BMJ Open Diabetes Research & Care

Objective. To determine the publication rate of abstracts presented at the American Diabetes Association Scientific Sessions and to evaluate the association between statistical significance of study results and subsequent publication. Research Design and Methods. We conducted a retrospective cohort study of abstracts presented at the 2018 American Diabetes Association Scientific Sessions. The primary exposure was study result category (statistically significant vs. non-statistically significant findings), and the primary outcome was publication in an indexed journal within 5 years after conference presentation. Publication status was determined through PubMed/MEDLINE and Scopus searches. Adjusted relative risks (RRs) and 95% CIs were estimated using generalized linear models with Poisson distribution and robust variance. Results. Among 541 included abstracts, 321 (59.3%) were subsequently published in indexed journals. Abstracts reporting statistically significant findings had a higher publication rate than those reporting non-statistically significant findings (61.9% vs. 42.3%; p=0.002). In the adjusted analysis, abstracts with non-statistically significant findings had a lower likelihood of publication compared with those reporting statistically significant findings (adjusted RR 0.71 [95% CI 0.55-0.93]; p=0.013). Conclusions. Approximately four in ten abstracts presented at the ADA Scientific Sessions were not published within 5 years. Abstracts reporting non-statistically significant findings had a lower likelihood of subsequent publication, suggesting persistent publication bias in diabetology research. Future initiatives promoting the interpretation of effect estimates, confidence intervals and clinical relevance, rather than statistical significance alone, may help reduce selective dissemination of evidence

Objectives: To examine the conformance to type 2 diabetes NICE guidelines across cardiovascular risk strata; and to quantify geographical variation in treatment pathways following the COVID-19 pandemic, encompassing guideline changes. Design: We carried out a retrospective observational study using linked electronic health records across England. Process mining, a data driven method that can reconstruct clinical treatment pathways, was applied to map 12-month treatment trajectories after treatment initiation. Conformance with NICE NG28 (2022) was quantified using a structural similarity index. Further, behavioural and entropy-based similarity (capturing treatment variability and complexity) measures were used to assess sequencing and heterogeneity of treatment. Setting: Primary and secondary care in England datasets within the National Health Service England Secure Data Environment (NHSE SDE), analysed first at national level and then across 42 Integrated Care Boards (ICBs) which are the devolved health care geographical delivery regions in England. Participants: 822,650 individuals with newly diagnosed T2DM between 1-February-2022 and 1-November-2025, stratified into low cardiovascular risk (LR-C; QRISK3<10), high risk (HR-C; QRISK3>=10 or receiving statins/blood pressure lowering treatment), and established cardiovascular disease (eCVD-C). Participants were followed for 12 months after first dispensed glucose lowering therapy. Main outcome measure: First line therapy, treatment intensification and switching within 12 months; change in glycated haemoglobin (HbA1c); quantified conformance to NICE recommended pathways; and regional variation in broader similarity measures. Results: Metformin monotherapy was the dominant initiation strategy in LR-C and HR-C cohorts (92.4% and 90.2%, respectively), whereas eCVD-C showed lower uptake of metformin (68.9%) and higher uptake of SGLT2 inhibitors (26.3%). Intensification from metformin to combination therapy was infrequent across all cohorts (<1%), although HR-C demonstrated the highest treatment transitions and switching behaviour. Dispensed SGLT2 inhibitor use was nearly threefold higher in eCVD-C (26.7%) than in LR-C (9.0%) or HR-C (10.7%). Overall, conformance to NICE-recommended pathways remained modest nationally, particularly in LR-C and HR-C. Across 42 ICBs, substantial regional heterogeneity in treatment pathways and guideline conformance was observed, with conformance ranging from 0.29 to 1.00 in LR-C pathways, 0.40 to 1.00 in HR-C pathways, and 0.54 to 0.92 in eCVD pathways. Conclusion: National T2DM treatment pathways for post-pandemic showed higher alignment to NICE guidelines in eCVD-C compared to the other risk groups, with ongoing gaps and large regional variations in other risk groups. Process mining offers a scalable approach to monitor implementation of guideline recommended care that could support learning health systems. Using T2DM during and post COVID-19 pandemic as a case study, this work demonstrates how these methods can assess the use of existing and innovative therapies, identify gaps and guide future adoption to ensure recommended treatments reach the right patient groups.

Objective Women carry disproportionate shares of caregiving and other life demands that may compound the work of diabetes self-management. We sought to examine gender differences in overall and digital treatment burden and their key contributors. Research Design and Methods Cross-sectional analysis of two cohorts of adults with type 1 or type 2 diabetes attending outpatient endocrinology visits who completed the Treatment Burden Questionnaire Plus Digital (TBQ+D) (n=472). Multivariable regression estimated gender differences in overall and digital treatment burden, ability to live a normal life, and sustainability of current self-care effort, adjusting for age, diabetes type, insulin intensity, HbA1c, and cohort. Item-level analyses identified contributors to observed differences. Results Compared to men, women reported higher median overall treatment burden (33 vs 20, adjusted mean difference 10.6 points, 95% CI 5.1-16.3; p<.0001) and digital treatment burden (13 vs 7, adjusted mean difference 3.5 points, 95% CI 1.1-6.1; p=.009). They also had higher odds of not living a normal life (OR 1.77, 95% CI 1.18-2.67; p=.006) and difficulty sustaining current self-care efforts indefinitely (OR 2.01, 95% CI 1.10-3.66; p=.023). Digital burden differences were concentrated in annoyance, precautions, and time and effort required to use digital medicine tools, whereas contributors to differences in overall burden varied, with relationships, self-monitoring, and injections contributing most. Conclusions After adjusting for treatment intensity and other factors, women living with diabetes were twice as likely to be overwhelmed by diabetes care than men. Their greater vulnerability to treatment burden demands healthcare service redesign and individualization of plans of care that minimally disrupt patients' and caregivers' lives.

Diabetes distress (DD) has a major impact on both diabetes control and emotional well-being but is mis- and underdiagnosed and undertreated. Treatment often starts with behavioral health (BH) through counseling or medications; in some patients, Certified Diabetes Care and Education Specialists (CDCES) are proven to better manage treatment burden and address distress. We performed an observational study comparing outcomes for people with high emotional distress (PHQ9 or GAD7 > 10) and high A1c 8.0 at baseline with CDCES support, BH treatment, both or neither. Results demonstrate both CDCES and behavioral health treatment were most effective (A1c -1.2%, PHQ -3.1) but received in only 4.3% of patients, while 50% of patients received BH treatment alone. Conclusion is that these services remain valuable in routine practice but are underutilized. Workflows that assist in CDCES treatment for patients at risk could improve outcomes.

Background: Digital diabetes programs have expanded quickly, but evidence of durable long-term benefit remains limited. In addition, as diabetes treatment guidelines changed to include cardiorenal-protective antihyperglycemics as first-line therapy, the effects of their adoption on glycemic control and program engagement within these programs remain poorly understood. Objective: To characterize longitudinal trends in glycemic control and estimate the extent to which these trends are associated with time-invariant and time-varying domains, among adults with T2D participating in Teladoc Health Remote Diabetes Monitoring Program (RDMP). Methods: This was a retrospective, longitudinal cohort study of adults with T2D participating in the Teladoc RDMP from 2021-2025. Domains were split into time-invariant (i.e. demographics and baseline clinical characteristic) and time-varying covariates (e.g. antihyperglycemic treatment complexity and adherence, program utilization and engagement, and adoption of cardiorenal protective antihyperglycemics). Primary outcome was estimated A1c (eA1c), calculated from FBG measurements captured through cellular-enable smart glucose meters. Longitudinal mixed-effects models were used to estimate adjusted annual trends in eA1c over 5 years, and Gelbach decomposition to quantify statistical contributions across domains. Secondary analyses examined attainment of eA1c <7% using GEE and complementary decomposition methods. Results: A total of 56,754 members with mean age 64.2 (SD 10.4), and 49% female were included in the analysis. Mean eA1c declined by 0.06 percentage points per year (95% CI, -0.06 to -0.06) and remained significantly lower after full adjustment for demographic, antihyperglycemic treatment and cardiorenal-protective therapy adherence, and program engagement factors ({beta}=-.04 percentage points/year; 95% CI, -.04 to -.03), demonstrating durable glycemic improvement over the five-year study period. Gelbach decomposition attributed most of the change between the base and fully adjusted trends to cardiorenal-protective therapies (170.8%), with an opposing contribution from program engagement (-71.9%) and minimal contribution from treatment history and complexity (1.1%). Adjusted odds of attaining eA1c <7% increased 8.0% annually (OR 1.08; 95% CI 1.07-1.09), corresponding to a 1.21-percentage-point annual increase in probability; adjusted predicted glycemic control increased from 75.2% in 2021 to 80.1% in 2025. Conclusion: In this five-year cohort, members who remained in the RDMP sustained improvements in eA1c and became more likely to reach an eA1c < 7%. Cardiorenal protective antihyperglycemics made the largest measured contribution to these trends, while program engagement contributed in the opposite direction. These findings show durable glycemic control but does not establish causal effects. Future evaluations of digital diabetes programs should account for pharmacotherapy, durability of improvements, and measure outcomes across cardiometabolic health.

Introduction The aim of this study was to compare patient-reported outcomes (PROs) related to hypoglycemia recovery with FLO23011, a glucose/beta-hydroxybutyrate Multi-Energy Substrate for Hypoglycemia (MESH) treatment, versus standard glucose gel in adults with type 1 diabetes, and to explore associations between by continuous glucose monitoring-derived metrics and perceived and objective treatment response. Research Design and Methods In a randomized, open-label, crossover study, 12 adults with type 1 diabetes used either FLO23011 or glucose gel to treat hypoglycemia during two 6-week periods, with continuous glucose monitoring throughout. PROs were assessed using 14-domain questionnaires and exit interviews. CGM analyses from a broader discovery analysis examined patient-relevant recovery signals: glucose-band exposure versus psychological PRO scores, and baseline glycemic variability versus time-in-range response. Results FLO23011 was rated more favorably than glucose gel in 13/14 domains, with statistically significant in 10. Differences included speed of action (8.0 vs. 7.3; P = 0.025), after-effects reduction (8.0 vs. 6.2; P = 0.014), ease-of-use (8.9 vs. 4.9; P = 0.002), and overall management ability (8.5 vs. 7.4; P = 0.019). Interviews described faster cognitive recovery, reduced disruption, and greater confidence. Reduced Level 1 hypoglycemia exposure was associated with higher reduced-worry and management-ability ratings (n=5; {rho} = 0.90; P = 0.037). Higher baseline coefficient of variation was associated with greater time-in-range improvement with FLO23011 (n=9; {rho} = 0.917; P = 0.0005). Conclusions FLO23011 showed more favorable patient-reported recovery than glucose gel. Initial CGM-PRO analyses findings suggest perceived benefit may align with reduced Level 1 hypoglycemia, while baseline variability may identify greater objective response. Results support integrating patient-reported and glycemic outcomes to evaluate hypoglycemia treatments, warranting confirmation in larger blinded studies.

Introduction Diabetes distress describes the psychological and emotional burden of living with diabetes and is associated with reduced self-management and adverse diabetes outcomes. Clinical guidelines recommend routine assessment and management of diabetes distress, but this is not always implemented. Therefore, there is a need to develop approaches to deliver emotional health support in routine clinical care more effectively. We describe here the protocol for a study to I) assess the feasibility of implementation of the D-stress Pathway, comprising Enhanced Usual Care (EUC) and an online, group-based, psychological diabetes distress reduction intervention called REDUCE, ii) evaluate the feasibility of the study protocol iii) detect an effect signal of diabetes distress score and Interstitial Glucose Time in Range and iv) refine initial programme theories of how both interventions (EUC and REDUCE) work, for whom, and under what circumstances. Methods This feasibility study includes a multicentre trial within a cohort design (TWICs) where sites have a staggered exposure to the interventions alongside a realist process evaluation. Four UK NHS diabetes services will recruit 80 adults with type 1 diabetes ([&ge;]1 year) using continuous glucose monitoring (CGM) ([&ge;]3 months). All participants will receive EUC and provide monthly data over 7 months on diabetes distress (measured by the Type 1 Diabetes Distress Assessment System (T1DDAS) and interstitial glucose measured by using continuous glucose monitoring. Participants with elevated diabetes distress, will be offered the six-week, group-based, online REDUCE intervention plus EUC, compared to EUC alone. Up to twenty participants with type 1 diabetes, ten family members/friends, sixteen healthcare professionals delivering EUC and five REDUCE facilitators will be interviewed to explore their experience of receiving training and delivering the D-stress Pathway. Up to 20 EUC consultations and REDUCE sessions will be observed. Analysis Feasibility will be assessed against pre-specified progression criteria and analysed descriptively using summary statistics. Primary outcomes include baseline level of diabetes distress, recruitment rate, intervention uptake, and data completeness, which will be analysed descriptively. Qualitative data will be analysed using framework analysis guided by realist programme theories developed for this study. Ethics Ethics approval has been granted by NHS Research Ethics Committee (REC) (Bromley REC: 25/LO/0469) and Health Research Authority obtained. All participants will provide informed consent. Trial registration no: Registered at ClinicalTrials.gov number NCT07193446 on 26/11/2025. Protocol and statistical analysis plan: The trial protocol and statistical analysis plan can be accessed at ClinicalTrials.gov.

IntroductionCurrent evidence suggests that patient health passports may improve care for patients with chronic illnesses. This systematic review aimed to evaluate the impact of patient health passports on health outcomes in adults with diabetes. MethodsA systematic review was conducted in February 2025 following PRISMA 2020 guidelines, using Ovid MEDLINE, Ovid EMBASE, EBSCO CINAHL, Web of Science, and Scopus. The review included studies of adult diabetic patients using paper or digital patient health passport as part of their care in comparison with the standard of care. Data were analysed using meta-analysis and a thematic analysis where appropriate; otherwise, the data are presented narratively. Quality appraisal was undertaken using the Cochrane Collaboration tool for assessing risk of bias and Evidence-based librarianship checklist. The certainty of the evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation. ResultsEleven studies (n=14,350) were included. Seven studies were randomised controlled trials, two were retrospective in nature, one was a qualitative and one was a pre-post study. Overall, the studies are limited in design, resulting in high or unclear risk of bias across multiple domains. Results of the meta-analysis of five studies showed a statistically significant mean difference reduction in HbA1c and total cholesterol in favour of the intervention group; however, the certainty of the evidence is low or very low. The narrative analysis of the data revealed little to no improvement in body mass index, blood pressure, blood glucose, and cholesterol levels. Patients opinions and perceptions revealed some benefits in usability, perceived value, and in enhancing collaboration. ConclusionThis review provides evidence suggesting that patient health passports may improve patient care and can inform the design of future high-quality studies. However, the low certainty of the evidence highlights the need for high-quality studies with larger sample sizes. Key PointsO_LIPatient health passports show promise in enhancing diabetes management, however current evidence is limited by high risk of bias; future high-quality studies are required to confirm efficacy. C_LIO_LINurses are pivotal in this process as they play a central role in diabetes education, self-management support and continuity of care. C_LIO_LIPatient health passports could be considered as a structured tool to facilitate ongoing monitoring, reinforce adherence, enhance communication between patient and nurses/multidisciplinary team. C_LI

Introduction: Ethnic minority populations are disproportionately affected by type 2 diabetes (T2D). We investigated ethnic differences in the risks of diabetes-related complications and mortality in the Netherlands, and identified clinical, sociodemographic and environmental determinants associated with these differences. Methods: We included 175,112 adults with T2D from the dynamic prospective primary care cohort DIAMANT. DIAMANT data were linked to national registries from Statistics Netherlands and GECCO, a database integrating geographic, environmental and contextual exposures. Ethnic differences in complications risks were estimated using Cox proportional hazards models. Potential mediating factors were explored using machine-learning-based variable selection and association decomposition approaches. Results: At baseline, mean age was 65.4 (SD 12.3) years, 46.6% were women and median T2D duration was 11.3 [IQR 7.2; 15.8] years. Substantial heterogeneity in complication risk was observed across ethnic groups compared with Dutch-origin individuals. Retinopathy risk was consistently higher across nearly all non-Dutch groups (HRs 1.37-2.37). For macrovascular complications, elevated risks were mainly observed among Surinamese and Turkish individuals, including heart failure (HR 1.30 and 1.46, respectively). In contrast, individuals of Indonesian and Moroccan origin showed similar or lower risk for most complications. Environmental exposures (e.g. air pollution, temperature) and sociodemographic factors (e.g. main benefit, household composition) accounted for a substantial attenuation of several observed associations. Discussion: Substantial ethnic differences exist in risks of T2D complications and mortality, which showed to be heterogeneous across outcomes and populations. Our findings suggest that a considerable proportion of these disparities is attributable to differences in environmental and sociodemographic context, highlighting the importance of interventions that take into account differences in environmental and socio-demographic context.

BackgroundContinuous glucose monitoring-derived time in range (TIR; glucose 70-180 mg/dL) has emerged as a complementary glycemic metric, but its association with DKD (Diabetic Kidney Disease) has not been systematically quantified. We aimed to synthesize the evidence on the association between CGM-derived TIR and DKD in adults with type 1 or type 2 diabetes by conducting a systematic review and meta-analysis of the current evidence. MethodsThis systematic review and meta-analysis adhered to PRISMA guidelines. PubMed, Embase, Cochrane CENTRAL, and Scopus were searched through March, 2026. Eligible studies were studies in adults with type 1 and type 2 diabetes that reported an association between CGM-derived TIR and any DKD outcome (albuminuria, eGFR decline, or composite nephropathy) with a quantifiable per-unit effect estimate. Random-effects meta-analysis (REML with Knapp-Hartung adjustment) pooled odds ratios per 10% TIR increment. Risk of bias was assessed using ROBINS-E and certainty of evidence using the GRADE framework. PROSPERO: CRD420261377763. ResultsEleven studies (n = 7,182; seven T2D, four T1D; ten cross-sectional, one retrospective cohort) were included. The pooled OR per 10% TIR was 0.89 (95% CI 0.84-0.95; P = 0.002; I{superscript 2} = 69.6%), and every leave-one-out iteration preserved significance (OR range 0.88-0.91; all P [&le;] 0.005). In the four studies adjusting for HbA1c, the association persisted (OR 0.91, 0.86-0.97; P = 0.015) with no detectable residual heterogeneity (I{superscript 2} = 0%), indicating the signal is not fully attributable to average glycemia. ConclusionsHigher CGM-derived TIR may be associated with lower odds of DKD (OR 0.89 per 10% increment). The HbA1c-adjusted subgroup (k = 4; I{superscript 2} = 0%) provided the most internally consistent signal, though its small size limits inference. Prospective studies with standardized CGM protocols and pre-specified hard kidney endpoints are needed to establish causality.

Background: Cardio-kidney-metabolic (CKM) diseases share risk factors, but their shared and distinct risk factors for disease progression remain unclear. We examined whether classical risk factors predict baseline CKM indicators and their longitudinal changes in a population-based German National Cohort (NAKO) sample. Methods: In 2,650 NAKO-IMMEDIATE participants selected for deep-phenotyping, baseline values and 5-year changes in glycated hemoglobin (HbA1c), systolic blood pressure (SBP), pulse wave velocity (PWV), and estimated glomerular filtration rate (eGFR) were linearly regressed on age, sex, education, alcohol and tobacco consumption, body mass index (BMI), and residuals of BMI-adjusted waist circumference (WC) with mutual adjustment. Results: Baseline values for HbA1c were 34.6{+/-}5.8 mmol/mol, for PWV 8.3{+/-}1.5 m/s, for SBP 128.0{+/-}15.7 mmHg and for eGFR 96.0{+/-}14.6 ml/min/1.73 m2. Cross-sectionally, all risk factors were associated with one or more of the CKM indicators, with age and BMI being associated with all four indicators. Over 5 years, HbA1c (1.2{+/-}4.2 mmol/mol), PWV (0.5{+/-}1.2 m/s) and SBP (0.6{+/-}14.2 mmHg) increased, whereas eGFR (-2.3{+/-}9.5 ml/min/1.73 m2) decreased. Age (0.03 m/s per 5 year, 95% CI 0.01, 0.06 m/s) was associated with higher and BMI (-0.02 m/s per 1kg/m2, -0.03, -0.01) with lower PWV changes. No other risk factors were associated with CKM indicator changes. Conclusion: Classical risk factors were more frequently related to baseline CKM indicators than to their 5-year changes. Within longitudinal analyses, only age and BMI were related to PWV 5-year changes. Keywords: Cardio-kidney-metabolic function, risk factors, longitudinal studies

Abstract Objective: To identify clinical and genetic factors associated with variation in glycemic response to glucagon-like peptide-1 receptor agonist (GLP-1RA) therapy among adults with type 2 diabetes, with a focus on common GLP1R variations, polygenic risk load, and pancreas-specific regulation annotation. Research Design and Methods: We conducted a retrospective cohort study using electronic health record (EHR)-linked biobank data from the All of Us research workbench platform that included 5784 adults with type 2 diabetes who initiated GLP-1RA therapy. Baseline HbA1c was measured within 3 months before medication initiation, and follow-up HbA1c was measured after 3 months. The patients with type 2 diabetes were classified as good responders (HbA1c reduction [&ge;] 2.5 percentage point) or poor responders (HbA1c reduction <0.5 percentage point). Models adjusted for demographic characteristics, anthropometric and metabolic measures, blood pressure, body mass index (BMI), lipid profile, liver function tests, polygenic risk score, and GLP1R variant carrier status were compared between the two groups. Common GLP1R variations were further investigated for carrier frequency and associated HbA1c levels before and after medication use. Results: The cohort included 3194 good responders and 2590 poor responders. Good responders were younger than poor responders (55.2 vs. 58.6 years) and had significantly higher glycemic improvement. HbA1c levels fell from 9.2% to 6.3% in good responders and 8.4% to 8.1% in poor responders, resulting in an absolute HbA1c reduction of 2.9% and 0.3%, respectively. Good responders also showed larger decreases in fasting glucose, BMI, systolic and diastolic blood pressure, triglycerides, total cholesterol, LDL cholesterol, and liver enzymes, as well as minor improvements in HDL-C. After multivariable adjustment, Poor responders had a greater T2D polygenic risk score (0.38 vs. 0.21), more GLP1R coding variant carrier status (10.1% vs. 8.0%), and a higher overall GLP1R variant burden (22.8% vs. 19.2%). Variant-level studies revealed rs2268650 and rs2003132 enrichment among poor responders, with negative post-treatment HbA1c patterns in carriers, whereas good-response carriers showed significant HbA1c improvement. Conclusions: Response to GLP-1RA in T2D is associated with baseline clinical and metabolic status, as well as inherited genetic susceptibility, which includes common GLP1R variation and a larger polygenic risk burden. Integrating clinical and pharmacogenomic profiling may improve patient classification and provide insight into treatment failure in poor responders.

Aims: To understand how users believe continuous glucose monitoring (CGM) changes their behaviour, which app features they credit, and whether endorsing more mechanisms of action (MoAs) is linked to reported diet and physical activity change. Methods: We surveyed 112 U.S. adults with type 1 or type 2 diabetes who had used a Dexcom or Abbott Libre CGM within 12 months. Participants rated 26 MoA statements mapped to the Capability, Opportunity, Motivation-Behaviour (COM-B) model, identified contributing app features, and reported CGM-attributed diet and physical activity change. Logistic regression examined MoA count and COM-B domains as predictors of behaviour change. Results: Participants (mean age 54.5 years; 60.7% female) reported dietary (82.1%) and physical activity (46.4%) change and endorsed a median of 18 MoAs, most often relating to knowledge, skills and behavioural consequences. Real-time glucose and graphs were attributed to many MoAs. Each additional MoA was associated with higher odds of dietary (OR 1.27, 95% CI 1.15-1.44) and physical activity change (OR 1.27, 95% CI 1.16-1.43). Motivation made the strongest distinct contribution among COM-B domains. Conclusions: Users perceive CGM as engaging many behavioural mechanisms; endorsing more was linked to behaviour change. Motivation may be a key target for CGM-based behavioural support.

BackgroundStructured cognitive screening in diabetes is recommended only from age 65, leaving younger adults with prolonged type 2 diabetes mellitus (T2DM) exposure unmonitored. We quantified the association of HbA1c and diabetes duration with Montreal Cognitive Assessment (MoCA) screen-positive status in adults aged [&le;] 60 years with T2DM of [&ge;] 5 years, and examined against matched controls how the MoCA cutoff (< 26, < 24, < 23) affects the group contrast in a lower-education population. MethodsCross-sectional study at a tertiary-care centre in North India: 110 adults with T2DM and 50 controls frequency-matched for age, sex, and education. Within diabetics, HbA1c and duration were modelled continuously by modified Poisson regression at each pre-specified cutoff and by Spearman correlation with MoCA total score. Prevalence ratios (PR) for diabetics versus controls at each cutoff were adjusted for age, sex, education, BMI, and hypertension. ResultsWithin diabetics, MoCA total score correlated with HbA1c ({rho} = -0.456) and duration ({rho} = -0.318; both p < 0.001). Screen-positive prevalence rose 5% per 1% HbA1c at < 26 (PR 1.05, 95% CI 1.02-1.09), 12% at < 24 (PR 1.12, 1.06-1.18), and 17% at < 23 (PR 1.17, 1.09-1.26), and 11% per year of duration at < 23 (PR 1.11, 1.06-1.17). Median education was 10 and 9 years; 76.0% of controls screened positive at < 26, and the diabetes association was cutoff-dependent: adjusted PR 1.08 (0.89-1.29) at < 26, 1.70 (1.10-2.63) at < 24, and 6.72 (2.23-20.23) at < 23, where 44.5% of diabetics versus 6.0% of controls screened positive (absolute difference 38.5 percentage points, 95% CI 25.0 to 48.7). ConclusionsIn working-age adults with long-standing T2DM, screen-positive prevalence rose continuously with HbA1c at every cutoff, a glycaemic signal independent of threshold choice. The standard < 26 cutoff flagged over three-quarters of both groups and could not triage; < 23 separated diabetics from controls. Screen-positive status is not a diagnosis; MoCA triage at a population-appropriate cutoff in this group warrants prospective validation against a neuropsychological reference standard.

ABSTRACT Background: To examine trends in Indonesia's diabetes care cascade from 2013 to 2023, identify key determinants, and assess progress toward global targets of 80% diagnosis and 80% glycemic control among those diagnosed. Methods: We analyzed nationally representative data from Indonesia's Health Surveys in 2013, 2018, and 2023. Diabetes was defined using fasting plasma glucose and oral glucose tolerance tests. We estimated diagnosis, treatment, and control rates and examined sociodemographic predictors of cascade progression using survey-weighted logistic regression models. Results: Between 2013 and 2023, the prevalence of diabetes among adults aged [&ge;]15 years remained stable, ranging from 10.7% to 11.8%. Diagnosis increased from 15.1% (95% CI: 13.4-16.7) to 20.7% (18.5-22.9), treatment nearly doubled from 10.5% (9.1-11.9) to 19.0% (16.9-21.2), and control rose modestly from 4.6% (3.6-5.6) to 6.5% (5.2-7.8). Older age, urban residence, higher socioeconomic status, and insurance coverage were associated with greater progression through the cascade. Wealth-related inequalities persisted in 2023: one-third of cases were diagnosed among the richest (35.3% [29.0-41.7]) versus only 11.0% (7.9-14.2%) among the poorest. Compared with the lowest quintile, wealthier individuals had higher odds of diagnosis (AOR 3.55 [2.11-5.98] for diagnosis, 3.59 [2.01-6.41] for treatment, and 2.24 [1.12-4.51] for control). Conclusions: Indonesia achieved meaningful improvements in the diabetes care cascade over the past decade, yet remains far below global 80/80 targets, with nearly 80% of cases undiagnosed and control below 10%. Persistent wealth-based inequities highlight that near-universal insurance coverage has not been translated into equitable care access, underscoring the need for equity-focused screening and primary care strengthening. Keywords: Diabetes, Care Cascade, Health Services, Indonesia

Objectives. To evaluate the impact of reimbursement restrictions for glucagon-like peptide-1 receptor agonists (GLP-1RAs) for type 2 diabetes, introduced in Denmark in November 2024, on injectable semaglutide (Ozempic) utilization patterns and subsequent HbA1c changes among discontinuers. Design. Nationwide registry-based cohort study. Setting. Denmark. Participants. Adults treated with injectable semaglutide for diabetes (January 2018 to December 2025). Main outcome measures. We described temporal patterns in injectable semaglutide use before and after the policy change. Among semaglutide continuers after the policy change, we assessed whether continuation met a key criterion in the new policy: non-feasibility of sodium-glucose cotransporter 2 inhibitor use and high cardiovascular risk. We characterized semaglutide discontinuers around the policy implementation (March 2024 to November 2024) and subsequent treatment switches. Among discontinuers, we evaluated HbA1c changes and performed interrupted time series (ITS) analyses. Results. Following the policy change, use of injectable semaglutide declined modestly before subsequently increasing. Among 61,120 individuals classified as semaglutide continuers, 27,143 (44%) were already using an SGLT2i. Of the remaining 33,977 (56%), only 1,862 (5.5%) met a key reimbursement criterion (i.e., non-feasibility of SGLT2i use and high cardiovascular risk). Among 79,305 individuals with a semaglutide fill between March 2024 and November 2024, 22,096 (28%) were classified as discontinuers. Within six months, ~40% of discontinuers switched to other glucose-lowering therapies, most commonly SGLT2is (24%). 37% of discontinuers later reinitiated semaglutide. Among individuals with an on-treatment HbA1c measurement (within 12 months before their last semaglutide fill) and an off-treatment HbA1c measurement (6-12 months after their last semaglutide fill) (n=13,017), mean HbA1c increased from 49 to 57 mmol/mol (mean change +7.4 mmol/mol, 95% CI 7.2-7.6). ITS analysis showed that HbA1c increased by 5.9 mmol/mol (95% CI 5.1-6.7) at six months post-discontinuation, which attenuated to 3.1 mmol/mol (95% CI 2.2-4.1) at 12 months; raw monthly means (not included in the ITS model) suggested this persisted through 18 months. Conclusions. Following the policy change, population-level use of injectable semaglutide declined modestly before increasing again. Most discontinuers did not initiate another glucose-lowering therapy and experienced an increase in HbA1c that did not fully return to pre-discontinuation levels during follow-up.

Background Cardiovascular-Kidney-Metabolic (CKM) syndrome encompasses interconnected conditions such as type 2 diabetes (T2D), hypertension, hypertriglyceridemia, metabolic syndrome (MetS), and chronic kidney disease (CKD). As CKM progresses, cardiorenal risks increase. Although Glucagon-like peptide-1 receptor agonists (GLP-1 RA) have demonstrated cardiorenal and cardiometabolic benefits, offering an opportunity to slow CKM progression, their use may vary across social determinants of health (SDoH) and stage 2 CKM subgroups. Objective To evaluate the influence of SDoH on access to GLP-1 RA among patients with T2D and other stage 2 CKM conditions. Methods This cross-sectional study used data from the U.S. National Health and Nutrition Examination Survey (NHANES), 2005?2020. Adults aged [&ge;]30 years with T2D and/or other stage 2 CKM conditions were included. Weighted descriptive analysis, multivariable logistic regression and LASSO were applied to assess associations between SDoH and GLP-1 RA use. Results Among 4,520 participants (representing approximately 84.0 million U.S. adults), weighted mean age was 61.4 years, 48.9% were female, and 61.5% were non-Hispanic White. Among participants with T2D, GLP-1 RA use was higher among individuals with higher education (3.39% vs 1.43%), private insurance (3.00% vs 0.58%), and higher income (4.70% vs 1.87%), while no use was observed among those without routine places for care. In adjusted analyses, individuals with lower income, less than high school education, lack of insurance, and being unmarried had 64%, 51%, 81%, and 40% lower likelihood of GLP-1 RA use, respectively. LASSO identified income, education, insurance, and access to care as predictors. Lower income, lower educational attainment, and lack of insurance were associated with 48%, 34%, and 79% lower likelihood of GLP-1 RA use, respectively, adjusting for age, sex, and race/ethnicity. Conclusion SDoH-driven disparities limit GLP-1 RA access. Expanding GLP-1 RA access by addressing socioeconomic barriers is critical to slowing CKM progression, reducing cardiovascular risk, and mitigating health disparities.

Glycemic control is key to prevention of complications of diabetes. Although eosinophils have been implicated in metabolic regulation, most human studies have been cross-sectional and have yielded inconsistent findings. We conducted a retrospective cohort study of adults with uncontrolled diabetes receiving primary care at Mass General Brigham. We evaluated the relationship between eosinophil count and HbA1c over one year, adjusting for demographic, socioeconomic, and clinical covariates. Among 21,447 patients included in the study, eosinophil count increased by a mean of 2.6 cells/L (SD 157.2 cells/L) and HbA1c decreased by a mean of 0.82% (SD 2.09%) during follow-up. Increases in eosinophil count were associated with reductions in HbA1c (parameter estimate -0.366 per 1,000 cells/L; 95% CI -0.526 to -0.206; P < 0.001), whereas baseline eosinophil count was not significantly associated with HbA1c changes. The association remained significant in a sensitivity analysis excluding systemic glucocorticoid users. Increases in eosinophil count were associated with improved glycemic control in adults with diabetes, whereas baseline eosinophil count was not. These findings extend prior cross-sectional observations and suggest that changes in eosinophils may represent a biomarker of glycemic improvement. Further prospective studies are needed to determine whether this relationship reflects underlying immune-metabolic mechanisms or treatment-related changes.

Introduction: Severe hypercholesterolemia has four primary causes: monogenic familial hypercholesterolemia (FH), polygenic hypercholesterolemia (PRS), severely elevated Lp(a) concentration, and hypercholesterolemia due to environmental/lifestyle/behavioral factors (i.e., no known genetic etiology). Here, we explore patient and clinician perspectives about the identification and management of each of these causes. Methods: Patients with severe hypercholesterolemia with a primary language of English or Spanish and clinicians (primary care, genetic counseling, cardiology) across two health systems (Geisinger, Mount Sinai) participated in semi-structured interviews. Analysis was completed using an a priori codebook informed by Proctor?s implementation outcomes to identify themes influencing the identification and management of the underlying causes of severe hypercholesterolemia. Results: A total of 28 patients and 25 clinicians participated. Patients emphasized the importance of receiving results directly from their clinician, requested take-home resources that mirrored the information from their clinician, were motivated to seek multidisciplinary care, and anticipated all results would be actionable, but that high-risk PRS and elevated Lp(a) may require more support (e.g., specialists, education) to act on. Clinicians stressed the importance of integrating workflows (e.g., test ordering) with the electronic health record, highlighted LDL-C levels and multidisciplinary care coordination as key to management, explained how they would tailor care to individual patients, and expressed a more limited understanding of Lp(a) and PRS result types based on their clinical experiences and, therefore, hesitation about the recommended clinical actions. Conclusions: Patients and clinicians identified complementary determinants influencing the identification and management of the underlying cause of severe hypercholesterolemia. Participants welcomed risk information and requested a higher level of informational support and specialty expertise to appropriately manage high Lp(a) and PRS results. Integrating genomic information into risk assessments will require a partnership between general practitioners and specialists to provide a multidisciplinary approach to the identification and management of the underlying causes of severe hypercholesterolemia.

Objective: To estimate how often remission of type 2 diabetes is recorded in routine care, how long it lasts, and what ends it, separating a return of hyperglycemia from a restart of treatment. Research design and methods: We studied 136,781 adults aged 18 years or older with laboratory confirmed type 2 diabetes in the Protege linked electronic health record (EHR) and claims database. The 96,817 adults with glucose-lowering treatment recorded at or before cohort entry formed the primary (previously treated) cohort; 39,964 adults with no treatment recorded at entry were analyzed in parallel. Remission required two HbA1c values <6.5%, 90 to 365 days apart, the first at least 3 months after all glucose-lowering drugs were discontinued, with no therapy recorded between them. After remission we followed glycemic relapse (HbA1c over 6.5%) and treatment restart (a new outpatient prescription or dispensed fill) separately, with death as a competing event (Aalen Johansen). Results: Remission was documented in 4.33% of previously treated adults cohort and 15.57% in the cohort of untreated adults at entry. Five-year cumulative incidence (Aalen Johansen) was 3.82% (95% CI 3.69 ;3.93) and 13.27% (12.90;13.59) in each cohort, respectively. Remission was less common with greater baseline treatment burden: exploratory adjusted 5-year incidence was 4.65% in adults with 1 glucose-lowering class with a treatment episode recorded at or before entry, 3.62% with two, 2.69% with three, and 2.02% with four or more such drugs.. The Median Kaplan Meier duration of first remission was 226 days (IQR 93 to 855) in previously treated adults and 371 days (166 to 1,027) in adults untreated at entry; 37.9% (treated cohort) and 23.1% (untreated cohort) of episodes had ended by 152 days. Among remission episodes that had ended, median duration was 159 days (71 to 362) and 265 days (129 to 565) for the treated and untreated at entry cohort, respectively. Within 5 years of remission in previously treated adults, the first event ending remission was glycemic relapse in 31.94%, treatment restart in 47.83%, and death in 4.65%.Treatment restart was about 1.5 times as common as glycemic relapse as the first event ending remission. A second remission followed within 5 years in 19.53% of previously treated and 24.10% of untreated remitters. Conclusions: Recorded remission was uncommon and short-lived, and it ended more often with a treatment restart than with a rise in HbA1c. Studies of remission in real-world data should report relapse and restart separately and state how they confirm remission and establish that treatment stopped.