Gait speed, a simple and reliable measure of physical function, has been associated with various health outcomes. However, limited evidence exists on the relationship between gait speed and diabetes mellitus (DM) risk among older adults in China.

We included 3,241 older adult participants from the 2011-2020 China Health and Retirement Longitudinal Study (CHARLS). Gait speed was assessed by a 4-meter walking test at baseline (2011-2012). Incident DM events were recorded during follow-up until 2020. Cox proportional hazards models were used to estimate hazard ratio (HR) and 95% confidence interval (95% CI) for the association between gait speed, including per 1-unit or 1-standard difference increase and tertile group, and DM risk, adjusting for potential confounders.

During a median follow-up of 9.0 years, 347 incident DM events were documented. In multivariable-adjusted analyses that adjusted for sociodemographic, lifestyle variables, and health status, compared to participants in the lowest tertile of gait speed (< 1.16 m/s), participants in the middle (1.16-1.51 m/s; adjusted HR: 0.791; 95% CI: 0.609-1.026) and highest (> 1.51 m/s; adjusted HR: 0.845; 95% CI: 0.647-1.102) tertile had a decreased risk of DM. Each per standard deviation increase in gait speed was associated with a 1.1% lower risk of DM (adjusted HR: 0.989; 95% CI: 0.885-1.106). In the restricted cubic spline regression, although a potential U-shaped pattern was observed, it was not statistically significant (P for non-linearity = 0.090).

Although faster gait speed showed a potential association with decreased risk of DM in older adults, the observed association did not reach statistical significance.

This study was developed and evaluated deep learning model for detecting chronic kidney disease (CKD) by retinal fundus images. This study included 42,963 clinical visits from 17,442 patients who underwent retinal fundus examination between October 19, 2006, and September 13, 2018, with estimated glomerular filtration rate (eGFR) measurements available within a 7-day interval of the imaging examination. We developed and compared three model configurations: using a single fundus image (Model A), combining a single image with demographic features (Model B), and integrating bilateral fundus images (Model C). We compared two base architectures, EfficientNet-B3 and EfficientNetV2-S, and evaluated the impact of different training strategies: a single model versus a 5-fold cross-validation (CV) ensemble. Model performance was assessed using the Area Under the Curve (AUC), sensitivity, specificity, Positive Predictive Value (PPV) and Negative Predictive Value (NPV). Among all evaluated models, the bilateral-image model (Model C) utilizing the EfficientNet-B3 architecture with a 5-fold CV ensemble strategy demonstrated the best overall performance, achieving an AUC of 0.868, with a sensitivity of 0.792 and a specificity of 0.788 on an independent test set. The performance of this ensemble strategy was statistically superior to its single-model counterpart trained on the full dataset (AUC 0.850, p < 0.001). Among single models, Model B yielded the highest AUC (0.857) and sensitivity (0.794), while Model C offered the highest specificity (0.799), revealing a clinical trade-off between the different approaches. Furthermore, benchmarking against the newer EfficientNetV2-S architecture did not yield a performance benefit in this study. The study exhibited a superior performance in detecting advanced chronic kidney disease in patients with diabetes mellitus through retinal fundus image.

We investigated the relationship between incidence of gastrointestinal tract cancers, metabolic dysfunction-associated steatotic liver disease (MASLD), and alcohol-related steatotic liver disease in diabetic population. A nationwide cohort of 2,616,828 individuals with diabetes under Korean National Health Insurance Service from 2015 to 2016 was divided into four subgroups: no steatosis (group 1), MASLD alone (group 2), MASLD with heavy alcohol intake (group 3), and alcoholic liver disease (group 4). We used fatty liver index to assess the probability of hepatic steatosis using cutoff scores of 30 and 60. We analyzed incidences of esophageal, stomach, colorectal, biliary, and pancreatic cancers until 2022. Compared with group 1 (reference), group 2 showed increased hazard ratios for stomach, colorectal, and biliary cancers, with a decreased hazard ratio for esophageal cancer (adjusted hazard ratio [95% confidence interval]: 1.10 [1.06-1.13], 1.13 [1.10-1.16], 1.10 [1.05-1.16], 0.88 [0.79-0.97], respectively). Probability of hepatic steatosis was positively correlated with all gastrointestinal tract cancers except esophageal cancer in non-drinkers, but only with stomach, colorectal, and biliary cancers in mild drinkers (p_trend < 0.001). In conclusion, MASLD increases gastrointestinal tract cancer risk, except esophageal cancer, in diabetic population. For non or mild drinkers, probability of hepatic steatosis serves as a predictor of gastrointestinal tract cancer risk.

Emerging evidence supports the role of type 2 diabetes (T2D) mellitus as a risk factor for cancer progression. In this study, we investigated and identified biomarkers related to diabetes and pancreatic ductal adenocarcinoma (PDAC) using systems biology to understand better the molecular landscape of PDAC and its connections with T2D.RNA-seq data related to blood samples of diabetes and pancreatic cancer were analyzed using bioinformatics tools in the Galaxy platform. After differential expression analysis using the DESeq2, the co-expression network associated with T2D and PDAC data was reconstructed using the WGCNA. Then, by visualizing the protein-protein interaction network in modules specifically related to T2D and PDAC, the key genes involved in these two diseases were identified, and their interaction network with long non-coding RNAs was reconstructed. Finally, the results of bioinformatics analysis were verified by qPCR in four groups, including T2D, PDAC, PDAC-T2D, and control groups.In this study, 1905 and 18,558 genes with significant differential expression were identified in the data of T2D and PDAC, respectively (|logFC| > 0.58, adj. p value < 0.05). The WGCNA showed 32 and 20 co-expression modules in diabetes and pancreatic cancer data, respectively. Among these, 303 genes were co-expressed, related to diabetes and pancreatic cancer. Based on the protein-protein interaction pattern, five hub genes were identified (using the CytoHubba Cytoscape plugin and the Maximal Clique Centrality (MCC) parameter). Finally, the co-expression network was reconstructed between these five genes and other lncRNAs. The qPCR showed that the expression of the CEBPZ gene was significantly increased in the blood samples of the diabetic (log2FC = 1.163, adj. p value = 0.0006), pancreatic cancer (log2FC = 3.22, adj. p value < 0.0001), and pancreatic cancer-diabetic (log2FC = 2.73, adj. p value < 0.0001) groups compared to the control group.For the first time, this study suggested that CEBPZ expression may serve as a diagnostic biomarker for assessing PDAC in individuals with T2D, given its differential expression in this specific cohort.

Myocardial infarction with non-obstructive coronary arteries (MINOCA) represents a heterogeneous clinical entity requiring angiography-assisted diagnostic confirmation.

This study proposes an innovative predictive algorithm for identifying MINOCA using non-invasive variables.

This retrospective cohort study included patients with acute myocardial infarction admitted to the Department of Cardiology at the Third Affiliated Hospital of Soochow University from June 2021 to October 2024. We systematically collected and analyzed baseline clinical data of demographics, imaging, and laboratory tests. Potential predictors were screened via Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis, followed by multivariate logistic modeling. Performance evaluation included discrimination metrics (receiver operating characteristic), calibration assessment, and decision curve analysis. A nomogram was created to visualize the multivariable prediction model, with internal validation achieved through bootstrap resampling.

613 patients were included, and 46 had MINOCA (7.50 %). Using LASSO for variable selection, five predictors were retained at log(λ) = -3.90: High-sensitivity cardiac troponin I, type of myocardial infarction, gender, age, and diabetes mellitus. In the subsequent multivariable logistic regression, all five were independently associated with MINOCA(P < 0.05). Among these predictors, high-sensitivity cardiac troponin I emerged as the best biomarker for MINOCA (AUC = 0.673, 95 % CI: 0.604-0.743). Finally, a multifactorial model was built with an AUC of 0.796 (95 % CI: 0.761 - 0.831). A dynamic calculator based on the multifactorial model was also deployed and is available in open-access format.

The model is efficacious in facilitating the accurate diagnosis of MINOCA, assisting clinicians with early identification of MINOCA, thereby improving patients' prognostic outcomes.

Undiagnosed ocular diseases and ocular complications from systemic diseases are common in primary care populations, and many can be detected through retinal imaging before symptoms develop. Asynchronous store-and-forward teleophthalmology offers a scalable way to integrate eye screening into primary care, yet its broader impact beyond diabetes and diabetic retinopathy detection remains underexplored.

This study evaluated the outcomes of asynchronous store-and-forward teleophthalmology screening in a primary care clinic, including detection and triage of ocular conditions and subsequent changes in eye and systemic management.

This was a retrospective cross-sectional analysis of the first 200 patients screened in a single primary care clinic in Elmhurst, New York, between January and May 2025. Each patient underwent nonmydriatic external and posterior eye imaging, which was reviewed by a remote reading eye clinician. Reports included eye findings, triage decisions (routine monitoring vs in-person referral), and management recommendations. Subsequent changes in care were extracted from primary care and in-person specialist consult notes.

Of 200 patients (mean age 62.1, SD 19.0, range 11-100 years), 71.5% (143/200, 95% CI 64.9-77.3) had positive eye findings, and 40% (80/200, 95% CI 33.5-46.9) were referred for in-person eye examinations. Only 8.8% (7/80, 95% CI 4.3-17.0) of referrals were for diabetic retinopathy; most were for glaucoma suspects, age-related macular degeneration, cataracts, and other eye diseases. Image quality was high, with 98.2% (390/397, 95% CI 96.4-99.1) of fundus images being at least partially adequate. Of the 32 patients with documented in-person eye follow-up, 87.5% (28/32) of evaluations confirmed the screening findings. Eye management changes were initiated in 11 patients, whereas systemic management changes occurred in 70 patients, including new prescriptions for Age-Related Eye Disease Study 2 supplements, antihypertensives, diabetes medications, and lipid-lowering agents.

Asynchronous teleophthalmology screening in a primary care setting effectively identified both ocular diseases and ocular complications from systemic diseases, leading to meaningful changes in eye and systemic management. The low rate of diabetic retinopathy among referrals highlights the broader diagnostic value of retinal imaging beyond diabetes management. This care model offers a scalable, high-yield strategy for proactive disease detection and interdisciplinary intervention at the primary care level.

The global burden of disease attributable to obesity continues to rise. The disease incidence is substantially higher in elderly populations, but how obesity affects disease risk across a lifetime is largely unknown. To quantify the long-term temporal impact of obesity, access to large-scale longitudinal cohorts spanning many decades would typically be required. However, these longitudinal studies are rare and may be heavily biased by the presence of unaccountable confounding. Here, we develop a method-time-resolved Mendelian randomization-to estimate the cumulative effect of body mass index on disease risk at different ages. Using the UK Biobank, we find strong age-varying patterns for type 2 diabetes mellitus, coronary artery disease, and atrial fibrillation, as well as for osteoarthritis. We demonstrate that some of the most notable temporal characteristics are sex specific, while other features are shared between sexes. Analyses suggest that these features can be manifestations of primary prevention strategies.

Hidradenitis suppurativa (HS) is a painful, chronic inflammatory skin disease associated with significant physical and psychosocial burden. Increasing evidence suggests HS is linked to systemic metabolic dysfunction, including components of metabolic syndrome such as obesity, hypertension, and hyperlipidemia. This study aimed to assess the prevalence of metabolic comorbidities in patients with HS using data from the National Ambulatory Medical Care Survey (NAMCS), a nationally representative dataset of U.S. outpatient visits from 2014 to 2019. We conducted a cross-sectional analysis comparing HS-related visits to age- and sex-matched non-HS visits, using multivariate logistic regression adjusted for demographic and clinical covariates. Among 1.8 million weighted HS-related visits, the most prevalent metabolic comorbidities were hypertension (15.7%), obesity (8.6%), and hyperlipidemia (7.4%). Compared to non-HS controls, HS visits had significantly higher odds of hypertension (adjusted odds ratio [aOR] 2.90; 95% confidence interval [CI]: 2.88-2.92), obesity (aOR 3.12; 3.10-3.15), and hyperlipidemia (aOR 1.76, 1.74-1.77). No significant association was found between HS and type 2 diabetes mellitus (T2DM) or cerebrovascular disease. Mechanistically, chronic systemic inflammation in HS, driven by elevated cytokines such as TNF-α, IL-6, and IL-17, may contribute to endothelial dysfunction and metabolic dysregulation. Obesity, which is commonly associated with HS, exacerbates the inflammatory state and promotes follicular occlusion, while hyperlipidemia may amplify inflammation through oxidative stress and impaired immune resolution. These findings underscore the importance of recognizing metabolic risk factors in patients with HS, particularly within the context of outpatient settings where early intervention is feasible. Early identification and management of these comorbidities may improve long-term health outcomes. Further longitudinal studies are warranted to clarify causal relationships and support the development of multidisciplinary screening and care strategies for this high-risk population.

Chronotype reflects an individual's circadian rhythm, which may be associated with lifestyle habits and metabolic profiles. A few studies have shown that disruptions in circadian rhythms may contribute to the pathogenesis of diabetic retinopathy. This prospective observational study aimed to investigate the association between lifestyle habits, including chronotype, and the incidence and progression of diabetic retinopathy.

The study participants were 731 Japanese outpatients with type 2 diabetes and no apparent history of cardiovascular disease. Lifestyle habits were assessed using questionnaires, including the Morningness-Eveningness Questionnaire (MEQ), to determine chronotype at baseline and at years 2 and/or 5. The composite endpoint of this study was the incidence and progression of diabetic retinopathy. The mean values of lifestyle factors were calculated by averaging the values from baseline to the date of endpoint onset or the end of the follow-up period. A Cox proportional hazards model was used to determine the association between lifestyle habits and the composite endpoint.

During the median follow-up period of 7.56 years (IQR 6.04-7.95), the composite endpoint was observed in 57 participants. Multivariate Cox models showed a significant negative association between the mean MEQ scores and the composite endpoint (HR 0.95; 95% CI 0.91, 0.99). In a sensitivity analysis in which the participants were divided into three groups based on mean MEQ scores, the 'more evening' chronotype group had a 2.29-fold higher risk (95% CI 1.15, 4.55) of the composite endpoint compared with the 'neither' group. Compared with the 'more morning' chronotype group, the more evening chronotype group had a 2.09-fold higher risk of the composite endpoint (95% CI 1.05, 4.13). Participants with the more evening chronotype experienced worsening glucose management over time compared with those with other chronotypes. However, a significant negative association between the mean MEQ scores and the composite endpoint was still observed after adjusting for the mean HbA_1c levels over time.

People with type 2 diabetes and an evening chronotype have worsened glucose management and are at a higher risk of incidence and/or progression of diabetic retinopathy.

University Hospital Medical Information Network Clinical Trials Registry UMIN000010932.

Type 2 diabetes mellitus is a major health burden in Fiji (19.3% prevalence). Evidence suggests increased physical activity improves glycaemic control and health outcomes; however, this remains unstudied in Fiji's population.

This study aimed to assess physical activity levels and explore its relationship with glycaemic control among diabetic patients.

A quantitative, cross-sectional pilot study was conducted at Samabula Health Center, Fiji, from September to November 2022 using convenience sampling for 174 adults with diabetes. The International Physical Activity Questionnaire, short form, assessed physical activity, whereas capillary fasting and random blood sugar assessed glycaemic control targets. Logistic regression analysed associations.

The study found 64% of participants were physically inactive, with females significantly less active than males (odds ratio (OR) = 0.49, 95% confidence interval (CI) = 0.25-0.98). Poor glycaemic control was common (75%), although adherence to lifestyle and pharmacological management plans were significantly associated with good control (OR = 2.37, 95% CI: 1.05-5.37). Increased physical activity levels were not significantly associated with meeting glycaemic control targets.

Despite clinic attendance, patients with diabetes remained inactive, had poor glycaemic control and were non-adherent to lifestyle and drug treatment. Contradicting previous evidence, physical activity was not associated with meeting glycaemic control targets, possibly reflecting point-of-care glucose variability compared to the gold-standard glycated hemoglobin measure (HbA1c), and cross-sectional study design limiting causal interpretation. Future research should investigate glycaemic control and physical activity barriers, especially among women, physician practices and test culturally adapted interventions. Fiji's National Wellness Policy and Non-Communicable Disease (NCD) Strategic Plan must consider strengthening diabetes management guidelines, clinician training and patient support to address systemic gaps.