Diabetes technology & therapeutics最新文献

{"title":"Long-Term Health Economic Evaluation of Intermittently Scanned Glucose Monitoring Compared with Self-Monitoring Blood Glucose in a Real-World Setting in Finnish Adult Individuals with Type 1 Diabetes.","authors":"Jyrki Mustonen, Päivi Rautiainen, Marja-Leena Lamidi, Piia Lavikainen, Janne Martikainen, Tiina Laatikainen","doi":"10.1089/dia.2024.0102","DOIUrl":"10.1089/dia.2024.0102","url":null,"abstract":"<p><p><i>B</i><b><i>ackground and Aims:</i></b> There has been an evolving trend in the use of intermittently scanned continuous glucose monitoring (isCGM) among individuals with type 1 diabetes. Although isCGM is proven to be beneficial in the treatment of individuals with type 1 diabetes, its use leads to increasing device costs. This study aimed to investigate the long-term cost-effectiveness of isCGM. <b><i>Methods:</i></b> Long-term clinical outcomes and costs were projected using the IQVIA Core Diabetes Model (v10.0) based on the observed real-world outcomes of isCGM. The clinical input data for the analysis were sourced from a real-world patient cohort from Eastern Finland, including 877 adult individuals with type 1 diabetes with isCGM (i.e., Freestyle Libre 1 and 2). At the baseline, the patients' mean age was 48 years, and the mean duration of diabetes was 25.8 years. The mean baseline HbA1c was 8.6%, and the mean 12-month change from baseline in HbA1c was -0.37% after the initiation of isCGM. The cost-effectiveness analysis was performed over a lifetime time horizon. A discount rate of 3% was used for the future costs and health outcomes. <b><i>Results:</i></b> The projected use of isCGM was associated with improved quality-adjusted life year (QALY) expectancy of 0.84 QALYs after the start of isCGM. The direct lifetime costs were 7861 EUR higher with the use of isCGM, which resulted in an incremental cost-effectiveness ratio of 9396 EUR per QALY gained. <b><i>Conclusions:</i></b> According to the present analysis, the use of isCGM is considered cost-effective in adult individuals with type 1 diabetes in a real-world setting in Finland.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":" ","pages":"918-924"},"PeriodicalIF":5.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141261004","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":"Reduced Rate of Hospitalizations for Acute Diabetes Events Before and After FreeStyle Libre^® System Initiation in Some People With Type 2 Diabetes on Insulin-Secretagogue Oral Drug Therapy Without Insulin in France.","authors":"Jean-Pierre Riveline, Fleur Levrat-Guillen, Bruno Detournay, Eric Vicaut, Gérard De Pouvourville, Corinne Emery, Bruno Guerci","doi":"10.1089/dia.2024.0171","DOIUrl":"10.1089/dia.2024.0171","url":null,"abstract":"<p><p><b><i>Objective:</i></b> Glycemic management in people with type 2 diabetes mellitus (T2DM) on insulin-secretagogue regimens without insulin is of importance, as this group still represents a significant proportion of patients. Risks for acute diabetes events (ADEs), including diabetic ketoacidosis (DKA) or hypoglycemia, using insulin-secretagogue drugs are well established. Few studies have suggested that continuous glucose monitoring (CGM) could be useful for monitoring glucose dynamics associated with the use of such therapies. To document this point an exploratory analysis was conducted in a group of individuals with noninsulin treated T2DM in France who are managed with oral insulin-secretagogues and initiating the FreeStyle Libre^® system (FSL). <b><i>Methods:</i></b> A retrospective study of the French national SNDS reimbursement claims database (≈66 million French people) was conducted to identify people with T2DM on oral insulin-secretagogues and receiving a first reimbursement of FSL between August 1, 2017 and December 31, 2018. The analysis included data for the 12 months before and up to 24 months after FSL initiation. Hospitalizations for diabetes-related acute events were identified using ICD-10 codes as main or related diagnosis, for: hypoglycemic events; DKA events; comas; and hyperglycemia-related admissions. <b><i>Results:</i></b> A total of 1272 people with T2DM on insulin-secretagogues without insulin initiated FSL during the selection period. Of these, 7.15% had at least one hospitalization for any ADE in the year before FSL initiation, compared with 2.52% at 12 months and 2.83% at 24 months following FSL initiation. Reductions in ADEs were driven by -73% fewer admissions for ADEs related to diabetic ketoacidosis (DKA) or other hyperglycemia-related events. These patterns of reduced ADEs persisted after 2 years. <b><i>Conclusions:</i></b> This study suggests the value of the FSL system in reducing ADEs in some people with T2DM in France being treated with insulin-secretagogues without insulin. Characteristics of these patients remain to be documented.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":" ","pages":"932-938"},"PeriodicalIF":5.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141418297","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":"Beyond Glucose Monitoring: Multianalyte Sensor Use in Diabetes.","authors":"Kathy Zhou, Steven James, Michele Gaca, Ashani Lecamwasam, Muamer Dervisevic, David O'Neal, Nicolas H Voelcker, Elif I Ekinci","doi":"10.1089/dia.2024.0250","DOIUrl":"10.1089/dia.2024.0250","url":null,"abstract":"<p><p>The incidence, prevalence, mortality, and health expenditure associated with diabetes continue to grow, despite efforts. The use of multianalyte sensors, which detect glucose as well as key analytes such as ketones, lactate, insulin, uric acid, and electrolytes, may provide additional information to guide earlier identification and management of diabetes and its complications. We undertook a narrative review using a systematic approach in May 2023, with a bridge search undertaken in April 2024. Four biomedical databases were searched: MEDLINE (Ovid), Embase, Emcare, and Cochrane Library. Searches for gray literature were conducted on ClinicalTrials.gov, Google Scholar, and websites of relevant organizations. Included studies incorporated articles on multianalyte sensors in diabetes and single-analyte sensors proposing integration into multianalyte diabetes management, with no limits placed on publication date and study design. Data were screened and extracted using Covidence^TM software. Overall, 11 articles were included, of which 7 involved multianalyte sensors (involving glucose and other analytes) and 4 single-analyte sensors (measuring non-glucose substances for proposed future integration into multianalyte systems). Analytes examined were ketones (<i>n</i> = 3), lactate (<i>n</i> = 4), uric acid (<i>n</i> = 3), insulin (<i>n</i> = 1), and potassium (<i>n</i> = 1). Results demonstrated that <i>in vitro</i> and <i>in vivo</i> measurements of multi- and single-analyte sensors accurately and reliably corresponded with human capillary and serum samples. While the literature on this topic is sparse, our review demonstrated that measurement of glucose and other analytes can be feasibly undertaken using multi- and single-analyte sensors. More studies in humans are needed to establish clinical utility in diabetes self-management and assist with technological improvements.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":" ","pages":"885-896"},"PeriodicalIF":5.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141757740","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":"Population-Based Study on the Implementation of Flash Glucose Monitoring and Severe Hypoglycemia in Adults With Type 1 Diabetes.","authors":"Pablo Rodríguez de Vera Gómez, Eduardo Mayoral Sánchez, Ángel Vilches Arenas, Reyes Ravé García, Manuel de la Cal Ramírez, Guillermo Umpierrez, María Asunción Martínez-Brocca","doi":"10.1089/dia.2024.0201","DOIUrl":"10.1089/dia.2024.0201","url":null,"abstract":"<p><p><b><i>Objective:</i></b> We analyzed the effect of implementing a flash glucose monitoring (FGM) technology in a public health care system with universal coverage on the rate of severe hypoglycemia requiring urgent care in adults with type 1 diabetes mellitus (T1DM). <b><i>Methods:</i></b> Using a comprehensive regional dataset, we extracted emergency care codes with hypoglycemia in individuals with T1DM who initiated the use of FGM in Andalucia, Spain, from January 1, 2020, to December 31, 2021. Severe hypoglycemia was defined as a confirmed blood glucose <70 mg/dL, which required the urgent dispatch of an emergency medical service (EMS) for onsite management. We compared hypoglycemic events reported in the 12 months before and after the initiation of FGM to determine the population incidence rates. <b><i>Results:</i></b> A total of 13,616 participants with a mean age of 43.7 ± 13.5 years were included. The follow-up periods were 23.4 and 24.8 months before and after FGM. There were 969 and 737 cases of hypoglycemia before and after the initiation of FGM. The baseline incidence rate was 358.58 episodes per 10,000 person-years, which decreased to 260.9 at the end of the follow-up (rate-ratio 0.72 [0.66; 0.80]). The reduction in hypoglycemia was significant in individuals aged ≥60 years (rate-ratio 0.40 [0.28; 0.55]) and males (0.64 [0.56; 0.72]). In addition, there was a reduction in the overall median HbA1c of -0.35% (95% CI [-0.38; -0.33], <i>P</i> < 0.001). <b><i>Conclusion:</i></b> The implementation of FGM systems in a public health care system as a provision for adults with T1DM was associated with significant reductions in the rate of severe hypoglycemic events that required urgent EMS care.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":" ","pages":"951-959"},"PeriodicalIF":5.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141418296","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":"Glycemic Risk Index in a Cohort of Patients with Type 1 Diabetes Mellitus Stratified by the Coefficient of Variation: A Real-Life Study.","authors":"Sandra Herranz-Antolín, Clara Coton-Batres, María Covadonga López-Virgos, Verónica Esteban-Monge, Visitación Álvarez-de Frutos, Leonel Pekarek, Miguel Torralba","doi":"10.1089/dia.2024.0181","DOIUrl":"10.1089/dia.2024.0181","url":null,"abstract":"<p><p><b><i>Objective</i></b>: To analyze the Glycemic Risk Index (GRI) and assess their possible differences according to coefficient of variation (CV) in a cohort of real-life type 1 diabetes mellitus (DM) patient users of intermittently scanned continuous glucose monitoring (isCGM). <b><i>Patients and Methods</i></b>: In total, 447 adult users of isCGM with an adherence ≥70% were included in a cross-sectional study. GRI was calculated with its hypoglycemia (CHypo) and hyperglycemia (CHyper) components. Multivariate linear regression analysis was performed to evaluate the factors associated with GRI. <b><i>Results:</i></b> Mean age was 44.6 years (standard deviation [SD] 13.7), 57.7% being male; age of DM onset was 24.5 years (SD 14.3) and time of evolution was 20.6 years (SD 12.3). In patients with CV >36% (52.8%) versus CV ≤36% (47.2%), differences were observed in relation to GRI (18.8% [SD 1.9]; <i>P</i> < 0.001), CHypo (2.9% [SD 0.3]; <i>P</i> < 0.001), CHyper (6.3% [SD 1.4]; <i>P</i> < 0.001), and all classical glucometric parameters except time above range level 1. The variables that were independently associated with GRI in patient with CV >36% were time in range (TIR) (β = -1.49; confidence interval [CI:] 95% -1.63 to -1.37; <i>P</i> < 0.001), glucose management indicator (GMI) (β = -7.22; CI: 95% -9.53 to -4.91; <i>P</i> < 0.001), and CV (β = 0.85; CI: 95% 0.69 to 1.02; <i>P</i> < 0.001). However, in patients with CV ≤36%, the variables were age (β = 0.15; CI: 95% 0.03 to 0.28; <i>P</i> = 0.019), age of onset (β = -0.15; CI: 95% -0.28 to -0.02; <i>P</i> = 0.023), TIR (β = -1.35; CI: 95% -1.46 to -1.23; <i>P</i> < 0.001), GMI (β = -6.67; CI: 95% -9.18 to -4.15; <i>P</i> < 0.001), and CV (β = 0.33; CI: 95% 0.11 to 0.56; <i>P</i> = 0.004). <b><i>Conclusions:</i></b> In this study, the factors independently associated with metabolic control according to GRI are modified by glycemic variability.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":" ","pages":"960-967"},"PeriodicalIF":5.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141476164","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":"An Update on the iglu Software Package for Interpreting Continuous Glucose Monitoring Data.","authors":"Elizabeth Chun, Nathaniel J Fernandes, Irina Gaynanova","doi":"10.1089/dia.2024.0154","DOIUrl":"10.1089/dia.2024.0154","url":null,"abstract":"<p><p><b><i>Background:</i></b> Continuous glucose monitors (CGMs) are increasingly used to provide detailed quantification of glycemic control and glucose variability. An open-source R package iglu has been developed to assist with automatic CGM metrics computation and data visualization, providing a comprehensive list of implemented CGM metrics. Motivated by the recent international consensus statement on CGM metrics and recommendations from recent reviews of available CGM software, we present an updated version of iglu with improved accessibility and expanded functionality. <b><i>Methods:</i></b> The functionality was expanded to include automated computation of hypo- and hyperglycemia episodes with corresponding visualizations, composite metrics of glycemic control (glycemia risk index and personal glycemic state), and glycemic metrics associated with postprandial excursions. The algorithm for mean amplitude of glycemic excursions has been updated for improved accuracy, and the corresponding visualization has been added. Automated hierarchical clustering capabilities have been added to facilitate statistical analysis. Accessibility was improved by providing support for the automatic processing of common data formats, expanding the graphical user interface, and providing mirrored functionality in Python. <b><i>Results:</i></b> The updated version of iglu has been released to the Comprehensive R Archive Network (CRAN) as version 4. The corresponding Python wrapper has been released to the Python Package Index (PyPI) as version 1. The new functionality has been demonstrated using CGM data from 19 subjects with prediabetes and type 2 diabetes. <b><i>Conclusions:</i></b> An updated version of iglu provides comprehensive and accessible software for analyses of CGM data that meets the needs of researchers with varying levels of programming experience. It is freely available on CRAN and on GitHub at https://github.com/irinagain/iglu.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":" ","pages":"939-950"},"PeriodicalIF":5.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141418272","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":"A Glycemic Status Classification Model Using a Radiofrequency Noninvasive Blood Glucose Monitor.","authors":"Fazle Karim, James H Anderson, Kaptain Currie, Connor Bui, Dominic Klyve, Virend K Somers","doi":"10.1089/dia.2024.0170","DOIUrl":"10.1089/dia.2024.0170","url":null,"abstract":"<p><p>Despite significant efforts in the development of noninvasive blood glucose (BG) monitoring solutions, delivering an accurate, real-time BG measurement remains challenging. We sought to address this by using a novel radiofrequency (RF) glucose sensor to noninvasively classify glycemic status. The study included 31 participants aged 18-65 with prediabetes or type 2 diabetes and no other significant medical history. During control sessions and oral glucose tolerance test sessions, data were collected from both a RF sensor that rapidly scans thousands of frequencies and concurrently from a venous blood draw measured with an US Food and Drug Administration (FDA)-cleared glucose hospital meter system to create paired observations. We trained a time series forest machine learning model on 80% of the paired observations and reported results from applying the model to the remaining 20%. Our findings show that the model correctly classified glycemic status 93.37% of the time as high, normal, or low.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":" ","pages":"979-983"},"PeriodicalIF":5.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141476163","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":"Starting Insulin Algorithms for Noncritical Illness: A Survey of 32 Academic Hospitals in the United States.","authors":"Hou-Hsien Chiang, Steven E Kahn, Irl B Hirsch","doi":"10.1089/dia.2024.0120","DOIUrl":"10.1089/dia.2024.0120","url":null,"abstract":"<p><p>Glycemic control immediately upon hospitalization is difficult. Endocrine Society guidelines suggest starting scheduled insulin therapy at 0.2-0.5 units/kg/day, but there has been no rigorous study to support this recommendation. To understand the variability of current practice, we surveyed starting insulin algorithms for noncritically ill patients among the top-ranking academic hospitals in the United States. Among the 20 hospitals with reported algorithms, 12 specified which patients should start with basal/nutritional insulin, whereas 5 specified who should start with only correction insulin. Weight-based and/or home-dose-based calculations were used to estimate the initial insulin requirements with various modifiers. In addition, various factors were considered when choosing among the correction dose algorithms. In summary, among the U.S. academic hospitals, there is variability in methods for determining insulin dosing on admission for noncritically ill patients. This inconsistency suggests that future studies to estimate initial insulin requirements are required.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":" ","pages":"968-978"},"PeriodicalIF":5.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141476165","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":"Association of Race and Ethnicity with Prescriptions for Continuous Glucose Monitoring Systems Among a National Sample of Veterans with Diabetes on Insulin Therapy.","authors":"Kasia J Lipska, Carol Oladele, Kelson Zawack, Barbara Gulanski, Pradeep Mutalik, Peter Reaven, Julie A Lynch, Kyung Min Lee, Mei-Chiung Shih, Jennifer S Lee, Mihaela Aslan","doi":"10.1089/dia.2024.0152","DOIUrl":"10.1089/dia.2024.0152","url":null,"abstract":"<p><p><b><i>Introduction and Objective:</i></b> Continuous glucose monitoring (CGM) can improve glycemic control in people with diabetes on insulin therapy. We assessed rates of prescriptions for CGM in a national sample of Veterans across subgroups defined by race and ethnicity. <b><i>Methods:</i></b> This cross-sectional analysis of data from the U.S. Veterans Health Administration included adults with type 1 or type 2 diabetes on insulin therapy. Main exposures included self-reported race and ethnicity, and primary outcome was the percentage of patients with at least one CGM prescription between January 1, 2020, and December 31, 2021. Association of race and ethnicity categories with CGM prescription was examined using multilevel, multivariable mixed-effects models. <b><i>Results:</i></b> Among 368,794 patients on insulin (mean age, 68.5 years; 96% male; 96.8% type 2 diabetes; 0.8% American Indian or Alaska Native, 0.7% Asian, 18.9% Black or African American, 0.9% Native Hawaiian or other Pacific Islander, 70.2% White, 2.8% multiracial, 5.7% with unknown race, and 7.0% Hispanic or Latino ethnicity), 11.2% were prescribed CGM. CGM was prescribed for 10.4% American Indian or Alaska Native, 9.7% Asian, 9.2% Black or African American, 9.3% Native Hawaiian or other Pacific Islander, 11.8% White, 11.8% multiracial, and 10.1% patients with unknown race. CGM was prescribed for 8.3% Hispanic or Latino, 11.4% non-Hispanic, and 11.5% of patients with unknown ethnicity. After accounting for patient-, clinical-, and system-level factors, Black or African American patients had significantly lower odds of CGM prescription compared with White patients (adjusted odds ratio [aOR] 0.62, 95% confidence interval [CI] 0.59-0.64), whereas Hispanic or Latino patients had significantly lower odds compared with non-Hispanic patients (aOR 0.79, 95% CI 0.74-0.84). Findings were consistent across subgroups with clinical indications for CGM use. <b><i>Conclusions:</i></b> Among Veterans with diabetes on insulin therapy, there were significant disparities in prescribing of CGM technology by race and ethnicity, which require further study and intervention.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":" ","pages":"908-917"},"PeriodicalIF":5.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142035520","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":"Long-Term Improvements in Glycemic Control with Dexcom CGM Use in Adults with Noninsulin-Treated Type 2 Diabetes.","authors":"Jennifer E Layne, Lauren H Jepson, Alexander M Carite, Christopher G Parkin, Richard M Bergenstal","doi":"10.1089/dia.2024.0197","DOIUrl":"10.1089/dia.2024.0197","url":null,"abstract":"<p><p><b><i>Aims:</i></b> The objective of this real-world, observational study was to evaluate change in continuing glucose monitoring (CGM) metrics for 1 year after CGM initiation in adults with noninsulin-treated type 2 diabetes (T2D). <b><i>Methods:</i></b> Data were analyzed from Dexcom G6 and G7 users who self-reported: T2D, ≥18 years, gender, no insulin use, and had a baseline percent time in range (TIR) 70-180 mg/dL of ≤70%. Outcomes were change in CGM metrics from baseline to 6 and 12 months overall and for younger (<65 years) and older (≥65 years) cohorts. Additional analyses explored the relationship between use of the high alert feature and change in TIR and time in tight range (TITR) 70-140 mg/dL. <b><i>Results:</i></b> CGM users (<i>n</i> = 3,840) were mean (SD) 52.5 (11.2) years, 47.9% female, mean TIR was 41.7% (21.4%), and 12.4% of participants were ≥65 years. Significant improvement in all CGM metrics not meeting target values at baseline was observed at 6 months, with continued improvement at 12 months. Mean baseline TIR increased by 17.3% (32.1%) from 41.7% (21.4%) to 59.0% (28.9%), and mean glucose management indicator decreased by 0.5% (1.2%) from 8.1% (0.9%) to 7.6% (1.1%) (both <i>P</i> < 0.001). Participants who maintained or customized the high alert default setting of 250 mg/dL had a greater increase in TIR and TITR compared with participants who disabled the alert. Days of CGM use over 12 months were high in 84.7% (15.9%). <b><i>Conclusion:</i></b> In this large, real-world study of adults with suboptimally controlled T2D not using insulin, Dexcom CGM use was associated with meaningful improvements in glycemic control over 12 months. Use of the high alert system feature was positively associated with glycemic outcomes. High use of CGM over 12 months suggests benefits related to consistent CGM use in this population.</p>","PeriodicalId":11159,"journal":{"name":"Diabetes technology & therapeutics","volume":" ","pages":"925-931"},"PeriodicalIF":5.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141431655","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}