Diabetes technology & therapeutics最新文献

{"title":"A Glucose Fraction Independent of Insulin Secretion: Implications for Type 1 Diabetes Progression in Autoantibody-Positive Cohorts.","authors":"Jay M Sosenko, David Cuthbertson, Laura M Jacobsen, Maria J Redondo, Emily K Sims, Heba M Ismail, Kevan C Herold, Jay S Skyler, Brandon M Nathan","doi":"10.1089/dia.2024.0422","DOIUrl":"10.1089/dia.2024.0422","url":null,"abstract":"<p><p><b><i>Objective:</i></b> We assessed whether there is an impactful glucose fraction independent of insulin secretion in autoantibody-positive individuals. <b><i>Research Design and Methods:</i></b> Baseline 2-h oral glucose tolerance test data from the TrialNet Pathway to Prevention (TNPTP; <i>n</i> = 6190) and Diabetes Prevention Trial-Type 1 (DPT-1; <i>n</i> = 705) studies were used. Linear regression of area under the curve (AUC) glucose versus Index60 was performed to identify two fractions: dependent (dAUCGLU) or independent (iAUCGLU) of insulin secretion. <b><i>Results:</i></b> The lack of correlation (<i>r</i> = 0.06) of iAUCGLU and the inverse correlation of dAUCGLU (<i>r</i> = -0.59) with the first-phase insulin response from DPT-1 were consistent with the independent and dependent designations of the glucose fractions. Correlations of AUC C-peptide were inverse with dAUCGLU and positive with iAUCGLU (TNPTP: <i>r</i> = -0.72, <i>r</i> = 0.57; DPT-1: <i>r</i> = -0.56, <i>r</i> = 0.60). The explained variance of AUC C-peptide increased markedly after separating AUC glucose into its fractions (from 4% to 85% in TNPTP; from 1% to 67% in DPT-1). The independent fraction contributed more to the increased glycemia of impaired glucose tolerance (IGT) than did the dependent fraction. Both dAUCGLU and iAUCGLU predicted IGT and type 1 diabetes (T1D) (<i>P</i> < 0.0001 for all). However, whereas dAUCGLU was more predictive of T1D (chi-square: 849 vs. 249), iAUCGLU was more predictive of IGT (chi-square: 451 vs. 176). <b><i>Conclusions:</i></b> A glucose fraction independent of insulin secretion was identified that was appreciable in autoantibody-positive individuals. It provides insight into the relation between glucose and C-peptide, contributes substantially to the glycemia of IGT, and predicts both T1D and IGT, particularly the latter.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":" ","pages":"179-186"},"PeriodicalIF":5.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142930813","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":"Cardiovascular and Renal Biomarkers in Overweight and Obese Adults with Type 1 Diabetes Treated with Tirzepatide for 21 Months.","authors":"Satish K Garg, Gurleen Kaur, Drew Renner, Monica S Lanning, Emma Mason, Christie Beatson, Kelly Ciesco, Janet Snell-Bergeon","doi":"10.1089/dia.2024.0481","DOIUrl":"https://doi.org/10.1089/dia.2024.0481","url":null,"abstract":"<p><p><b><i>Introduction:</i></b> Overweight (OW) and obesity (OB) affect nearly two thirds of adults with type 1 diabetes (T1D), contributing to suboptimal glucose control, cardiovascular disease (CVD), and diabetic kidney disease (DKD). Many newer drugs such as tirzepatide (a dual-incretin) and sodium-glucose cotransporter-2 inhibitors are approved for people with type 2 diabetes associated with CVD and DKD. We evaluated CVD and DKD biomarkers with off-label long-term (21 months) use of tirzepatide in OW/OB adults with T1D. <b><i>Materials and Methods:</i></b> In this retrospective chart review study, we analyzed data for 84 OW/OB adults with T1D who were prescribed tirzepatide since July 2022 and had used tirzepatide for at least 6 months. Controls (<i>n</i> = 38) were frequency matched for age, diabetes duration, sex, glycosylated hemoglobin (HbA1c), and body mass index (BMI). Data were collected from electronic medical records before initiating tirzepatide and over 21 months of treatment. Linear mixed effects models were used to examine the changes in lipids, blood pressure, and estimated glomerular filtration rate (eGFR) over time in tirzepatide-treated adults versus controls. <b><i>Results:</i></b> Baseline characteristics were similar except that tirzepatide users had a slightly higher baseline BMI than controls; 35.2 ± 4.8 kg/m² and 33.3 ± 4.2 kg/m² (<i>P</i> = 0.03), respectively. Patients using tirzepatide lost significantly more weight (-59 ± 4.6 lbs [-23.4%]) compared with a gain of (+1.7 ± 5.0 lbs [+1.8%]) in controls over 21 months. The HbA1c decreased more in patients using tirzepatide than controls (-0.50 ± 0.07% and -0.24 ± 0.09%, respectively, <i>P</i> = 0.017). Patients using tirzepatide significantly improved total and low-density lipoprotein cholesterol, triglycerides, systolic blood pressure, and eGFR; these changes remained significant even after adjusting for weight and HbA1c. The eGFR declined significantly in controls but not in the tirzepatide users. <b><i>Conclusions:</i></b> We conclude that long-term use of tirzepatide in OW/OB adults with T1D results in more than 23% weight loss and sustained improvement in glucose control. Irrespective of changes in weight and/or HbA1c, we observed significant improvement in cardiovascular biomarkers and preservation of kidney function. We strongly recommend a long-term randomized control trial with tirzepatide in patients with T1D.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":"27 3","pages":"152-160"},"PeriodicalIF":5.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143647679","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":"Diabetes Technology in the Hospital.","authors":"Georgia M Davis, Tim Hropot, Francisco J Pasquel","doi":"10.1089/dia.2025.8813.gmd","DOIUrl":"https://doi.org/10.1089/dia.2025.8813.gmd","url":null,"abstract":"","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":"27 S1","pages":"S183-S188"},"PeriodicalIF":5.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143647716","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":"Randomized, Crossover Trial of Control-IQ Technology with a Lower Treatment Range and a Modified Meal Bolus Module in Adults, Adolescents, Children, and Preschoolers with Varying Levels of Baseline Glycemic Control.","authors":"Sue A Brown, Lori M Laffel, Halis K Akturk, Gregory P Forlenza, Viral N Shah, R Paul Wadwa, Erin C Cobry, Elvira Isganaitis, Melissa Schoelwer, Virginia S Lu, Ricardo Rueda, Nicholas Sherer, John P Corbett, Ravid Sasson-Katchalski, Jordan E Pinsker","doi":"10.1089/dia.2024.0501","DOIUrl":"10.1089/dia.2024.0501","url":null,"abstract":"<p><p><b><i>Objective:</i></b> We evaluated a modified version of Control-IQ technology with a lower treatment range and a modified meal bolus module in adults, adolescents, children, and preschoolers with type 1 diabetes in a multicenter, randomized, and crossover trial. <b><i>Research Design and Methods:</i></b> After a 2-week run-in with Control-IQ technology v1.5, the modified system was evaluated for 2 weeks using treatment range of 112.5-160 mg/dL (standard range [SR]), and for 2 weeks using lower treatment range of 90-130 mg/dL (lower range, LR), at home in random order. Two late bolus meal challenges were performed in each 2-week period, bolusing 45 min after meals with and without a new late bolus feature. <b><i>Results:</i></b> Overall, 72 participants aged 3-57 years completed the study. There were no diabetic ketoacidosis or severe hypoglycemia events. All meal challenges were completed safely. Time in range (TIR) 70-180 mg/dL improved the most with LR to 68.0% (+3.1%, <i>P</i> < 0.001, for LR vs. run-in and +2.1%, <i>P</i> < 0.001, for LR vs. SR). Similar improvements were observed for time in tight range (TITR) 70-140 mg/dL (+3.3%, <i>P</i> < 0.001, for LR vs. run-in and +4.0%, <i>P</i> < 0.001, for LR vs. SR), time >180 mg/dL, and mean glucose. Participants with lower baseline hemoglobin A1c (HbA1c) achieved the highest TIR and TITR with LR use, while the greatest improvements in TIR and TITR were evident in those with higher baseline HbA1c. <b><i>Conclusions:</i></b> The lower treatment range and late bolus feature of the modified Control-IQ system were safe for use in all age-groups. TIR and TITR improved with LR regardless of baseline HbA1c.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":" ","pages":"187-193"},"PeriodicalIF":5.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142726882","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":"New Medications for Diabetes Care.","authors":"Satish K Garg, Drew Renner, Amanda Rewers, Gurleen Kaur, Irl B Hirsch","doi":"10.1089/dia.2025.8816.dr","DOIUrl":"https://doi.org/10.1089/dia.2025.8816.dr","url":null,"abstract":"","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":"27 S1","pages":"S208-S219"},"PeriodicalIF":5.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143647761","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":"Comparison of Computational Statistical Packages for the Analysis of Continuous Glucose Monitoring Data with a Reference Software, \"Ambulatory Glucose Profile,\" in Type 1 Diabetes.","authors":"Kagan E Karakus, Janet K Snell-Bergeon, Halis K Akturk","doi":"10.1089/dia.2024.0410","DOIUrl":"10.1089/dia.2024.0410","url":null,"abstract":"<p><p><b><i>Objective:</i></b> To compare the accuracy of commonly used continuous glucose monitoring (CGM) analysis programs with ambulatory glucose profile (AGP) and Dexcom Clarity (DC) in analyzing CGM metrics in patients with type 1 diabetes (T1D). <b><i>Research Methods:</i></b> CGM data up to 90 days from 152 adults using the same CGM and automated insulin delivery system with T1D were collected. Six of the 19 CGM analysis programs (CDGA, cgmanalysis, Glyculator, iglu, EasyGV, and GLU) were selected to compare with AGP and DC. Metrics were compared etween all tools with two one-sided <i>t</i>-tests equivalence testing. For the equivalence test, the acceptable range of deviation was set as ±2 mg/dL for mean glucose, ±2% for time in range (TIR), ±1% for time above range (TAR), time above range level 1 (TAR1), time above range level 2 (TAR2), and coefficient of variation (CV). <b><i>Results:</i></b> All packages were compared with each other for all CGM metrics, and most of them had statistically significant differences for at least some metrics. All tools were equivalent to AGP for mean glucose, TIR, TAR, TAR1, and TAR2 within ±2 mg/dL, ±2%, ±1%, ±1% and 1%, respectively. CDGA, Glyculator, cgmanalysis, and iglu were not equivalent to AGP for CV within ±1%. All tools were equivalent to DC for mean glucose, TIR, and TAR2 within ±2 mg/dL, ±2%, and ±1%, respectively. Glyculator was not equivalent for TAR1, TAR, and CV. CGDA, cgmanalysis, and iglu were not equivalent to DC for TAR1 and TAR. EasyGV and GLU were not equivalent for TAR within ±1%. <b><i>Conclusions:</i></b> CGM analysis programs reported CGM metrics statistically differently, but these differences may not be applicable in clinical practice. The equivalence test also confirmed that the differences are negligible for TIR and mean glucose, while they can be important for hyperglycemic ranges and CV. A standardization for CGM data handling and analysis is necessary for clinical studies reporting CGM-generated outcomes.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":" ","pages":"202-208"},"PeriodicalIF":5.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142603294","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":"Primary Care and Diabetes Technologies and Treatments.","authors":"Gregg D Simonson, Thomas W Martens, Anders L Carlson, Richard M Bergenstal","doi":"10.1089/dia.2025.8810.gds","DOIUrl":"https://doi.org/10.1089/dia.2025.8810.gds","url":null,"abstract":"","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":"27 S1","pages":"S141-S156"},"PeriodicalIF":5.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143647779","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 Impact of Public Policy on Equitable Access to Technology for Children and Youth Living with Type 1 Diabetes in British Columbia, Canada.","authors":"Jeffrey Bone, Courtney Leach, Ananta Addala, Shazhan Amed","doi":"10.1089/dia.2024.0366","DOIUrl":"10.1089/dia.2024.0366","url":null,"abstract":"<p><p><b><i>Objective:</i></b> Structural inequities impede technology uptake in marginalized populations living with type 1 diabetes (T1D). Our objective was to describe hemoglobin A1c (HbA_1c), time in range (TIR), and pump use to evaluate the impact of a universal funding policy for continuous glucose monitoring (CGM) across levels of deprivation in children with T1D in the Canadian province of British Columbia (BC). <b><i>Methods:</i></b> Patients with T1D and at least one outpatient visit after June 10, 2020 (1-year before universal CGM funding) who were enrolled in the BC Pediatric Diabetes Registry were included (<i>n</i> = 477). The Canadian Index of Multiple Deprivation (quintile 1 = least deprived; quintile 5 = most deprived) was determined using postal code. Mixed effects models were used to describe HbA_1c, TIR, and pump use, and an interrupted time series generalized additive model estimated the change in CGM use pre- and postintroduction of universal coverage. <b><i>Results:</i></b> No differences were observed among the five levels of deprivation for HbA_1c and TIR; however, for residential instability, those with the highest level of deprivation had a lower probability of pump use (-18.9%, 95% confidence interval [CI] = -26.1% to -11.7% for quintile 5 vs. 1). There was an increase in CGM uptake across all levels of deprivation 1-year after introduction of universal CGM funding. For example, the difference in sensor use from the most to least deprived situational group was -21.0% (-35.4%, -6.6%) at the time of universal coverage and shrank to -4.6% (-21.6%, 12.4%) after 12 months of coverage. However, an equity gap in CGM use persisted between the least and most deprived groups (-21.9, 95% CI = -34.5 to -9.4 for quintile 5 vs. 1 in economic dependency). <b><i>Conclusions:</i></b> Universal coverage of CGM improved uptake; however, equity gaps persisted. More research is needed to explore nonfinancial barriers to diabetes technology use in marginalized populations.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":" ","pages":"194-201"},"PeriodicalIF":5.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142715656","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 and Intermittent Glucose Monitoring in 2024.","authors":"Klemen Dovc, Bruce W Bode, Tadej Battelino","doi":"10.1089/dia.2025.8802.kd","DOIUrl":"https://doi.org/10.1089/dia.2025.8802.kd","url":null,"abstract":"","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":"27 S1","pages":"S14-S30"},"PeriodicalIF":5.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143647702","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 Diabetes Technologies on Psychosocial Outcomes.","authors":"Alon Liberman, Katharine Barnard-Kelly","doi":"10.1089/dia.2025.8814.aln","DOIUrl":"https://doi.org/10.1089/dia.2025.8814.aln","url":null,"abstract":"","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":"27 S1","pages":"S189-S199"},"PeriodicalIF":5.7,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143647750","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}