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.

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.

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.

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.

Continuous glucose monitoring (CGM) is increasingly used for inpatient glycemic surveillance, but evidence in non-critical care wards remains limited, particularly in real-world public healthcare settings. Intermittent capillary glucose testing may fail to detect transient, nocturnal, or asymptomatic dysglycemia. We sought to evaluate whether CGM improves detection of clinically significant dysglycemia compared with seven-point capillary glucose monitoring in hospitalized patients with type 2 diabetes mellitus or hyperglycemia. This is a prospective, observational, non-randomized, real-world study performed in a tertiary referral center in Mexico. 56 hospitalized patients were included: 28 underwent flash CGM and 28 underwent seven-point capillary glucose monitoring. Patients were followed for up to 6 hospitalization days. The main analytical focus was detection of clinically significant dysglycemia, including hypoglycemia <70 mg/dL, clinically significant hypoglycemia <54 mg/dL, and severe hyperglycemia >250 mg/dL. Secondary outcomes included time in range, mean daily glucose, insulin requirements, infectious complications, length of stay, and mortality. CGM detected more hypoglycemia <70 mg/dL than capillary monitoring (71.4% vs 35.7%, p=0.005), more clinically significant hypoglycemia <54 mg/dL (median 3 [IQR 0-6.5] vs 0, p=0.030), and more severe hyperglycemia >250 mg/dL (median 8.5 [IQR 0.5-17] vs 0 [IQR 0-9.52], p=0.030). Time in range was not significantly different between groups (59.86 +/- 23.46% vs 69.28 +/- 24.99%, p=0.151). After adjustment for age, diabetes duration, and admission hyperglycemia, CGM remained associated with hypoglycemia detection (OR 4.7, 95% CI 1.2-19.0, p=0.027). We concluded that CGM improved detection of clinically significant dysglycemia during up to 6 hospitalization days. Although CGM did not improve time in range or short-term clinical outcomes, it provided superior glycemic surveillance compared with intermittent capillary glucose testing.

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

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.

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.

Introduction Continuous Glucose Monitoring (CGM) is considered standard care in high-income countries. There is, however, limited published evidence on CGM use in low- and middle-income countries. The purpose of this study was to assess the usability, acceptability, and feasibility of CGM use among people living with type 1 diabetes (T1D) and caregivers in a low-resource setting. Research Design and Methods This prospective study conducted at the Kenyatta National Hospital purposively enrolled persons aged 4-25 years who had been on management for T1D for at least six months, and caregivers of those under 18 years. Fourty youth living with T1D used CGM for three months in place of self monitoring of blood glucose (SMBG). The System Usability Scale (SUS), a Theoretical Framework of Acceptability-based questionnaire, the Diabetes Distress Scale (DDS), the Glucose Monitoring Satisfaction Survey (GMSS), and a feasibility survey were administered. Outcomes were summarized descriptively, including means, medians, and frequencies using R statistical software. Results The median SUS score was 98.8 (IQR 92.5-100.0). Acceptability was high, and the median total GMSS score improved from 3.73 to 4.73. Among adolescents and adults, the median overall DDS score reduced from 1.54 to 1.36, with reductions in scores in all domains, except for hypoglycemia distress which increased, and physician distress which remained low. Among caregivers, the median overall DDS score declined from 2.05 (moderate distress) to 1.90 (low distress), with modest reductions in teen management and parent-teen relationship distress and a slight increase in personal distress. Median CGM active wear time was 89%. Conclusion This study comprehensively evaluated CGM across usability, acceptability, and feasibility outcomes, with the findings supporting the integration of CGM into routine diabetes management in low-resource settings. The short follow-up period, however, may not capture changing perceptions or long-term adherence.

Introduction. Diabetes is a growing global health challenge, necessitating effective management strategies. Glycosylation, a highly regulated post-translational protein modification, has emerged as a pivotal factor in diabetes pathophysiology. However, the modulation of protein glycosylation by antidiabetic treatment is still largely unknown. This study explored the longitudinal effects of four distinct antidiabetic therapies - metformin, insulin, sodium-glucose cotransporter-2 (SGLT2) inhibitors, and glucagon-like peptide-1 receptor agonists (GLP-1RA) - on plasma protein and immunoglobulin G (IgG) glycosylation in patients with type 2 diabetes (T2D). Research Design and Methods. Plasma protein and IgG N-glycans were enzymatically released, purified and chromatographically profiled in a cohort of 124 patients, examined at four time points, to assess therapy-induced glycan alterations. Linear mixed models adjusting for covariates and multiple testing (FDR<0.05) were used to investigate the associations between plasma protein and IgG N-glycosylation and antidiabetic therapy. Results. Our findings reveal that metformin, SGLT2 inhibitors, and GLP-1RA induce significant alterations in IgG glycosylation, including the increased core fucosylation and galactosylation, features associated with a reduced inflammatory IgG potential. Notably, IgG monogalactosylation, previously linked to cardioprotective effects in women, was elevated in response to GLP-1RA and SGLT2 inhibitor treatments. Plasma protein glycosylation changes were more limited, with distinct alterations observed for each therapy. Metformin and GLP-1RA similarly reduced certain fucosylated and sialylated glycans, while SGLT2 inhibitors decreased a high-mannose glycan, previously positively associated with diabetes progression. Insulin therapy had a minimal effect on protein glycosylation, with only one plasma glycan significantly altered. Conclusions. Our findings emphasise the importance of protein glycosylation as a dynamic and responsive marker in T2D treatment. The distinct glycan alterations observed in response to metformin, SGLT2 inhibitors, and GLP-1 receptor agonists provide novel insights into the molecular effects of these therapies, potentially contributing to the development of glycan-based biomarkers for personalized diabetes management.

Introduction: Continuous glucose monitoring (CGM) offers an advancement over traditional self-monitoring of blood glucose (SMBG) for people living with type 1 diabetes (T1D). However, evidence on the acceptability and feasibility of different CGM use cases in African populations remains limited. Methods: This was a pragmatic three-arm, randomised controlled trial on CGM conducted among people living with T1D in three public healthcare clinics in South Africa. Participants were assigned to Arm 1 (continuous CGM), Arm 2 (periodic CGM), or Arm 3 (SMBG). Diabetes education was provided at all study visits. Feasibility was assessed by adherence to CGM use and through the Glucose Monitoring Satisfaction Survey (GMSS). Diabetes distress was measured by the Diabetes Distress Scale (DDS), health-related quality of life (HRQoL) by the EQ-5D scales, and acceptability using the Theoretical Framework of Acceptability (TFA). Surveys were collected on paper and transferred to OpenClinica. Analyses were performed in R. The trial was registered in the Clinical Trials Registry (NCT05944718) on July 13, 2023. Results: A total of 83 participants were included in Arm 1, 85 in Arm 2, and 80 in Arm 3. CGM mean active time was 55% in Arm 1 versus 69% in Arm 2. The proportion of participants meeting the [&ge;]70% active time threshold was higher in Arm 2 (52%) than in Arm 1 (34%). Diabetes' distress declined across arms during the intervention period, with no significant difference between arms; distress increased slightly six months post-intervention but remained below baseline. At 6 months, glucose monitoring satisfaction was significantly higher in both CGM arms than in the SMBG arm, and satisfaction increased over time in CGM arms. Health-related quality of life remained stable across arms during the intervention period with no significant difference between arms. High acceptability was observed in both CGM arms, with higher ratings in the periodic arm. Conclusions: CGM was acceptable to people living with type 1 diabetes and feasible to use in public-sector clinics in South Africa, with high acceptability under continuous and periodic use. Health-related quality of life remained stable across arms, and diabetes-related distress declined, during the intervention period, across arms. Glucose monitoring satisfaction rose significantly in both CGM arms compared to SMBG. Periodic CGM might be a promising and potentially more scalable option than continuous use for public-sector care.

Objectives To evaluate the early implementation of tirzepatide for the management of obesity in primary care in England, including variations in Integrated Care Board (ICB) service delivery models, access criteria, and initial prescribing activity following national policy introduction (June 2025). This paper reports the initial phase of a wider mixed methods national evaluation of tirzepatide delivery models for initial priority cohorts defined in NHS England interim commissioning guidance. Design National study combining 1) mapping of ICB implementation plans using a questionnaire, publicly available data and documents, and stakeholder discussions, and 2) analysis of English Prescribing Dataset (EPD) to investigate tirzepatide prescribing trendsusing interrupted time-series methods to compare monthly prescriptions before and after June 2025 (implementation start) against a synthetic control series based on semaglutide prescribing. Setting ICBs across England. Participants 23/42 ICBs (55%) responded, of which 13 also took part in stakeholder meetings. For 17 ICBs (40%), we additionally extracted information from publicly available documents. Main outcome measures Descriptions of service delivery models, access criteria, and ICB characteristics; stakeholder-reported implementation challenges; and prescribing trends over time. Results We were able to categorise models of care for 40/42 ICBs. A general practice-led delivery model was most commonly planned (18/40; 45%), followed by community/local-based delivery (8; 20%), custom models (8; 20%), and specialist weight management service (SWMS) community outreach (6; 15%). Four ICBs (10%) planned to use more than one model of care. Most ICBs reported following national priority cohort eligibility criteria 31/39 (79%), while eight (21%) applied additional prioritisation criteria due to funding constraints. Stakeholder discussions highlighted variation in the interpretation of model definitions, variation in operationalisation, and challenges related to affordability, insufficient workforce capacity, and tight timelines, with some ICBs not yet prescribing at the time of stakeholder meetings (November 2025). Analyses of EPD showed a steady increase in tirzepatide prescribing over time, with no evidence that the June 2025 policy implementation date produced any additional increase beyond background diabetes-related trends. Conclusions Early implementation of tirzepatide prescribing in primary care has been characterised by heterogeneous service models, local adaptations of access criteria, and slow implementation of obesity-related prescribing. Findings highlight the challenges of implementing new pharmacological treatments including patient management within routine care and the need for clear guidance, realistic timelines, and system capacity. Ongoing evaluation is needed to understand how service models evolve and implications for access, equity, and outcomes.

Background. The imprecision of current metrics to capture the complex genetic admixture and racial identity among Hispanic/Latino individuals in the United States [US] is a concern. We examined the relationship of self-reported race and genetic ancestry with hypertension [HTN] among Hispanics/Latinos. Methods. Cross-sectional study of the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), including 10,586 Hispanic/Latino unrelated adults. Genetic ancestry: West African [AA], Amerindian [AI], and European [EA]. Self-reported race: White, Black, Native American, or Multiple/Missing (More than one race or Unknown/Not reported/Refused). HTN: systolic (SBP) [&ge;]130 mmHg, diastolic blood pressure (DBP) [&ge;]80 mmHg, and/or use of HTN medications. Age- and sex adjusted models were used. Results. Self-reported race was White (38{middle dot}6%), Black (3{middle dot}6%), Native American (4{middle dot}1%), and Multiple/Missing (53{middle dot}7%), with Unknown/Not reported/Refused representing 32{middle dot}7%. Black and White Hispanics/Latinos had the greatest AA (55{middle dot}7%) and EA (69{middle dot}3%) ancestries, respectively. Each 10% AA increase was associated with OR 1{middle dot}15, SBP beta +0{middle dot}9 mmHg, and DBP beta +0{middle dot}7 mmHg. Conversely, each 10% AI increase was associated with OR 0{middle dot}83, SBP beta -0{middle dot}4 mmHg, and DBP beta -0{middle dot}6 mmHg. HTN prevalence was highest among those with Black race or in the highest AA quantile (45{middle dot}6% and 48{middle dot}0%, respectively), and lowest among those with Native American race or in the highest AI quantile (37{middle dot}6% and 26{middle dot}7%, respectively). Conclusion. One-third of Hispanics/Latinos did not self-report race. Black or White self-reporting race did somewhat relate to AA or EA ancestry, respectively. HTN profiles were related to self-reported race and genetic ancestry in this admixed population.

Importance. Metformin may influence risk of dementia, with prior conflicting observations of protection or harm. Objective. To determine the association of randomization to metformin vs. placebo or intensive lifestyle intervention (ILS) in the Diabetes Prevention Program (DPP) with cognitive outcomes (cognitive impairment syndromes and trajectories of cognitive test performance) during the DPP Outcomes Study (DPPOS). Design, Setting & Participants. Prospective long-term follow-up of DPP/DPPOS participants at 27 U.S. centers among adults who were at high risk for type 2 diabetes (T2D) at baseline. Exposures. Randomization to metformin, placebo, or ILS (1996-1999) for 3.2 years followed by open-label metformin in the original randomized metformin group until 2021. Main Outcomes & Measures. Cognitive impairment syndromes were adjudicated in 2022-2024 in 1,483 participants (median age 74 [IQR 68, 80]) using the National Alzheimer's Coordinating Center Uniform Dataset version 3. Cognitive performance in executive and memory domains was ascertained with repeated cognitive tests between 2009 and 2024. Multinomial logistic regression and mixed-effects models were fit to examine associations of randomization to metformin with cognitive outcomes. Results. Total metformin exposure (mean {+/-} SD) was 15.5 {+/-}7.7 years/person in the metformin group. Persons in the placebo and ILS groups received out-of-study metformin usually after developing diabetes with mean metformin total exposure of 4.5 {+/-}5.1 and 3.8 {+/-}4.8 years/person in the placebo and ILS groups, respectively. Overall, the frequency distributions of the cognitive syndromes did not differ significantly by treatment group; however, randomization to metformin was associated with a 60% (OR 0.40 [95%CI 0.17, 0.97]) and 62% (OR 0.38 [95%CI 0.16, 0.89]) lower odds of dementia compared with placebo and ILS, respectively, after adjustment for demographics, education, income, and APOE-{varepsilon}4 genotype. Randomization to metformin was also associated with significantly better memory performance over time ( {beta} =0.58; 95%CI: 0.09, 1.1; p=0.02; Cohen's d=0.1). Conclusions and Relevance. Long-term metformin treatment is associated with a reduced risk of dementia and better memory performance among persons with pre-diabetes or T2D. Estimates were imprecise due to a limited number of dementia cases. Longer follow-up with more dementia cases is needed to confirm our findings.

Objective: To determine whether continuous glucose monitoring (CGM) identifies clinically relevant glycemic heterogeneity and subclinical end-organ alterations in adults without diabetes. Research Design and Methods: We analyzed 1,017 AI-READI Year 3 participants without diabetes (558 with normoglycemia and 459 with prediabetes by A1C). Fifty-two metrics from 10-day blinded CGM were reduced to nonredundant glycemic axes. Partial Spearman correlations between representative CGM metrics and clinical measures across 13 domains were adjusted for age, sex, and BMI and controlled for false discovery rate. CGM-derived subphenotypes were identified using unsupervised UMAP-HDBSCAN-based clustering. Results: Among 462 glycemic-clinical associations tested, 99 (21.4%) remained significant after false discovery rate correction. Hyperglycemia-related metrics, including mean glucose, time above range, and time in tight range, showed more associations than variability metrics. The strongest signals involved cardiometabolic, cardiovascular, and cognitive measures. Greater hyperglycemia and glucose excursions were associated with lower language performance, slower processing speed, and lower cognitive efficiency ({rho} {approx} -0.10 to -0.14; all P < 0.01). Clustering identified four reproducible glycemic subphenotypes: Healthy, Mild Hyperglycemia, High Variability, and Hyperglycemia. CGM phenotypes reclassified A1C-defined groups: 58.1% of participants with normoglycemia fell into dysglycemic phenotypes, whereas 18.8% of participants with prediabetes fell into more favorable phenotypes. The Hyperglycemia phenotype had the most adverse cardiometabolic profile and lower cognitive performance. Conclusions: In adults without diabetes, CGM revealed glycemic patterns associated with distinct subclinical alterations. CGM-based phenotyping may complement A1C for characterizing early dysglycemia and selecting individuals for longitudinal risk-stratification studies.

Background: Type 1 diabetes (T1D) is a growing public health concern in low- and middle-income countries, where access to glucose monitoring and consistent routine care remains limited. Continuous glucose monitoring (CGM) may improve diabetes outcomes, but evidence of its acceptability and use in low-resource settings is limited. This study explored the perceptions and experiences of CGM use among people living with T1D, their caregivers, and healthcare providers (HCPs). Methods: Participants were recruited from the ACCEDE-U study, a usability study on CGM use among people living with T1D attending a tertiary referral hospital in Nairobi, Kenya. Among 40 participants in the ACCEDE-U study, those who had completed at least seven weeks of CGM use were eligible to participate in the qualitative component. Three focus group discussions (FGDs) were conducted: one with nine caregivers, one with nine adolescents (12-17 years), and one with six young adults (18-24 years). Semi-structured interviews were conducted with 9 HCPs. Data was collected using guides, audio-recorded, transcribed, and analyzed thematically guided by the socioecological framework. CORE-Q guidelines were used to report results. Results: Participants reported increased engagement in glucose monitoring and high acceptability of CGM. Reduced finger-prick testing and real-time alerts were key benefits, particularly among adolescents and young adults, who valued its discreetness and convenience. CGM was perceived to facilitate sharing of glucose data with HCPs. Caregivers reported a reduced monitoring burden. HCPs perceived CGM as valuable for clinical decision-making by providing real-time insights into glycemic patterns. Cost and limited device availability were identified as major barriers to sustained use. Conclusion: CGM was well accepted and perceived as beneficial. However, challenges related to cost and access may limit broader uptake. Improving affordability and availability could enhance feasibility and promote wider implementation in similar settings.

Aims To develop a 'core' dataset of diabetes related variables to support reproducible research using UK routinely collected health data. Methods A workshop was conducted bringing together diabetes healthcare professionals, researchers, and patient and public representatives to discuss and prioritise variables for inclusion in the Diabetes Core Dataset. Core variables were those considered to be highest priority for diabetes research and available at high quality in NHS data routinely used for research (primary care [GP] and Hospital Episode Statistics [HES] data). Candidate variables for inclusion in the Diabetes Core Dataset were from a review of existing core datasets and expert opinion. Participants scored variables anonymously based on priority for diabetes research. Results 25 variables from existing diabetes core datasets and 87 other candidate variables were considered for inclusion in the Diabetes Core Dataset. All 25 of those from existing diabetes core datasets and 5 of the 87 candidate variables met the core requirements for inclusion. In addition, 7 variables were identified as high priority but not included in the core dataset as they are not currently available in GP/HES data; these were labelled as 'future high priority' variables for diabetes research. Conclusions A new diabetes core dataset for UK EHR research has been developed using a consensus-based process. The core dataset is openly available and can be flexibly applied in UK EHR (https://healthdatagateway.org/en/tool/426), including in new NHS Research Secure Data Environment platforms, to enhance reproducible research to improve the clinical care of people with diabetes and associated conditions.

Objective: To examine how medial plantar nerve shear wave speed (Cs) and viscosity coefficient (Vi) are associated with the severity of diabetic peripheral neuropathy (DPN), and to assess their ability to differentiate adjacent severity categories. Materials and Methods: Based on TCSS, the 113 patients with type 2 diabetes mellitus were assigned to the non-DPN (n = 33), mild DPN (n = 46), and moderate DPN (n = 34) groups. Medial plantar nerve Cs and Vi were measured using shear wave elastography and viscosity imaging. Receiver operating characteristic analysis evaluated Cs, Vi, and their logistic regression-based combination; areas under the curves (AUCs) were compared using DeLong tests. Results: Cs and Vi increased progressively across the three groups (both P < 0.001). For non-DPN versus mild DPN, the AUCs of Cs, Vi, and the combined model were 0.688 (95% CI, 0.604-0.772), 0.741 (0.660-0.822), and 0.745 (0.665-0.826), respectively, without significant pairwise differences. For mild versus moderate DPN, the corresponding AUCs were 0.707 (0.625-0.789), 0.794 (0.724-0.865), and 0.799 (0.731-0.867). The combined model outperformed Cs (P = 0.045), whereas Cs versus Vi and Vi versus the combined model did not differ significantly (P = 0.162 and 1.000, respectively). Conclusion: Medial plantar nerve Cs and Vi increased with DPN severity. Their combination improved discrimination between mild and moderate DPN compared with Cs alone but not with Vi alone. Quantitative medial plantar nerve viscoelastic assessment may complement clinical severity grading.