Diabetes Care最新文献

{"title":"Novel Phenotypic Clusters of Youth-Onset Type 2 Diabetes Offer No Added Prognostic Value to Simple Clinical Measures","authors":"Raymond J. Kreienkamp, Kirk Smith, Thinley Yidzin Wangden, Aaron J. Deutsch, Steven D. Gage, Anna Bellatorre, Dana M. Dabelea, Ralph B. D’Agostino, Lawrence M. Dolan, Jose C. Florez, Elizabeth T. Jensen, Catherine Pihoker, Toni I. Pollin, Amy S. Shah, Lukasz Szczerbinski, Miriam S. Udler, Shylaja Srinivasan","doi":"10.2337/dc25-1765","DOIUrl":"https://doi.org/10.2337/dc25-1765","url":null,"abstract":"OBJECTIVE Clinical heterogeneity in youth-onset type 2 diabetes is less understood than that of adult-onset type 2 diabetes. We performed phenotypic clustering of youth-onset type 2 diabetes to determine whether clusters provided clinical utility. RESEARCH DESIGN AND METHODS We performed data-driven clustering in a diverse subset of autoantibody-negative, clinician-diagnosed type 2 diabetes before age 20 years in the Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) (n = 525) and the SEARCH for Diabetes in Youth (SEARCH) (n = 333) studies. Participants were clustered using 1) similar variables as previously described in adults and 2) novel routinely available clinical variables. We assessed the effectiveness of the clusters, as well as that of simple clinical measures, to predict treatment response in the TODAY clinical trial. RESULTS There were three youth-onset type 2 diabetes clusters: 1) youth-onset insulin-deficient diabetes (YIDD-T2), 2) youth-onset insulin-resistant diabetes, and 3) intermediate youth-onset diabetes. These clusters had differential responses to therapies and risk of treatment failure in the TODAY study, with those in the YIDD-T2 cluster experiencing the highest rate of treatment failure, regardless of treatment arm. YIDD-T2 also had high rates of type 2 diabetes complications. We then generated three novel clusters, with different rates of treatment failure, using variables available in routine clinical practice. Compared with both clustering methods, simple clinical measures performed comparably or better at predicting treatment response and complications. CONCLUSIONS Youth-onset type 2 diabetes can be characterized into reproducible clusters that demonstrate differential response to treatments and risk of complications. Nevertheless, cluster membership did not add clinical utility beyond simple clinical measures for predicting outcomes.","PeriodicalId":11140,"journal":{"name":"Diabetes Care","volume":"18 1","pages":""},"PeriodicalIF":16.2,"publicationDate":"2025-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145515564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sodium-Glucose Cotransporter-2 Inhibitors, Glucagon-Like Peptide-1 Receptor Agonists, and Frailty Progression in Older Adults With Type 2 Diabetes","authors":"Chan Mi Park, Saran Thanapluetiwong, Xiecheng Chen, Gahee Oh, Darae Ko, Dae Hyun Kim","doi":"10.2337/dc25-1031","DOIUrl":"https://doi.org/10.2337/dc25-1031","url":null,"abstract":"OBJECTIVE Older adults with type 2 diabetes are at high risk for frailty. The effects of glucagon-like peptide-1 receptor agonists (GLP-1RAs) and sodium-glucose cotransporter-2 inhibitors (SGLT-2is) on frailty remain uncertain. RESEARCH DESIGN AND METHODS Using a 7% random sample of Medicare data, we compared new users of dipeptidyl peptidase-4 inhibitors (DPP-4is), GLP-1RAs, SGLT-2is, and sulfonylureas on 1-year frailty progression, measured by a claims-based frailty index (CFI) (range: 0–1; higher scores indicate greater frailty). Mediation analyses assessed whether cardiovascular or safety events explained differences in frailty progression. RESULTS Compared with DPP-4i users, the mean CFI change (95% CI) was significantly lower for GLP-1RA (−0.007 [−0.011, −0.004]) and SGLT-2i (−0.005 [−0.008, −0.002]) users; no difference was found for sulfonylurea users. These associations were minimally mediated by cardiovascular or safety events. CONCLUSIONS GLP-1RAs and SGLT-2is may slow frailty progression through mechanisms independent of cardiovascular benefits. Future trials should confirm these preliminary findings.","PeriodicalId":11140,"journal":{"name":"Diabetes Care","volume":"115 1","pages":""},"PeriodicalIF":16.2,"publicationDate":"2025-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145509213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GLP-1s Versus DPP-4s and Risk of Dementia in Patients Requiring Hemodialysis: A Target Trial Emulation Study","authors":"Dustin Le, Mark Kilpatrick, Walter K. Kraft, Morgan E. Grams, Bernard G. Jaar, Jung-Im Shin","doi":"10.2337/dc25-1836","DOIUrl":"https://doi.org/10.2337/dc25-1836","url":null,"abstract":"OBJECTIVE Glucagon-like peptide 1 agonists (GLP-1s) compared with dipeptidyl peptidase 4 inhibitors (DPP-4s) are associated with reduced risk of dementia in the general population with diabetes, but whether this association is true for patients requiring hemodialysis is unknown. RESEARCH DESIGN AND METHODS Using the U.S. Renal Data System and Medicare Parts A, B, and D claims data from 2011 to 2021, we used the active comparator, new-user design to evaluate incident dementia comparing GLP-1s versus DPP-4s among individuals with both diabetes and hemodialysis dependence. We used inverse probability of treatment weights (IPTW) to balance baseline characteristics and Fine-Gray models to estimate subdistribution hazard ratios (sHRs) accounting for competing risks of death and kidney transplantation. We estimated intention-to-treat and as-treated effects. RESULTS We identified 3,619 GLP-1 users and 11,502 DPP-4 users. After IPTW, the average individual was 63 years old, 63% were White, and mean BMI was 31 kg/m2. The median (interquartile interval) follow-up was 1.5 (0.6–2.9) years, and 2,014 patients received a dementia diagnosis. In the intention-to-treat analysis, the IPTW-sHR for dementia was 0.82 (95% CI 0.67–0.98), and after 2 years of follow-up, the cumulative incidence of dementia was 10.2% on GLP-1s vs 11.2% on DPP-4s. As-treated and subgroup analyses were consistent. GLP-1s were also associated with an increased risk of ketoacidosis (sHR 1.52, 95% CI 1.14–2.02; 2-year cumulative incidence: 3.1% vs. 2.2%). CONCLUSIONS In patients with diabetes requiring hemodialysis, GLP-1s (vs. DPP-4s) may be a promising therapy to reduce the risk of dementia.","PeriodicalId":11140,"journal":{"name":"Diabetes Care","volume":"25 1","pages":""},"PeriodicalIF":16.2,"publicationDate":"2025-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145509212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Use of Teplizumab to Modulate Stage 2 Type 1 Diabetes in Two Individuals With Autoimmune Polyendocrine Syndrome 1","authors":"Christopher S. Wilson, Alexander Falk, Jonathan M. Williams, Melissa Hilmes, Jordan Ross, Lauren LeStourgeon, Michael J. Haller, Martina Drawdy, Joseph Pechacek, Taura Webb, Alicia Diaz-Thomas, William E. Russell, Justin M. Gregory, Jack Virostko, Michail S. Lionakis, Daniel J. Moore","doi":"10.2337/dc25-1444","DOIUrl":"https://doi.org/10.2337/dc25-1444","url":null,"abstract":"OBJECTIVE Autoimmune polyendocrine syndrome type 1 (APS-1) is a rare, monogenic autoimmune disorder that may manifest as type 1 diabetes (T1D). Teplizumab, an anti-CD3 monoclonal antibody, delays progression of stage 2 T1D, but its effects in APS-1–associated diabetes are unknown. RESEARCH DESIGN AND METHODS We report clinical responses of two adolescents with APS-1 and stage 2 T1D who received 14-day courses of teplizumab. In one patient, pancreatic MRI and spectral immune cell phenotyping were performed before and after treatment. RESULTS Both patients exhibited improved glycemia. One who briefly required insulin recovered insulin independence 2 weeks after therapy. Pancreatic volume transiently increased, and circulating lymphocytes showed changes in homing receptors and senescence markers in the individual who underwent those studies. Nonpancreatic APS-1 manifestations were unchanged. CONCLUSIONS Teplizumab may preserve β-cell function in APS-1–associated T1D. Larger studies are needed to define efficacy, durability, and immunologic and tissue mechanisms in this rare context.","PeriodicalId":11140,"journal":{"name":"Diabetes Care","volume":"175 1","pages":""},"PeriodicalIF":16.2,"publicationDate":"2025-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145498757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Changes in Type 2 Diabetes Medications Among Primary Care Patients After California’s 2022 Medicaid Expansion","authors":"Annie E. Ro, Celina Morales, Luohua Jiang, Jung Min Choi, Nicole Tavares Kuhn, Cecilia Wu","doi":"10.2337/dc25-0787","DOIUrl":"https://doi.org/10.2337/dc25-0787","url":null,"abstract":"OBJECTIVE In May 2022, California expanded full-scope Medicaid (Medi-Cal) to low-income undocumented immigrants aged 50 years or older, which provided access to newer type 2 diabetes (T2D) medications. This study examined whether the expansion led to more prescriptions of newer therapies like glucagon-like peptide-1 receptor agonists and sodium-glucose cotransporter-2 inhibitors among older undocumented immigrants. RESEARCH DESIGN AND METHODS We used patient records between January 2019 to June 2023 from two Federally Qualified Health Centers (FQHCs) in Los Angeles County. We compared prescriptions among 1) older undocumented immigrants newly eligible for Medi-Cal; 2) younger undocumented immigrants not eligible for Medi-Cal; and 3) documented patients (n = 20,420 encounters and 4,601 patients). We used generalized linear mixed models with patient-level random intercepts to examine whether the patient groups differed in their likelihood of being prescribed newer medications and if there were changes over time. RESULTS The odds of being prescribed newer classes of drugs was significantly lower for both the older and younger undocumented patients than documented patients at baseline. Prescriptions for newer T2D medications increased over time for all patients, but the monthly rate of increase in the odds was 6% higher for the older undocumented group compared with the documented patient group. CONCLUSIONS Medi-Cal expansion was effective in changing prescription patterns for older undocumented immigrants with T2D. Although the older undocumented immigrants were prescribed newer drugs at a much lower level than were documented immigrants, they ended at a similar level as the documented patients by the end of the study period.","PeriodicalId":11140,"journal":{"name":"Diabetes Care","volume":"109 1","pages":""},"PeriodicalIF":16.2,"publicationDate":"2025-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145448176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancing Continuous Glucose Monitoring for Inpatient Clinical Decision Support: Individual Algorithmic Mean Absolute Relative Difference","authors":"Jill von Conta, Fin H. Bahnsen, Lutz Heinemann, Lukas van Baal, Jens Kleesiek, Dagmar Führer-Sakel, Susanne Tan","doi":"10.2337/dc25-1494","DOIUrl":"https://doi.org/10.2337/dc25-1494","url":null,"abstract":"OBJECTIVE Continuous glucose monitoring (CGM) is widely used to monitor glucose levels in patients with diabetes and guide insulin dosing in outpatients. In inpatient care, special regulatory requirements necessitate CGM accuracy as a prerequisite for its integration into clinical decision support. RESEARCH DESIGN AND METHODS To meet the specific demands of in-hospital care, CGM accuracy was retrospectively evaluated in 226 patients using paired CGM and point-of-care glucose measurements, assessed via mean absolute relative difference (MARD), Clarke Error Grid (CEG) analysis, and a modified version of the U.S. Food and Drug Administration agreement rule. A dynamic, patient-specific algorithm incorporating time lag correction and linear modeling was developed to minimize MARD and applied in a second cohort of 24 patients within the clinical workflow. RESULTS Data analysis showed an initial MARD of 10.30%, with 99.02% of data points located in zones A and B of the CEG. The application of the patient-specific optimization algorithm improved the MARD by 4.33%. Evaluation of the patient-specific algorithm on the second inpatient cohort demonstrated a 5.58% reduction in intrapersonal MARD, indicating its potential applicability within clinical workflows. CONCLUSIONS Patient-specific algorithmic refinements of CGM data demonstrate the potential to adequately address the unique demands of inpatient diabetes care by reducing intrapersonal MARD, paving the way for the adoption of CGM systems into hospital environments.","PeriodicalId":11140,"journal":{"name":"Diabetes Care","volume":"1 1","pages":""},"PeriodicalIF":16.2,"publicationDate":"2025-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145435094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Natural Language Processing for Automated Extraction of Continuous Glucose Monitoring Data","authors":"Yaguang Zheng, Yulin Song, Eduardo Iturrate, Bei Wu, Susan Zweig, Stephen B. Johnson","doi":"10.2337/dc25-1595","DOIUrl":"https://doi.org/10.2337/dc25-1595","url":null,"abstract":"OBJECTIVE Continuous glucose monitoring (CGM) is essential in diabetes care and research; however, extracting key data (e.g., time above, in, or below range) from CGM reports is manual, time-consuming, and inefficient. Natural language processing (NLP) can extract data from unstructured sources (e.g., images), but its application in CGM remains unexplored. We aimed to evaluate the accuracy of extracting CGM data using NLP. RESEARCH DESIGN AND METHODS We analyzed CGM reports stored as PDF files from the electronic health record at New York University Langone Health. The steps of our algorithm pipeline consist of 1) performing optical character recognition (OCR) to obtain glucose matrix data from CGM reports, 2) determining the type of CGM documents based on keywords in OCR results, 3) extracting variables of glucose based on CGM document type, and 4) storing the extracted glucose data in a structured database. Two experts with experience in CGM research and clinical practice conducted an independent manual review of 1% of the documents (n = 226). We calculated accuracy (correct extraction of CGM data) by comparing the algorithm’s results with the manual review. RESULTS Of the documents analyzed, 36.8% were Freestyle Libre and 63.2% were Dexcom. For information extraction, the agreement in evaluating Libre results between two experts was 99.93%. When comparing algorithm accuracy with manual review, the accuracy for Libre was 99.87% and, for Dexcom, 100.00%. CONCLUSIONS Using an NLP approach to extract valuable glucose data from CGM PDF files is feasible and accurate, which can benefit clinical practice and diabetes research. ARTICLE HIGHLIGHTS • Why did we undertake this study? Extracting key metrics from continuous glucose monitoring (CGM) reports is currently a manual and inefficient process. We sought a scalable, automated method to improve clinical and research workflows. • What is the specific question we wanted to answer? Can a natural language processing (NLP) algorithm, such as optical character recognition, accurately extract structured glucose data from CGM reports stored as unstructured documents in electronic health records? • What did we find? Our NLP pipeline processed CGM reports stored as PDF files with high accuracy: 99.87% for Freestyle Libre and 100% for Dexcom compared with manual expert review. • What are the implications of our findings? NLP is a reliable, scalable tool for automated CGM data extraction, which can significantly enhance efficiency and data quality in diabetes care and research.","PeriodicalId":11140,"journal":{"name":"Diabetes Care","volume":"106 1","pages":""},"PeriodicalIF":16.2,"publicationDate":"2025-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145405225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Incidence of Type 2 Diabetes With Verapamil Compared With Other Calcium Channel Blockers","authors":"Julian W. Sacre, John M. Wentworth, Dianna J. Magliano, Jonathan E. Shaw","doi":"10.2337/dc25-1440","DOIUrl":"https://doi.org/10.2337/dc25-1440","url":null,"abstract":"OBJECTIVE Evidence that the calcium channel blocker (CCB) verapamil slows type 1 diabetes progression suggests possible preventive benefits among people at risk of developing type 2 diabetes. We compared type 2 diabetes incidence between users of verapamil versus other CCBs in a population-based cohort. RESEARCH DESIGN AND METHODS From a random sample of Australians in national subsidized health care databases, we identified 90,026 individuals who initiated treatment with a CCB (at least two supplies) between July 2003 and December 2014. Incident diabetes was captured by subsequent receipt of glucose-lowering treatment or registration with the National Diabetes Services Scheme. Individuals were followed from first CCB supply until discontinuation, diabetes onset, death, or end of 2014. Multistate Poisson regression models characterized associations of CCB subclass with type 2 diabetes incidence and death (the competing event), after multivariable propensity score adjustment. RESULTS The cohort comprised 4,485 verapamil users (5.0%) and 85,541 treated with other CCBs (mostly dihydropyridines). During a median 1.6-year follow-up, 101 individuals treated with verapamil developed type 2 diabetes (8.8 per 1,000 person-years) compared with 2,622 people treated with other CCBs (11.4 per 1,000 person-years). This translated to an incidence rate ratio of 0.77 (95% CI 0.63–0.94) in favor of verapamil (fully adjusted) and a lower probability of type 2 diabetes at 6 years (4.2% [95% CI 3.3–5.3] vs. 5.4% [4.7–6.3] for a typical clinical profile; absolute risk difference 1.3% [95% CI –0.1–2.4]). Results were robust across multiple sensitivity analyses. CONCLUSIONS Verapamil use is associated with a lower incidence of type 2 diabetes compared with other CCBs.","PeriodicalId":11140,"journal":{"name":"Diabetes Care","volume":"1 1","pages":""},"PeriodicalIF":16.2,"publicationDate":"2025-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145405224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of Modern Glucose Monitoring and Insulin Delivery Technologies on Patient-Reported Outcomes and Experiences in Individuals With Type 1 Diabetes: A Systematic Review and Meta-analysis","authors":"Miao Gao, Swathi Saravanan, Theresa Munyombwe, Jane Speight, Andrew J. Hill, Gemma Traviss-Turner, Ramzi A. Ajjan","doi":"10.2337/dc25-1178","DOIUrl":"https://doi.org/10.2337/dc25-1178","url":null,"abstract":"BACKGROUND Use of technology is central to the management of type 1 diabetes (T1D), while patient reported outcomes measures (PROMs) can support in the management of these individuals. PURPOSE To assess the effect of diabetes technologies on patient-reported outcome measures (PROMs) in type 1 diabetes (T1D). DATA SOURCES Cochrane Library CENTRAL, Embase, MEDLINE, Scopus, and Web of Science were searched for relevant articles from 2013 to August 2025. STUDY SELECTION We included longitudinal diabetes technology studies assessing validated PROMs in nonpregnant adults with T1D. DATA EXTRACTION Study characteristics and PROM data were extracted, and standardized mean differences (SMDs) for PROs were pooled using a random-effects meta-analysis. DATA SYNTHESIS We identified 4,885 articles, comprising 81 independent studies (n = 19,148 participants) and 70 different PROMs. The Hypoglycemia Fear Survey (HFS) was most commonly used (k = 39 studies), followed by the Diabetes Treatment Satisfaction Questionnaire (status [DTSQs] or change version [DTSQc]; k = 38), Diabetes Distress Scale (DDS; k = 25), and Problem Areas in Diabetes (PAID) scale (k = 24). Technology use was associated with lower HFS total score compared with control (SMD −0.177; 95% CI −0.319, −0.036; P = 0.014; I2 = 0.0%), with the largest effect observed in automated insulin device users. A moderate positive effect of diabetes technologies was observed on DTSQs and DTSQc scores (SMD 0.429; 95% CI 0.206, 0.653; P < 0.001; I2 = 72.3%), with a small to moderate reduction in DDS and PAID scores (SMD −0.265; 95% CI −0.363, −0.166; P < 0.001; I2 = 0.0%). LIMITATIONS Differences in type of technology, varied use and incomplete reporting of PROMs, and different duration of studies. CONCLUSIONS Diabetes technologies offer psychological benefits in adults with T1D. The large number of reported PROMs suggests a need to standardize their use.","PeriodicalId":11140,"journal":{"name":"Diabetes Care","volume":"1 1","pages":""},"PeriodicalIF":16.2,"publicationDate":"2025-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145405153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Screening Natriuretic Peptide Levels Predicts Heart Failure and Death in Individuals With Type 1 and Type 2 Diabetes Without Known Heart Failure","authors":"Rodica Pop-Busui, Enrico Repetto, Jason Baron, Dagmar Schumacher, Muthiah Vaduganathan, Ambarish Pandey","doi":"10.2337/dc25-1260","DOIUrl":"https://doi.org/10.2337/dc25-1260","url":null,"abstract":"OBJECTIVE Heart failure (HF) is common in diabetes and may be asymptomatic in early stages. N-terminal pro-brain natriuretic peptide (NT-proBNP) and B-type natriuretic peptide (BNP) (collectively natriuretic peptides [NPs]) are markers that can be used to detect early HF in asymptomatic individuals who may benefit from disease-modifying therapies. We examined the prognostic role of NP levels in people with type 1 diabetes (T1D) or type 2 diabetes (T2D) without known HF. RESEARCH DESIGN AND METHODS Optum’s de-identified Market Clarity Data were queried for adults (aged ≥18 years) with T1D or T2D without known HF who received an outpatient NP test between 2017 and 2023. Associations between NP levels and incident HF or death were assessed using multivariable Cox proportional hazard models. RESULTS Among 116,466 eligible adults (n = 2,990 with T1D; n = 113,476 with T2D) followed for up to 7 years (54% female; median age 64 years; mean HbA1c 7.1% at baseline), approximately 39.6% of individuals with T1D and 42.3% of individuals with T2D had BNP ≥50 pg/mL or NT-proBNP ≥125 pg/mL. In adjusted Cox models, increased NT-proBNP level was significantly associated with increased risk of incident HF or mortality among individuals with T1D (for NT-proBNP level 125–300 pg/mL: HR [95% CI] 2.04 [1.35–3.07], for NT-proBNP level >300 pg/mL: 4.48 [3.11–6.47], reference: NT-proBNP <125 pg/mL) and T2D (for NT-proBNP level 125–300 pg/mL: HR [95% CI] 1.85 [1.74–1.97], for NT-proBNP >300 pg/mL: 3.58 [3.39–3.78], reference: NT-proBNP <125 pg/mL). Similar findings were observed for BNP. CONCLUSIONS Increased NP levels among individuals with diabetes are highly prognostic for future risk of HF or mortality. These findings support the implementation of NP screening for HF risk assessment in people with diabetes.","PeriodicalId":11140,"journal":{"name":"Diabetes Care","volume":"153 1","pages":""},"PeriodicalIF":16.2,"publicationDate":"2025-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145405152","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}