Obesity, type 2 diabetes mellitus and chronic kidney disease (CKD) are highly prevalent conditions that frequently coexist and result in an excess burden of cardiovascular disease (CVD), premature death and health-care resource utilization. The concept of cardiovascular-kidney-metabolic (CKM) syndrome highlights the overlap of pathophysiological mechanisms that underlie obesity, diabetes mellitus and CKD and, together with adverse socioecological factors, amplify CVD risk. This framework encourages a holistic approach that recognizes the interconnectedness between metabolic factors, CKD and CVD, and the importance of screening for these factors at a population level to identify windows for CVD prevention across the lifespan. CKD is a key risk factor, mediator and therapeutic target to reduce CVD burden. The approach to using guideline-directed medical therapies for CKM syndrome is facilitated by assessment of absolute risk using validated CVD calculators, enabling therapy to be tailored to match absolute risk for maximal net benefit. In addition, screening for adverse social drivers of health is necessary to identify structural barriers to optimal care and move towards a multidisciplinary approach to ensure alignment between healthy lifestyle, risk factor control and guideline-directed medical therapies for all individuals living with CKM syndrome.

The global prevalence of diabetic retinopathy (DR) is increasing in parallel with the rising burden of diabetes, posing a substantial public health challenge. Current automated DR screening systems often lack lesion-level interpretable, robustness against class imbalance, and reliable uncertainty estimation, limiting their applicability in real-world clinical settings. The study suggests a clinical-guided deep learning framework of diabetic retinopathy (CG-DRNet) that considers lesion-conscious attention, adversarial data augmentation, and Bayesian uncertainty measurement to achieve reliable and explainable DR severity detection with objective to allow early-stage detection, particularly mild nonproliferative diabetic retinopathy (NPDR), and reciprocate clinical diagnostic procedures. The proposed framework uses a multi-task deep learning framework and lesion-aware attention network to explicitly predict microaneurysms, hemorrhages, exudates, and neovascularization. The system consists of a conditional generative adversarial network (CWGAN-GP) that is employed to overcome extreme imbalance in classes by generating clinically realistic images of minority classes of the fundus. Monte Carlo dropout is used to model Bayesian uncertainty to estimate predictive confidence, and an uncertainty-informed semi-supervised strategy of learning is used to enhance data efficiency. Evaluation of the framework is carried out on publicly available fundus image datasets APTOS 2019, Messidor-2 and Clinical metadata with the use of PyTorch 2.0.1. The proposed CG-DRNet reached 93.8% accuracy on APTOS 2019 and 91.2% on Messidor-2 with only 2.6% difference between generalization and the original model, macro F1-score of 0.891, quadratic weighted kappa of 0.912, referable DR detection AUC of 0.963 and expected calibration error of 0.034. The framework was shown to have 84.7% sensitivity when detecting Grade 2 + with 67 ms inference time and therefore has been shown to be viable in clinical use.

Arteriovenous fistula (AVF) is the preferred vascular access for hemodialysis; however, its patency is limited, particularly in patients with diabetes mellitus (DM). This study aimed to obtain exploratory data on whether changes in the venous transcriptome are present at the time of AVF creation in patients with DM and whether these changes are related to the graft prognosis.

We conducted prospective transcriptome analyses using venous samples obtained during AVF creation from 22 patients (12 with DM and 10 without DM). RNA sequencing was performed, and clinical outcomes, including primary patency, were tracked for one year.

AVF patency was significantly lower in the DM group (median patency: 134 vs. 365 days, p＜0.05). Transcriptome profiling identified 285 differentially expressed genes, including those related to extracellular matrix organization, mitochondrial electron transport, TGF-β signaling, and the unfolded protein response. A network analysis highlighted hub genes, including MRPL27, MRPL23, and MRPL1, as potential biomarkers. A Cox regression analysis identified genes associated with the AVF prognosis, including PER3, SERINC2, COMMD10, TTC4, FKBP2, FN3KRP, KIF24, SNX32, MOB3C, SUV39H1, and TIGD6. Notably, a high COMMD10 expression, a core component of the commander complex, was associated with a shortened patency in patients with DM.

Our findings demonstrate that DM is associated with distinct transcriptomic alterations in the access veins at the time of AVF creation. This integrative approach provides novel insights into the molecular basis of DM-related AVF failure and the potential to identify novel therapeutic targets.

Urolithiasis in renal allografts is rare, but large or complex stones present unique surgical challenges due to altered pelvic anatomy and proximity to vascular and visceral structures. Percutaneous nephrolithotomy (PCNL) is the gold-standard treatment for staghorn calculi but is technically demanding in transplanted kidneys. This complexity is amplified in recipients of simultaneous pancreas-kidney (SPK) transplants, where both grafts drain into the bladder. We describe a man in his 40s with type 1 diabetes and end-stage renal disease who underwent SPK transplantation in 2018. He presented with intermittent haematuria, and imaging demonstrated an 18 mm partial staghorn calculus in the transplanted kidney located in the left iliac fossa. Antegrade access was obtained under fluoroscopic guidance, and the stone was fragmented. Stone fragments were extracted, achieving complete clearance. This case highlights the potential value of tailored access planning, image guidance and multidisciplinary involvement when considering stone clearance in anatomically complex transplant recipients.

Using two-sample Mendelian randomization (MR) based on GWAS data from the IEU OpenGWAS project and a retrospective clinical cohort, this study investigated risk factors for progression from type 2 diabetes mellitus (T2DM) to end-stage renal disease (ESRD) and developed a predictive model. The T2DM GWAS dataset (ebi-a-GCST010118; 2020) included 433,540 individuals (77,418 cases and 356,122 controls). Multivariable MR, with inverse variance weighted as the primary method, was used to evaluate the causal effects of metabolic and hematologic traits on ESRD, while MR-Egger and Cochran's Q test assessed pleiotropy and heterogeneity. MR-PRESSO was used for outlier removal. In parallel, 875 patients with T2DM were analyzed using univariable and multivariable logistic regression; 140 patients (16%) progressed to ESRD. MR showed that elevated body mass index (BMI) was a causal risk factor, whereas higher hematocrit was protective. In the clinical cohort, BMI, diastolic blood pressure, and creatinine were identified as independent risk factors, while albumin and hematocrit were protective. Sensitivity analyses showed no significant horizontal pleiotropy, and all instrumental variables were sufficiently strong (F-statistics >10). A logistic regression-based nomogram achieved an AUC of 0.88 (95% CI: 0.85-0.91) with good calibration and outperformed XGBoost, Random Forest, and support vector machine models. Elevated BMI and lower hematocrit increase ESRD risk in T2DM, and the nomogram may support early risk stratification and precision intervention.

To estimate the magnitude of reduction in major adverse cardiovascular events (MACE) that would be observed in clinical practice from adding tirzepatide to standard of care treatment.

Population based cohort study, using a design, data, and analytical approach previously benchmarked against randomised trials.

Two national US claims databases, May 2022 to May 2025.

52 971 participants aged ≥40 years with type 2 diabetes and established atherosclerotic cardiovascular disease who initiated tirzepatide (n=35 353) or sitagliptin (n=17 618), a cardiovascular outcome neutral comparator serving as a placebo proxy. Baseline characteristics were well balanced between treatment groups after propensity score overlap weighting.

The main outcome, MACE, was a composite of myocardial infarction, stroke, and all cause mortality and its individual components. Follow-up started the day after treatment initiation and continued until occurrence of the outcome, disenrollment from the health plan, treatment discontinuation or switching, or one year. Safety outcomes included infections requiring hospital admission and infection related mortality. Two negative control outcomes, lumbar radiculopathy and abdominal hernia, were analysed to assess residual confounding.

At one year, the weighted one year risk of MACE was 2.9% (95% confidence interval (CI) 2.5% to 3.4%) in the tirzepatide group and 4.4% (3.8% to 4.9%) in the sitagliptin group (risk difference -1.4%, 95% CI -2.1% to -0.7%; number needed to treat (NNT)=70), corresponding to a hazard ratio of 0.68 (95% CI 0.58 to 0.80). For individual MACE components, tirzepatide was associated with a lower hazard for myocardial infarction (hazard ratio 0.67, 0.52 to 0.87; NNT=130), whereas ischaemic stroke showed no meaningful difference (0.91, 0.64 to 1.28; NNT 2500). Infections requiring hospital admission were lower with tirzepatide (0.64, 0.55 to 0.75; NNT=48), as was infection related mortality (0.40, 0.26 to 0.61; NNT=200) and all cause mortality (0.55, 0.42 to 0.72; NNT=122). Negative control outcomes showed no association.

In this cohort study using an approach benchmarked against randomised trials, initiating tirzepatide reduced the risk of MACE compared with a placebo proxy among people with type 2 diabetes and established atherosclerotic cardiovascular disease. Reductions in infection related events suggest broader non-atherosclerotic biological mechanisms may contribute to the observed benefit. This study shows how trial-anchored evidence from clinical practice can estimate the expected cardiovascular benefit of initiating tirzepatide beyond standard background treatment and inform shared decision making.

ClinicalTrials.gov NCT07203677.

To investigate the behavioural and social determinants of type 2 diabetes mellitus (T2DM) self-care adherence in South Ethiopia using the integrated health belief model (HBM) and health-related quality-of-life (HRQoL) frameworks.

A cross-sectional study.

Three public hospitals in South Ethiopia: Wolaita Sodo University Comprehensive Hospital, Humbo Primary Hospital and Boditi Primary Hospital.

404 systematically sampled adults aged 18-60 years with a confirmed diagnosis of T2DM who had been attending follow-up clinics for at least 12 months. Exclusion criteria included newly diagnosed T2DM, pregnancy, severe comorbidities or critical illness and unwillingness to participate.

The primary outcome was adherence to diabetes self-care, assessed using the Summary of Diabetes Self-Care Activities scale across five domains: diet, physical activity, medication intake, blood glucose monitoring and foot care. Good adherence was defined as engagement in recommended behaviours on ≥50% of days per week. Secondary outcomes included socio-demographic factors, clinical variables, HBM constructs (perceived susceptibility, severity, benefits, barriers, cues to action and self-efficacy) and HRQoL domains (physical, psychological, social and environmental).

Of 404 participants, 58.4% demonstrated good adherence. In multivariable analysis, insulin-only treatment (AOR=3.0; p<0.001), having comorbidities (AOR=2.02; p=0.007) and poor glycaemic control (AOR=3.6; p=0.003) were positively associated with adherence. Factors associated with poor adherence included low income (AOR=0.18; p=0.002), living alone (AOR=0.19; p=0.012), low self-efficacy (AOR=0.18; p<0.001) and poor psychological health (AOR=0.53; p=0.024).

The findings challenge the direct application of standard behavioural models in low-resource settings. Structured factors, such as poverty, can overwhelm psychological mechanisms. Effective interventions must integrate economic support with psychological care to improve self-care adherence.

Diabetes mellitus (DM) is associated with negative psychological conditions, specifically burnout, in cases where there is less glycemic control and longer illness time. The aim of this study was to adapt and validate the Diabetes Burnout Scale [DBS, Escala do Burnout na Diabetes (EBD)] into European Portuguese, as an evaluation measure tailored to the Portuguese context.

The scale was translated, retranslated and adapted. This study resorted to online and in-person collection of a convenience sample of people with DM. Reliability tests and convergent validation tests were performed, using the EQ-5D-5L and Problem Areas in Diabetes Scale 5 (PAID-5) as reference. Factor structure was evaluated using fit and invariance tests. Associations between the total score of the scale and variables like the respondents' most recent glycated hemoglobin (HbA1c) and socioeconomic index were analyzed.

A total of 1070 people with DM participated, 50.6% male and 49.3% female, with an average age of 56.0 ± 15.7 years and an average time since diagnosis of 20 ± 12.3 years. A three-factor structure was ascertained with a good fit: exhaustion, detachment and loss of control - invariant by sex and DM type. The internal consistency, as given by Cronbach's Alpha, was 0.885. Spearman's correlation showed the relation between EBD total score and EQ-5D-5L utility index (ρ = -0.382, p < 0.001), PAID-5 total score (ρ = 0.638, p < 0.001), and most recent HbA1c (ρ = 0.295, p < 0.001).

The EBD scale was successfully adapted and validated for European Portuguese.

Patients with myasthenia gravis (MG) are frequently associated with other autoimmune diseases. However, the temporal relationship between autoimmune diseases and MG remains unclear. This study aimed to evaluate the rates and temporal patterns of autoimmune diseases during the 10 years preceding MG diagnosis.

This retrospective population-based cohort study analyzed claims data from the Korean National Health Insurance Service between 2010 and 2021 and included individuals aged ≥20 years. MG was defined using the International Classification of Diseases, 10th Revision (ICD-10) code (G70.0) and Rare Intractable Disease registration (V012). Each MG case was matched with 10 controls by age, sex, and index year. Outcomes were autoimmune thyroid disease (AITD), systemic lupus erythematosus (SLE), seropositive rheumatoid arthritis (SRA), Sjögren syndrome (SjS), psoriasis, type 1 diabetes mellitus (T1DM), Crohn disease, and ulcerative colitis occurring during the 10 years before the index year. Rate ratios (RRs) and 95% CIs were estimated using Poisson regression models for 0-2, 2-5, and 5-10 years before the index year.

A total of 8,355 patients with MG and 83,550 matched controls were included. The mean age (SD) was 53.7 (16.0) years, and 44.1% were male. Patients with MG had a higher rate of any autoimmune disease during 10 years before diagnosis than controls (RR 2.12, 95% CI 1.97-2.28), with the highest rates in 0-2 years before diagnosis (RR 4.27, 95% CI 3.78-4.83). SLE (RR 4.87, 95% CI 2.71-8.77), SjS (RR 4.75, 95% CI 3.01-7.50), AITD (RR 3.66, 95% CI 3.29-4.07), and SRA (RR 2.45, 95% CI 1.89-3.19) showed the strongest associations. Psoriasis (RR 1.68, 95% CI 1.25-2.25) and T1DM (RR 2.03, 95% CI 1.52-2.71) were associated with MG only within 0-2 years before diagnosis, whereas Crohn disease and ulcerative colitis were not associated.

Autoimmune diseases were more frequent in the years preceding MG diagnosis than in controls, particularly within 2 years before diagnosis. Strong associations were observed for SLE, SjS, AITD, and SRA. However, these findings should be interpreted with caution because of limitations of administrative claims data.

This study examined changes in body composition and bone mineral density (BMD) over 12 months in people with obesity and type 1 diabetes (T1D) treated with a GLP-1 receptor agonist alone (GLP-1RA) or a dual glucose-dependent insulinotropic polypeptide (GIP/GLP-1RA).

This real-world observational study included 70 people with obesity and T1D treated with GLP-1RA alone or dual GIP/GLP-1RA. Dual-energy X-ray absorptiometry (DEXA) was used to quantify regional and total fat mass, lean mass, bone mineral content (BMC) and BMD at baseline and after 12 months of treatment. Overall changes were quantified, and changes stratified by percentage weight loss using repeated measures analysis.

Over 12 months body weight (-6.33%; 95% CI: -7.92, -4.73; p < 0.001), HbA1c (-0.48%; 95% CI: -0.74, -0.22; p < 0.001), total tissue fat (-1.42%; 95% CI: -2.47, -0.36; p = 0.009), fat mass (-5.90%; 95% CI: -10.50, -1.57; p = 0.001), and lean mass (-1.75%; 95% CI: -3.50, -0.48; p = 0.005) decreased, while total BMC and BMD remained unchanged. Total lean mass loss was associated with body weight loss (R² = 0.36, p < 0.001).

In people with obesity and T1D, 12-month GLP-1RA alone or dual GIP/GLP-1RA therapy resulted in clinically meaningful weight loss, improved glycaemic control, preferential fat mass reduction, modest lean mass loss, and preservation of total BMD. People achieving > 10% weight loss derived the greatest metabolic benefit without compromising bone health, although the loss of lean mass was greater.