Diabetes technology & therapeutics最新文献

{"title":"Real-World Accuracy of Continuous Glucose Monitoring During Intensive Hematological Care: A Prospective Study.","authors":"Marieke Tienstra, Riemer A Been, Janneke W de Boer, Reinold O B Gans, André P van Beek, Hilde A M Kooistra, Valerie R Wiersma, Omar G Mustafa, Pratik Choudhary, Tom van Meerten, Peter R van Dijk","doi":"10.1089/dia.2025.0232","DOIUrl":"https://doi.org/10.1089/dia.2025.0232","url":null,"abstract":"<p><p><b><i>Background:</i></b> Patients treated for a hematological malignancy are susceptible to hyperglycemia, which can negatively affect treatment outcomes. Therefore, close monitoring of glucose levels is crucial. Data demonstrated that capillary measurement methods underreport hyperglycemic episodes compared with continuous glucose monitoring (CGM). However, the accuracy of CGM during intensive hematological treatments, and the associated metabolic and hemostatic imbalances, is unknown, which we aim to investigate in the current study. <b><i>Methods:</i></b> For the analysis, data collected during a prospective study that compared CGM with capillary point-of-care (POC) glucose measurements in adult patients hospitalized for intensive hematological care with three different treatment modalities, namely chimeric antigen receptor T-cell therapy, allogeneic stem cell transplantation (allo-SCT), or autologous stem cell transplantation (auto-SCT), were used. POC and CGM measurements were performed concurrently. Accuracy was assessed using mean and median absolute relative difference (MARD), Diabetes Technology Society (DTS) Error Grid analysis as well as percentages of values within 15%/15, 20%/20, and 30%/30 mg/dL. <b><i>Results:</i></b> A total of 60 patients (28% female, median age 64 [58-68] years and 10% with a history of diabetes mellitus) were included, yielding 1999 matched measurement pairs. The overall mean ARD was 21.5%, whereby the lowest mean ARD was observed during allo-SCT (18.3%) and the highest mean ARD during auto-SCT (27.1%). The percentages of glucose values within 15%/15, 20%/20, and 30%/30 mg/dL agreements were 38.1%, 51.1%, and 75.1%. The DTS Error Grid analysis showed good clinical accuracy with 99.6% of pairs within zone A + B. <b><i>Conclusions:</i></b> Despite the relative high MARD, the use of CGM is unlikely to result in harmful insulin dosing errors and seems feasible to use during intensive hematological care.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":" ","pages":""},"PeriodicalIF":5.7,"publicationDate":"2025-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144552590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Continuous Glucose Monitoring in Type 1 Diabetes, Type 2 Diabetes, and Diabetes During Pregnancy: A Systematic Review with Meta-Analysis of Randomized Controlled Trials.","authors":"Evangelos C Rizos, Georgios Markozannes, Nikolaos Charitakis, Panagiotis Filis, Anastasia E Stoimeni, Kirsten Nørgaard, Evangelia E Ntzani, Konstantinos K Tsilidis","doi":"10.1089/dia.2024.0599","DOIUrl":"10.1089/dia.2024.0599","url":null,"abstract":"<p><p><b><i>Background:</i></b> Continuous glucose monitoring (real-time CGM [RT-CGM] and retrospective [professional] CGM [non-RT-CGM]) is an emerging tool to assess glucose levels and variability. We performed a meta-analysis of randomized controlled trials (RCTs) to assess the effect of RT/non-RT-CGM on type 1 (T1D), type 2 (T2D), and diabetes in pregnancy (DiP) compared with self-monitoring of blood glucose (BGM). <b><i>Methods:</i></b> We searched PubMed/EMBASE/Cochrane Central Register of Controlled Trials until October 2024. The coprimary outcomes were the weighted mean change differences (WMCDs and absolute differences) from baseline in glycated hemoglobin (HbA1c) and in time in range (TIR%), time below range (TBR%), and time above range (TAR%). <b><i>Results:</i></b> A total of 64 RCTs were analyzed: (1) RT-CGM/T1D: CGM was superior to BGM for HbA1c reduction (WMCD -0.24, 95% confidence interval [CI]: -0.35; -0.14, <i>I</i>²= 71%), decrease in TBR <70 mg/dL (WMCD -2.41, 95% CI: -3.46; -1.35, <i>I</i>²= 96%), decrease in TBR < 54 mg/dL (WMCD -1.18 95% CI: -1.9; -0.47, <i>I</i>²= 97%), decrease in TAR >180 mg/dL (WMCD -2.99, 95% CI: -5.28; -0.71, <i>I</i>² = 92%), decrease in TAR >250 mg/dL (WMCD -3.99, 95% CI: -5.76; -2.21, <i>I</i>²= 92%), and increase in TIR 70-180 mg/dL (WMCD 5.57, 95% CI: 4.13; 7.01, <i>I</i>²= 84%); (2) RT-CGM/T2D: CGM was superior to BGM for HbA1c reduction (WMCD -0.40, 95% CI: -0.55; -0.24, <i>I</i>²= 52%), decrease in TAR > 180 mg/dL (WMCD -6.32, 95% CI: -9.87; -2.78, <i>I</i>²= 84%), decrease in TAR > 250 mg/dL (WMCD -5.73, 95% CI: -8.96; -2.49, <i>I</i>²= 89%), and increase in TIR 70-180 mg/dL (WMCD 5.46, 95% CI: 2.76; 8.16, <i>I</i>²= 69%); (3) RT-CGM/DiP: CGM was superior to BGM for TIR 63-140 mg/dL (WMCD: 17.77, 95% CI: 4.17; 31.36, <i>I</i>²= 92%). No benefit was shown for HbA1c, TBR < 63 mg/dL, TAR > 140 mg/dL, and most of the maternal and neonatal outcomes of interest; (4) Non-RT CGM: HbA1c significantly decreased with non-RT CGM compared with BGM in T2D (WMCD -0.35, 95% CI: -0.5; -0.2, <i>I</i>²= 19%). <b><i>Discussion:</i></b> In T1D and T2D, RT-CGM decreased HbA1c and increased time in target range for glycemia (70-180 mg/dL) while decreasing time spent in hypoglycemia (T1D) and time in hyperglycemia (T1D, T2D).</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":" ","pages":"537-552"},"PeriodicalIF":5.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143572423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial Pancreas: The First 20 Years.","authors":"Francis J Doyle, Boris P Kovatchev","doi":"10.1089/dia.2025.0134","DOIUrl":"https://doi.org/10.1089/dia.2025.0134","url":null,"abstract":"","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":"27 S3","pages":"S1-S8"},"PeriodicalIF":5.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144539481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Association of Time-in-Range and Time-in-Tight-Range with Retinopathy Progression in the Virtual Diabetes Control and Complications Trial Continuous Glucose Monitoring Dataset.","authors":"Benjamin Lobo, Lauren Kanapka, Boris P Kovatchev, Craig Kollman, Roy W Beck","doi":"10.1089/dia.2025.0033","DOIUrl":"10.1089/dia.2025.0033","url":null,"abstract":"<p><p><b><i>Background:</i></b> In a prior work, a virtual continuous glucose monitoring (CGM) trace was generated for each of the 1441 participants in the landmark Diabetes Control and Complications trial (DCCT). These new data allow us to compare whether time-in-tight-range (TITR) is a better predictor of diabetic microvascular complications (specifically retinopathy development or progression) than time-in-range (TIR). <b><i>Methods:</i></b> Discrete Cox proportional hazard models were used to calculate the hazard ratios (HRs) for the development/progression of retinopathy. <b><i>Results:</i></b> For a 1.0 standard deviation (SD) change, the adjusted HR (95% confidence interval) was 2.67 (2.33-3.06) for TIR, 2.74 (2.36-3.18) for TITR, and 2.37 (2.13-2.65) for HbA1c; a similar pattern of results was obtained for a 0.5 SD change. Computing Harrell's C-statistic showed that a survival model adjusted for TIR, TITR, or HbA1c had similar predictive performance. <b><i>Conclusion:</i></b> The associations of TIR and TITR with retinopathy development or progression were similar to HbA1c in the virtual DCCT CGM dataset.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":" ","pages":"558-561"},"PeriodicalIF":5.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143482422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Role of a Continuous Glucose Monitoring-Derived Glycation Ratio in the Development of Microvascular Complications.","authors":"Laura B Bovee, Theodore A Gooley, Jordan E Perlman, Irl B Hirsch","doi":"10.1089/dia.2024.0580","DOIUrl":"10.1089/dia.2024.0580","url":null,"abstract":"<p><p><b><i>Background:</i></b> Previous studies have evaluated the associations between HbA1c discordance and diabetes complications using indices of glycation. The ideal index would allow for identification of those at increased risk for microvascular complications. This analysis evaluates the association of a newly published index, the glycation ratio (GR), with diabetic retinopathy (DR) and diabetic kidney disease (DKD). <b><i>Methods:</i></b> This is a retrospective review of 661 patients with diabetes seen at the University of Washington. All patients used continuous glucose monitoring (CGM) before the study. Diabetes duration was greater than 20 years in 59%. Median age was 45 years. GR was defined as the ratio of the glucose management indicator (GMI) to the HbA1c. The associations of GR with microvascular complications were each assessed using logistic regression. <b><i>Results:</i></b> Modeling GR as a continuous linear variable, each increase in GR of 0.20 units was associated with a 38% relative reduction in the odds of DR (adjusted odds ratio [OR] = 0.62; 95% confidence interval [CI]: 0.45-0.86, <i>P</i> = 0.004] and a similar reduction in the odds of DKD (OR = 0.61; 95% CI: 0.41-0.93, <i>P</i> = 0.02). <b><i>Conclusions:</i></b> GR may be a useful marker for risk of diabetic microvascular complications. Longitudinal assessment will be required to see how well GR compares with GMI or HbA1c alone.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":" ","pages":"553-557"},"PeriodicalIF":5.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143381832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Metabolic Models, in Silico Trials, and Algorithms.","authors":"Ali Cinar, Ananda Basu, B Wayne Bequette, Marc D Breton, Bruce Buckingham, Eda Cengiz, Claudio Cobelli, Eyal Dassau, Francis J Doyle, Chiara Fabris, Andrea Facchinetti, Irl Hirsch, Roman Hovorka, Peter G Jacobs, Boris P Kovatchev, Chiara Dalla Man, Laurie Quinn, Jay Skyler","doi":"10.1089/dia.2025.18800.ac","DOIUrl":"https://doi.org/10.1089/dia.2025.18800.ac","url":null,"abstract":"<p><p>Artificial pancreas (AP) systems, also called automated insulin delivery systems, have improved the time in range of glucose levels, reduced the daily burden of the user for glucose regulation, and improved their quality of life. Several commercially available AP systems operate in hybrid closed-loop mode that requires manual information from the user for meals and exercise. This article summarizes the progress on mathematical models of glucose-insulin dynamics, continuous glucose monitoring systems, and insulin pumps that form the building blocks of AP systems, the shift from animal studies to in silico clinical trials that accelerated the rate of progress in AP technologies and the efforts for developing the next-generation AP systems, and the fully automated AP that eliminates manual inputs and mitigates the effects of disturbances to glucose homeostasis-meals, physical activities, acute stress, and variations in sleep characteristics. A section is devoted to discuss the unique glycemic management challenges faced by women with diabetes across the lifespan (menstrual cycle, menopause, pregnancy) and summarize progress made to reduce their impact on glycemic management.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":"27 S3","pages":"S21-S32"},"PeriodicalIF":5.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144539483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of Meal Insulin Bolus Timing and Bedtime Snacking on Continuous Glucose Monitoring-Derived Glycemic Metrics in Hospitalized Inpatients.","authors":"Sara M Alexanian, Michael C Cheney, Jenny C Bello Ramos, Nicole L Spartano, Howard A Wolpert, Devin W Steenkamp","doi":"10.1089/dia.2025.0027","DOIUrl":"10.1089/dia.2025.0027","url":null,"abstract":"<p><p><b><i>Objective:</i></b> In hospitalized inpatients, timely administration of prandial insulin with meals is challenging. Furthermore, the glycemic impact of snacking after dinner (\"bedtime snacking\") without prandial insulin administration has not been previously explored. We present an analysis of the impact of delayed mealtime insulin administration and bedtime snacking on inpatient glycemic control. <b><i>Research Design and Methods:</i></b> We conducted a post hoc analysis from the In-Fi study: a randomized controlled trial comparing Fiasp versus insulin aspart (Novolog) in inpatients with type 2 diabetes. Glycemic outcomes were assessed using the Dexcom G6 PRO continuous glucose monitoring (CGM). We analyzed CGM and insulin administration data from 122 randomized subjects who completed the primary study protocol, which included wearing a CGM for ≥4 meals. This analysis evaluates the impact of delayed mealtime insulin administration and bedtime snacking on glucose control. <b><i>Results:</i></b> Four-hour postprandial time in range (TIR_70-180) was 48% for insulin boluses administered before meals (<i>n</i> = 149) versus 24% when a meal bolus was delayed for >5 min after a meal (mean delay 58.7 min; <i>n</i> = 112; <i>P</i> < 0.001). Bedtime snacking (9 pm-12 am) was associated with significantly higher fasting glucose the next morning (35.2 mg/dL, standard error [SE] = 15.4, <i>P</i> = 0.026) and with a reduced overnight (9 pm-6 am) TIR_70-180 (31.9%, SE = 8.06, <i>P</i> < 0.001), adjusting for bedtime sensor glucose. Bedtime snacking was associated with higher overnight glucose standard deviation (12.3 mg/dL, SE = 3.46, <i>P</i> < 0.001) and with higher overnight glucose percentage coefficient of variation (3.6%; SE = 1.7, <i>P</i> = 0.044), adjusting for initial bedtime sensor glucose. <b><i>Conclusions:</i></b> Delayed mealtime insulin administration and bedtime snacking without insulin administration are significant causes of postprandial and overnight hyperglycemia in hospitalized inpatients. Adjustments in mealtime insulin protocols, attention to food intake, and the potential inpatient adoption of technology, such as CGM and automated insulin delivery systems, are needed to address this shortcoming in inpatient diabetes care.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":" ","pages":"511-516"},"PeriodicalIF":5.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143604173","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Early Stages of Automated Insulin Delivery.","authors":"Howard Zisser, Roman Hovorka, Ananda Basu, Tadej Battelino, Charlotte K Boughton, Marc D Breton, Bruce A Buckingham, Sue A Brown, Daniel R Cherñavvsky, Eyal Dassau, Mark D DeBoer, Francis J Doyle, Laya Ekhlaspour, Chiara Fabris, Gregory P Forlenza, Ahmad Haidar, David C Klonoff, Boris Kovatchev, Aaron J Kowalski, Carol J Levy, Yogish C Kudva, David M Maahs, Moshe Phillip, Eric Renard, Steven J Russell, Viral N Shah, Garry M Steil, R Paul Wadwa, Stuart A Weinzimer","doi":"10.1089/dia.2025.18802.hz","DOIUrl":"https://doi.org/10.1089/dia.2025.18802.hz","url":null,"abstract":"<p><p>The development of automated insulin delivery systems has seen tremendous improvements from individual components to interoperable system combinations of devices and new drugs besides insulin. The components have become progressively smaller, more accurate, and more user friendly. This article summarizes the history of the artificial pancreas from the earliest concepts to fully functional systems to research into further improvements in the future. The authors include many of the developers of this technology who received research support from the National Institute of Diabetes and Digestive and Kidney Diseases at various stages to develop these systems.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":"27 S3","pages":"S33-S47"},"PeriodicalIF":5.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144539482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Practical Considerations and Implementation of Automated Insulin Delivery Systems.","authors":"Laurel H Messer, Gregory P Forlenza, Linda Gonder-Frederick, Korey Hood, Osagie Ebekozien, Katharine Barnard-Kelly, Lori M Laffel, Jennifer L Sherr, Rayhan Lal, Stuart A Weinzimer","doi":"10.1089/dia.2025.0132","DOIUrl":"https://doi.org/10.1089/dia.2025.0132","url":null,"abstract":"<p><p>Automated Insulin Delivery (AID) is in a new era of implementation challenges and opportunities for people with diabetes (PWD) and healthcare providers (HCPs). Beyond technologic variation, cost, access, and HCP endorsement/experience lead to uneven uptake of AID technologies, and attenuate universal ease of use. For AID to be broadly implemented, we must prioritize the lived experience for PWD, and consider how to alleviate burden to promote holistic wellbeing. Expectations and education help HCPs and PWD navigate the similarities and differences between AID devices, and help find common ties: users need to give the system time to work, learn to trust it, and not try to \"trick\" the system. Despite these learnings, disparities in uptake exist, both in clinical trials and in routine clinical care. Strategies to proactively address AID disparities are needed at multiple levels, all of which increase in importance as AID becomes more common for people with type 2 diabetes. Further, broader implementation will require comprehensive healthcare system integration efforts, including new data solutions. Overall, the success of AID requires ongoing transformation of clinical paradigms, with lockstep alignment between PWD and their families, healthcare professionals, researchers, funders, policy makers, and industry partners.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":"27 S3","pages":"S72-S78"},"PeriodicalIF":5.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144539484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research Gaps, Challenges, and Opportunities in Automated Insulin Delivery Systems.","authors":"Peter G Jacobs, Carol J Levy, Sue A Brown, Michael C Riddell, Ali Cinar, Charlotte K Boughton, Marc D Breton, Eyal Dassau, Greg Forlenza, Robert J Henderson, Roman Hovorka, David M Maahs, Medha Munshi, Helen Murphy, Sarit Polsky, Richard Pratley, Melissa S Putman, Viral N Shah, Leah M Wilson, Howard Zisser, Laya Ekhlaspour","doi":"10.1089/dia.2025.0129","DOIUrl":"https://doi.org/10.1089/dia.2025.0129","url":null,"abstract":"<p><p>Since the discovery of the life-saving hormone insulin in 1921 by Dr. Frederick Banting in 1921, there have been many critical discoveries and technical breakthroughs that have enabled people living with type 1 diabetes (T1D) to live longer, healthier lives. The development of insulin pumps, continuous glucose monitoring systems, and automated insulin delivery (AID) systems has enabled people living with T1D to safely manage their glucose, reduce their HbA1c, and improve their overall health and quality of life. Nevertheless, AID systems are not yet designed for all people with T1D, and they perform best during the overnight period when meals and exercise are not occurring. AID systems are not fully automated in that they require the person using the system to announce meals and exercise to the system to avoid dangerous hyper- or hypoglycemia, respectively. In this review, which is one of a collection of articles to commemorate the 75th anniversary of the National Institute for Diabetes and Digestive and Kidney Diseases, we celebrate the commercialization of the AID and discuss the major challenges and research gaps that remain to be solved to enable single- and multihormone AID systems to more fully support glucose management in people living with T1D. More research is required to design and evaluate more intelligent AID systems that do not require accurate carbohydrate estimations or announcements for meals and exercise. Current AID systems are also not designed to be used by older adults or pregnant people. Results are presented on new AID systems that can automatically respond to meals and exercise. Results are also presented on evaluations of AID systems in older adults and pregnant people. Next-generation AID systems will need to support all people, including older adults, people during pregnancy, athletes, and people who may be too busy to announce carbohydrates or exercise to the system. Solutions are now becoming available that will enable AID systems to support a broader range of people living with T1D by leveraging the latest technologies in artificial intelligence and adaptive control.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":"27 S3","pages":"S60-S71"},"PeriodicalIF":5.7,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144539486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}