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Abstract Background So far, high-density lipoprotein cholesterol (HDL-C) levels and mortality were shown to have a U-shaped relationship. Additionally, high HDL-C levels increase the risk of developing a variety of diseases. However, a paucity of data exists regarding the characteristics of people with high HDL-C levels. The aim of this study was to assess the demographics and characteristics of patients with high HDL-C levels and compare their features with normal and low HDL-C groups. Methods As a cross-sectional, matched case–control study, a total of 510 patients with type 2 diabetes (T2D) were enrolled in the study and categorized into three matched groups according to their HDL-C concentrations. The studied groups were matched by their age and gender. Restricted cubic spline (RCS) curves were designed to evaluate the relationship between height, blood pressure, triglyceride, and vitamin D concentrations with the probability of having high HDL-C levels. Furthermore, violin plots were conducted to illustrate the distribution of continuous variables within each group. Results This study showed that having high HDL-C (more than 70 mg/dL) compared to having low HDL-C (less than 40 mg/dL in men and 50 mg/dL in women) was significantly associated with height (OR 0.918, 95% CI 0.866–0.974), systolic blood pressure (SBP) (0.941, 0.910–0.972), vitamin D (0.970, 0.941–0.999), and triglyceride (0.992, 0.987–0.998) serum concentrations. Further analysis investigated that having high HDL-C levels compared to desired HDL-C levels (40 ≤ HDL-C levels

Abstract Purpose Diabetes is the leading cause of kidney disease. Up to 40% of the population with diabetes experience diabetic kidney disease (DKD). The correlation of DKD with insulin resistance (IR) indices has been shown in previous studies. In this study, the objective was to evaluate surrogate IR indices, including the Triglyceride-Glucose (TyG) index, Visceral Adiposity Index (VAI), Lipid Accumulation Product (LAP), and Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) to find the most valuable index for the correlation between albuminuria and IR in the type 2 diabetes (T2D) population. Albuminuria is defined as urine albumin excretion of > 30 mg/day. Methods In this cross-sectional study, 2934 participants were enrolled and evaluated for urinary albumin excretion, and albuminuria was detected in 526 of the entries. The logistic regression models and Receiver Operating Characteristic (ROC) curve analysis were performed to assess the relationship of TyG index, VAI, LAP, and HOMA-IR's with albuminuria in patients with T2D. Results The TyG index had the highest association (OR 1.67) with the presence of albuminuria in patients with T2D, followed by HOMA-IR (OR 1.127), VAI (OR 1.028), and LAP (OR 1.004). These four indices remained independent after adjustment for multiple confounders. Based on the ROC curve, TyG revealed the best area under the curve (AUC) for revealing albuminuria with sufficient accuracy (AUC: 0.62) in comparison with other measured indices. The calculated TyG index cut-off point for the presence of albuminuria was 9.39. Conclusion Among the indices, TyG index had the most significant correlation with albuminuria in patients with T2D.

Abstract Background Metabolic-associated fatty liver disease (MAFLD), formerly known as non-alcoholic fatty liver disease, is the leading cause of liver disease that can ultimately lead to cirrhosis. Identifying a screening marker for early diagnosis of MAFLD in patients with type 2 diabetes (T2D) can reduce the risk of morbidity and mortality. This study investigated the association between the atherogenic index of plasma (AIP) and MAFLD in patients with T2D. Method A retrospective case–control study was conducted and medical records of patients with T2D were assessed. The baseline characteristics, anthropometric indices, laboratory measurements including liver functions tests, fasting blood sugar, HbA1C, lipid profile were documented. Results Out of 2547 patients with T2D, 824 (32.4%) had MAFLD. The multivariate logistic regression analysis showed a significant difference in female-to-male ratio (1.11 vs. 1.33, OR = 0.347, P-value