Search Results (3,096)

Background: Fixed-dose combinations of rosuvastatin and ezetimibe are increasingly used in clinical practice, but real-world data on their effectiveness and safety in large populations remain limited. Methods: This prospective, single-group, open-label, non-interventional observational study was conducted in the Republic of Korea to evaluate the effectiveness and safety of Rovazet^® (a fixed-dose combination of rosuvastatin and ezetimibe). Patients were prospectively enrolled from 235 institutions (50 general hospitals and 185 private clinics) as part of routine clinical practice over a five-year period. Lipid profiles and medication compliance questionnaire results were collected at baseline, 12 weeks, and 24 weeks of treatment. Results: A total of 5527 patients with dyslipidemia, the majority were men (53.0%), and the mean age was 60.4 years. Rovazet^® significantly reduced low-density lipoprotein cholesterol (LDL-C) by 23.5% at 12 weeks (from 117.47 ± 50.65 mg/dL to 81.14 ± 38.20 mg/dL; p < 0.0001) and by 27.4% at 24 weeks (from 117.47 ± 50.65 mg/dL to 74.52 ± 33.36 mg/dL; p < 0.0001). Total cholesterol was significantly reduced by 17.7% at 12 weeks and by 19.8% at 24 weeks. Rovazet^® treatment reduced triglycerides by 4.1% at 12 weeks and by 7.2% at 24 weeks. High-density lipoprotein cholesterol increased by 4.5% at 12 weeks and by 7.9% at 24 weeks following Rovazet^® treatment. These changes in lipid profiles were consistent, regardless of cardiovascular risk profiles. By 24 weeks of treatment with Rovazet^®, 91.8% of patients had reached their target LDL-C goals. Adverse drug reactions were reported in 2.81% of patients, most of which were minor, indicating that Rovazet^® was well tolerated. Conclusions: Rovazet^® was effective in improving lipid profiles and well tolerated in Korean adults with dyslipidemia. Full article

Chrysanthemum × morifolium (Ramat) Hemsl. (Hangbaiju), which has been widely consumed as a herbal tea for over 3000 years, is renowned for its biosafety and diverse bioactivities. This study investigates the impact of polyphenol-rich Hangbaiju extracts (HE) on high-fat diet-induced obesity in mice. HE contains phenolic acids and flavonoids with anti-obesity properties, such as apigenin, luteolin-7-glucoside, apigenin-7-O-glucoside, kaempferol 3-(6″-acetylglucoside), etc. To establish the obesity model, mice were randomly assigned into four groups (n = 8 per group) and administered with either HE or water for 42 days under high-fat or low-fat dietary conditions. Administration of low (LH) and high (HH) doses of HE both significantly suppressed body weight growth (by 16.28% and 16.24%, respectively) and adipose tissue enlargement in obese mice. HE significantly improved the serum lipid profiles, mainly manifested as decreased levels of triglycerides (28.19% in LH and 19.59% in HH) and increased levels of high-density lipoprotein cholesterol (44.34% in LH and 54.88% in HH), and further attenuated liver lipid deposition. Furthermore, HE significantly decreased the Firmicutes/Bacteroidetes ratio 0.23-fold (LH) and 0.12-fold (HH), indicating an improvement in the microecological balance of the gut. HE administration also elevated the relative abundance of beneficial bacteria (e.g., Allobaculum, norank_f__Muribaculaceae), while suppressing harmful pathogenic proliferation (e.g., Dubosiella, Romboutsia). In conclusion, HE ameliorates obesity and hyperlipidemia through modulating lipid metabolism and restoring the balance of intestinal microecology, thus being promising for obesity therapy. Full article

Background/Objectives: Hyperlipidemia is a major risk factor for cardiovascular disease and atherosclerosis. Polyphenols found in polyphenol-rich extra virgin olive oil (EVOO) have been shown to possess strong antioxidant, anti-inflammatory, and cardioprotective properties. The present study aimed to assess the effects of two types of EVOO with different polyphenol content and dosages on the lipid profile of hyperlipidemic patients. Methods: In this single-blind, randomized clinical trial, 50 hyperlipidemic patients were randomized to receive either a higher-dose, lower-phenolic EVOO (414 mg/kg phenols, 20 g/day) or a lower-dose, higher-phenolic EVOO (1021 mg/kg phenols, 8 g/day), for a period of 4 weeks. These doses were selected to ensure equivalent daily polyphenol intake in both groups (~8.3 mg of total phenols/day), based on chemical analysis performed using NMR spectroscopy. The volumes used (8–20 g/day) reflect typical daily EVOO intake and were well tolerated by participants. A group of 20 healthy individuals, separated into two groups, also received the two types of EVOO, respectively, for the same duration. Primary endpoints included blood levels of total blood cholesterol, low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglycerides, lipoprotein-a (Lpa), and apolipoproteins A1 and B. Measurements were performed at baseline and at the end of the 4-week intervention. Linear mixed models were performed for the data analysis. Results: The higher-phenolic, lower-dose EVOO group showed a more favorable change in total blood cholesterol (p = 0.045) compared to the lower-phenolic, higher-dose group. EVOO intake was associated with a significant increase in HDL (p < 0.001) and reduction in Lp(a) (p = 0.040) among hyperlipidemic patients in comparison to healthy individuals. Conclusions: EVOO consumption significantly improved the lipid profile of hyperlipidemic patients. Higher-phenolic EVOO at lower dosages appears to be more effective in improving the lipid profile than lower-phenolic EVOO in higher dosages. Full article

Background/Objectives: Conventional ketogenic diets, although effective for weight loss, often contain high total and saturated fat intake, which leads to increased low-density lipoprotein cholesterol (LDL-C). Thus, the Healthy Ketogenic Diet (HKD) was developed to address these concerns. It emphasizes calorie restriction, limiting net carbohydrate intake to 50 g per day, prioritizing unsaturated fats, and reducing saturated fat intake. However, adherence to the HKD remains a challenge in urban, time-constrained environments. Therefore, this pilot randomized controlled trial aimed to investigate the effects of Healthy Ketogenic Diet Ready-To-Eat (HKD-RTE) meals (provided for the first month only) versus HKD alone on weight loss and metabolic parameters among overweight adults. Methods: Multi-ethnic Asian adults (n = 50) with a body mass index (BMI) ≥ 27.5 kg/m² were randomized into the HKD-RTE group (n = 24) and the HKD group (n = 26). Both groups followed the HKD for six months, with the HKD-RTE group receiving HKD-RTE meals during the first month. Five in-person workshops and mobile health coaching through the Nutritionist Buddy Keto app helped to facilitate dietary adherence. The primary outcome was the change in body weight at 6 months. Linear regression was performed on the change from baseline for each continuous outcome, adjusting for demographics and relevant covariates. Logistic regression was performed on binary weight loss ≥ 5%, adjusting for demographics and relevant covariates. Results: In the HKD group, participants’ adherence to the 50 g net carbohydrate target was 15 days, while that in the HKD-RTE group was 19 days over a period of 30 days. Participants’ adherence to calorie targets was 21 days in the HKD group and 23 days in the HKD-RTE. The average compliance with the HKD-RTE meals provided in the HKD-RTE group was 55%. The HKD-RTE group experienced a greater percentage weight loss at 1 month (−4.8 ± 3.0% vs. −1.8 ± 6.2%), although this was not statistically significant. This trend continued up to 6 months, with the HKD-RTE group showing a greater percentage weight reduction (−8.6 ± 6.8% vs. −3.9 ± 8.6%; p = 0.092). At 6 months, the HKD-RTE group had a greater reduction in total cholesterol (−0.54 ± 0.76 mmol/L vs. −0.05 ± 0.56 mmol/L; p = 0.283) and LDL-C (−0.43 ± 0.67 mmol/L vs. −0.03 ± 0.52 mmol/L; p = 0.374) compared to the HKD group. Additionally, the HKD-RTE group exhibited greater reductions in systolic blood pressure (−8.3 ± 9.7 mmHg vs. −5.3 ± 11.0 mmHg), diastolic blood pressure (−7.7 ± 8.8 mmHg vs. −2.0 ± 7.0 mmHg), and HbA1c (−0.3 ± 0.5% vs. −0.1 ± 0.4%) than the HKD group (not statistically significant for any). Conclusions: Both HKD-RTE and HKD led to weight loss and improved metabolic profiles. The HKD-RTE group tended to show more favorable outcomes. Short-term HKD-RTE meal provision may enhance initial weight loss, with sustained long-term effects. Full article

Background: Despite significant advancements in diabetes care, many individuals with type 2 diabetes (T2D) do not receive optimal care and treatment. Digital interventions promoting behavioral changes have shown promising long-term results in supporting healthier lifestyles but are not implemented in most healthcare offerings, maybe due to lack of general practice support and collaboration. This study evaluates the efficacy of the Digital, Individualized, and Collaborative Treatment of T2D in General Practice Based on Decision Aid (DICTA), a randomized controlled trial integrating a patient-centered smartphone application for lifestyle support in conjunction with a clinical decision support (CDS) tool to assist general practitioners (GPs) in optimizing antidiabetic treatment. Methods: The present randomized controlled trial aims to recruit 400 individuals with T2D from approximately 70 GP clinics (GPCs) in Denmark. The GPCs will be cluster-randomized in a 2:3 ratio to intervention or control groups. The intervention group will receive one year of individualized eHealth lifestyle coaching via a smartphone application, guided by patient-reported outcomes (PROs). Alongside this, the GPCs will have access to the CDS tool to optimize pharmacological decision-making through electronic health records. The control group will receive usual care for one year, followed by the same intervention in the second year. Results: The primary outcome is the one-year change in estimated ten-year cardiovascular risk, assessed by SCORE2-Diabetes calculated from age, smoking status, systolic blood pressure, total and high-density lipoprotein cholesterol, age at diabetes diagnosis, HbA1c, and eGFR. Conclusions: If effective, DICTA could offer a scalable, digital-first approach for improving T2D management in primary care by combining patient-centered lifestyle coaching with real-time pharmacological clinical decision support. Full article

Acute hepatopancreatic necrosis disease (AHPND), caused by the bacterium Vibrio parahaemolyticus, is a major threat to global shrimp aquaculture. In this study, we evaluated the therapeutic effects of phage therapy in Litopenaeus vannamei challenged with AHPND-causing Vibrio parahaemolyticus. Phage application at various concentrations significantly improved shrimp survival, with the 1 ppm group demonstrating the highest survival rate. Enzymatic assays revealed that phage-treated shrimp exhibited enhanced immune enzyme activities, including acid phosphatase (ACP), alkaline phosphatase (AKP), and lysozyme (LZM). In addition, antioxidant defenses such as superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GSH-PX), and total antioxidant capacity (T-AOC) significantly improved, accompanied by reduced malondialdehyde (MDA) levels. Serum biochemical analyses demonstrated marked improvements in lipid metabolism, particularly reductions in triglyceride (TG), total cholesterol (TC), and low-density lipoprotein (LDL), alongside higher levels of beneficial high-density lipoprotein (HDL). Transcriptomic analysis identified 2274 differentially expressed genes (DEGs), notably enriched in pathways involving fatty acid metabolism, peroxisome functions, lysosomes, and Toll-like receptor (TLR) signaling. Specifically, phage treatment upregulated immune and metabolic regulatory genes, including Toll-like receptor 4 (TLR4), myeloid differentiation primary response protein 88 (MYD88), interleukin-1β (IL-1β), nuclear factor erythroid 2-related factor 2 (Nrf2), and peroxisome proliferator-activated receptor (PPAR), indicating activation of innate immunity and antioxidant defense pathways. These findings suggest that phage therapy induces protective immunometabolic adaptations beyond its direct antibacterial effects, thereby providing an ecologically sustainable alternative to antibiotics for managing bacterial diseases in shrimp aquaculture. Full article

Metabolic and bariatric surgery (MBS) is an effective treatment for severe obesity, though individual responses vary widely, partly due to genetic predisposition. This study investigates the association of a body mass index (BMI) polygenic score (PGS) with weight loss and metabolic outcomes following surgery. A cohort of 225 patients undergoing MBS was analyzed at baseline (T₀), six (T₆), and twelve (T₁₂) months, with anthropometric and biochemical parameters recorded at each time point. Total weight loss (TWL) and excess weight loss (EWL) percentages were calculated. PGS was computed using the LDpred-grid Bayesian method. The mean age was 45.9 ± 9.4 years. Males had a higher baseline prevalence of type 2 diabetes (T2D) and comorbidities (p < 0.001). Linear regression analysis confirmed an association between PGS and baseline BMI (p = 0.012). Moreover, mediation analysis revealed that baseline BMI mediated the effect of the PGS on %TWL at T₁₂, with an indirect effect (p-value = 0.018). In contrast, high-density lipoprotein-cholesterol (HDL-C) at T₆ and triglycerides (TG) at T₁₂ showed direct associations with the PGS (p-value = 0.004 and p-value = 0.08, respectively), with no significant mediation by BMI. This study showed a BMI-mediated association of PGS with %TWL and a direct association with lipid changes, suggesting its potential integration into personalized obesity treatment. Full article

Background: Type 2 diabetes (T2D) and overweight or obesity are strongly associated, with a high prevalence of these concomitant conditions contributing significantly to global healthcare costs. Given this burden, there is an urgent need for effective interventions. Mobile health (mHealth) technologies represent a promising strategy to address both conditions simultaneously. Objectives: This systematic review and meta-analysis aimed to evaluate the effectiveness of mHealth-based interventions for the management of adults with T2D and overweight/obesity. Specifically, it assessed the quantitative impact of these interventions on glycosylated hemoglobin (HbA1c), body weight, triglycerides, total cholesterol, low-density lipoprotein (LDL), and high-density lipoprotein (HDL) levels. Methods: A systematic search was conducted in PubMed, Web of Science, and Scopus databases from inception to 9 July 2025. The inclusion criteria focused on randomized controlled trials (RCTs) using mHealth interventions in adults with T2D and overweight/obesity, reporting HbA1c or weight as primary or secondary outcomes. The risk of bias was assessed using the Cochrane Risk of Bias tool 2. A total of 13 RCTs met the inclusion criteria. Results: Meta-analysis indicated significant improvements after 6–12 months of intervention in HbA1c (MD −0.23; 95% CI −0.36 to −0.10; p < 0.001; I² = 72%), body weight (MD −2.47 kg; 95% CI −3.69 to −1.24; p < 0.001; I² = 79%), total cholesterol (MD −0.23; 95% CI −0.39 to −0.07; p = 0.004; I² = 0%), and LDL (MD −0.27; 95% CI −0.42 to −0.12; p < 0.001; I² = 0%). Conclusions: mHealth interventions are effective and scalable for managing T2D and obesity, particularly when incorporating wearable technologies to improve adherence. Future research should focus on optimizing personalization, engagement strategies, and long-term implementation. Full article

Background: The global increase in type 2 diabetes mellitus (T2DM) cases necessitates the need for early detection of metabolic changes. This study investigated variations in liver enzymes, renal markers, electrolytes, and lipid profiles among T2DM patients stratified by hemoglobin A1c (HbA1c) categories to support early identification and better management of diabetes-related complications. Methods: A retrospective observational study at King Khalid University Hospital (KKUH), Riyadh, included 621 adult patients diagnosed with T2DM categorized into four HbA1c groups: normal (<5.7%), prediabetes (5.7–6.4%), controlled diabetes (6.5–7.9%), and uncontrolled diabetes (≥8.0%). Biochemical parameters included the liver profile: alkaline phosphatase (ALP) and bilirubin, renal profile: creatinine, blood urea nitrogen (BUN), glucose, sodium, and chloride, and lipid profile: cholesterol, high-density lipoprotein (HDL), low-density lipoprotein (LDL), and triglycerides. Regression models identified predictors of ALP, cholesterol, and LDL. Results: ALP was higher in uncontrolled diabetes (89.0 U/L, Q1–Q3: 106.3–72.0) than in the prediabetes group (75.0 U/L, Q1–Q3: 96.8–62.3). Sodium and chloride were lower in uncontrolled diabetes (Na: 138.3 mmol/L, Q1–Q3: 140.3–136.4; Cl: 101.1 mmol/L, Q1–Q3: 102.9–99.4) compared to the normal group (Na: 139.5 mmol/L, Q1–Q3: 142.4–136.9; Cl: 103.5 mmol/L, Q1–Q3: 106.1–101.7). LDL was lower in uncontrolled diabetes (2.1 mmol/L, Q1–Q3: 2.8–1.7) than in the normal group (2.8 mmol/L, Q1–Q3: 3.7–2.2), while triglycerides were higher in patients with uncontrolled diabetes compared to the normal group (1.45 mmol/L, Q1–Q3: 2.02–1.11 vs. 1.26 mmol/L, Q1–Q3: 1.44–0.94). Regression models showed low explanatory power (R² = 2.1–7.3%), with weight, age, and sex as significant predictors of select biochemical markers. Conclusions: The study observed biochemical variations across HbA1c categories in T2DM patients, likely reflecting insulin resistance. Monitoring these markers in conjunction with HbA1c can enhance early detection and improve the management of complications. Full article

Background: Metabolic syndrome (MetS) is a multifactorial condition involving central obesity, dyslipidemia, hypertension, and impaired glucose metabolism, significantly increasing the risk of type 2 diabetes and cardiovascular disease. Objectives: Given the clinical heterogeneity of MetS, this study aimed to identify distinct metabolic phenotypes, referred to as metabotypes, using validated biomarkers and to examine their association with MetS. Materials and Methods: A total of 1245 Korean adults aged 19–79 years were selected from the 2016–2023 Korea National Health and Nutrition Examination Survey. Metabotype risk clusters were derived using k-means clustering based on five biomarkers: body mass index (BMI), uric acid, fasting blood glucose (FBG), high-density lipoprotein cholesterol (HDLc), and non-HDL cholesterol (non-HDLc). Multivariable logistic regression was used to assess associations with MetS. Results: Three distinct metabotype risk clusters (low, intermediate, and high risk) were identified. The high-risk cluster exhibited significantly worse metabolic profiles, including elevated BMI, FBG, HbA1c, triglyceride, and reduced HDLc. The prevalence of MetS increased progressively across metabotype risk clusters (OR: 5.46, 95% CI: 2.89–10.30, p < 0.001). In sex-stratified analyses, the high-risk cluster was strongly associated with MetS in both men (OR: 9.22, 95% CI: 3.49–24.36, p < 0.001) and women (OR: 3.70, 95% CI: 1.56–8.75, p = 0.003), with notable sex-specific differences in lipid profiles, particularly in HDLc. Conclusion: These findings support the utility of metabotyping using routine biomarkers as a tool for early identification of high-risk individuals and the development of personalized prevention strategies in clinical and public health settings. Full article

Hyperlipidemia (HLP) is a disorder of human lipid metabolism or transport, primarily characterized by abnormally elevated levels of total cholesterol (TC), triglycerides (TGs), and low-density lipoprotein cholesterol (LDL-C) in the blood. It is a key factor contributing to the development of non-alcoholic fatty liver disease, obesity, diabetes, atherosclerosis, and cardiovascular and cerebrovascular diseases. Statistics show that the prevalence of dyslipidemia among Chinese adults is as high as 35.6%, and it has shown a trend of younger onset in recent years, posing a serious threat to public health. Therefore, the prevention and treatment of dyslipidemia carry significant social significance. The pathogenesis of hyperlipidemia is complex and diverse, and currently used medications are often accompanied by side effects during treatment, making the research and development of new therapeutic approaches a current focus. Numerous studies have shown that flavonoids, which are abundant in most medicinal plants, fruits, and vegetables, exert effects on regulating lipid homeostasis and treating hyperlipidemia through a multi-target mechanism. These compounds have demonstrated significant effects in inhibiting lipid synthesis, blocking lipid absorption, promoting cholesterol uptake, enhancing reverse cholesterol transport, and suppressing oxidative stress, inflammation, and intestinal microbiota disorders. This article reviews the latest progress in the mechanisms of flavonoids in the treatment of hyperlipidemia, providing a theoretical basis for future research on drugs for hyperlipidemia. Full article

Background/Objectives: Astaxanthin, a xanthophyll carotenoid, has garnered significant interest due to its benefits with regard to dyslipidemia. This multifaceted functional food ingredient modulates several key enzymes associated with lipid regulation, including HMG-CoA reductase, CPT1, ACCβ, and acyl-CoA oxidase. It influences key antioxidant molecular pathways like the Nrf2, limiting dyslipidemia occurrence and regulating liver cholesterol uptake through the modulation of liver lipid receptors. Due to the current lack of systematic reviews and meta-analyses assessing moderate to high dosages (6–24 mg/d) of astaxanthin supplementation on lipid dysregulation, the present manuscript aims to fill this gap in the literature. Methods: Following the PRISMA guidelines, we included eight studies comprising eleven results from the PubMed, Springer Link, Science Direct, Cochrane, and Google Scholar databases. The Jamovi (Version 2.6.26, Solid) software was utilized for statistics. Our primary objective was to assess in detail the effects of astaxanthin on LDL-C, HDL-C, triglyceride, and total cholesterol levels. Results: The meta-analysis concludes positive effects of astaxanthin (6–20 mg/d) on HDL-C (0.4200; 95% CI: 0.1081 to 0.7319) and triglyceride (−0.3058; 95% CI: −0.5138 to −0.0978) levels. Unfortunately, astaxanthin (6–20 mg/d) does not appear to significantly influence LDL-C (−0.0725; 95% CI: −0.3070 to 0.1620) and total cholesterol (−0.0448; 95% CI: −0.3369 to 0.2473) levels. Regarding HDL-C, improvements were observed from 55 ± 8 mg/dL (pre-intervention) to 63 ± 8 mg/dL (post-intervention) (p < 0.01) in the 12 mg/d of astaxanthin groups. In the assessment of triglyceride levels, results show a decrease from 151 ± 26 mg/dL (pre-intervention) to 112 ± 40 mg/dL (post-intervention) (p < 0.01) for 18 mg/d astaxanthin supplementation. Conclusions: Further research is necessary to fully harness the potential of astaxanthin, which includes assessing astaxanthin in different subsets of patients, using a GWAS, and in combination with other nutraceuticals to understand the compound’s effectiveness with regard to varying health conditions, genetic and epigenetic factors, and synergistic effects with other compounds. Full article

Background and Objectives: Despite significant advances in surgical techniques and perioperative care, major adverse cardiovascular events (MACE) remain a leading cause of postoperative morbidity and mortality in patients undergoing coronary artery bypass grafting and/or aortic valve replacement. Accurate preoperative risk stratification is essential yet often limited by models that overlook atrial mechanics and underutilized biomarkers. Materials and Methods: This study aimed to develop an interpretable machine learning model for predicting perioperative MACE by integrating clinical, biochemical, and echocardiographic features, with a particular focus on novel physiological markers. A retrospective cohort of 131 patients was analyzed. An Extreme Gradient Boosting (XGBoost) classifier was trained on a comprehensive feature set, and SHapley Additive exPlanations (SHAPs) were used to quantify each variable’s contribution to model predictions. Results: In a stratified 80:20 train–test split, the model initially achieved an AUC of 1.00. Acknowledging the potential for overfitting in small datasets, additional validation was performed using 10 independent random splits and 5-fold cross-validation. These analyses yielded an average AUC of 0.846 ± 0.092 and an F1-score of 0.807 ± 0.096, supporting the model’s stability and generalizability. The most influential predictors included total atrial conduction time, mitral and tricuspid annular orifice areas, and high-density lipoprotein (HDL) cholesterol. These variables, spanning electrophysiological, structural, and metabolic domains, significantly enhanced discriminative performance, even in patients with preserved left ventricular function. The model’s transparency provides clinically intuitive insights into individual risk profiles, emphasizing the significance of non-traditional parameters in perioperative assessments. Conclusions: This study demonstrates the feasibility and potential clinical value of combining advanced echocardiographic, biochemical, and machine learning tools for individualized cardiovascular risk prediction. While promising, these findings require prospective validation in larger, multicenter cohorts before being integrated into routine clinical decision-making. Full article

Obesity is currently one of the most critical public health problems. Although there is no doubt that obesity is a significant risk factor for developing metabolic disorders, this relationship is not completely straightforward. On the one hand, some patients affected by obesity are metabolically unhealthy, while others are metabolically healthy; on the other hand, metabolic syndrome (MetS) can also occur in people with a normal body weight. A commonly used tool for diagnosing obesity is the body mass index (BMI), but the search for better anthropometric measures is ongoing due to the significant limitations of this measure. Obesity can lead to MetS and cardiovascular diseases (CVDs). Adipose tissue dysfunction is the fundamental mechanism linking obesity and cardiometabolic diseases, which is rooted in the disturbed secretion of adipokines. The visceral adiposity index (VAI) is calculated based on the BMI, waist circumference (WC), blood triglycerides (TG), and high-density lipoprotein cholesterol (HDL-C) concentrations. It was proposed in 2010 by Amato et al. as a parameter indicating adipose tissue dysfunction and cardiometabolic risk. According to the research conducted so far, some data confirm a relationship between the VAI value and the risk of developing prediabetes, diabetes, insulin resistance, fatty liver disease, MetS, CVD, and chronic kidney disease. Further research is needed to support the implementation of VAI assessment in routine clinical practice. The purpose of this paper is to present the results of a narrative literature review summarizing current knowledge regarding the VAI and its usefulness in clinical practice for assessing cardiometabolic risk. Full article

Background and aim: Low-density lipoprotein cholesterol (LDL-C) is an important and well-established modifiable risk factor for cardiovascular disease, including peripheral artery disease (PAD). We aimed at evaluating the lipid profile at admission in PAD patients with an indication for invasive treatment. Methods: Among patients with PAD diagnosis admitted to the vascular surgery department, those receiving statins and those with LDL-C values in the recommended target (<55 mg/dL) were identified. The correlation of LDL-C values with different clinical variables was investigated. Results: Of the 399 patients, 259 (65%) were on statin therapy. According to multivariate linear regression analysis, diabetes (p = 0.004), previous CAD history (p < 0.001), and statin therapy (p < 0.001) were independently associated with LDL-C levels. Patients with LDL-C < 55 mg/dL at admission were 89 (22% of the overall cohort). Among these patients, diabetes (48.3% versus 35.8%, p = 0.036), CAD history (52.8% versus 30%, p < 0.001), and statin use (91% versus 57.4%, p < 0.001) were more frequent as compared with patients not at target. Conclusion: Despite the very high cardiovascular risk of our group, the rate of statin prescription was very low and far from ideal. Only a small percentage of patients achieved target LDL-C values. Patients with coexistent diabetes and CAD had lower LDL-C values, suggesting management by specialists with greater attention to lipid profile and pointing out an urgent need for information on cardiovascular disease management. Full article