Current research on the association between the Gamma-glutamyl transferase to high-density lipoprotein ratio (GHR) and the risk of prediabetes (pre-DM) remains scarce. This study aims to explore the potential link between GHR and the risk of progression from normoglycemia to pre-DM.

This retrospective cohort study included 8,168 individuals who voluntarily underwent health examinations at Shenzhen Dapeng New District Kuichong People's Hospital between January 2018 and December 2023. To assess the association between GHR and the risk of developing pre-DM, Cox proportional hazards regression models were employed. Cox proportional hazards regression model with cubic spline function was further utilized to investigate potential nonlinear association. Moreover, a competing risk Cox proportional hazards model was applied to account for the progression from normoglycemia to diabetes (DM) as a competing event in the progression from normoglycemia to pre-DM. Subgroup analyses and multiple sensitivity analyses were also performed to ensure the robustness of the findings.

Following multivariate adjustment, elevated GHR demonstrated a significant correlation with increased risk of progression from normoglycemia to pre-DM, showing a hazard ratio(HR) of 1.061 (95% CI: 1.028-1.095) for each 5-unit increment. A nonlinear relationship between them was identified, with an inflection point at a GHR value of 24.37. On the left side of the inflection point, the HR for the association between GHR (per 5-unit increase) and pre-DM risk was 1.394 (95% CI: 1.197, 1.623). Furthermore, the competing risk model revealed an HR of 1.05 (95% CI: 1.02, 1.09) for the association between GHR (per 5-unit increase) and pre-DM risk. Multiple sensitivity analyses confirmed the stability and reliability of these results.

This study demonstrates that elevated GHR exhibits both a positive and nonlinear relationship with the risk of progression from normoglycemia to pre-DM among Chinese adults. Maintaining GHR values below the threshold of 24.37, coupled with further reduction efforts, may serve as an effective strategy to minimize pre-DM risk.

To identify factors influencing hypoglycemia in patients with type 2 diabetes mellitus (T2DM) following gastrointestinal tumor surgery and construct a predictive model for assessing hypoglycemia risk.

We retrospectively collected data on 1280 patients with T2DM who underwent gastrointestinal tumor surgery and divided them into two groups-one for model building (n = 982) and another for validation (n = 298). We used multivariate logistic regression to develop a predictive model for hypoglycemia following gastrointestinal tumor surgery. The model's predictive performance was evaluated using the area under the receiver operating characteristic (ROC) curve, and its generalization ability was evaluated using the bootstrap test and the five-fold cross-validation test.

We identified hypoglycemia following gastrointestinal tumor surgery in 124 of 982 (12.6%) T2DM patients in the developmental cohort. Finally, five predictors, including duration of diabetes, operation duration, preoperative fasting time, preoperative hypoglycemic regimen (subcutaneous insulin injection), and glucose fluctuation on the day of surgery, were integrated into the predictive model. The performance of the hypoglycemia risk prediction model for patients with T2DM undergoing gastrointestinal tumor surgery was comprehensively evaluated. The model demonstrated an area under the ROC curve (AUC) of 0.837 (95% CI: 0.792-0.882), indicating a strong discriminative ability. Internal validation via five-fold cross-validation with bootstrap resampling revealed close approximation of the calibration curve to the ideal line, refining high consistency between predicted probabilities and actual hypoglycemia occurrence. Decision curve analysis (DCA) further supported its clinical utility, indicating value in clinical decision making for hypoglycemia risk stratification and preventive intervention selection.

The developed model exhibits high discriminative ability and good calibration. Following visualization (e.g., nomogram), it provides a clinical tool for healthcare providers to stratify hypoglycemia risk in T2DM patients undergoing gastrointestinal tumor surgery, enabling personalized perioperative glucose management and informed decision making to improve patient outcomes.

To estimate the economic burden of type 2 Diabetes Mellitus management and its influencing variables, on urban households in North India.

A community-based prospective, observational, cost-of-illness study was carried out from the patient's perspective, in urban Rohtak, Haryana. Probit, GLM (log link with gamma) and two-part regression techniques were used to model predictors of cost estimates.

Catastrophic health expenditure (CHE) due to T2DM management, was experienced by 10.14% of patients, and 19.59% faced impoverishment. The normalized poverty gap increased by 4.34% post-payment for T2DM as compared to pre-payment. The total cost was ₹17,113 per annum and out-of-pocket payments were ₹10,424. Direct medical cost formed the biggest portion i.e., 54.65% of total cost, whereas direct non-medical cost was 6.26%, and indirect cost was 39.09%. Majority of the total spending was attributed to drugs (42.39%). Insulin therapy, complications, socio-economic status and age at diagnosis were the most common significant predictors of economic burden.

The economic burden of diabetes in India is substantial, driven by both direct medical costs and indirect costs such as lost productivity. This high cost is responsible for significant CHE, impoverishment and deepening poverty gap. The study underscores the urgent need for comprehensive and cost-effective management strategies to mitigate the long-term economic impact of T2DM on urban households.

Patients with liver fibrosis and type 2 diabetes mellitus (T2DM) have an increased risk of cardiovascular events. However, long-term prognosis of liver fibrosis and T2DM after acute myocardial infarction (AMI) remain to be investigated. This study compared clinical characteristics and prognosis of AMI patients with T2DM and evidence of liver fibrosis. Patients were stratified into low, intermediate and high-risk for fibrosis, using serum-based non-invasive tests (NITs): Fibrosis-4 Index (FIB-4), Aspartate Aminotransferase to Platelet Ratio Index (APRI) and Non-alcoholic Fatty Liver Disease Fibrosis Score (NFS). The primary outcome was all-cause mortality, Kaplan-Meier curves were constructed for 5-year all-cause mortality. Cox regression analysis was used to determine the independent predictors of mortality, adjusting for confounders. Out of 3287 AMI patients, 1547 were stratified as high-risk by any NIT (mean follow-up duration 2.7 ± 2.3 years). A dose-response relationship was found with increasing mortality risk for higher APRI and NFS scores. High-risk FIB-4 also predicted mortality significantly (adjusted HR [aHR] 1.791, 95% CI 1.436-2.235, p < 0.001). High-risk FIB-4 and APRI independently predicted mortality regardless of T2DM status, while NFS only predicted mortality in T2DM patients. Following AMI, individuals stratified by FIB-4, APRI, NFS as high-risk for liver fibrosis were associated with excess long-term mortality (aHR 1.780, 95% CI 1.442-2.196, p < 0.001). Hence, readily available NITs may be beneficial in risk prognostication of AMI patients.

The prevalence of type 2 Diabetes Mellitus (T2DM) is increasing globally. Besides the traditional complications associated with T2DM, such as diabetic retinopathy, neuropathy, and kidney diseases, new complications including liver diseases, are increasingly being documented. This study aimed to examine serum biomarkers of liver injury and the related risk factors in T2DM patients at the Buea Regional Hospital, Cameroon. The sociodemographic, clinical, and behavioral characteristics of patients with T2DM were captured using a structured questionnaire. Anthropometric parameters were measured, and the Body Mass Index was calculated. Blood samples were analyzed for biomarkers of liver damage (ALT, AST, GGT, and ALP), considering a liver enzyme profile abnormal if it had more than 2 abnormally elevated values. Bivariate and multivariate logistic regressions analysis were used to identify risk factors, with significance set at P < 0.05. Among the 170 participants recruited, 75.9% were female. The median age was 62 years. Over half (52.9%) were married, 64.7% attended primary school and 55.3% were retired. Also, 59.4% had diabetes for over five years and all reported knowledge of diabetes care. About 73.3% adhered to their medication, 64.7% consumed alcohol, 28.8% smoked tobacco, with 22.4% engaged in physical activity and 77.6% with comorbidities. Blood sugar monitoring was practiced by 80%, with 66.5% having high blood pressure. Healthy weight individuals were 31.2% while 41.2% were obese and 56.5% had abnormal liver enzyme profiles. Five factors: duration of illness, physical inactivity, tobacco smoking, comorbidities and overweight/obesity were significantly (P < 0.05) associated with abnormal liver enzyme profile. Our findings identify risk factors linked to elevated liver enzyme markers indicating liver injury in T2DM patients.

This report aims to better define the rare adverse event of immune checkpoint inhibitor-associated diabetes mellitus(ICI-DM). We present 10 cases of patients including six of the patients had no prior history of diabetes, while four had varying degrees of pre-existing diabetes. Eight who received anti-PD-1 combination therapy, one who received anti-PD-1 monotherapy, and one who received dual anti-PD-1/CTLA-4 therapy. The mean time from initiation of immunotherapy to the onset of ICI-DM was 245.4 days (median, 149 days; range, 11 to 787 days). Diabetic ketoacidosis (DKA) occurred in 60% (6/10) of the patients, with a median fasting blood glucose level of 25.85 mmol/L (range, 14.76 to 38.23 mmol/L), and all had C-peptide levels below the normal range. Through a retrospective analysis of the clinical data of these 10 patients, we found that monitoring fasting blood glucose and HbA1c is crucial for patients undergoing or having undergone immunotherapy, as rapid pancreatic β-cell destruction can be observed in those who develop ICI-DM, potentially due to disruption of the PD-1/PD-L1 pathway.

To study the prevalence and characteristics of embolic stroke of undetermined source (ESUS) among Sudanese patients.

This cross-sectional study included 70 patients with recent ischemic strokes at the National Center for Neurological Sciences of Ibrahim Malik Hospital and Omdurman Teaching Hospital in Khartoum from November 2019 to March 2020. Characteristics of ESUS patients were analyzed and compared with stroke of determined source (SDS) patients. Demographics were analyzed, alongside clinical history. Imaging findings from computed tomography (CT) scans, carotid Doppler ultrasound, and echocardiographic evaluations were also assessed.

There were 18 (25.7%) cases in ESUS group and 52 (74.3%) cases in SDS group. ESUS group was significantly younger (44.3 ± 9.9 vs. 62.3 ± 17.7 years; p value < 0.001) with female predominance (66.7% vs. 46.2%; p value = 0.001) than SDS group. Risk factors such as hypertension (44.2%) and diabetes mellitus (DM) (35.6%) were prevalent in the SDS group. In electrocardiography (ECG) findings, left ventricular hypertrophy (LVH) (ESUS = 16.7% vs. SDS = 7.7%) and bradycardia (ESUS = 5.6% vs. SDS = 0%) were common among ESUS patients, while, atrial fibrillation (AF) (ESUS = 0% vs. SDS = 15.4%), ischemic changes (ESUS = 11.1% vs. SDS = 32.7%), and left bundle branch block (LBBB) (ESUS = 0% vs. SDS = 7.7%) were common among SDS patients. Normal echocardiography (64.7% vs. 17.3%; p value = 0.003) as well as carotid ultrasonography (US) findings (61.1% vs. 36.5%; p value = 0.002) were more prevalent in the ESUS group than in the SDS group. Multivariate analysis identified female gender (OR = 2.33; 95% CI: 1.76-7.16; p value = 0.016), normal findings on echocardiography (OR = 8.19; 95% CI: 2.76-24.32; p value 0.003), normal carotid Doppler ultrasound (OR = 5.0; 95% CI: 1.87-32.7; p value = 0.023), and normal ECG findings (OR = 3.5; 95% CI: 1.17-10.44; p value = 0.036) as significant predictors of ESUS.

The study underscores significant differences between ESUS and SDS patients, highlighting the need for tailored clinical approaches based on stroke classification.

Restless legs syndrome (RLS) is a common neuro-sensory disorder associated with various metabolic diseases, including diabetes mellitus and its complications. Observational studies suggest a potential association between RLS and diabetic complications; however, the causal relationship remains unclear due to confounding factors and reverse causation. This study aims to assess the causal relationship between RLS and diabetes, including its complications, using a bidirectional Mendelian randomization (MR) approach.

Genetic instruments derived from the latest genome-wide association study (GWAS) data for RLS, Type 1 diabetes, Type 2 diabetes, and diabetic complications (diabetic nephropathy, diabetic retinopathy, and diabetic neuropathy) were selected on the basis of MR assumptions. For causal inference, RLS was used as the exposure, whereas diabetes and its complications were considered outcomes. Reverse MR analyses were performed to assess potential causal effects of diabetes and its complications on RLS. Primary analysis used the inverse-variance weighted (IVW) method, with IVW radial and robust adjusted profile score (RAPS) as supplementary methods. Heterogeneity, pleiotropy, and robustness were assessed in both discovery (UK Biobank) and validation (FinnGen) datasets.

Forward MR analysis revealed a significant causal effect of RLS on the risk of diabetic nephropathy in both the discovery (IVW: OR = 1.049, p = 0.0238) and validation cohorts (IVW: OR = 1.067, p = 0.0028). However, no significant causal relationships were found for other primary outcomes, including Type 2 diabetes (IVW: OR = 1.011, 95% CI: 0.994-1.029) and Type 1 diabetes (IVW: OR = 0.995, 95% CI: 0.967-1.023). Sensitivity analyses showed no evidence of heterogeneity or horizontal pleiotropy. Reverse MR analysis did not demonstrate a causal effect of diabetes or its complications on RLS.

The findings suggest that RLS causally increases the risk of diabetic nephropathy. Early recognition and management of RLS in patients with diabetes may help prevent or delay the progression of nephropathy. Further studies are warranted to explore underlying mechanisms and potential clinical interventions.

Intensive systolic blood pressure (SBP) control reduces cardiovascular outcomes in hypertensive patients, but its effects in those with diabetes and prior stroke need further evidence. Among 4733 patients with elevated SBP enrolled in the ACCORD-BP (Action to Control Cardiovascular Risk in Diabetes-Blood Pressure) trial, this post-hoc analysis focused on 307 patients with type 2 diabetes and prior stroke to evaluate intensive versus standard SBP control. The primary outcome was major adverse cardiovascular events (MACE), a composite of cardiovascular death, nonfatal myocardial infarction, or nonfatal stroke. Inverse probability of treatment weighting (IPTW)-adjusted Kaplan-Meier and Cox regression analyses were performed with a 3-year conditional landmark. Multivariable Cox regression models and overlap weighting models were constructed in sensitivity analysis. In landmark analysis at the 3-year time point, intensive SBP control was associated with a significantly lower risk of MACE (hazard ratio [HR] 0.55, 95% CI, 0.32-0.95) using the IPTW Cox model. The associations remained consistent across multivariable Cox regression model (HR 0.53, 95% CI, 0.31-0.90) and overlap weighting model (HR 0.55, 95% CI, 0.32-0.94). Patients in the intensive SBP control group showed a trend toward lower recurrent stroke risk, though it was not statistically significant (HR 0.65, 95% CI, 0.30-1.37). Similar trends were observed in subgroup analyses. In conclusion, targeting an SBP below 120 mmHg in patients with diabetes and prior stroke is associated with a lower risk of major cardiovascular events without increasing the risk of recurrent stroke. Trial Registration: ClinicalTrials.gov identifier: NCT00000620.

Diabetes prevalence is rising and projected to affect 783 million globally by 2045. Effective diabetes self-management relies on diabetes knowledge, lifestyle modifications, and health care support; yet global health care workforce shortages hinder the provision of adequate care. Socially assistive technologies, such as robots or artificial intelligence, are proposed as potential solutions to meet rising demands.

To map the current literature on Socially Assistive Robots for diabetes care, identifying robotic types, barriers and enablers to use, and impact on health-related outcomes. A scoping review using Arskey and O'Malley's Framework was conducted, screening studies published between 2013 and 2025 across key databases and extracting data using COVIDENCE.

Twenty-two studies met the inclusion criteria, mostly focused on children with type 1 diabetes. Studies were largely conducted in Europe, cross-sectional, and with small sample sizes. Socially assistive robots demonstrated high acceptability, especially among younger children, positively affecting knowledge acquisition, self-management, and self-efficacy. Personalized interactions, gamified features, and emotional responsiveness were key enablers of engagement. However, engagement waned over time, particularly when participants' practical and emotional expectations were unmet. Barriers included usability challenges, privacy concerns, and lack of customization. Economic and sustainability evaluations were absent.

Despite growing evidence for robotics in diabetes care, research remains methodologically limited and focused primarily on younger populations. Future studies should include adults, employ multi-faceted robotics designs, and be adequately powered to assess acceptability and efficacy across diverse groups, facilitating broader application in diabetes care.