Insulin resistance in the early pregnancy stage can independently lead to the occurrence of gestational diabetes mellitus and adverse pregnancy outcomes. To evaluate the relationship between the Triglyceride-Glucose (TyG) index in early pregnancy and pregnancy complications and adverse pregnancy outcomes using meta-analysis.

Search the CNKI, Wanfang, VIP, China Biomedical Literature database, PubMed, Embase, Web of Science, and the Cochrane Library. The search covered the period from the establishment of each database to December 28, 2025. Two researchers using the Newcastle-Ottawa Scale to assess the quality of the included studies and extracted data. Statistical analysis was performed using RevMan 5.4 and Stata 17.0.

Twenty-three studies were included, involving 220,985 participants with 61,774 exposed individuals. Meta-analysis revealed that compared with low TyG index in early pregnancy, high TyG index was significantly associated with increased risks of gestational diabetes mellitus, gestational hypertension, preeclampsia, preterm birth, large for gestational age, and macrosomia (p < 0.05).

A high TyG index in early pregnancy is significantly positively associated with the occurrence of gestational diabetes, gestational hypertension, preeclampsia, preterm birth, large for gestational age, and macrosomia. The TyG index can serve as a simple and reliable indicator for the early diagnosis of high-risk pregnancies in pregnant women, facilitating timely clinical intervention by healthcare providers to reduce the incidence of pregnancy complications and adverse pregnancy outcomes.

https://www.crd.york.ac.uk/PROSPERO/view/CRD420261293271, Identifier CRD420261293271.

The atherogenic index of plasma (AIP), calculated from triglyceride and high-density lipoprotein cholesterol levels, is associated with atherosclerosis and coronary artery disease (CAD). However, evidence concerning the impact of the AIP on CAD severity remains limited. This study aims to assess the correlation between AIP and the severity of CAD.

This study included 19,929 hospitalized participants diagnosed with CAD. After excluding participants with missing data, aged >75 years, or diagnosed with chronic kidney disease or cancer, a total of 2561 individuals were included. The 2561 participants were divided into three AIP tertile groups: AIP1 (AIP <0.016, n = 854), AIP2 (0.016 ≤ AIP < 0.216, n = 853), and AIP3 (AIP ≥0.216, n = 854). In this study, CAD severity was determined by the count of coronary arteries exhibiting stenosis of 50% or greater. Multivessel CAD was defined as ≥50% stenosis in two or more major coronary arteries. The relationship between AIP and CAD severity was assessed using logistic regression models.

Results indicate that the AIP independently predicts CAD severity, with an odds ratio of 1.700 (95% confidence interval (CI): 1.160-2.491; p = 0.007). The AIP3 group demonstrated a significantly higher risk of multivessel CAD compared to the AIP1 group (odds ratio (OR), 1.441; 95% CI: 1.124-1.848; p = 0.004), particularly in patients without diabetes mellitus (OR, 1.421; 95% CI: 1.030-1.962; p = 0.033).

The AIP was significantly associated with CAD severity, suggesting that it could be a convenient and valuable marker for severity stratification in patients with CAD in clinical practice.

Type 2 diabetes mellitus (T2DM) is a heterogeneous condition in which patients differ markedly in glycemic patterns, treatment responses, and self-management capacity, limiting the effectiveness of uniform care models. Personalized medicine aims to tailor diabetes management using patient-specific data, behaviors, and risk profiles, but the clinical impact of different personalization strategies remains variable. A comprehensive search of major biomedical databases was conducted to identify eligible studies evaluating individualized interventions in adults with T2DM, and 27 studies were included. Evidence was synthesized narratively due to clinical and methodological heterogeneity. Across the included studies, personalized approaches were generally associated with improved glycemic control compared with usual care, although the magnitude and consistency of benefit varied by intervention type and implementation intensity. Larger and more durable improvements were most often observed in interventions that combined objective patient data with actionable care pathways, particularly in high-risk populations or during periods of therapeutic change. These findings suggest that personalization may improve glycemic outcomes in certain settings, although the certainty of evidence remains limited due to study heterogeneity and variations in design and quality.

Patients with chronic kidney disease (CKD) have an increased risk of cardiovascular morbidity. Circulating endostatin is associated with both cardiovascular morbidity and impaired kidney function in the general population, but the utility of endostatin as a prognostic marker for CKD progression and mortality in patients with CKD is not well studied. The aim was to study association between serum endostatin and mortality, and also kidney function decline in a cohort of CKD patients (Salford Kidney Study [SKS]).

Analyses were performed on baseline and annual follow-up samples from 970 adults in the SKS cohort with CKD stage 3-5. Association with mortality was studied using Cox proportional hazard models adjusted for age, gender, systolic and diastolic blood pressure, smoking status, diabetes mellitus, prior cardiovascular disease, creatinine-based estimated glomerular filtration rate (eGFR), and urine protein-to-creatinine ratio (uPCR). Associations between endostatin and eGFR decline were studied with linear regression analyses. eGFR decline was defined as the percentage difference between baseline eGFR and follow-up eGFR (median follow-up, 6.2 years).

Median age of the cohort was 66 years, with a median eGFR of 30 mL/min/1.73 m². Multivariate Cox regression models revealed an association between higher endostatin levels and mortality with adjustments for established cardiovascular risk factors (HR: 1.14; CI: 1.02-1.28; p = 0.02) but was attenuated and nonsignificant after adjustments for baseline eGFR and uPCR. Baseline levels of endostatin were associated with eGFR decline but were nonsignificant after adjustments for baseline eGFR and uPCR. Changes of endostatin concentrations during the study were significantly associated with eGFR decline in all models (regression coefficient 0.0023% decrease per month [95% confidence intervals 0.0012-0.0034, p < 0.001]).

The clinical utility of plasma endostatin for risk prediction in CKD patients seems limited. Importantly, longitudinal changes of endostatin were significantly associated with eGFR decline. The clinical relevance of this warrants further studies.

Cognitive dysfunction is an increasingly recognized complication of diabetes, contributing substantially to morbidity in the aging population, yet disease-modifying therapies remain scarce. Dietary intervention, a cornerstone of diabetes management, may offer neuroprotective potential. Low-carbohydrate ketogenic diets (LCKDs), typically restricting carbohydrates to < 50 g/day, effectively improve glycemic control and metabolic health. Emerging preclinical and clinical evidence suggests that LCKDs may also confer cognitive benefits through mechanisms including enhanced mitochondrial bioenergetics, reduced neuro-inflammation, and modulation of the gut-brain axis. This narrative review critically evaluates the current evidence regarding the efficacy, mechanisms, and safety of LCKDs for managing diabetes-associated cognitive dysfunction, identifies key limitations in the existing literature, and proposes a framework for future research to enhance translational value.

Gestational diabetes mellitus (GDM) is a common pregnancy complication with adverse maternal and fetal outcomes, yet its genetic basis is not fully understood. Previous genome-wide association studies (GWAS) have identified only a limited number of susceptibility loci, most of which overlap with genes for type 2 diabetes (T2D).

We performed a meta-analysis of GWAS datasets from British, Finnish, and Chinese populations to identify novel genetic susceptibility loci for GDM. Functional annotation of associated variants was conducted using FUMA. We assessed cross-population genetic correlations (Popcorn) and fine-mapped ancestry-specific signals (SuSiEx). Candidate gene was then prioritized using multiple approaches, including eQTL mapping, MAGMA, TWAS-Fusion, GCTA-mBAT, and PoPs. Finally, we integrated proteomic data from BLISS and performed in-depth pathway and tissue enrichment analyses using MAGMA and GSA-MiXeR.

Our multi-pronged approach identified two novel susceptibility genes associated with GDM risk: ELL2 and ATRAID. In addition, three enriched biological pathways linked to GDM loci were discovered, including: the regulation of hexokinase activity, the regulation of insulin, and the regulation of protein.

Our study links the expression of ELL2 and ATRAID with the risk of GDM, and identifies three GDM-related enriched pathways. These findings provide new insights into the pathogenesis of GDM and highlights potential new targets for future research and therapeutic intervention.

To analyze and evaluate the impact of SGLT2 inhibitors on the renal outcomes of patients with type 2 diabetes mellitus and chronic kidney disease, and to provide evidence-based basis for clinical rational treatment.

Relevant literatures on the impact of SGLT2 inhibitors on the renal outcomes of patients with type 2 diabetes mellitus and chronic kidney disease published in domestic and foreign databases were retrieved and collected. The time limit was from the establishment of each database to November 2025. After screening, the quality of the research literature was evaluated using the Cochrane library. Literature management was conducted using NoteExpress 3.2, and data collection and extraction were carried out using Excel 2003. Statistical analysis was performed using RevMan 5.4.1 software. Based on the size of the Q test (P value), it was determined whether there was heterogeneity in the studies, and then the fixed or random effect model was used to calculate the combined effect OR value, and a forest plot was drawn. Then, the publication bias was evaluated by drawing a funnel plot.

A total of 10 studies that met the inclusion criteria were finally included. The meta-analysis results showed that compared with the control group, the eGFR and CrCI levels of patients treated with 5 mg dapagliflozin showed a more significant decline, renal-related adverse events (OR = 0.91, 95% CI: 0.84 to 0.99, P = 0.04), and the occurrence of doubling of serum creatinine, end-stage renal disease, and renal death events (OR = 0.68, 95% CI: 0.60 to 0.78, P < 0.00001). However, there was no statistically significant difference in acute kidney injury or failure between the two groups. Sensitivity analysis suggested that the results of this study were stable and reliable.

SGLT2 inhibitors can cause a short-term decline in eGFR and CrCl, and significantly reduce the risk of renal composite endpoint events. This indicates that their early hemodynamic effects are predictable physiological changes.

https://www.crd.york.ac.uk/PROSPERO/view/CRD420261294499, identifier CRD420261294499.

Polycystic ovary syndrome (PCOS) is associated with an increased risk of type 2 diabetes mellitus (T2DM), and the risk of PCOS increases in patients with T2DM of reproductive age. The bidirectional link between PCOS and T2DM has been confirmed through experimental and epidemiological evidence; however, the genetic factors that contribute to deeper insights into the shared pathogenesis of these two diseases remain unclear. We aimed to identify shared immune- and inflammation-related genes and pathways in PCOS and T2DM, further explore the molecular mechanisms in developing this comorbidity, and predict drugs with potential effects to develop novel therapeutic strategies.

We obtained microarray expression profiling datasets (GSE34526 and GSE25724) of PCOS and T2DM from the Gene Expression Omnibus (GEO) database. The differential expression genes (DEGs) between disease and control groups were identified and analyzed via the R package "limma" following data preprocessing. The R package "clusterProfiler" was applied to conduct Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) pathway enrichment analyses. Hub genes were identified from the protein-protein interaction (PPI) network using the Molecular Complex Detection (MCODE) and cytoHubba plug-ins of Cytoscape. Transcription factor (TF)-hub and miRNA-hub gene regulatory networks were constructed and visualized using Cytoscape. The Drug-Gene Interaction Database (DGIdb) was used to predict prospective drugs targeting hub genes. In addition, hub genes were verified by RT-qPCR.

A total of 239 common DEGs, including 140 upregulated genes and 99 downregulated genes, were discovered. These common DEGs were primarily associated with immune regulation and inflammatory processes. Moreover, ITGAM, ITGB2, SPI1, C1QB, CCR5, C3AR1, LY86, AIF1, and IRF8 were identified as hub genes and the RT-qPCR results showed significant differences. These hub genes were predominantly related to the regulation of neutrophil degranulation (ITGAM, ITGB2, and SPI1), dendritic cell chemotaxis (CCR5 and SPI1), follicular B cell differentiation (SPI1 and IRF8), synapse pruning (ITGAM and C1QB), integrin αM-β2 complex (ITGAM and ITGB2), the regulation of prostaglandin-E synthase activity (ITGAM and ITGB2), Staphylococcus aureus infection (ITGAM, ITGB2, C1QB, and C3AR1) and pertussis (IRF8). Finally, we predicted 19 TFs, 170 miRNAs, and 40 potential therapeutic drugs interacting with hub genes.

We identified nine hub genes and related gene regulatory networks and discussed novel perspectives on the roles of immunity and inflammation in patients with PCOS and T2DM. Moreover, maraviroc, cenicriviroc, PF-04634817 (targeting CCR5), butein (targeting ITGB2), dimethyl sulfoxide (targeting ITGAM), and rovelizumab (targeting both ITGB2 and ITGAM) are potential therapeutic drugs. However, these findings require validation through further clinical and experimental studies.

Chronic Wounds are one of the most prevalent types of Dermatoses, which are the result of impaired Healing and Complications. In addition, Type 2 Diabetes Mellitus is one of the main causes of impaired Healing (due to the development of Complications and other factors). Therefore, it is of interest to evaluate the way T2DM influences Healing, Recurrence and Clinical Outcomes (in Dermatology Clinics) over a period of five years. A retrospective review of medical records (of chronic wound patients) identified differences between the T2DM and the Non-Diabetic Groups. The T2DM patients demonstrated a significantly longer median Healing Time than the Non- Diabetic Patients, with increased Infection Rates and an increased need for Advanced Wound Care. The rate of Recurrence and Amputation were also higher than in the Non-Diabetic Group. A Multivariate Analysis indicated that T2DM, Baseline Wound Infection and Wound Size >10 cm² were significant predictors of Delayed Healing for T2DM Patients. Thus, these data demonstrate that T2DM places a significant burden on Wound Outcomes in a Dermatology Practice. Early identification of risk factors, multidisciplinary management and optimised glycaemic control are crucial to improving Healing and reducing complications associated with Chronic Wounds and T2DM.

To evaluate whether sustained use of continuous glucose monitoring (CGM) is associated with long-term patterns in glycemic control, safety indicators, and health care utilization among adults with type 2 diabetes (T2D) in routine clinical care.

A two-year retrospective chart review was conducted at a tertiary care center in Saudi Arabia. Adults with T2D who initiated second-generation CGM (FreeStyle Libre 2) and maintained use for 24 months were included. Glycemic, metabolic, and clinical outcomes were assessed at baseline, 12 months (T12), and 24 months (T24).

Among 222 adults (mean age 48.7 years; 48.2% female), sustained CGM use was associated with improvements across multiple glycemic parameters. Glycated hemoglobin (HbA1c) declined from 8.2% at baseline to 7.8% at T24, accompanied by reductions in mean glucose, self-monitoring of blood glucose frequency, glycemia risk indices, and glucose variability. %TIR_70-180 increased, time spent in hyperglycemia decreased, and time below range remained low throughout follow-up. Directionally similar glycemic improvements were observed across subgroups, including individuals with obesity, those treated with oral agents only, and those receiving insulin-based regimens. Beyond glycemic outcomes, body weight decreased by approximately 2 kg over 24 months. Diabetes-related emergency department visits declined from five participants (2.3%) at T0 to two (0.9%) at T12 and one (0.5%) at T24.

Two-year use of CGM in routine care was associated with favorable trends in glycemic control, glycemic stability, self-monitoring behavior, and health care utilization. Long-term CGM integration may be feasible and potentially beneficial across diverse T2D populations, although prospective studies are needed to clarify the causal effects.