Journal of Diabetes Science and Technology最新文献

{"title":"Temporal Glycemic Patterns in Type 1 and Type 2 Diabetes: Insights From Extended Continuous Glucose Monitoring.","authors":"Tomoki Okuno, Lucas Sort, Bowen Zhang, Kerry Zhou, Matthew Kitchen, Victor Li, Donald R Miller, Gregory J Norman, Peter Reaven, Jin J Zhou","doi":"10.1177/19322968251341264","DOIUrl":"10.1177/19322968251341264","url":null,"abstract":"<p><strong>Background: </strong>Achieving optimal glycemic control for persons with diabetes remains difficult. Real-world continuous glucose monitoring (CGM) data can illuminate previously underrecognized glycemic fluctuations. We aimed to characterize glucose trajectories in individuals with Type 1 and Type 2 diabetes, and to examine how baseline glycemic control, CGM usage frequency, and regional differences shape these patterns.</p><p><strong>Methods: </strong>We linked Dexcom CGM data (2015-2020) with Veterans Health Administration electronic health records, identifying 892 Type 1 and 1716 Type 2 diabetes patients. Analyses focused on the first three years of CGM use, encompassing over 2.1 million glucose readings. We explored temporal trends in average daily glucose and time-in-range values.</p><p><strong>Results: </strong>Both Type 1 and Type 2 cohorts exhibited a gradual rise in mean daily glucose over time, although higher CGM usage frequency was associated with lower overall glucose or attenuated increases. Notable weekly patterns emerged: Sundays consistently showed the highest glucose values, whereas Wednesdays tended to have the lowest. Seasonally, glycemic control deteriorated from October to February and rebounded from April to August, with more pronounced fluctuations in the Northeast compared to the Southwest U.S.</p><p><strong>Conclusions: </strong>Our findings underscore the importance of recognizing day-of-week and seasonal glycemic variations in diabetes management. Tailoring interventions to account for these real-world fluctuations may enhance patient engagement, optimize glycemic control, and ultimately improve health outcomes.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968251341264"},"PeriodicalIF":4.1,"publicationDate":"2025-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12104196/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144142749","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":"User Perceptions of Behavioral Change Strategies in Diabetes Apps: Feedback From Online Support Groups.","authors":"Eirik Årsand, Elia Gabarron, Pietro Randine","doi":"10.1177/19322968251343918","DOIUrl":"10.1177/19322968251343918","url":null,"abstract":"<p><strong>Background: </strong>Behavioral change strategies are used in mobile health applications to help individuals manage chronic conditions like diabetes. However, there is limited research on user preferences and perceptions regarding these strategies in the context of diabetes management apps. This study aimed to investigate the preferences of individuals with diabetes and their relatives concerning behavioral intervention functions used in mobile health apps to enhance the design and effectiveness of future applications.</p><p><strong>Methods: </strong>An online survey was conducted to gather sociodemographic information, details about diabetes diagnoses, and the target group's preferences for the use of nine main behavioral change strategies, possible to include in mobile health apps. Participants were asked to rate their agreement with specific statements related to each of the nine strategies on a three-point scale: \"Agree,\" \"Don't know,\" or \"Disagree.\" Recruitment efforts targeted 12 diabetes support groups on Facebook.</p><p><strong>Results: </strong>A total of 107 responses were received, all from Norwegian Facebook groups. The most valued behavior intervention function for diabetes apps was enablement, where 85% of the respondents wanted app functions based on this. Second, environmental restructuring received 70.1% votes, followed by incentivization and training, with 68.2% and 67.3%, respectively.</p><p><strong>Conclusions: </strong>We identified that the users in this survey preferred more, and other behavior change strategies that were identified were used in a recent review. We conclude that more awareness is needed among app developers of preferences among end users.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968251343918"},"PeriodicalIF":4.1,"publicationDate":"2025-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12104217/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144142750","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":"Accuracy and Safety of a Novel Intravenous Continuous Glucose Monitoring System in Patients Admitted to a Cardiothoracic ICU: A Pilot Trial.","authors":"Daniel Hochfellner, Tina Poettler, Michael Schoerghuber, Edita Lukic, Ameli Yates, Ingeborg Keeling, Daniel Zimpfer, Felix Aberer, Francesca Berti, Fausto Lucarelli, Francesco Valgimigli, Julia K Mader","doi":"10.1177/19322968251342598","DOIUrl":"10.1177/19322968251342598","url":null,"abstract":"<p><strong>Background: </strong>In critically ill patients, deviations in glucose levels may lead to significant harm to individuals with and without diabetes. Although subcutaneous continuous glucose monitoring (scCGM) has proven beneficial for patients in standard wards, its implementation in critical care settings has been limited due to multiple factors, potentially resulting in inadequate glycemic control and consequent complications; here, intravascular systems (ivCGM) have the potential to overcome these limitations.</p><p><strong>Method: </strong>This single-center, open-label study, aimed to assess accuracy and safety of a novel intravenous glucose monitoring system in patients with and without diabetes, admitted to a cardiothoracic surgery intensive care unit. Glucose levels were continuously monitored for up to 72 hours in the predefined glucose range of 20 to 400 mg/dL and compared with arterial glucose measurements (blood gas analyses [BGAs]).</p><p><strong>Results: </strong>Twenty-eight participants successfully completed the study, allowing the collection of 1224 ivCGM/BGA data pairs. Due to the exploratory nature of the trial in this vulnerable patient population, no data pairs <70 mg/dL and limited data pairs in level 2 hyperglycemia (>250 mg/dL) were observed. A mean absolute relative difference (MARD) of 8.7 ± 7.8% was found, whereas the mean absolute difference (MAD) for values <100 mg/dL was 3.3 ± 2.7 mg/dL. In participants with diabetes (N = 8,332 ivCGM/BGA data pairs), MARD was 9.6 ± 8.1%. Diabetes Technology Society Error Grid (DTSEG) analysis revealed that all data pairs fell within clinically acceptable zones A and B. Notably, no serious adverse events associated with the device were observed during the study.</p><p><strong>Conclusion: </strong>The present findings indicate that the investigated intravenous glucose monitoring system provides accurate glucose monitoring and demonstrates its safety in critical care settings. This technology offers promise for improved glycemic management in critically ill patients, particularly those with diabetes, potentially mitigating the associated risks and complications.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968251342598"},"PeriodicalIF":4.1,"publicationDate":"2025-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12104219/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144142747","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":"Comparator Value Pairing Impacts Reported Continuous Glucose Monitoring System Accuracy.","authors":"Stefan Pleus, Guido Freckmann, Robbert J Slingerland, Peter Diem, Elisabet Eriksson Boija, Marion Fokkert, Rolf Hinzmann, Johan Jendle, David C Klonoff, Jingyi Lu, Konstantinos Makris, Viswanathan Mohan, James H Nichols, John Pemberton, Elizabeth Selvin, Andreas Thomas, Nam K Tran, Lilian Witthauer, Manuel Eichenlaub","doi":"10.1177/19322968251344303","DOIUrl":"10.1177/19322968251344303","url":null,"abstract":"","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968251344303"},"PeriodicalIF":4.1,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12102080/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144127743","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":"Minimum requirements for continuous glucose monitors: What does it mean?","authors":"Jan S Krouwer","doi":"10.1177/19322968251343645","DOIUrl":"10.1177/19322968251343645","url":null,"abstract":"","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968251343645"},"PeriodicalIF":4.1,"publicationDate":"2025-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12085550/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144086293","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":"Supported Open-Source Automated Insulin Delivery for Management of Type 1 Diabetes in Pregnancy.","authors":"Kate Hawke, Maryam Kabootari, Tom Elliott","doi":"10.1177/19322968251336779","DOIUrl":"10.1177/19322968251336779","url":null,"abstract":"<p><strong>Background: </strong>The tight glycemia required to optimize type 1 diabetes (T1D) pregnancy outcomes is difficult to achieve with standard insulin therapies. Automated insulin delivery (AID) offers an avenue to improve glycemia, but most available systems are not configurable to tight pregnancy glucose targets. Open-source AID may meet the needs of some pregnant women with T1D, but available data on its efficacy and safety in pregnancy are limited.</p><p><strong>Methods: </strong>This single-center retrospective study describes the glycemic and obstetric outcomes of pregnancies in which supported open-source AID (SOSAID) was used. Included patients had a pregnancy managed on SOSAID at BCDiabetes between January 2023 and October 2024 and consented for inclusion of their clinical data. Charts were reviewed to obtain comprehensive glycemic data, obstetric outcomes, and adverse events.</p><p><strong>Results: </strong>Ten patients, mean age 33 years, had a mean pre-pregnancy A1c of 6.7% (range 5.8%-8.0%). There were no episodes of DKA or severe hypoglycemia. Mean time-in-range (TIR_{63-140 mg/dL}) was 68% in trimester 2 and 70% in trimester 3. Seven patients commenced SOSAID during pregnancy, with their median 14-day TIR rising from 52% pre-SOSAID to 71% immediately after commencing SOSAID. There were no perinatal deaths or congenital anomalies. Pre-term delivery occurred in 1/10 and hypertensive disorders of pregnancy occurred in 2/10 women. Birthweight above 4 kg was present in 3/10, and neonatal hypoglycemia occurred in 4/10.</p><p><strong>Conclusions: </strong>SOSAID systems represent a promising tool for managing T1D in pregnancy and were successful in reaching target pregnancy glycemia in this single-center cohort.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968251336779"},"PeriodicalIF":4.1,"publicationDate":"2025-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12085552/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144086295","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":"Assessing the Financial Sustainability of a Virtual Clinic Providing Comprehensive Diabetes Care.","authors":"Paul Dupenloup, Grace Guan, Grazia Aleppo, Richard M Bergenstal, Korey Hood, Davida Kruger, Teresa McArthur, Beth Olson, Sean Oser, Tamara Oser, Ruth S Weinstock, Robin L Gal, Craig Kollman, David Scheinker","doi":"10.1177/19322968251340664","DOIUrl":"10.1177/19322968251340664","url":null,"abstract":"<p><strong>Introduction: </strong>The Virtual Diabetes Specialty Clinic (VDiSC) study demonstrated the feasibility of providing comprehensive diabetes care entirely virtually by combining virtual visits with continuous glucose monitoring support and remote patient monitoring (RPM). However, the financial sustainability of this model remains uncertain.</p><p><strong>Methods: </strong>We developed a financial model to estimate the variable costs and revenues of virtual diabetes care, using visit data from the 234 VDiSC participants with type 1 or type 2 diabetes. Data included virtual visits with certified diabetes care and education specialists (CDCES), endocrinologists, and behavioral health services (BHS). The model estimated care utilization, variable costs, reimbursement revenue, gross profit, and gross profit margin per member, per month (PMPM) for privately insured, publicly insured, and overall clinic populations (75% privately insured). We performed two-way sensitivity analyses on key parameters.</p><p><strong>Results: </strong>Gross profit and gross profit margin PMPM (95% confidence interval) were estimated at $-4 ($-14.00 to $5.68) and -4% (-3% to -6%) for publicly insured patients; $267.26 ($256.59-$277.93) and 73% (58%-88%) for privately insured patients; and $199.41 ($58.43-$340.39) and 67% (32%-102%) for the overall clinic. Profits were primarily driven by CDCES visits and RPM. Results were sensitive to insurance mix, cost-to-charge ratio, and commercial-to-Medicare price ratio.</p><p><strong>Conclusions: </strong>Virtual diabetes care can be financially viable, although profitability relies on privately insured patients. The analysis excluded fixed costs of clinic infrastructure, and securing reimbursement may be challenging in practice. The financial model is adaptable to various care settings and can serve as a planning tool for virtual diabetes clinics.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968251340664"},"PeriodicalIF":4.1,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12075182/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143998917","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":"Practical Approach to Continuous Glucose Monitoring (CGM) Interpretation and Automated Insulin Delivery (AID) Use in Pregnancy: Considerations for Obstetric Providers.","authors":"Emily D Szmuilowicz, Celeste Durnwald, Denice S Feig","doi":"10.1177/19322968251330651","DOIUrl":"10.1177/19322968251330651","url":null,"abstract":"<p><p>While automated insulin delivery (AID) systems have multiple well-established benefits outside of pregnancy and are widely used in non-pregnant individuals with type 1 diabetes (T1D), none of the commercially available AID systems in North America are approved for use during pregnancy. Use of commercially available AID systems off-label in pregnancy is currently limited by: (1) glucose targets higher than the fasting glucose target range recommended during pregnancy and (2) algorithms which were not designed for the dynamic changes in insulin resistance which occur across gestation. However, as AID use in the general population expands, many individuals will opt to continue using these systems off-label during pregnancy, and thus, guidance for providers regarding AID use and optimization during pregnancy is of the utmost importance. A cornerstone to the effective use of AID systems is the systematic and accurate interpretation of continuous glucose monitoring (CGM) data. One obstacle to the use of both CGM and AID systems by obstetric providers is the lack of comfort with CGM interpretation. We therefore present here: (1) a systematic approach to CGM interpretation during pregnancy and (2) practical guidance regarding AID use during pregnancy for individuals who opt to use commercially available AID systems off-label during pregnancy after consideration of individualized risks and benefits.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968251330651"},"PeriodicalIF":4.1,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12075183/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143995953","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":"Provider Perspective on Automated Insulin Devices in Pregnancy and Considerations for Implementation in Clinical Practice.","authors":"Jane Hand, Carol J Levy","doi":"10.1177/19322968251334397","DOIUrl":"https://doi.org/10.1177/19322968251334397","url":null,"abstract":"<p><p>Pregnancy in people with type 1 diabetes mellitus (T1D) is well-known to be linked to adverse maternal and neonatal outcomes. Although advancements in diabetes technology, especially hybrid closed-loop (HCL) and advanced hybrid closed-loop (AHCL) systems, have greatly enhanced management for nonpregnant individuals with T1D, pregnant patients still represent a high-risk group that requires further research. Existing trials have shown mixed data in terms of clinically meaningful benefits in glycemic control, but these may be specific to the closed-loop system. Currently, there is one AHCL system approved and available for use in pregnancies complicated by diabetes in the United Kingdom, Europe, and Australia. However, there are no Food and Drug Administration (FDA)-approved closed-loop systems for use during pregnancy in the United States. Existing HCL/AHCL system use is off-label for pregnancy in the United States and often requires assistive techniques to target the tighter glucose levels needed during pregnancy. For patients struggling on multiple daily injections (MDIs) or sensor-augmented pump therapy (SAPT), studies have shown that HCL/AHCLs can reduce the burden of care and enable some people to achieve tighter glucose levels. This review aims to provide an overview of the existing evidence of closed-loop systems in pregnancies complicated by T1D and to discuss their implications and considerations with system use.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968251334397"},"PeriodicalIF":4.1,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12061893/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144020740","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":"Using Journey Mapping and Service Blueprinting to Design Digital Health Behavior Change Innovations: A Scoping Review.","authors":"Paula Voorheis, Julia Victoria Wong, Natasa Lazarevic, Bisma Imtiaz, Aunima Bhuiya, Carolyn Steele Gray","doi":"10.1177/19322968251334396","DOIUrl":"https://doi.org/10.1177/19322968251334396","url":null,"abstract":"<p><strong>Introduction: </strong>Solutions to support disease self-management and health-related behavior changes require a deep understanding of patient experiences, needs, and challenges across the care journey. Journey mapping (JM) and service blueprinting (SB) are valuable tools for visualizing user experiences and system processes over time. This scoping review explores how JM/SBs have been applied to design digitally enabled interventions targeting health-related behaviors among patients and the public.</p><p><strong>Methods: </strong>The JBI reviewer manual was used to guide the review. Studies were sourced from Embase, Psych Info, PubMed, Medline, Web of Science, and Scopus. Inclusion criteria required studies to describe how JM/SBs informed the design of a digitally enabled health innovation that aimed to impact health or health care-related behaviors of patients or the public. A two-level screening process and iterative data extraction were applied.</p><p><strong>Results: </strong>A total of 28 studies met the inclusion criteria, with a majority published between 2019 and 2024. The JM/SBs rarely used behavioral science theory and were structured, organized, and presented in diverse ways. Most studies designed their digital health behavior change innovations by using JM/SB to identify relevant innovation touchpoints across the patient journey. Patients frequently participated in the digital health behavior change innovation design process, with JM/SBs often serving as sensemaking tools. Innovations tended to address multifaceted health service problems through multimodal, digitally enabled solutions.</p><p><strong>Conclusions: </strong>JM/SBs are emerging as versatile tools to help digital health innovations to conduct user research, engage diverse partners, identify complex problems, and ideate creative solutions. However, limited integration of behavioral science theory indicates an area for future exploration.</p>","PeriodicalId":15475,"journal":{"name":"Journal of Diabetes Science and Technology","volume":" ","pages":"19322968251334396"},"PeriodicalIF":4.1,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12061902/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144026486","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}