and date-stamped data were saved once per minute for up to 22 days. Ten healthy volunteer subjects were recruited to wear an RCW for two weeks while keeping a diary of don/doff times. Sensor data were then compared with volunteers' wear diaries using confusion matrix predictive analytics.</p><p><strong>Results: </strong>Algorithms were developed for data processing. Correlation coefficients between algorithms and diaries were calculated for individual and multiple sensor combinations. Differential temperature and accelerometer algorithms were significantly better at predicting subject wear-time than individual temperature sensor algorithms (<i>P</i> = .009, <i>P</i> = .001, respectively). Foot proximity had significantly better correlation with subject diaries than temperature (<i>P</i> = .024), and acceleration algorithms (<i>P</i> = .005). Multi-sensor analysis showed high correlation (.96) with wear-time from subject diaries.</p><p><strong>Conclusions: </strong>Removable cast walker wear-time can be accurately determined using an electronic data recorder and multiple sensors. Wear-time measurement accuracy can be improved using algorithms that operate on data from multiple sensors that use a variety of sensor technologies.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968241304751"},"PeriodicalIF":4.1,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11664564/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142877341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Behavioral Intervention Functions in Type 2 Diabetes Apps: Literature Review.","authors":"Elia Gabarron, Pietro Randine, Eirik Årsand","doi":"10.1177/19322968241305646","DOIUrl":"10.1177/19322968241305646","url":null,"abstract":"<p><strong>Background: </strong>As type 2 diabetes (T2D) is expected to increase, self-management becomes more crucial. Mobile apps are increasingly supporting self-management with tasks like blood glucose monitoring and medication management. Understanding the behavioral intervention functions used by diabetes apps today, is essential for improving future apps and systems for diabetes management.</p><p><strong>Objective: </strong>To analyze the behavioral intervention functions used in apps for managing T2D that integrate the three main elements: medication management, nutrition tracking, and blood glucose management.</p><p><strong>Methods: </strong>We conducted a literature review on T2D diabetes apps using SCOPUS, PubMed, and PsycINFO. After screening and removing duplicates, we analyzed app details and behavioral intervention functions based on the Behavior Change Wheel (BCW) framework.</p><p><strong>Results: </strong>We reviewed 644 scientific publications describing diabetes apps in clinical studies, narrowing it down to 20 studies, including 16 unique apps, after screening and exclusions. These studies were published between 2016 and 2024. Among the identified apps, automatic processing of medication data was reported in one study, while blood glucose data were automatically processed in 13 studies. Nutrition data processing varied. Most apps used <i>Enablement</i> and <i>Persuasion</i> as behavioral intervention functions, with <i>Education</i> and <i>Training</i> reported less frequently. <i>Environmental Restructuring, Incentivization, Coercion, Restriction</i>, and <i>Modeling</i> were not reported as being used in any studies.</p><p><strong>Conclusions: </strong>This review shows that while <i>Enablement</i> and <i>Persuasion</i> are common, other behavioral intervention functions seem to be underused or underreported. Future research could explore the potential of integrating additional behavioral intervention functions to enhance diabetes app efficacy and users' self-management.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968241305646"},"PeriodicalIF":4.1,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11664556/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142877345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Effective Use by Primary Care Clinicians of a Comprehensive Computerized Insulin Dose Adjustment Algorithm.","authors":"Mayer B Davidson","doi":"10.1177/19322968241306127","DOIUrl":"10.1177/19322968241306127","url":null,"abstract":"<p><p>Primary care clinicians (PCCs) manage 90% of patients with diabetes, 30% of whom require insulin with a substantial number poorly controlled because of the challenges that PCCs face (time constraints and lack of experience). The author has developed Federal Drug Administration cleared and Conformite Europeenne mark registered comprehensive computerized insulin dose adjustment algorithms (CIDAAs) to enable PCCs to significantly lower HbA1c levels in insulin-requiring patients. Reports sent to PCCs contain scatter plots of glucose readings, their organization into pre- and postprandial and before bedtime values, their analyses, and recommendations for insulin dose adjustments (if indicated) that the PCC can accept or modify. The glucose readings are provided to the CIDAAs for analysis at either in-person visits or remotely. The new doses accepted by PCCs serve as the basis for the subsequent report. Published studies evaluating this comprehensive CIDAA involved 104 poorly controlled patients taking insulin for greater than or equal to six months who were independently managed by PCCs. Over four to six months, initial HbA1c levels of 9.7% fell by 1.7%. Combining these results with 138 other better controlled patients in real-world situations, initial measured and estimated HbA1c levels of 8.3% fell by 0.7% in 6.4 months enabling PCCs to significantly improve glycemic control. Other advantages of PCCs utilizing these comprehensive CIDAAs are saving time for PCCs so that they can address non-diabetes issues and/or see other patients and ongoing PCC education in adjusting insulin doses by matching glucose patterns and dose-change recommendations with subsequent glycemic responses.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968241306127"},"PeriodicalIF":4.1,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11664563/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142877351","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How the Diabetes Research Hub Will Modernize and Enhance Diabetes Data Utilization.","authors":"Alessandra T Ayers, Cindy N Ho, Emma Friedman, Juan Espinoza, Shahid N Shah, David C Klonoff","doi":"10.1177/19322968241306129","DOIUrl":"10.1177/19322968241306129","url":null,"abstract":"<p><p>The Diabetes Research Hub (DRH) is a centralized data management system and repository that will revolutionize how diabetes data are gathered, stored, analyzed, and utilized for research. By harnessing advanced analytics for large datasets, the DRH will support a nuanced understanding of physiological patterns and treatment effectiveness, ultimately advancing diabetes management and patient outcomes. This is an opportune time for researchers who are collecting continuous glucose data and related physiological data sources, to leverage the capabilities of the DRH to enhance the value of their data.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968241306129"},"PeriodicalIF":4.1,"publicationDate":"2024-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11662337/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142872346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantification of Different Types of Waste and Batteries Associated With the Widespread Usage of Continuous Glucose Monitoring Systems.","authors":"Sebastian F Petry, Marie Bienhaus, Friedrich W Petry, Johannes K Petry, Lutz Heinemann, Stefan Gäth","doi":"10.1177/19322968241305161","DOIUrl":"10.1177/19322968241305161","url":null,"abstract":"<p><strong>Background: </strong>People with diabetes benefit from continuous glucose monitoring (CGM) systems. A downside of these valuable aids for diabetes management is the generation of a tremendous amount of waste. This study aimed to quantify this CGM-related waste.</p><p><strong>Method: </strong>Twenty-four used CGM sensors from two different manufacturers (8× FreeStyle Libre 2, 11× FreeStyle Libre 3, and 5× Dexcom G7) were dismantled manually and separated in case, circuit board, and battery. Each component as well as included packaging, applicator, and leaflet were weighed separately.</p><p><strong>Results: </strong>Packaging, applicators, and leaflets accounted for most of the waste (FL2: 93.4 g; FL3: 58 g; G7: 108.1 g). The plastic case contributed mainly to the total sensor weight (FL2: 1.9 g/63% of 3.3 g; FL3: 0.5 g/49% of 1.1 g; G7: 1.9 g/59% of 3.2 g), whereas the weight of the electronic circuit board and battery varied (FL2: 0.8 g/25%, 0.4 g/12%; FL3: 0.2 g/17%, 0.4 g/34%; G7: 0.7 g/22%, 0.6 g/19%). Extrapolating these data based on annual worldwide usage of around 230 million glucose sensors, approximately 20,000 tons of packaging, applicators, and leaflets and 580 tons of glucose sensors are disposed of, including about 340 tons of casings, 130 tons of circuit boards, and 110 tons of batteries.</p><p><strong>Conclusions: </strong>Our data highlight the potential for optimized resource utilization by reduction of packaging, sensor size, longer application periods, implementation of multiuse applicators, and the need for recycling options.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968241305161"},"PeriodicalIF":4.1,"publicationDate":"2024-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11662339/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142872256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Expectations and Outcomes From Glucagon-Like Peptide-1 Receptor Agonists As Adjunct Treatment for Type 1 Diabetes - Case Presentations.","authors":"Sujatha Seetharaman, Eda Cengiz","doi":"10.1177/19322968241305641","DOIUrl":"10.1177/19322968241305641","url":null,"abstract":"<p><strong>Background: </strong>Type 1 diabetes (T1D) is characterized by the autoimmune destruction of pancreatic beta cells, leading to lifelong insulin dependence. Despite advancements in insulin therapies and glucose monitoring, maintaining optimal blood glucose control remains challenging with common issues like weight gain and glucose variability. Glucagon-like peptide 1 receptor agonists (GLP-1 RAs), approved for type 2 diabetes and obesity, are being explored off-label for T1D.</p><p><strong>Case report: </strong>This case series investigates the effectiveness of GLP-1 RAs, mainly semaglutide and tirzepatide, as an adjunct therapy to insulin in adolescents and young adults (AYA) with T1D, in a single center, providing real-world insights and highlighting practical issues.</p><p><strong>Discussion: </strong>Most patients had obesity, consistent with typical indication for use in AYA. Common gastrointestinal side effects improved with dose titration, but careful monitoring is needed for persistent symptoms. One patient developed an eating disorder, underscoring the need for vigilance. Insurance and medication shortage issues impacted treatment continuity, highlighting the need for better support. Glycemic parameters improved in most patients, with weight reduction in several patients with obesity, and no reported diabetic ketoacidosis.</p><p><strong>Conclusions: </strong>GLP-1 RAs can be a beneficial adjunct therapy in T1D, improving glycemic control, reducing insulin needs, and supporting weight management, while potentially preventing long-term cardiovascular and renal complications.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968241305641"},"PeriodicalIF":4.1,"publicationDate":"2024-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11662345/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142872345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}