Women with previous gestational diabetes mellitus (GDM) have an increased risk of developing both type 1 and type 2 diabetes. However, predicting the risk on a personal level is challenging. Polygenic scores (PGSs), which capture an individual's genetic susceptibility to disease, may improve risk prediction. We aimed to examine the utility of PGSs for type 1 diabetes (T1D-PGS) and type 2 diabetes (T2D-PGS) to predict overt diabetes in women with previous GDM, with a median follow-up time of 30 years after index pregnancy.

We conducted an observational study including 370 women diagnosed with GDM between 1978 and 1996. Development of type 1 and type 2 diabetes was identified using national registry data comprising ICD-10 diagnosis codes on diabetes until 2019, combined with a glucose tolerance test performed in 2000-2002. The predictive ability of T1D-PGS and T2D-PGS and clinical risk factors during index pregnancy for type 1 and type 2 diabetes, including maternal age at delivery, pre-pregnancy BMI, fasting plasma glucose, insulin treatment and family history of diabetes, was evaluated using receiver operating characteristic area under the curve (AUC).

During a median follow-up of 30 years, 200 (54.1%) women were diagnosed with diabetes: 30 (8.1%) with type 1 diabetes, 157 (42.4%) with type 2 diabetes and 13 (3.5%) carried monogenic diabetes variants. The mean T1D-PGS was higher in women with type 1 diabetes compared with those without (13.6 vs 11.5, p<0.001), while the T2D-PGS was similar between women with and without type 2 diabetes (52.9 vs 52.8, p=0.16). The T1D-PGS and clinical risk factors during pregnancy were discriminative of type 1 diabetes with AUCs of 0.788 and 0.839, respectively, while a combined model yielded an AUC of 0.887. The T2D-PGS and clinical risk factors during pregnancy yielded AUCs of 0.539 and 0.745, respectively. The combined model had an AUC of 0.752.

In women with previous GDM, the T1D-PGS showed good predictive ability for the development of type 1 diabetes, especially when combined with clinical risk factors during pregnancy, and may have potential to guide targeted follow-up and early treatment interventions. The T2D-PGS showed no predictive ability for type 2 diabetes.

 Diabetic retinopathy (DR) is a major cause of avoidable vision loss, yet public awareness is low, hindering early detection and treatment. Many people living with diabetes are unaware of their risk for DR and the need for screening.

 To assess the knowledge, attitudes and practices of people living with diabetes regarding DR prevention.

 Ten primary health care clinics in the Maruleng sub-district in Limpopo province of South Africa.

 A cross-sectional study utilised a self-reported questionnaire with yes/no questions to measure knowledge and practices, and attitudes were assessed with a 5-point Likert scale. Scores above the median for knowledge, attitudes and practices were indicative of good knowledge and practices and positive attitudes.

 Almost two-thirds of participants (n = 255; 65.6%) were female. Approximately 268 participants (61.2%) knew that uncontrolled high blood sugar can lead to DR. The majority (n = 355; 86.1%) showed positive attitudes towards their eye health, while 216 (55.8%) had good practices towards DR prevention. Higher education and duration of diabetes were associated with good knowledge (adjusted odds ratio [AOR]: 2.2; 95% confidence interval [CI]: 1.3-3.9; p  0.05) and (AOR: 1.9; 95% CI: 1.2-2.9; p  0.05), respectively, while good knowledge about diabetic eye complications was associated with positive attitudes (AOR: 2.0; 95% CI: 1.3-3.1; p  0.05). Patients diagnosed with diabetes mellitus for more than five years were more likely to attend regular eye exams (AOR: 2.3; 95% CI: 1.5-3.6; p  0.05).

 Although participants had high median scores for knowledge and attitudes, important deficiencies were noted that could hinder effective DR screening.Contribution: These findings provide the baseline evidence on the need for ongoing patient education in primary care to enhance DR prevention.

Diabetic foot ulcers (DFU) continue to occur despite established prevention guidelines, yet consumer perspectives, particularly from socioeconomically disadvantaged and culturally and linguistically diverse (CALD) communities, have been underrepresented in shaping prevention. To address this gap, we aimed to co-design a consumer-derived prevention research agenda by identifying barriers and enablers, establishing research priorities, prioritising implementation strategies, and defining meaningful outcome measures.

Four sequential workshops were conducted with 11 consumers with a history of DFU in South East Queensland, including Aboriginal and Pacific Islander participants (n = 4) and those from areas of socioeconomic disadvantage (n = 8). Rapid qualitative analysis informed iterative refinement across workshops, with priorities, implementation strategies, and outcome measures ranked by participants.

Participants identified barriers across clinical, self-care, psychosocial, social, and financial domains, including feeling unsupported when trying to prevent DFU, the cognitive burden of constant vigilance, conflicting guidance, and the financial and travel costs of care. The highest-ranked research priorities were better ways to predict problems before they happen (median 2, IQR 1-4.5), formal education support (median 4, IQR 3-9), and tools to support regular foot checks (median 5, IQR 3-6). Across all three priorities, consumers consistently selected technology enabled implementation strategies, including wearable sensors, AI powered personalised learning, and smart interventions. Participants defined prevention success through quality of life, function, and confidence outcome measures rather than clinical endpoints alone.

For socioeconomically disadvantaged and CALD populations, effective DFU prevention must be technology enabled, personalised, and developed in partnership with the consumer.

PurposeTo elucidate the dynamic molecular evolution and immune heterogeneity in diabetic retinopathy (DR) and identify diagnostic biomarkers.MethodsMulti-omics integrative analysis was performed on peripheral blood transcriptomic data from diabetic patients with and without DR. Techniques included differential expression analysis, immune infiltration profiling, unsupervised clustering, and LASSO regression for biomarker selection. Findings were validated in an independent high-glucose-treated endothelial cell model.ResultsDR progression exhibits staged molecular evolution from diabetes (immune suppression) to early DR (cell cycle inhibition, immune burst) and advanced DR (metabolic stress, persistent immune dysregulation). Six co-downregulated immune modules indicated systemic immune suppression. Patients were classified into three immune subtypes: vascular-inflammatory, metabolic disorder, and oxidative stress-tissue remodeling. A diagnostic model based on IK, PLBD2, FLNA, H6PD, and ZMAT2 achieved an AUC of 0.876 for distinguishing DR from diabetes alone.ConclusionThis study delineates the dynamic molecular landscape and immune heterogeneity of DR, providing a potential multi-gene diagnostic signature and a framework for patient stratification, which may facilitate early detection and personalized management.

Rectal neuroendocrine tumors (NETs) are uncommon neoplasms that are increasingly detected due to the widespread adoption of colorectal cancer screening programs. They typically present as small submucosal nodules, facilitating early diagnosis and minimally invasive treatment. We present the case of a 58-year-old woman with a history of type 2 diabetes mellitus who underwent screening colonoscopy while asymptomatic. During the procedure, an 18-mm non-polypoid submucosal lesion was identified on the anterior rectal wall, 8 cm from the anal verge. Contrast-enhanced computed tomography of the chest, abdomen, and pelvis demonstrated no evidence of regional or distant metastasis. Complete local excision was performed using transanal minimally invasive surgery (TAMIS) without complications. Histopathological examination revealed a well-differentiated grade 1 rectal NET staged as pT1bN0M0, with a Ki-67 proliferation index of 1%, positive immunohistochemical staining for chromogranin A, negative surgical margins, and no evidence of lymphovascular or perineural invasion. Follow-up imaging demonstrated no evidence of local recurrence or distant metastatic disease, and the patient remains under clinical and radiological surveillance. This case highlights the importance of colorectal cancer screening programs for the incidental detection of rare rectal NETs and supports TAMIS as a safe and effective treatment option for selected patients with localized disease.

Fasting hyperglycaemia (FHG) in insulin resistance is due to oxidative stress wherein gamma-glutamyl transferase (GGT) and uric acid (UA) are known to impair insulin secretion from pancreatic beta cells due to their pro-oxidant action and their role in metabolism of antioxidant glutathione. This study aims to determine the association of GGT and UA with FHG and its role in predicting the onset of prediabetes.

This cross-sectional study was conducted in Government Villupuram Medical College, Villupuram, India, from July to December 2023. Individuals in the age range of 25-65 years attending the master health check-up clinic were included. The subjects were classified as normoglycaemic (FBG <100 mg/dL) or hyperglycaemic (FBG ≥100 mg/dL). GGT, UA, glucose (Glu):GGT ratio, Glu:UA ratio, lipid profile and GGT: high-density lipoprotein (HDL) were compared between the two groups using Student's t test. The parameters were compared between the quintiles of glucose using ANOVA. Pearson's correlation was used to analyse the correlation between the study parameters.

A total of 500 adults were included in this study. Triglyceride (TG), TG:HDL ratio, GGT, UA and Glu:GGT, Glu:UA and GGT:HDL ratios were significantly high in fifth quintile compared to other glucose quintiles. Glu:UA and Glu:GGT ratios showed significant positive correlation with glucose levels. Receiver operating characteristic analysis showed that Glu:UA ratio was a good predictor of FHG (AUC = 0.808; P <0.0001) with a sensitivity of 70.1% and specificity of 79.8% at a cut-off value of 26.5 to diagnose insulin resistance.

Glu:UA and Glu:GGT ratios are surrogate markers of underlying oxidative stress and insulin resistance and good predictors of fasting hyperglycaemia.

Hepatocellular carcinoma is a primary liver malignancy that may invade vascular structures, including the inferior vena cava, in advanced stages. Detection during cardiac imaging is uncommon. A 73-year-old man with hypertension and type 2 diabetes mellitus presented with chest pain suggestive of acute coronary syndrome. Initial electrocardiographic assessment and cardiac biomarkers showed no evidence of myocardial injury. During transthoracic echocardiographic evaluation, an unexpected mass was identified within the inferior vena cava on the subcostal view. Subsequent contrast-enhanced computed tomography demonstrated a large right hepatic lobe mass with characteristic arterial enhancement and portal venous/delayed-phase washout, along with inferior vena cava invasion. Histopathological examination confirmed hepatocellular carcinoma. This case illustrates the importance of a systematic echocardiographic approach, as incidental extracardiac findings may reveal significant underlying disease and alter clinical management.

To develop and externally validate a liquid neural network (LNN)-based model for predicting peri-procedural hypoglycemia in hospitalized patients undergoing colonoscopy, and to develop a cross-platform web application integrating real-time SHAP-based interpretability analysis.

A total of 719 hospitalized patients undergoing colonoscopy were retrospectively enrolled from Changshu No.1 People's Hospital and Changshu Traditional Chinese Medicine Hospital between January and December 2025, with peri-procedural hypoglycemia as the outcome and 28 candidate variables. Internal validation was performed using stratified five-fold cross-validation combined with out-of-fold (OOF) prediction, and LASSO feature selection and SMOTE class balancing were carried out within the training folds. Logistic regression (LR), decision tree (DCT), random forest (RF), extreme gradient boosting (XGBoost), and LNN models were constructed, and model performance was evaluated in terms of discrimination, calibration, and clinical utility; SHAP was used for global and individualized interpretation, and a web application was developed using Python-Streamlit.

The incidence of peri-procedural hypoglycemia was 15.2%. LASSO selected seven features: bowel preparation solution volume, sex, fasting duration, nutritional risk, insulin use, history of diabetes mellitus, and albumin. After SMOTE, the internal-validation AUCs in descending order were LNN 0.851 (95% CI: 0.804-0.893), RF 0.831, XGBoost 0.829, LR 0.765, and DCT 0.750; LNN simultaneously showed the best sensitivity-specificity balance (76.83%/85.50%) and the lowest Brier score (0.116), and decision curve analysis showed the highest net benefit across the 0.05-0.55 threshold range. The LNN-based web application achieved an AUC of 0.848 (95% CI: 0.758-0.921) in the external validation set of 168 patients, with a sensitivity of 74.07%, a specificity of 86.52%, and a negative predictive value of 94.57%; SHAP analysis identified nutritional risk (mean |SHAP| = 0.689), albumin (0.480), and sex (0.431) as the principal predictors.

The LNN-based model can effectively assess the risk of peri-procedural hypoglycemia in hospitalized patients undergoing colonoscopy and maintained good predictive performance in external validation; the web application integrating real-time SHAP interpretation provides convenient, interpretable, individualized risk assessment, offering support for early screening and intervention decision-making. A publicly accessible demonstration of the web application is available at https://ml-model-for-hypoglycemia.streamlit.app/.

The term "micromegaly" historically refers to patients with acromegalic features, elevated IGF-1, but normal growth hormone (GH) levels. The physiological mechanism, the appropriate clinical and treatment approaches, as well as its existence as a separate clinical entity are not well-defined.

We retrospectively collected clinical and hormonal data from 30 patients with acromegaly and 30 with micromegaly (displaying high IGF-1 but GH < 0.4 µg/L after glucose load), matched for age and sex. Data about acromegaly related comorbidities were collected (goiter, colonic polyps, malignancies, hypertension, cardiopathy, obstructive-sleep-apnea, carpal tunnel, and hyperglycemia). We performed a laboratory analysis of pituitary tissue samples from both groups, examining GH isoform expression and proliferative rate. We compared data of the two groups and described follow-up and treatment response in micromegalic patients.

Patients with acromegaly exhibited higher IGF-1 values at diagnosis (+8.3 vs. +3.2 SDS, p < 0.01) and higher GH nadir levels after glucose load (6 vs. 0.15 μg/L, p < 0.01). All patients with acromegaly had a detectable pituitary adenoma (70% macroadenomas), whereas 52% of patients with micromegaly showed no evidence of pituitary adenoma. Despite different GH/IGF-1 values, the prevalence of most comorbidities was similar in both groups, except for valve disease and diabetes mellitus, which were more frequent in acromegaly (valvopathy: 42.9% vs. 16.7%, p = 0.006; diabetes: 56.7% vs. 23.3%, p = 0.016, respectively). Laboratory analyses in patients with micromegaly indicated a lower proliferative profile in tumor cells (D3 cyclin expression).

Patients with a clinical diagnosis of acromegaly and high IGF-1 levels but a GH nadir < 0.4 µg/L following glucose load exhibit a high burden of comorbidities and therefore require appropriate screening and follow-up. Therapeutic strategies in these cases should be individualized, considering the frequent absence of neuroradiological findings, which may reflect a lower proliferative profile.

The COVID-19 pandemic disrupted primary care delivery and may have exacerbated disparities in chronic disease management, particularly for diabetes mellitus. This study sought to investigate how living in areas with low access to primary care providers (PCP) affected the delivery of diabetes care during the pandemic.

This is a retrospective longitudinal study using the Panel 24 of the Medical Expenditure Panel Survey data merged with the 2019 County Health Rankings data to classify areas by PCP availability (low vs. high). Dependent variables included measures of care processes (e.g., number of HbA1c tests), quality (e.g., diet modification) and outcomes (e.g., eye complications). Multivariable models were adjusted for demographics, insurance status and COVID-19 diagnosis.

HbA1c testing, foot examinations and retinal examinations decreased during the pandemic for both groups, with much more pronounced declines in low PCP density areas. The largest change occurred in the frequency of attending group classes, dropping nearly 80% in low PCP areas. Individuals in low PCP areas were more likely to initiate oral diabetes medications (as opposed to insulin) compared with those in high PCP areas (0.84% vs. 0.28%, p = 0.015). Older age was associated with new diabetes (HR = 1.05) and new kidney disease (HR = 1.04), but less likely to start diet modification (HR = 0.99). Being female (HR = 0.69) and non-Hispanic whites (HR = 0.60) were associated with a lower likelihood of diabetes incidents.

These findings highlight the importance of preparing public health responses for future events that limit access to routine care, particularly for individuals with or at risk of diabetes. Strengthening both in-person and virtual primary care services is critical to reducing gaps in chronic disease management and to supporting ongoing PCP follow-up.