Diabetes care最新文献

{"title":"Comment on Pop-Busui et al. Screening Natriuretic Peptide Levels Predicts Heart Failure and Death in Individuals With Type 1 and Type 2 Diabetes Without Known Heart Failure. Diabetes Care 2025;48:2145-2153.","authors":"Jianxin Deng","doi":"10.2337/dc25-2919","DOIUrl":"10.2337/dc25-2919","url":null,"abstract":"","PeriodicalId":93979,"journal":{"name":"Diabetes care","volume":"49 6","pages":"e116"},"PeriodicalIF":16.6,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13195048/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147984774","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":"Increased Early Postprandial Glucagon Concentrations in Humans With Newly Diagnosed Type 2 Diabetes and Steatotic Liver Disease.","authors":"Maximilian Huttasch, Sabine Kahl, Tim Mori, Geronimo Heilmann, Martin Schön, Sandra Trenkamp, Yuliya Kupriyanova, Vera Schrauwen-Hinderling, Nicolai Jacob Wewer Albrechtsen, Philipp Westhoff, Patrick Schrauwen, Robert Wagner, Michael Roden","doi":"10.2337/dc25-3077","DOIUrl":"10.2337/dc25-3077","url":null,"abstract":"<p><strong>Objective: </strong>Glucagon-based polyagonists improve metabolic dysfunction-associated steatotic liver disease (MASLD), which could result from glucagon-stimulated hepatic lipid oxidation. Nevertheless, people with long-standing type 2 diabetes (T2D) exhibit a paradoxical rise in both hepatic lipid content (HLC) and glucagon levels, which has been related to disturbed hepatic metabolism generating glucagonotropic metabolites such as amino acids and nonesterified fatty acids (NEFAs). We examined these relationships in individuals with normal glucose tolerance (NGT) and newly diagnosed T2D.</p><p><strong>Research design and methods: </strong>Fifty individuals with newly diagnosed T2D and 50 age-, sex-, and BMI-matched individuals with NGT underwent liquid mixed-meal tolerance tests to measure glucagon and metabolites, hyperinsulinemic-euglycemic clamps with stable isotope dilution, indirect calorimetry to assess insulin sensitivity and lipid oxidation, and 1H/31P magnetic resonance spectroscopy and MRI to quantify HLC, ATP, and visceral adipose tissue (VAT) volume.</p><p><strong>Results: </strong>Individuals with T2D had an ∼65% higher HLC as well as higher fasting and postprandial glucagonemia (∼30% and ∼75%) than those with NGT. Multivariable linear regression analyses revealed that the presence of MASLD, but not T2D, was associated with higher fasting glucagonemia. Interestingly, postprandial glucagon was related to HLC only in T2D, leading to ∼47% higher early postprandial glucagonemia in individuals with combined MASLD and T2D. These differential associations were independent of insulin sensitivity or VAT volume, and neither were mediated by amino acids or NEFAs.</p><p><strong>Conclusions: </strong>Hyperglucagonemia in the face of higher HLC in early T2D is not due to differences in insulin sensitivity or glucagonotropic metabolites but could suggest hepatic glucagon resistance.</p>","PeriodicalId":93979,"journal":{"name":"Diabetes care","volume":" ","pages":"1048-1056"},"PeriodicalIF":16.6,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13191396/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147610745","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":"Precision Prescribing of SGLT2 Inhibitors in Individuals With Type 2 Diabetes for Primary Prevention of Heart Failure: Model Development and Validation Study.","authors":"Katherine G Young, Andrew P McGovern, Rhian Hopkins, Thijs T Jansz, Pedro M Cardoso, Rury R Holman, Ewan R Pearson, Andrew T Hattersley, Angus G Jones, Kieran Docherty, Naveed Sattar, Beverley M Shields, John M Dennis","doi":"10.2337/dc25-2973","DOIUrl":"10.2337/dc25-2973","url":null,"abstract":"<p><strong>Objective: </strong>Sodium-glucose cotransporter 2 inhibitors (SGLT2i) reduce heart failure (HF) risk in type 2 diabetes (T2D) and are recommended for patients with T2D who have atherosclerotic cardiovascular disease (ASCVD), HF, or chronic kidney disease (CKD). However, most individuals with T2D do not have these conditions, and current guidelines for this group do not indicate which individuals may benefit most from SGLT2i. We aimed to develop and validate a model to predict the individual-level HF benefit of SGLT2i in individuals with T2D without ASCVD, HF, or CKD.</p><p><strong>Research design and methods: </strong>We developed the SGLT2i Absolute Benefit Response (SABRE) model, combining absolute HF risk from the validated QDiabetes-HF model with the SGLT2i-associated hazard ratio (HR) for HF hospitalization from a trial meta-analysis (HR 0.63) to estimate individual 5-year HF benefit. Model components and predictions were validated using U.K. primary care data with linked hospital and death records from 2013 to 2020.</p><p><strong>Results: </strong>Among 57,368 SGLT2i initiators and 111,673 comparator (dipeptidyl peptidase 4 inhibitor or sulfonylurea) initiators, SGLT2i use was associated with a 30% lower risk of new-onset HF (HR 0.70 [95% CI 0.63-0.78]), consistent with trial evidence. Relative HF benefit did not vary by baseline absolute HF risk (P = 0.82). The SABRE model-predicted 5-year absolute HF benefit with SGLT2i ranged from <0.1% to 14.1% (median 1.0% [interquartile range 0.6-1.8%]) and calibrated well against observed HF outcomes. SABRE provided more targeted HF prevention than current guidelines in those with T2D without ASCVD, HF, or CKD.</p><p><strong>Conclusions: </strong>The SABRE model is an easily deployed clinical prediction model integrating trial evidence and allowing more precise targeting of SGLT2i for primary HF prevention in T2D.</p>","PeriodicalId":93979,"journal":{"name":"Diabetes care","volume":"49 6","pages":"1115-1123"},"PeriodicalIF":16.6,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7619156/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147984753","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":"Young Age at Onset of Hypertension: A Potentially Modifiable Risk Factor for Diabetes Complications.","authors":"Sarah H Wild","doi":"10.2337/dci25-0130","DOIUrl":"10.2337/dci25-0130","url":null,"abstract":"","PeriodicalId":93979,"journal":{"name":"Diabetes care","volume":"49 6","pages":"937-939"},"PeriodicalIF":16.6,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147984793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comment on Van Der Meer et al. Impact of Metabolic Bariatric Surgery on Weight Loss and Glycemic Control in Adults With Type 1 Diabetes: A Multicenter Retrospective Cohort Study. Diabetes Care 2026;49:658-663.","authors":"Sean M Brown, Roeland J Middelbeek, Florence M Brown, Mary Elizabeth Patti","doi":"10.2337/dc26-0649","DOIUrl":"10.2337/dc26-0649","url":null,"abstract":"","PeriodicalId":93979,"journal":{"name":"Diabetes care","volume":"49 6","pages":"e119-e120"},"PeriodicalIF":16.6,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13191376/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147984800","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":"Comment on Echouffo-Tcheugui et al. Is the Current Lifestyle Modification Approach to Diabetes Prevention in the U.S. a Success? Diabetes Care 2025;48:863-870.","authors":"Shihchen Kuo, Wen Ye, Laura N McEwen, Claudia Villatoro Santos, William H Herman","doi":"10.2337/dc25-1736","DOIUrl":"10.2337/dc25-1736","url":null,"abstract":"","PeriodicalId":93979,"journal":{"name":"Diabetes care","volume":"49 6","pages":"e113"},"PeriodicalIF":16.6,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13191416/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147984794","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":"Comparing Approaches for Deriving Diabetes Care Cascades to Inform Policy: A Cross-sectional Analysis Using National Data From 88 Countries.","authors":"Felix Teufel, Michaela Theilmann, Maja E Marcus, Mubarak A Sulola, David Guwatudde, Hedley K Quintana, José R Banegas, Aamna Soniwala, Sophia Kim, Krishna Aryal, Silver Bahendeka, Brice Bicaba, Albertino Damasceno, Farshad Farzadfar, Corine Houehanou, Christina Howitt, Khem Karki, Nuno Lunet, João Martins, Mary T Mayige, Kibachio J Mwangi, Sarah Quesnel-Crooks, Reina G Roa Rodríguez, Fernando Rodríguez-Artalejo, Sahar Saeedi Moghaddam, Abla M Sibai, Lela Sturua, Lindiwe Tsabedze, Zhaxybay Zhumadilov, Till Bärnighausen, Pascal Geldsetzer, Rifat Atun, Sebastian Vollmer, Jennifer Manne-Goehler, David Flood, Edward W Gregg, Justine I Davies, Mohammed K Ali, Jithin Sam Varghese","doi":"10.2337/dc26-0267","DOIUrl":"10.2337/dc26-0267","url":null,"abstract":"<p><strong>Objective: </strong>Care cascade indicators are widely used to monitor national diabetes control efforts. However, diabetes definitions used to derive care cascades vary across studies, which may markedly affect results and subsequent policy decisions. Here, we examine the magnitude of resultant differences between approaches.</p><p><strong>Research design and methods: </strong>We analyzed nationally representative, cross-sectional data of 800,348 individuals aged ≥25 years from 88 countries in 2008-2021. We used two different diabetes definitions: elevated biomarkers (glycated hemoglobin [HbA1c] ≥6.5%; fasting plasma glucose ≥7.0 mmol/L; or random plasma glucose ≥11.1 mmol/L) or self-reported diagnosis (\"diagnosis-based definition\") versus elevated biomarkers or self-reported treatment (\"treatment-based definition\"). Care cascade estimates included 1) proportions of individuals with diabetes who were diagnosed, and proportions of individuals with diagnosed diabetes who 2) received treatment and 3) attained glycemic control. We benchmarked results against World Health Organization (WHO) diabetes targets.</p><p><strong>Results: </strong>Diabetes prevalence was 12.9% (95% CI 12.1-13.8) applying the diagnosis-based definition and 11.3% (95% CI 10.5-12.1) with the treatment-based definition. Using the diagnosis-based rather than treatment-based diabetes definition to derive care cascades consistently increased the percentages of those who attain diagnosis and control stages but decreased percentages of those receiving treatment. Across countries, median differences between approaches were 11.3% (interquartile range [IQR] 5.1-24.7) for diabetes diagnosis, 21.6% (IQR 14.5-37.8) for treatment, and 16.4% (IQR 7.8-26.8) for control. The WHO 80% glycemic control target was met by 22% versus 6% of countries when using the diagnosis-based versus treatment-based definition, respectively.</p><p><strong>Conclusions: </strong>Care cascade estimates diverged substantially and consistently across diabetes definitions, skewing policy implications in predictable ways. Harmonizing diabetes performance metrics may improve decision-making and facilitate cross-country comparisons.</p>","PeriodicalId":93979,"journal":{"name":"Diabetes care","volume":"49 6","pages":"1106-1114"},"PeriodicalIF":16.6,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147984758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Food Coloring Additives and Incidence of Type 2 Diabetes in the NutriNet-Santé Prospective Cohort.","authors":"Sanam Shah, Anaïs Hasenböhler, Guillaume Javaux, Marie Payen de la Garanderie, Fabien Szabo de Edelenyi, Paola Yvroud, Cédric Agaësse, Alexandre De Sa, Inge Huybrechts, Fabrice Pierre, Marc Audebert, Xavier Coumoul, Chantal Julia, Emmanuelle Kesse-Guyot, Benjamin Allès, Valérie Deschamps, Serge Hercberg, Benoit Chassaing, Emmanuel Cosson, Sopio Tatulashvili, Mélanie Deschasaux-Tanguy, Bernard Srour, Mathilde Touvier","doi":"10.2337/dc25-2727","DOIUrl":"10.2337/dc25-2727","url":null,"abstract":"<p><strong>Objective: </strong>To investigate potential association between exposure to food coloring additives and type 2 diabetes incidence.</p><p><strong>Research design and methods: </strong>The study followed 108,723 participants (79.2% female, mean age 42.5 [SD 14.6] years) from the French NutriNet-Santé cohort (2009-2023). Dietary data were assessed using repeated 24-h dietary records, including industrial food brands. Cumulative time-dependent exposure to food additives was evaluated through multiple composition databases and ad hoc laboratory assays in food matrices. Associations between exposures to food coloring additives (sex-specific tertiles if proportion of exposed participants was more than two-thirds, or nonexposed/lower/higher exposed based on sex-specific median otherwise) and type 2 diabetes incidence were assessed using multivariable Cox proportional hazards models.</p><p><strong>Results: </strong>There were 1,131 incident type 2 diabetes cases diagnosed (median follow-up, 8.05 years). After false discovery rate correction, intakes of the following colors were associated with higher type 2 diabetes incidence: total food coloring additives (hazard ratio [HR]higher vs. non/lower consumers 1.38 [95% CI 1.17-1.63], P = 0.0002), total caramel (1.43 [1.21-1.67], P = 0.0002), plain caramel (1.46 [1.26-1.70], P = 0.0002), sulfite ammonia caramel (1.30 [1.07-1.59], P = 0.007), total carotene (1.27 [1.08-1.48], P = 0.007), carotenoids (1.39 [1.19-1.62], P = 0.0002), β-carotene (1.44 [1.23-1.68], P = 0.0002), paprika-capsanthin-capsorubin (1.26 [1.08-1.46], P = 0.004), lutein (1.20 [1.02-1.40], P = 0.0002), curcumin (1.49 [1.29-1.73], P = 0.0002), cochineal-carminic acid-carmines (1.27 [1.10-1.48], P = 0.003), and anthocyanins (1.40 [1.17-1.68], P = 0.0002).</p><p><strong>Conclusions: </strong>Several positive associations were observed between exposure to natural and synthetic food coloring additives and type 2 diabetes incidence. Further studies are needed to gain insights into underlying mechanisms, and if confirmed, call for reevaluation of food coloring additives to protect consumer health.</p>","PeriodicalId":93979,"journal":{"name":"Diabetes care","volume":"49 6","pages":"1067-1077"},"PeriodicalIF":16.6,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13191426/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147978082","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":"Comment on Rossing et al. Nuances in Interpretation: Assessing the Interaction Between Semaglutide and MRAs in the FLOW Trial.","authors":"Qian Liu, Jing-Feng Yang, Zhi-Gang Wang","doi":"10.2337/dc25-2808","DOIUrl":"10.2337/dc25-2808","url":null,"abstract":"","PeriodicalId":93979,"journal":{"name":"Diabetes care","volume":" ","pages":"e91"},"PeriodicalIF":16.6,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13191384/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147345677","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":"Challenges in and Opportunities for Individualizing Diabetes Technology: A Position Statement by the European Association for the Study of Diabetes (EASD) and the American Diabetes Association (ADA) Diabetes Technology Working Group.","authors":"Daniela Bruttomesso, John R Petrie, Mark Evans, G Alexander Fleming, Helene Hanaire, Reinhard W Holl, Jennifer L Sherr, Richard M Bergenstal, Lutz Heinemann, Anne L Peters","doi":"10.2337/dci26-0018","DOIUrl":"10.2337/dci26-0018","url":null,"abstract":"<p><p>From finger-stick blood glucose monitoring and mechanical insulin pens in the 1970s to modern automated insulin delivery systems, rapidly progressing advances in diabetes technology are transforming management options for people with diabetes, particularly those with type 1 diabetes but also, increasingly, people with type 2 diabetes. However, access to life-changing diabetes technologies is neither uniform nor universally covered, and there is no one-size-fits-all approach. In this position statement, we emphasize to health care professionals the importance of supporting individuals with diabetes to access and use the right diabetes technology according to personal needs, capabilities, and preferences. In doing so, we highlight the equal importance of avoiding disparities in the provision of diabetes technology by challenging preconceived barriers, which can be overcome with education and determination. We also make a series of suggestions for action to advance the more widespread adoption of diabetes technology while minimizing the \"digital divide.\"</p>","PeriodicalId":93979,"journal":{"name":"Diabetes care","volume":" ","pages":"916-930"},"PeriodicalIF":16.6,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147438628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}