BMJ Open Diabetes Research & Care

BackgroundGLP-1 receptor agonists (GLP-1RAs) and SGLT2 inhibitors (SGLT2Is) have established cardiovascular benefits for patients with type 2 diabetes mellitus (T2DM), with similar class-level effectiveness found in previous studies. However, real-world comparative effectiveness assessments of individual agents remain limited. ObjectivesTo compare the cardiovascular effectiveness of individual GLP-1RAs and SGLT2Is. MethodsWe conducted a multi-national, retrospective, new-user active-comparator cohort study using 10 US and non-US administrative claims and electronic health record databases. The study included 1,245,211 adults with T2DM receiving metformin who initiated second-line therapy with one of six GLP-1RAs (albiglutide, dulaglutide, exenatide, liraglutide, lixisenatide, semaglutide) or one of four SGLT2Is (canagliflozin, dapagliflozin, empagliflozin, ertugliflozin). Empagliflozin (393,499; 31.6%), semaglutide (235,585; 18.9%), dapagliflozin (208,666; 16.8%), and dulaglutide (207,348; 16.8%) were most commonly used. A secondary subgroup analysis included 316,242 patients with established cardiovascular diseases (CVD). Primary outcomes were 3-point major adverse cardiovascular events (MACE: acute myocardial infarction, stroke, sudden cardiac death) and 4-point MACE (adding hospitalization/ER visit with heart failure). Secondary outcomes included the individual components. Hazard ratios (HRs) were estimated for pairwise agent comparisons while on-treatment (per-protocol) and over total follow-up using Cox proportional hazards models, with propensity score adjustments, negative control calibration, and pre-specified study diagnostics to guard against potential confounding. Random-effects meta-analysis produced summary HR estimates across data sources that passed diagnostics. ResultsAcross the study cohort, individual GLP-1RAs and SGLT2Is demonstrated broadly similar cardiovascular effectiveness, both within and across drug classes. For example, semaglutide and empagliflozin showed comparable risks for 3-point MACE (meta-analytic HR 1.05; 95% CI 0.79-1.39) and 4-point MACE (meta-analytic HR 0.95; 95% CI 0.81-1.12), with consistent findings in the CVD subgroup. Study diagnostics confirmed adequate equipoise, covariate balance and statistical power to detect similarity in HRs between 0.8 and 1.2 for commonly used agents. ConclusionsIn this large-scale real-world study, individual GLP-1RAs and SGLT2Is exhibited largely comparable cardiovascular benefits, including in patients with established CVD. These findings align with network meta-analytic estimates from major cardiovascular outcome trials and broadly support current treatment guidelines. Clinical choices should be guided by relevant factors such as safety, adherence, tolerability, cost, and patient preference, where further work is needed.

ObjectivesTo estimate potential launch prices of generic semaglutide following patent expiry from 2026 and to quantify the global obesity and type 2 diabetes (T2DM) burden in countries where generic access may become possible. MethodsWe used World Bank population data and World Obesity and Diabetes Atlas prevalence estimates to calculate obesity and T2DM burden in countries where semaglutide patents expire in 2026 or were not filed. Patent status was identified using MedsPaL and cross-checked with regional databases. We updated established cost-plus pricing methodologies using 2024-2025 Indian API shipment data to estimate production costs for oral and injectable semaglutide, incorporating formulation, packaging, taxation, and profit assumptions. ResultsTen countries with 2026 patent expiry represent 44% of the global population and 48% of the global obesity burden. No patent filings were identified in 150 additional countries. By the end of 2026, generic injectable semaglutide could be distributed in 160 countries where 69% of global T2DM and 84% of clinical obesity occurs. Estimated generic injectable costs ranged from $28-140 per person-year, while oral formulations ranged from $186-380 per person-year. Injection devices contributed disproportionately to total cost. ConclusionPatent expiry could substantially expand access to semaglutide at dramatically lower prices, particularly in high-burden settings. However, device costs, secondary patents, and health system constraints may limit equitable uptake without coordinated policy action. Study ImportanceO_ST_ABSWhat is already known about this subject?C_ST_ABSO_LISemaglutide is highly effective for obesity and cardiometabolic disease but remains unaffordable in many low- and middle-income countries due to high branded prices and patent protections. C_LIO_LIPrevious cost-plus analyses show that generic competition can substantially reduce prices of essential medicines after patent expiry. C_LI What are the new findings in your manuscript?O_LIUsing 2024-2025 API shipment data, we estimate generic injectable semaglutide could be produced for $28-140 per person-year following 2026 patent expiry. C_LIO_LIBy 2026, generic semaglutide could be available in 160 countries comprising 69% of global T2DM and 84% of clinical obesity burden. C_LI How might your results change the direction of research or the focus of clinical practice?O_LIProvides an evidence base for procurement planning and price negotiations ahead of patent expiry. C_LIO_LIHighlights the importance of addressing device costs and secondary patents to ensure equitable global access. C_LI

Aims/hypothesisTo investigate the feasibility and preliminary efficacy of a 12-week remotely-delivered exercise snacks (ES) intervention in adults with type 2 diabetes. MethodsInsufficiently active adults with type 2 diabetes (N=69; 46 females; mean age {+/-} SD: 58{+/-}11 years) were randomized to an ES or mobility/stretching comparator group (CON), which involved 4 x 1-min bouts of either vigorous or low intensity exercise, respectively, on [&ge;]5 days/week. The primary outcome was feasibility based on adherence. Secondary outcomes included exercise enjoyment (1-7 scale), rating of perceived exertion (RPE; 0-10 scale), heart rate (HR), hemoglobin A1c (HbA1c), blood biomarkers of cardiometabolic health, 30-second sit-to-stand capacity, grip strength, estimated maximal oxygen uptake, and anthropometrics. ResultsWeekly adherence (estimated marginal mean [95% confidence interval]: 18 bouts [16 to 21] for both groups; P=0.99) and total enjoyment (ES: 4.5 [4.1 to 4.8] vs CON: 4.3 [4.0 to 4.7]; P=0.64) were high and not different between groups. Despite higher RPE (5.7 [5.4 to 6.1]) and peak HR (73 [70 to 77] % of age-predicted HR maximum) in ES vs CON (2.0 [1.7 to 2.4] and 61 [58 to 64] % of age-predicted HR maximum, respectively) (all P<0.001), there were no between-group differences in the change in any secondary outcome (all P>0.05) except for greater sit-to-stand capacity in ES after training (between-group effect estimate [95% confidence interval]: 1.9 repetitions [0.3 to 3.4]; P=0.02). Conclusions/interpretationExercise snacks were feasible to perform in the real-world and improved physical capacity to a greater extent than CON in adults living with type 2 diabetes. Trial registrationClinicalTrials.gov ID: NCT06407245 Research in ContextO_ST_ABSWhat is already known about this subject?C_ST_ABSO_LIExercise snacks ([&le;]1-min bouts of vigorous exercise spaced out across the day) are a time-efficient and practical approach to promote vigorous exercise and break up sedentary time. C_LIO_LIReal-world exercise snack interventions appear feasible for middle-aged and older adults. C_LI What is the key question?O_LIAre 12 weeks of exercise snacks performed in the real-world feasible for insufficiently active adults living with non-insulin treated type 2 diabetes? C_LI What are the new findings?O_LIExercise snacks are feasible for those living with type 2 diabetes to perform unsupervised in the real-world based on high adherence, enjoyment, and participant retention rates. C_LIO_LIExercise snacks improved 30-second sit-to-stand capacity and reduced waist circumference suggesting enhancements in physical capacity and body composition. C_LI How might this impact on clinical practice in the foreseeable future?O_LIExercise snacks could be utilized to help individuals living with type 2 diabetes build a routine or habit of incorporating small amounts of physical activity into their daily lives. C_LIO_LIThe improved physical capacity observed in the current study could contribute to lower fall risk and greater lower body strength in those with type 2 diabetes as they age. C_LI

BackgroundDigital health self-monitoring tools are widely used to support weight management and metabolic health. Higher engagement with these tools is often associated with better clinical outcomes; however, real-world engagement-outcome relationships for consumer metabolic monitoring devices remain incompletely characterized, particularly in heterogeneous user populations. ObjectiveTo evaluate whether engagement with a portable breath-based metabolic device (Lumen; Metaflow Ltd.) is associated with greater weight loss and reduction in body fat among real-world glucagon-like peptide-1 receptor agonist (GLP-1RA) users. The study also explores correlations between engagement and a device-specific measure of metabolic flexibility (FLEX score). MethodsWe retrospectively analyzed 2,296 adult Lumen users who self-reported GLP-1RA use over 24 weeks. Engagement was quantified as total engagement days over a 24-week period and ordered engagement consistency groups defined by weekly use frequency thresholds. Weight and body fat percentage data were collected by a combination of connected devices and manual user input in the Lumen smartphone application. Associations with weight loss and reduction in body fat percentage were evaluated using linear regression and ANCOVA adjusted for age, baseline BMI, and sex, with HC3 robust standard errors. Body fat percentage data were available for only 490 of the 2,296 subjects. In addition, similar associations were evaluated for FLEX score. GLP-1RA exposure was self-reported at onboarding and not verified longitudinally. ResultsAt 24 weeks, low/medium/high engagement users lost 3.2%, 4.6%, and 5.2% of body weight (trend p=2.36x10-11). Engagement days were associated with percent weight change (slope -0.0214% per day; P(HC3)=7.9x10- 18). Engagement days showed modest association with body fat percentage change (n=490; slope -0.0105% per day; P(HC3)=.010). The adjusted ANCOVA trend across engagement groups was not significant (P=.19). Engagement days and consistency both showed a highly significant trend in increase in FLEX score (slope +0.0185 per day; P(HC3)=2.0x10- 36). ConclusionsIn a real-world digital health dataset, higher engagement with a breath-based metabolic monitoring device and its smartphone application was associated with greater 24-week weight loss after adjustment for age, baseline BMI, and sex. The absolute difference between low and high engagement (2.0% body weight) is modest but clinically meaningful in real-world settings after 24 weeks of tracking. Associations with body fat percentage change were smaller and not consistently significant in adjusted analyses. Associations with metabolic flexibility were highly significant, but it remains unknown whether this parameter is predictive or reflective. Prospective controlled studies are needed to test causality and determine whether device-driven biofeedback and sustained engagement independently improve outcomes because GLP-1RA use was self-reported and unverified, and the present analysis was observational. These findings should be interpreted as engagement-outcome associations and reflect behavioral motivation and adherence rather than evidence of device efficacy.

ObjectiveTo introduce and evaluate the clinical utility of the "adipo-B index" as a novel metric of the adipose tissue-pancreatic beta cell axis. To our knowledge, no prior clinical metric has integrated adipose tissue insulin resistance and pancreatic beta-cell function into a single index applicable across therapeutic classes. MethodsTreatment-naive subjects with T2DM received monotherapy with modified traditional diet for diabetes (MJDD, n=61), canagliflozin (n=67), pioglitazone (n=54), or sitagliptin (n=63). Correlations between the baseline and changes in adipo-IR or adipo-B and clinical parameters were analyzed. This is a prospective, non-randomized observational study. ResultsAt baseline, among all the subjects, adipo-B significantly correlated with FBG, HbA1c, non-HDL-C and BMI, while adipo-IR did not. At 3 months, across all therapeutic strategies, significant negative correlations were observed between the changes in ({Delta})adipo-B and baseline adipo-B. By contrast, in MJDD, canagliflozin and pioglitazone, significant negative correlations were seen between {Delta}adipo-IR and baseline adipo-IR, while with sitagliptin, no correlations were noted. {Delta}adipo-B, but not {Delta}adipo-IR, correlated with the improvements of glycemic (FBG, HbA1c) and lipid (non-HDL-C) parameters across all these therapies. While significant correlations were seen between {Delta}adipo-B and {Delta}adipo-IR with MJDD, pioglitazone and sitagliptin, canagliflozin uniquely "decoupled" this axis. With sitagliptin and pioglitazone, adipo-B improved despite weight gain. ConclusionThe adipo-B index is a superior indicator of systemic metabolic status and therapeutic response and could serve as a useful tool for precision therapy for diabetes.

ObjectiveHbA1c thresholds used to define dysglycemia in autoantibody-positive individuals at risk for type 1 diabetes do not account for age-related increases in HbA1c and may overestimate progression risk in adults. We evaluated whether age-adjusted HbA1c or a higher HbA1c threshold improves risk stratification across age groups. Research Design and MethodsWe analyzed 5,024 autoantibody-positive relatives (3,720 children and 1,304 adults) participating in the TrialNet Pathway to Prevention study. Age-related HbA1c effects were modelled using 6,273 adults from the population-based Exeter 10,000 cohort. Progression risk was compared using the standard dysglycemia threshold (HbA1c [&ge;] 5.7% [39 mmol/mol]), age-adjusted HbA1c, and an alternative threshold of HbA1c [&ge;]6.0% (42 mmol/mol). ResultsUsing HbA1c [&ge;] 5.7%, children had higher 1-year progression risk than adults among single autoantibody-positive participants (38% [95% CI 28, 47] vs. 13% [7.2, 19]) and multiple autoantibody-positive participants (55% [49, 60] vs. 38% [27, 47]; both p<0.001). Age adjustment reduced these differences; progression risk was similar among single autoantibody-positive participants (38% [28, 47] vs. 27% [13, 39]; p=0.32), with attenuated differences among multiple autoantibody-positive participants. An HbA1c threshold [&ge;]6.0% yielded comparable progression risk between adults and children across autoantibody subgroups. In post hoc analyses, adults aged <30 years had progression risk similar to children (p=0.1). ConclusionsAge-related variation in HbA1c influences dysglycemia classification in adults at risk for type 1 diabetes. Age-adjusted HbA1c or a higher HbA1c threshold ([&ge;]6.0% [42 mmol/mol]) in adults [&ge;]30 years identifies individuals with progression risk comparable to children and may improve age-specific risk stratification in prevention seungs.

Uric acid (UA) is traditionally regarded as a metabolic risk marker; however, its dynamic behavior during glucose-lowering therapy remains incompletely understood. We compared UA responses to a modified traditional Japanese diet (MJDD) and the DPP-4 inhibitor alogliptin in patients with early-stage type 2 diabetes mellitus (T2DM). In this prospective observational study, drug-naive patients received MJDD (n=58) or alogliptin (n=52) monotherapy for 3 months. Changes ({Delta}) in serum UA were analyzed in relation to glycemic control, insulin resistance, adipose tissue insulin resistance (adipo-IR), and beta-cell function. Both interventions significantly reduced fasting blood glucose and HbA1c while paradoxically increasing serum UA and HOMA-B. Baseline UA was the primary determinant of {Delta}UA in both cohorts. MJDD significantly reduced body mass index, insulin, free fatty acids, HOMA-R, and adipo-IR, with effects most pronounced in subjects with baseline BMI >25. In contrast, alogliptin selectively reduced adipo-IR in leaner subjects (BMI <25). Across both treatments, {Delta}UA correlated positively with {Delta}HOMA-B and inversely with {Delta}HbA1c. Notably, during MJDD, {Delta}UA showed a paradoxical negative correlation with {Delta}BMI and {Delta}FBG, and a positive correlation with {Delta}FFA. Patients exhibiting the greatest UA increases demonstrated the most marked improvements in beta-cell function and, with MJDD, the greatest weight loss. These findings indicate that MJDD and alogliptin exert distinct metabolic effects in early T2DM, yet both link rising UA to enhanced beta-cell function, suggesting that UA may serve as a dynamic pharmacometabolic biomarker reflecting therapy-specific metabolic adaptation rather than metabolic deterioration.

IntroductionDysglycemia is a well-established risk factor for cardiovascular disease (CVD); yet traditional glycemic traits, including fasting plasma glucose (FPG) and HbA1c, do not capture dynamic glucose fluctuations that may inform CVD risk. We cross-sectionally investigated the association of continuous glucose monitor (CGM)-derived metrics and 2-h post-prandial glucose (2-h PPG) with estimated 10-year CVD risk among individuals without diabetes. MethodsWe included 1,360 Framingham Heart Study participants (Third Generation, New Offspring Spouse, and Omni 2 cohorts at exam 4) without prevalent diabetes or CVD who had [&ge;]3 days of CGM data and completed a mixed meal tolerance test (MMTT) with corresponding 2-PPG. We included 7 CGM summary metrics and defined data-driven glucotypes according to CGM measures of glycemic burden and variability. The 10-year CVD risk was estimated using the Predicting Risk of CVD EVENTs (PREVENT) base equations. We performed linear regression on standardized glycemic traits and glucotypes with log-transformed PREVENT risk scores and multinomial regression to relate standardized CGM metrics and 2-h PPG with PREVENT categories (low <5%[reference], borderline 5-<7.5%, intermediate/high [&ge;]7.5%). All models were adjusted for FPG and body mass index (BMI). ResultsAmong participants (55.9% women, 43.4% with prediabetes), mean age was 59.3 years, and mean BMI was 27.9 kg/m2. All CGM-derived metrics and 2-h PPG were positively associated with higher overall 10-year CVD risk (per 1 SD increase of each exposure variable, {beta} range: 0.06-0.16, all p<0.001). A glucotype representing high glycemic burden and high glycemic variability was associated with higher overall 10-year CVD risk, compared with the glucotype representing low glycemic burden and low glycemic variability. Higher CGM-derived metrics and 2-h PPG were also associated with higher odds being in the intermediate/high CVD risk (OR range: 1.20-1.65, all p<0.001), adjusting for FPG and BMI. ConclusionDynamic glycemic traits, including novel glucotypes that capture glycemic burden and variability, may provide novel insights into CVD risk prevention among individuals without T2D.

Background: Type 2 diabetes is a growing challenge in low- and middle-income countries, where health systems face major capacity gaps. Participatory learning and action (PLA) has shown effectiveness in preventing type 2 diabetes in Bangladesh, but little is known about its use in other LMICs for diabetes. The EMPOWER-D (Engagement of community through Participatory learning and action for cOntrol and prevention of type 2 diabetes) trial is testing PLA for diabetes prevention in communities in Pakistan and Afghanistan. This protocol describes the plans for the embedded process evaluation (PE). Methods: The PE will use a mixed-methods design across three sites, following the UK Medical Research Council framework for PE, examining implementation, mechanisms of impact and context. Implementation will be assessed using adaptation reports, fidelity checklists, attendance data, and supervisor reports. Mechanisms of impact will be explored through interviews, focus group discussions and photovoice. Contextual factors will be examined through interviews with participants, community mobilisers, supervisors, and key stakeholders. Quantitative data will be analysed descriptively, while qualitative data will undergo thematic analysis using a theory of change framework. Comparative analysis will identify common and context-specific influences. Discussion: This is the first multi-country PE of a PLA intervention for diabetes prevention to our knowledge, and the first in Afghanistan and Pakistan. The study will provide insights into how the intervention was delivered, how and why it worked (or did not work), and the contextual factors shaping outcomes. Findings will inform the adaptation and scale-up of participatory approaches for non-communicable disease prevention in resource strained setting health systems.

Background and AimsThe glucagon-like peptide-1 receptor agonist (GLP-1 RA) semaglutide has demonstrated efficacy for the secondary prevention of cardiovascular disease among patients with overweight/obesity without diabetes mellitus. However, the comparative effectiveness of GLP-1 RA versus other antiobesity medications (e.g. phentermine-topiramate) not been evaluated. MethodsThis was a retrospective, observational, cohort study using target trial emulation methodology using the Truveta electronic health record database of more than 120 million patients. Adult patients with a body mass index (BMI) >=27 kg/m2, a history of cardiovascular disease (prior ischemic stroke, transient ischemic attack, or myocardial infarction, or known coronary artery disease, heart failure, or peripheral artery disease) without diabetes mellitus were included in the study. The primary endpoint was time to first major adverse cardiovascular or cerebrovascular event (MACCE, defined as stroke or myocardial infarction). ResultsIn total, 35,240 were included in the bupropion-naltrexone versus GLP-1 RA comparison, and 27,051 were included in the phentermine-topiramate versus GLP-1 RA comparison. In the pre-weighting cohort, GLP-1 RA use was associated with decreased hazard of MACCE compared to bupropion-naltrexone (HR 0.50 [95% confidence interval (CI) 0.36-0.69]) and phentermine-topiramate (HR 0.43 [95% CI 0.30-0.60]). In the propensity score-overlap weighted cohort, GLP-1 RA prescription was not associated with a lower hazard of MACCE than bupropion-naltrexone (aHR 0.69 [95% CI 0.47-1.00]) but was associated with a lower hazard compared to phentermine-topiramate (aHR 0.61 [95% CI 0.41-0.91]; adjusted absolute rate difference 0.98 per 1000 person-years). ConclusionsPrescription of a GLP-1 RA was associated with a lower risk of subsequent MACCE than phentermine-topiramate.

Type 2 diabetes (T2D) affects 11.1% of the global population, underscoring the need for biomarkers that inform treatment response and glycemic outcomes. We evaluated the association between the FTO variant rs9939609-A and glycemic control in a Mexican population. A total of 174 individuals living with T2D from Merida and Sisal, Yucatan, were included, of whom 85% were receiving oral hypoglycemic agents as main treatment. Glycemic control was defined cross-sectionally as good ([&le;]130 mg/dL, n=63) or poor (>130 mg/dL, n= 111) with fasting glucose. Linear mixed models incorporating relevant covariates and a family random intercept were used. Effect size estimates were transformed to logit odds ratios. After adjustment for age, sex, BMI, years with T2D, and treatment, we observed a significant association in the additive (OR = 1.15 [1.003-1.31]) and recessive (OR = 1.51 [1.03-2.23]) models. To conclude, rs9939609-A may be associated with poorer glycemic control despite pharmacologic therapy.

IntroductionPolygenic risk scores (PRS), metabolomics, and proteomics have each shown promise in improving type 2 diabetes risk prediction, but their combined utility beyond established clinical models remains unclear. We aimed to evaluate whether integrating multi-omics biomarkers enhances 10-year type 2 diabetes risk prediction beyond single-omics extensions and the clinical Cambridge Diabetes Risk Score (CDRS), which includes HbA1c measurements. MethodsWe analysed data from 23,325 UK Biobank participants without diagnosed diabetes at baseline. Data for a PRS for type 2 diabetes, 11 metabolites, and 15 proteins were added to the CDRS to develop multi-omics prediction models. Model performance was evaluated using Harrells C-index and the net reclassification index (NRI). ResultsDuring 10 years of follow-up, 719 participants developed incident type 2 diabetes. Among individual omics layers, proteomics contributed the greatest improvement in predictive performance, increasing the C-index from 0.857 (clinical CDRS) to 0.880 ({Delta}C-index; +0.023; P < 0.001), with an NRI of 30.0%. The full multi-omics model, further significantly increased the C- index compared to a model combining the clinical CDRS with proteomics data (C-index, 0.886; {Delta}C-index; +0.006; P < 0.033). ConclusionIntegrating proteomics, metabolomics, and a diabetes-PRS into a clinical model substantially improves type 2 diabetes risk prediction beyond single-omics extensions. However, the C-index difference between the proteomics extended and full multi-omics extended models is small, and the clinical models extended with proteomics data would be easier to translate into routine care because it needs only the measurement of 15 proteins.

ObjectiveTo evaluate risk of dementia after cancer diagnosis among Medicaid beneficiaries with HIV. DesignLongitudinal observational study of Medicaid enrollment, inpatient, and outpatient claims data from 14 states, 2001-2015. MethodsBeneficiaries aged 18-64 with HIV and [&ge;]6 months of enrollment were matched 1:1 on cancer status by age, sex, race, year, and state. We estimated the weighted cumulative incidence functions (CIFs) of dementia at 1, 2, and 5 years after cancer diagnosis using the Aalen-Johansen estimator to account for the competing risk of death and cluster stratified analyses to account for matching. We calculated the corresponding risk differences (RD) and 95% confidence intervals (CI) using nonparametric bootstrap. ResultsAt 5 years, the CIF of dementia was 9.6% (95%CI: 8.2, 11.6) and 4.7% (95%CI: 3.7, 6.1) among those with and without AIDS-defining cancer, respectively (RD: 4.9%; 95%CI: 2.9, 7.0). At 5 years, the CIF of dementia was 7.1% (95%CI: 5.9, 7.8) and 5.3% (95%CI: 4.2, 6.2) among those with and without non-AIDS-defining cancer, respectively (RD: 1.8%; 95%CI: 0.34, 2.9). Dementia incidence appeared higher among beneficiaries with lung cancer (2yr RD: 1.9%; 95%CI: 0.01, 5.2) and beneficiaries [&le;]50 with colon cancer (2yr RD: 4%; 95%CI: 0.3, 10.5), but lower among beneficiaries [&le;]50 with prostate cancer (2yr RD: -1.9%; 95%CI: -2.3, -1.6). Dementia incidence did not differ among beneficiaries with and without breast cancer. ConclusionsDementia risk may be increased among people with HIV with certain cancers, including AIDS-defining cancers. Dementia risk appears to vary by cancer type and age at diagnosis.

BackgroundDiabetes mellitus (DM) remains a major global health challenge and is associated with vision-threatening complications, including diabetic macular edema (DME), a leading cause of visual impairment. Dyslipidemia has been implicated in the development of macular edema through mechanisms involving vascular permeability, endothelial dysfunction, and chronic inflammation. However, evidence regarding the relationship between lipid abnormalities and macular edema remains inconsistent across studies. AimThis study aimed to evaluate the association between abnormal lipid profiles and diabetic macular edema among patients with type 2 diabetes mellitus attending Kilimanjaro Christian Medical Centre (KCMC). MethodsA hospital-based analytical cross-sectional study was conducted among 296 diabetic outpatients at KCMC. Participants underwent comprehensive ophthalmic evaluation including fundoscopy and imaging with optical coherence tomography (OCT) for assessment of macular edema. Blood samples were collected for biochemical lipid analysis. Data were cleaned and analyzed using STATA version 17. ResultsDiabetic macular edema was identified in 56.4% (167/296) of participants. Abnormal lipid parameters were common, with elevated total cholesterol observed in 48.6%, triglycerides in 43.6%, low-density lipoprotein (LDL) in 36.1%, and reduced high-density lipoprotein (HDL) in 38.9% of patients. Elevated total cholesterol, triglycerides, and LDL levels showed significant associations with macular edema (p < 0.05). After multivariable adjustment, serum triglycerides remained independently associated with macular edema (p = 0.002). ConclusionDyslipidemia demonstrated a significant association with diabetic macular edema, with serum triglycerides emerging as an independent predictor. These findings highlight the importance of lipid monitoring, lifestyle modification, and strengthened screening strategies in reducing the burden of vision-threatening diabetic complications.

BackgroundWith growing efforts aimed at optimizing health care services by reducing "low value care", medical deprescribing represents a critical policy challenge at the intersection of clinical quality, fiscal sustainability, and environmental stewardship. Despite growing evidence of its benefits, France lacks a comprehensive national framework for systematic medication review and deprescribing implementation. ObjectiveTo identify areas of consensus and divergence among key French stakeholders using an adapted Policy Delphi approach to inform national deprescribing policy development. MethodsAn exploratory survey was conducted among stakeholders across five groups (healthcare professionals, patients, academia, policymakers, and the pharmaceutical industry). Consensus levels were assessed using graded Likert scales and analysed across policy domains, including knowledge and training, collaboration, resources, policy support, and sustainability opportunities. ResultsHigh consensus emerged around knowledge gaps, the need for interprofessional collaboration, and clinical benefits of deprescribing. Moderate consensus existed regarding resource constraints and environmental sustainability. Divergence was observed between professionals/academia and policymakers/industry regarding financial incentives and regulatory readiness. A policy Delphi heatmap revealed specific alignment patterns that could serve as policy entry points. ConclusionsMulti-stakeholder consensus mapping provides an innovative governance tool for identifying actionable policy opportunities and contributes to recent tools aimed at reducing low-value care. High-consensus domains, including training, patient safety, and sustainability, offer immediate entry points for coalition-building. On the contrary, areas of divergence require structured dialogue and iterative policy learning among Frances fragmented governance structures to translate stakeholder alignment into systematic deprescribing implementation.

BackgroundHypertension (HTN) constitutes a major and growing public health challenge in South Africa, a setting where HIV prevalence also remains high. Despite this dual burden, longitudinal evidence describing how individuals move through the HTN care cascade particularly comparing people living with HIV (PLHIV) and people not living with HIV (PNLHIV) remains limited. Understanding patterns of progression and regression across the cascade is essential to inform health system strategies for integrated chronic disease management. Methods and FindingsWe conducted a longitudinal secondary analysis using data collected from the iHEART-SA trial, which was implemented across nine public primary healthcare clinics in Johannesburg between August 2022 and May 2024. with follow-up through May 2025. Adults ([&ge;]18 years) with a known HIV status and a completed medical file review were included. Progression and regression were assessed across the HTN care cascade. Of 23 855 participants, 78.5% were PLHIV (median age 42 years, IQR 36-49; 69% female). Overall, 34.4% had high blood pressure (BP), with prevalence higher among PNLHIV than PLHIV (53.5% vs 29.3%; p<0.001). Along the HTN care cascade, PLHIV were substantially more likely to remain undiagnosed compared with PNLHIV (aRR 3.40; 95% CI 3.12-3.71). Among those treated, PLHIV were less likely to achieve BP control (aRR 0.83; 95% CI 0.75-0.91). During follow-up, PLHIV experienced higher rates of cascade regression, including regression to untreated HTN (29% vs 19%; aRR 1.51; 95% CI 1.35-1.70) and from controlled to uncontrolled BP (aRR 1.12; 95% CI 1.05-1.18). ConclusionsDespite frequent health-system contact, PLHIV had lower HTN diagnosis and higher regression, including treatment discontinuation and loss of BP control, underscoring persistent gaps in longitudinal HTN management within HIV programmes and the need for integrated and targeted chronic care models that ensure treatment continuity and sustained control.

PurposeThe objective of this study was to identify predictors of statin adherence in the primary and secondary prevention of CVD among patients in the first two years after the date of first prescription using real-world data. MethodsThe Electronic Practice Based Research Network Linked Dataset was used in this study. Statin adherence was calculated using a modified proportion of days covered (PDC) formula. Individuals with PDC [&ge;] 80% during the two years of observation period were considered as adherent. All analyses were performed with R software. Descriptive and multivariate logistic regression analyses were performed. Sensitivity analysis was performed using the Akaike Information Criterion model selection method. ResultsOverall, 3,432 patients accounting for 57,227 visits met the selection criteria. The mean PDC was 91.6% ({+/-}22.2%), and 72.0% of the patients were adherent to statins (PDC [&ge;] 80%) in the first two years after the date of first prescription. After adjusting for all other variables, statin adherence was positively associated with age (AOR 1.7, 95% CI 1.4 - 2.0), SEIFA index (AOR 1.8, 95% CI 1.2 - 2.6), polypharmacy (AOR 1.8, 95% CI 1.3 - 2.5) and comorbidities (AOR 1.4, 95% CI 1.1 - 1.7), and negatively associated with the number of statin types (AOR 0.6, 95% CI 0.5 - 0.9) and smoking status (AOR 0.7, 95% CI 0.6 - 0.9). The sensitivity analysis showed similar results as the regression model. ConclusionsStatin adherence is influenced by an aging, multimorbid population, who are exposed to polypharmacy, multiple statin options and socioeconomic diversity. Key pointsO_LIAdherence in the first two years after the first date of statin prescription was measured as proportion of days covered (PDC) C_LIO_LIThe mean PDC was 91.6% ({+/-}22.2%) C_LIO_LI72.0% of the patients were adherent to statins, with PDC [&ge;] 80% C_LIO_LIStatin adherence was positively associated with age, area-based social advantage and disadvantage index, polypharmacy and comorbidities C_LIO_LIStatin adherence was negatively associated with the number of statin types prescribed to the patients and the smoking status of patients C_LI Plain Language SummaryThe objective of this study was to identify predictors of statin adherence among patients in the first two years after the date of first prescription using real-world data. The dataset used was the Electronic Practice Based Research Network Linked Dataset. Statin adherence was calculated using proportion of days covered (PDC). A PDC [&ge;] 80% during the two years of observation period were considered as adherent. Overall, 3,432 patients were eligible for this study, and 72.0% of them were adherent to statins in the first two years after the date of first prescription. Statin adherence was positively associated with age, area-based social advantage and disadvantage index, number of medicines taken by the patient and number of chronic conditions that the patient suffered. Moreover, statin adherence was negatively associated with the number of statin types prescribed to the patients and smoking status of patients.

Introduction: Neurodegenerative diseases (NDDs) including Alzheimer's disease (AD), Parkinson's disease (PD), multiple sclerosis (MS), amyotrophic lateral sclerosis (ALS), and non-AD dementias share chronic neuroinflammatory mechanisms that contribute to neuronal injury and disease progression. While anti-inflammatory therapies (AITs) are associated with reduced neurodegenerative disease risk, knowledge regarding the impact of biological sex and treatment duration across multiple NDDs remains limited. Methods: We conducted a retrospective cohort analysis using a large propensity-score-matched population (n = 190,308; 95,154 treated vs 95,154 untreated) to evaluate associations between long-term AIT exposure and incidence of major NDDs. Disease-specific and combined outcomes were assessed across drug classes (NSAIDs, corticosteroids, immunomodulators), sex, age, and therapy duration. Results: AIT exposure was associated with a significantly lower risk of developing any NDD (RR = 0.47, 95% CI 0.43-0.48, p < .0001) and was equally effective in both sexes. Risk reduction was observed for each individual disease: AD (RR = 0.40), non-AD dementia (RR = 0.51), PD (RR = 0.43), MS (RR = 0.25), and ALS (RR = 0.48). Among drug classes, immunomodulators conferred the largest reduction (RR = 0.19), followed by corticosteroids (RR = 0.41) and NSAIDs (RR = 0.42). Duration analyses revealed a graded benefit, with RR declining from 0.94 (<1 year) to 0.25 (>6 years). Risk reduction was strongest in older participants (75-79 years). Discussion: Chronic use of anti-inflammatory or immunomodulatory therapies was associated with substantially reduced incidence of multiple neurodegenerative diseases in both sexes. The strongest effects were observed with immunomodulator use and prolonged therapy duration, suggesting that sustained modulation of systemic inflammation confers broad neuroprotective effects in both sexes. These findings highlight the potential of targeting immune-inflammatory pathways for neurodegenerative disease prevention and can inform prospective mechanistic and interventional studies.

BackgroundGenetic risk scores (GRS) for type 1 diabetes (T1D) have been developed primarily in European populations, limiting their generalisability across ancestries. Indians differ from Europeans in clinical characteristics of T1D and overall genetic architecture, yet systematic evaluation of T1D GRS performance in multi-regional Indian cohorts is lacking. MethodsThe study included 597 T1D patients and 3347 non-diabetic controls from different regions in India. Genotyping, imputation, quality control analysis, and construction of the 67-SNPs T1D GRS were performed using standardised pipelines. Discriminative performance was assessed using Receiver Operative Curve-Area under Curve (ROC-AUC) analysis, and optimal thresholds were derived using Youdens index. HLA-DQ diplotype frequencies were compared, and association analysis was conducted using multivariable logistic regression. FindingsT1D GRS showed consistent discriminative performance across Indian cohorts [ROC-AUC=0.84 (range=0{middle dot}78-0{middle dot}87)], supporting its comprehensive use for T1D classification in India. Notably, its performance was lower in islet cell autoantibody (IA) negative compared with IA positive T1D patients (ROC-AUC, 0{middle dot}75 vs 0{middle dot}85) and in adult-onset than in childhood-onset patients (0{middle dot}74 vs 0{middle dot}84). We observed a lower frequency of protective HLA-DQ diplotypes and a strong association of HLA-DQ81 containing diplotypes in childhood-onset T1D. Application of an India-specific T1D GRS score improved the sensitivity than the European cut-off. InterpretationT1D GRS is a valuable unified diagnostic tool in Indians, but its performance varies by islet cell autoantibody status and age at onset, likely reflecting population-specific HLA architecture. European-derived T1D GRS thresholds under-classify the genetic risk, highlighting the importance of ancestry-aware optimisation in Indians. FundingCDRC grant CDRC202111026 and CSIR Intramural Grant P50. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSPrevious studies have shown that a 67-SNPs T1D genetic risk score (GRS) can distinguish T1D patients from non-diabetic controls and other forms of diabetes, but its performance varies across ancestries. Islet cell autoantibodies (IA) have important diagnostic value for classifying type 1 diabetes (T1D). However, their prevalence in India varies widely, with up to one-quarter of patients testing negative, limiting their clinical utility. Evidence supporting the use of the T1D GRS in India, combined with IA antibodies status is limited to a single cohort representing one linguistic group. The applicability of T1D GRS across multi-centric clinical settings has not been systematically evaluated. Added value of this studyThis study validates the 67-SNPs T1D GRS across multiple Indian cohorts representing major linguistic groups, supporting its use as a unified diagnostic tool. Differences in T1DGRS performance between childhood-and adult-onset T1D are linked to enrichment of protective HLA-DQ diplotypes in adult-onset disease, providing genetic insight into disease heterogeneity. The study also demonstrates that European-derived GRS thresholds systematically under-classify genetic risk in Indians and the population-specific threshold is essential. Implications of all the available evidenceThe European-derived T1D GRS can be applied across Indian clinical settings with consistent discriminative performance. However, its utility is influenced by islet cell autoantibody status and the age at onset of disease. Ancestry-aware threshold optimisation substantially improves diagnostic accuracy and is essential for equitable implementation of T1D GRS in Indians. Larger studies are needed to identify population-specific risk variants and further refine genetic tools for clinical diagnosis.

ObjectiveThe objective of this study was to explore the predictors of statin intolerance in the primary and secondary prevention of CVD among patients in the first two years after the date of first prescription using real-world data. MethodsThis study used the Electronic Practice Based Research Network Linked Dataset. An algorithm, which considered the muscle symptoms and creatinine kinase of patients, was used to identify statin intolerant patients. The R software was used for all analyses. Descriptive and multivariate logistic regression analyses were performed along with sensitivity analysis which was done using the Akaike Information Criterion model selection method. ResultsOverall, 4,016 patients accounting for 60,873 visits met the selection criteria. About 3.5% of the patients were statin intolerant. After adjusting for all other variables, statin intolerance was positively associated with gender (AOR 1.5, 95% CI 1.0 - 2.2), SEIFA index (AOR 3.8, 95% CI 2.3 - 6.7), employment status (AOR 2.4, 95% CI 1.1 - 5.7), and comorbidities (AOR 7.0, 95% CI 2.2 - 19.0). A similar direction of associations was seen for the exposures of the model from the sensitivity analysis and the regression model. However, since the unrecorded employment status showed a positive association, the sensitivity analysis suggests that the relationship may be influenced by residual confounding or information bias, indicating that this finding should be interpreted with caution. ConclusionStatin intolerance within the diverse community represented in the dataset is driven by gender, employment status, area-based social advantage and disadvantage index, and comorbidities.