Category: Diabetes

Introduction and Objective: The difference between cystatin C (cys)- and creatinine (cr)-based estimated glomerular filtration rate (eGFRdiff) is recently documented to be associated with adverse cardiovascular outcomes and diabetes microvascular complications. We examined association between eGFRdiff and carotid plaque score (PS) in patients with type 2 diabetes (T2D).Methods: We enrolled 1,576 patients with T2D. The […]

Introduction and Objective: Urinary C-peptide (UCP) could provide an easily measurable alternative to serum C-peptide (SCP). We aimed (i) to check over-time stability of UCP and (ii) to use UCP to predict homeostasis modelling assessment 2 indices of insulin resistance and beta cell function (HOMA2-IR and -B) and (iii) to be able to assign type […]

Introduction and Objective: Alpha-lipoic acid (ALA) is used for diabetic neuropathy, but their potential impact on macrovascular complications remains unclear. This study aimed to investigate the association between ALA use and the risk of cardiovascular outcomes and mortalityMethods: We conducted a retrospective cohort study using the Korean National Health Insurance Service Health Screening Cohort. Participants […]

Introduction and Objective: Compared to a low caloric Mediterranean diet (LC-med), Very Low Calories Ketogenic Diet (VLCKD) obtains weight loss with a greater caloric deficit and an almost complete carbohydrates restriction that markedly reduces insulin secretion. We compared the impact of VLCKD and LC-med on visceral fat (VAT) and muscle loss.Methods: We studied prospectively 116 […]

Introduction and Objective: Type 2 diabetes (T2D) and obesity are independently associated with increased risk of cardiovascular disease (CVD) and kidney outcomes. This study aimed to explore the impact of body mass index (BMI) at T2D diagnosis on CVD and kidney outcomes, which is less understood.Methods: Data from people diagnosed with T2D from January 2010 […]

Introduction and Objective: Diabetes (DM) is an independent risk factor for ischemic heart disease (IHD). We aim to investigate disparities in diabetes-related ischemic heart disease (DRIHD) mortality trends within specific epidemiological groups.Methods: We extracted data from the CDC WONDER database from 1999 to 2020.IHD was listed as the main cause of death (ICD codes: I20-I25), […]

Introduction and Objective: Coronary angiography is the gold standard for diagnosing coronary artery stenoses, but is invasive and confers potential risks. This study aimed to develop a Machine Learning (ML) model to predict significant stenoses while minimizing false negatives, ensuring accurate risk stratification and better patient selection.Methods: Data from 2,310 patients undergoing coronary angiography were […]

Introduction and Objective: Type 1 diabetes (T1D) is an autoimmune disease that causes loss of β-cell mass and insulin secretion. Early Stage 3 T1D includes β-cell dysfunction and activation of intrinsic stress pathways before clinical diagnosis, making this ‘asymptomatic’ period critical for prediction and prevention. Circulating plasma extracellular vesicles (EVs) are promising non-invasive biomarkers for […]

Introduction and Objective: The rise of Big Data necessitates artificial intelligence-driven analyses to extract valuable insights, particularly for risk prediction in high-risk patient populations. This observational study applied machine learning (ML) algorithms to predict 5-year overall mortality in heart failure patients with type 2 diabetes mellitus (T2DM) or prediabetes.Methods: A cohort of 290 heart failure […]

Introduction and Objective: In general population screening for type 1 diabetes (T1D), large proportion of islet autoantibodies (IAbs) detected by the standard radio-binding assay (RBA) are not predictive due to low-affinity. Electrochemiluminescence (ECL) IAb assay has been shown in multiple studies to improve predictive accuracy by detecting high-affinity IAbs. Our new bridging ELISA for insulin […]