Journal of Diabetes Science and Technology最新文献

{"title":"Continuous Glucose Monitoring and Driving Safety: Clarifying the Inference From a Survey of Insulin-Treated Adults With Type 2 Diabetes.","authors":"Ngoc-Nguyen Thi Nguyen","doi":"10.1177/19322968261483747","DOIUrl":"10.1177/19322968261483747","url":null,"abstract":"","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968261483747"},"PeriodicalIF":4.9,"publicationDate":"2026-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13546383/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148891935","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":"Control-IQ Technology Provides Similar Glycemic Outcomes Across Two Different Continuous Glucose Monitoring Sensors.","authors":"Halis Kaan Akturk, Andy K Johnson, John B Welsh, Laurel H Messer","doi":"10.1177/19322968251330308","DOIUrl":"10.1177/19322968251330308","url":null,"abstract":"<p><p>The t:slim X2 insulin pump with Control-IQ technology (Tandem Diabetes Care) is interoperable with G6 and, more recently, G7 sensors (Dexcom). CGM-derived metrics from customers who transitioned from using Control-IQ technology with G6 and then G7 sensors were compared. Median times in various glucose concentration ranges for the final 30 days of G6 use and the initial 30 days of G7 use changed by <1% and remained within consensus target recommendations for TIR (70-180 mg/dL) >70% and TBR (<70 mg/dL) <4%. Differences in sensor use, time in closed loop, and median glucose levels were clinically insignificant. Control-IQ-based pump users experienced similar outcomes and achieved excellent glycemic control with G6 or G7 sensors.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"1668-1670"},"PeriodicalIF":4.9,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11955995/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143752925","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":"Mind the Gap: A Sequential 4-Step Missing Data Management for Continuous Glucose Monitoring-Derived Endpoints in Diabetes Clinical Trials.","authors":"Yoonhee Kim, Wenda Tu, Roberto Crackel, Yuhao Li, Joanne Lin, Hye Soo Cho, Yun Wang","doi":"10.1177/19322968261459449","DOIUrl":"10.1177/19322968261459449","url":null,"abstract":"","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"1743-1744"},"PeriodicalIF":4.9,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13283602/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148277635","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":"Glycaemic Variability and Preserved Performance in Elite Futsal Players With Type 1 Diabetes.","authors":"Mateja Zadravec, Ana-Marija Liberati Prso, Maja Cigrovski Berkovic","doi":"10.1177/19322968261458821","DOIUrl":"10.1177/19322968261458821","url":null,"abstract":"","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"1745-1746"},"PeriodicalIF":4.9,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13253561/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148211421","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":"AI-Driven Diabetes Care and Its Relevance in the Philippine Context: Opportunities and Persistent Digital Barriers.","authors":"Darin Jan Tindowen","doi":"10.1177/19322968261464150","DOIUrl":"10.1177/19322968261464150","url":null,"abstract":"","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"1747-1748"},"PeriodicalIF":4.9,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13318834/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148352091","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":"Continuous Glucose Monitoring and Early Dysglycemia: Toward an Emerging Stage Preceding Prediabetes.","authors":"Gabriella Rákóczi, Péter Hegyi, Emese Sipter","doi":"10.1177/19322968261456768","DOIUrl":"10.1177/19322968261456768","url":null,"abstract":"","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"1741-1742"},"PeriodicalIF":4.9,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13337547/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148391031","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":"Automated Oral Minimal Models for Rapid Estimation of Insulin Sensitivity and Beta-Cell Responsivity in Large-Scale Data Sets: A Validation Study.","authors":"Simone Perazzolo, Alfonso Galderisi, Alice Carr, Colin Dayan, Claudio Cobelli","doi":"10.1177/19322968251365274","DOIUrl":"10.1177/19322968251365274","url":null,"abstract":"<p><p>The Oral Minimal Model (OMM) analysis offers unique measures of glucose-insulin regulation during glucose challenges. However, its manual test-by-test implementation limits scalability in large studies. We introduce the Automated Oral Minimal Model (AOMM), a tool that streamlines and automates the entire OMM workflow while preserving analytical fidelity, enabling efficient batch processing of large datasets. Built on SAAM II software, AOMM was validated against manually extracted results from <i>Sunehag</i> et al (<i>Obesity (Silver Spring)</i>, 2008), accurately reproducing key parameters such as insulin sensitivity (<i>Si</i>) and beta-cell responsivity (<i>Φ</i>) with high precision and substantial time savings. AOMM, with its user-friendly interface, facilitates broader application of minimal modeling in research and clinical studies.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"1645-1649"},"PeriodicalIF":4.9,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12408534/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144956134","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":"Recycling Insulin Pens: A Call for Action!","authors":"Lutz Heinemann, Chris Unsöld, Sebastian Friedrich Petry","doi":"10.1177/19322968251358229","DOIUrl":"10.1177/19322968251358229","url":null,"abstract":"<p><p>Insulin pens are widely used by people with diabetes for insulin application. Most often ready-to-use pens are used; however, disposal of these pens generates a considerable amount of plastic waste. Until now such pens have almost always been disposed of with household waste. We recommend to establish a nationwide recycling process for insulin pens in Germany over the next few years (PenDE). Collecting and sorting of the finished pens have several facets, which are discussed in this commentary. It is primarily about recycling the actual product, ie, the finished pens, and not their packaging and packaging inserts. Such a project is only possible in close cooperation with the insulin pen manufacturers. The goal is to establish material cycles, ie, multiple use of materials such as recycled plastic.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"1726-1730"},"PeriodicalIF":4.9,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12267213/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144642697","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":"Unlocking Real-Time Data Access in Diabetes Management: Toward an Interoperability Model.","authors":"Pietro Randine, Miriam Kopperstad Wolff, Matthias Pocs, Ian R O Connell, Joseph A Cafazzo, Eirik Årsand","doi":"10.1177/19322968251327602","DOIUrl":"10.1177/19322968251327602","url":null,"abstract":"<p><strong>Background: </strong>In today's data-driven era, openness promotes transparency and accessibility, particularly in health initiatives like the European Health Data Space. Diabetes management relies on real-time data from medical devices, such as continuous glucose monitors (CGMs), insulin pumps, and hybrid closed-loop systems. These devices provide critical insights for treatment adjustments, making real-time data access essential.</p><p><strong>Methods: </strong>This article explores real-time data access for third-party applications, focusing on primary (treatment) and secondary (research) use. We examine how application programming interfaces (APIs) enable secure data retrieval and assess the impact of terms of service and copyright law on patient-driven innovation in open-source communities. Our research evaluates diabetes medical devices and software solutions in Norway, assessing their real-time data access and API functionalities. In addition, we analyze legal frameworks governing these technologies, focusing on challenges faced by open-source solutions. Based on our findings, we propose an interoperability model to improve data accessibility while ensuring security and transparency.</p><p><strong>Results: </strong>Findings reveal seven diabetes devices and nine regulated software solutions, with only one offering a publicly accessible API. This emphasizes a significant gap in real-time data access. Comparisons between vendor-specific and open-source software expose interoperability and accessibility challenges. While Do-It-Yourself (DIY) solutions foster innovation, they face technical and legal barriers.</p><p><strong>Conclusion: </strong>Real-time diabetes management presents security, transparency, and access challenges. Regulatory decisions are needed to implement an interoperability model. The lack of real-time data access highlights the necessity of publicly accessible APIs that prioritize transparency, accessibility, and patient-driven innovation-marking a shift from today's constrained diabetes management landscape.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"1565-1575"},"PeriodicalIF":4.9,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11954377/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143730238","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":"Time at High Risk of Hypoglycemia: Validation of a Consensus-Based Continuous Glucose Monitoring-Metric for Hospitalized Patients.","authors":"Mikkel Thor Olsen, Katrine Bagge Hansen, Ulrik Pedersen-Bjergaard, Peter Lommer Kristensen","doi":"10.1177/19322968251331600","DOIUrl":"10.1177/19322968251331600","url":null,"abstract":"<p><strong>Background: </strong>Time at high risk of hypoglycemia (THRH), 3.9 to 5.6 mmol/L, is a continuous glucose monitoring (CGM)-based metric recommended for reporting in hospitalized patients. This study aims to validate THRH as a predictor of hypoglycemia.</p><p><strong>Methods: </strong>The CGM data from 166 non-intensive care unit (non-ICU) inpatients with type 2 diabetes from the DIATEC trial were analyzed. All participants received basal-bolus insulin therapy. Of these, 82 were monitored with point-of-care glucose testing and blinded CGM, while 84 had open CGM. Linear and negative binomial regression analyses assessed the relationship between THRH and time below range (TBR) (<3.0 mmol/L, 3.0-3.9 mmol/L, and <3.9 mmol/L) and hypoglycemic events. Analyses were conducted for day (07:00-23:00), night (23:01-06:59), and 24-hour periods.</p><p><strong>Results: </strong>For CGM-monitored patients, every 10%-point increase in THRH was associated with a 0.13%-point increase in TBR (<3.0 mmol/L) (95% confidence interval [CI] = 0.06-0.21), 0.66%-point increase in TBR (3.0-3.9 mmol/L) (95% CI = 0.47-0.86), and 0.74%-point increase in TBR (<3.9 mmol/L) (95% CI = 0.51-0.97), all <i>P</i> < .001. A THRH threshold below 50% was linked to a TBR <3.9 mmol/L of less than 4%, as recommended. Similar results were observed during both day and night analyses and for point-of-care monitored patients, also for hypoglycemic events.</p><p><strong>Conclusions: </strong>The THRH is strongly associated with hypoglycemia in non-ICU hospitalized patients with type 2 diabetes on basal-bolus insulin. Aiming for THRH below 50% aligns with the recommended TBR target of <3.9 mmol/L below 4%, supporting THRH's role in guiding hypoglycemia prevention strategies.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"1630-1635"},"PeriodicalIF":4.9,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11993535/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144020887","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}