Diabetes affects 537 million people worldwide, with type 2 diabetes (T2D) estimated to account for most cases. Type 1 diabetes (T1D), latent autoimmune diabetes in adults (LADA) and other specific types due to other causes remain under-recognised, especially LADA, given the absence of a standardised definition. In the province of Quebec (Canada), no population-based prevalence and incidence estimates are available for all diabetes phenotypes. Current medico-administrative algorithms fail to distinguish among diabetes subtypes, limiting accurate surveillance and effective prevention and clinical strategies.

This retrospective, longitudinal study (1997-2027) will be conducted in Quebec.Phase 1 will assess classification performance of the Corsenac et al. (2022) medico-administrative algorithms. Diagnostic performance metrics will be calculated per phenotype (T1D, T2D, LADA and others), using three independent subsamples as references in a first cohort (A1-A2-A3; n≈5200). It composed respectively of: (A1) self-reported diagnoses of T1D and LADA; (A2) diagnoses of T2D and other specific types due to others causes, confirmed by a physician; and (A3) general population respondents reporting diabetes status and phenotypes (if applicable). Subsamples are structured to capture the diversity and relative proportions of diabetes phenotypes, ensuring sufficient statistical power for population-based and subgroup analyses. All records (A1, A2, A3) will be probabilistically linked with medico-administrative and pharmaceutical claims from the Régie de l'assurance maladie du Québec (RAMQ) by the Institut de la statistique du Québec (ISQ). Machine learning methods will be then applied to refine algorithmic definitions for the four phenotypes (T1D, T2D, LADA, others).In phase 2, refined algorithms will be applied to a second medico-administrative population-based cohort, named C (n=50 000) to produce the first simultaneous prevalence and incidence estimates for the four phenotypes.Analyses will be restricted to individuals continuously covered by RAMQ's public drug insurance, which provides pharmaceutical data and covers 46% of the Quebec population. Calibration on population margins (phase 1) and standardised inverse probability weighting (phase 2) will reweight estimates (performance metrics in phase 1 and frequencies in phase 2) to represent the general Quebec population.

The different ethics boards of partner institutions approved the feasibility of the study. The study was registered on ClinicalTrials.gov, NCT06573905. Results will be disseminated through scientific and public health channels.

Diabetes has reached epidemic proportions in Pakistan. This study applied machine learning (ML) techniques to identify comorbidity-based and diabetic complications-based clusters in hospitalised patients with diabetes and examine their association with in-hospital mortality.

Retrospective cross-sectional study.

Aga Khan University Hospital, Pakistan.

Adult patients (≥18 years) with diabetes admitted between 2008 and 2021.

Diagnoses were extracted using International Classification of Diseases (ICD-9 and ICD-10) codes. Data was integrated from the Hospital Information Management Systems (HIMS). The K-Modes clustering algorithm was applied to categorical diagnostic data, with the optimal number of clusters determined using elbow curve and silhouette score analysis. Latent-Dirichlet Allocation and Term Frequency-Inverse Document Frequency were applied to identify frequent terms from each cluster followed by expert validation. Logistic regression was performed to assess the association between cluster membership and in-hospital mortality.

Among 78 271 patients, four clusters were identified with varying mortality risks: (1) cardio, tumour and tobacco (CTT), (2) renal complication cluster (RCC), (3) cardiovascular cluster (CVC) and (4) uncontrolled diabetes mellitus, hypertension, stroke and kidney (HSK). The within cluster mortality was highest in the RCC cluster (682; 18.1%), followed by CVC (543; 4.4%), HSK (1,379; 4%) and CTT (603; 2.2%). Compared with CTT, the unadjusted odds of in-hospital mortality were significantly higher in RCC (OR=9.9, 95% CI 8.9 to 11.2, p<0.001), CVC (OR=2.1, 95% CI 1.9 to 2.3, p<0.001) and HSK (OR=1.9, 95% CI 1.7 to 2.1, p<0.001).

Among hospitalised patients with diabetes, the RCC cluster demonstrated the highest mortality risk, comprising predominantly older patients with severe complications. These findings highlight the utility of unsupervised ML approaches for identifying high-risk clinical phenotypes and informing risk stratification in resource-constrained settings. Longitudinal studies are warranted to evaluate progression and long-term outcomes across clusters.

Sodium-glucose cotransporter 2 inhibitors (SGLT2i) reduce proteinuria in patients with diabetes mellitus and chronic kidney disease. However, their effect on vascular endothelial growth factor inhibitor-induced proteinuria remains unclear. This study evaluated the prophylactic effect of SGLT2i on bevacizumab-induced proteinuria in patients with hepatocellular carcinoma (HCC) treated with atezolizumab plus bevacizumab.

This multicenter retrospective study included patients with HCC who started therapy with atezolizumab plus bevacizumab between September 2020 and December 2023. The primary outcome was the time to exacerbation of proteinuria from baseline within 6 months after treatment initiation according to SGLT2i use. Secondary outcomes included the development of grade ≥2 proteinuria.

A total of 188 patients were included, of whom 29 received SGLT2i. No significant difference in the time to exacerbation of proteinuria was observed between the SGLT2i and non-SGLT2i groups considering the overall population (median: 157 vs. 116 days, p=0.95). Multivariate analysis identified diabetes with systolic blood pressure ≥130 mmHg as an independent risk factor for proteinuria exacerbation (hazard ratio=2.19, 95% confidence interval=1.18-4.06, p=0.013), whereas SGLT2i use was not significantly associated with proteinuria exacerbation. In patients with both diabetes and systolic blood pressure ≥130 mmHg, SGLT2i significantly prolonged the time to proteinuria exacerbation.

SGLT2i may suppress proteinuria progression only in high-risk patients with HCC complicated by diabetes and hypertension.

To analyse the temporal trend of stroke incidence from 2019 to 2024 in Macao and evaluate its relationship with hypertension (HTN) and type 2 diabetes mellitus (T2DM) management within a universal health coverage (UHC) system.

Retrospective observational study using routinely collected electronic health records.

Macao Health Bureau's primary care system, which provides free, publicly funded community health services to all residents.

Macao residents aged ≥15 years with a confirmed diagnosis of ischaemic or haemorrhagic stroke recorded in the Macao Health Bureau medical system between 1 January 2019 and 31 December 2024 (n=8265).

Age-standardised stroke incidence declined from 250.03 per 100 000 in 2019 to 219.95 per 100 000 in 2022, followed by a rebound in 2023-2024 which may partly reflect pandemic-related data entry delays. Over 88% of patients with pre-existing HTN or T2DM had documented healthcare follow-up in the year preceding their stroke. Stroke incidence among these high-risk patients declined and the interval from diagnosis to stroke onset lengthened significantly, yet a substantial stroke burden persisted.

High healthcare engagement was associated with improved risk monitoring and delayed stroke onset. However, the persistent stroke burden suggests that achieving high coverage alone is not sufficient-ongoing quality improvement in chronic disease management is essential to translate engagement into better outcomes.

Nintedanib (NIB), a small-molecule tyrosine kinase inhibitor (TKI), is approved for idiopathic pulmonary fibrosis (IPF) and systemic sclerosis-associated interstitial lung disease. Although nephrotoxicity is uncommon, cases of nephrotic syndrome (NS), acute kidney injury (AKI) and glomerular lesions including thrombotic microangiopathy (TMA) and anti-glomerular basement membrane (GBM) nephritis have been reported. However, the optimal management of NIB-associated glomerular disease remains undefined. We report a 69-year-old man with IPF, hypertension, diabetes and underlying chronic kidney disease who developed persistent NS and renal dysfunction 16 months after initiation of NIB. Kidney biopsy demonstrated glomerular endothelial injury with microangiopathic features, accompanied by secondary collapsing focal segmental glomerulosclerosis (FSGS) and background diabetic kidney disease. Despite discontinuation of NIB and intensification of renin-angiotensin system inhibition and mineralocorticoid receptor blockade, nephrotic-range proteinuria persisted. Subsequent initiation of the sodium-glucose cotransporter 2 inhibitor (SGLT2i) dapagliflozin was temporally associated with a gradual and sustained reduction in proteinuria, with partial remission achieved while preserving the estimated glomerular filtration rate. To our knowledge, this is the first report of NIB-associated glomerular endothelial injury with secondary collapsing FSGS in which SGLT2i initiation was temporally associated with sustained proteinuria reduction under concomitant supportive therapy. TKIs may induce both endothelial and podocyte injury and therapeutic options beyond drug withdrawal remain limited. In this context, SGLT2 inhibition may represent a potential adjunctive therapeutic strategy in selected cases with underlying chronic kidney disease and warrants further systematic evaluation.

The glycated hemoglobin ratio (HbA1c %) serves as the gold standard for diabetes diagnosis, but traditional detection methods require invasive blood testing. Although saliva holds promising noninvasive potential, the complex salivary matrix and the low abundance of salivary hemoglobin (Hb) and glycated hemoglobin (HbA1c) restrict the development of reliable immunoassays. Here, we present an HbA1c/Hb dual-detection lateral flow assay (LFA) platform for rapid and noninvasive quantification of salivary HbA1c %. The assay integrates two distinct capture strategies onto a single LFA strip: a streptavidin (SA)-biotin bridging system for HbA1c (T1 line) and a conventional double-antibody sandwich format for nonglycated Hb (T2 line). Consequently, our platform enables simultaneous and single-step measurement for the absolute concentrations of both Hb and HbA1c, facilitating the precise calculation of the HbA1c %. The analytical accuracy was validated against paired venous blood samples. Additionally, coupling with a low-cost, 3D-printed, and smartphone-based fluorescence reader, the system provides an economical and efficient point-of care testing solution, particularly for clinical preliminary screening and at-home self-testing.

The role of endogenous oestrogen exposure (EEE) in type 2 diabetes (T2D) remains understudied despite its potential importance. This study aimed to assess T2D incidence in women with different endogenous oestrogen durations.

At the initiation of the study, 6273 post-menarche women above 20 years were included. After applying the exclusion criteria, 3,411 women remained (2,754 premenopausal and 657 menopausal). Each woman's EEE was determined, and they were monitored for the incidence of T2D. Based on the EEE duration, hazard ratios (HRs) and 95% confidence intervals (CI) for the T2D event were reported using Cox proportional hazards regression models.

The mean age and menarcheal age (standard deviation) of participants were 39.3(12.5) and 13.5(1.5) years, respectively. Finally, 30.9% (1053) of the women developed diabetes (819 (29.7%) premenopausal and 234 (35.6%) menopausal). The age and BMI-adjusted model's findings indicated that, overall, the EEE z-score was inversely associated with T2D incidence in postmenarcheal women [HR 0.91, 95% CI 0.85-0.97], meaning that the risk of T2D decreased by 9% for every 1-SD increase in the EEE z-score. Furthermore, after full adjustment for potential confounders, the association remained statistically significant (HR = 0.90, 95% CI: 0.84-0.96).

The findings suggest that longer EEE duration may reduce the risk of T2D, emphasising the importance of reproductive history in health assessments.

Gestational diabetes mellitus (GDM) affects 1-in-7 pregnancies globally and is associated with significant short- and long-term health consequences. Although health behaviour change interventions can effectively reduce these risks, a significant implementation gap exists in translating this evidence into routine practice. Bump2Baby and Me (B2B&Me) was a mobile health (mHealth) coaching intervention provided to women at-risk of GDM from early pregnancy through to 1-year postpartum. B2B&Me Plus (B2B&Me+) aims to refine, implement and evaluate the implementation of this personalised intervention across 4 countries (Ireland, Spain, Poland and Norway) with differing health systems and population profiles.

This study employs a hybrid type 3 implementation-effectiveness design using a non-randomised ABA block approach within a longitudinal cohort. Participants will be screened using the Monash machine learning GDM screening tool (MMLGDST). During the intervention (Block B), women at risk of developing GDM will be offered access to a smartphone-based coaching application featuring 1:1 synchronous sessions, asynchronous text and video messaging along with a Bluetooth-enabled weighing scale for self-monitoring. Support continues from early pregnancy through to nine months postpartum. The study's primary objective is to evaluate reach, adoption, implementation and maintenance of the B2B&Me+ intervention programme when delivered within routine maternity care. Implementation success will be assessed using the RE-AIM framework, while secondary outcomes will assess intervention effectiveness. The study will examine population-level uptake at each site, evaluate the benefits and costs of implementation across varying contexts, and analyse how four different referral methods, randomised at the site level, affect uptake. In addition, a European implementation toolkit will be developed to provide health services with scalable strategies to bridge the evidence-to-practice gap.

This study will contribute to a growing literature on the implementation of a successfully trialled mHealth intervention in a real-world context. Understanding variation in both intervention and implementation success within a routine maternity care context across diverse settings will inform the development of an implementation toolkit to support health services in reducing the incidence of GDM and improving maternal and child health outcomes. This study was registered with ClinicalTrials.gov (NCT07189221) on 28 August 2025 (https://clinicaltrials.gov/study/NCT07189221?cond=diabetes).

Cardiometabolic diseases, including cardiovascular disease, type 2 diabetes mellitus (T2DM), obesity-related metabolic dysfunction, and hypertension, remain major causes of global morbidity and mortality. Beyond traditional risk factors, environmental exposure to toxic metals is increasingly recognized as a contributor to vascular and metabolic injury. Lead, cadmium, arsenic, and mercury are persistent toxicants that may accumulate in human tissues and interfere with essential trace-element homeostasis. This narrative review examines how toxic metal exposure disrupts the biological balance of iron, zinc, copper, and selenium, thereby weakening mitochondrial function, antioxidant defense, endothelial regulation, and metabolic stability. A central focus is ferroptosis, an iron-dependent form of regulated cell death driven by lipid peroxidation and failure of protective systems such as the selenium-GPX4-glutathione axis. Toxic metal-essential trace-element imbalance may create a pro-ferroptotic environment that promotes endothelial dysfunction, nitric oxide impairment, vascular stiffness, atherosclerotic plaque instability, myocardial ischemic vulnerability, insulin resistance, β-cell dysfunction, and cardiometabolic clustering. This review reframes heavy metal-associated cardiometabolic disease as a consequence of toxic metal-essential trace-element dyshomeostasis rather than direct toxicity alone. Clinically, this framework supports targeted exposure history, careful interpretation of metal and trace-element biomarkers, correction of documented deficiencies, and avoidance of indiscriminate supplementation. Future studies integrating exposomics, metallomics, ferroptosis biomarkers, and longitudinal cardiometabolic outcomes are needed to clarify causality and guide prevention.

To investigate the association between systemic arterial stiffness and choroidal vascular parameters in patients with type 2 diabetes (T2D) using optical coherence tomography angiography (OCTA).

This study includes 177 eyes from 95 patients with T2D underwent clinical assessment and wide-field OCTA imaging (24 × 20 mm, TowardPi BMizar). Vascular density in superficial capillary plexus, choriocapillaris, and Sattler's and Haller's layers, and three-dimensional choroidal parameters, including choroidal vessel volume (CVV), stromal volume (CSV), and choroidal vascularity index (CVI), were acquired based on a 12 × 12 mm fovea-centered grid. Systemic arterial stiffness was assessed using brachial-ankle pulse wave velocity (baPWV). Associations were analyzed using correlation and regression models, including age-adjusted and age-stratified models.

CVV and CSV showed significant negative correlations with age (p < 0.05) and baPWV (p < 0.05 in all regions except the central-nasal area). These reduction patterns were not observed in two-dimensional vascular parameters. These correlations lost statistical significance after adjusting for age. The age-stratified analysis revealed that baPWV was linear negatively associated with CVV and CSV in patients aged 30-50 years (p < 0.05 in most regions except the superior-temporal area), with maximum coefficients of - 0.14 and - 0.25, respectively.

CVV and CSV are associated with systemic arterial stiffness in patients with T2D, particularly among those aged 30-50 years, indicating that choroidal parameters can serve as valuable biomarkers of systemic vascular health.