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Background and Aims. Non-alcoholic fatty liver disease (NAFLD) and obesity are independently related to an increased risk for atherosclerotic cardiovascular disease (ASCVD), the primary cause of mortality in NAFLD patients. Even though many subjects with NAFLD are normal weight, it still remains uncertain whether their ASCVD risk is of major importance. The aim of this study is to assess and compare the ASCVD risk between lean and obese patients with NAFLD. Methods. Normal weight and obese patients were evaluated between January 2020 and February 2023 and their data was analyzed. NAFLD was diagnosed by vibration-controlled transient elastography (VCTE) with controlled attenuation parameter (CAP) and the American College of Cardiology/American Heart Association guidelines was used to evaluate the ASCVD risk. Results. In the obese group, 104 (63.8%) patients were diagnosed with NAFLD, compared to 32 (12.3%) in the lean population. In comparison to those with obese NAFLD, subjects with lean NAFLD had significantly higher ASCVD scores (mean 15.3% vs 22.7%, p<0.001). Moreover, subjects with lean NAFLD and significant liver fibrosis had a higher risk of ASCVD events, compared to their obese counterparts (OR, 2.51 vs 1.95, p=0.034). Regarding the presence of the components of the metabolic syndrome, the prevalence of type 2 diabetes mellitus was higher the obese group, while changes in the lipid profile and higher systolic blood pressure were more frequently found in lean subjects. Conclusions: Subjects with lean NAFLD had an ASCVD score that were significantly higher than those with obese NAFLD. In both study groups, the presence of significant liver fibrosis was an essential risk factor associated with an ASCVD event, but the effects were more pronounced in lean individuals. [ABSTRACT FROM AUTHOR]

The latest technological progress provided significant changes in the approach of several areas of daily life, healthcare, and research. In this context, there are many solutions based on artificial intelligence (AI) that were designed to provide assistance in repetitive, ultraprecision, and high-performance data analysis tasks. While the benefits of using AI in Medicine are suggestive, they are shadowed by potential limitations based on the perception of the targeted users due to lack of awareness, mistrust, and human versus machine controversy. Thus, we aimed to find the current opinion of the medical workers and students regarding the modern applications of AI in medical care and research. Using an online specialised platform, we conducted a survey addressed to the members of academic and healthcare community. They were invited to answer specific questions evaluating their knowledge on AI, and their availability to accept and use AI-based applications in daily life and profession. Also, they were challenged to identify advantages and weaknesses of AI-based applications in healthcare and medical research. We found that the responses regarding the use of AI-based solutions in daily life and healthcare suggested several differences in awareness. Also, some of the participants identified several possible sources of inequity in receiving medical care when intelligence-based applications were used in decision making demarche. Similarly, despite that AI-based resources could offer high performance solutions to medical care and research consequent to technology progress, the participants pointed out that the main negative outcome of artificial would be the lack of empathy involved in patients' management. AI-based solutions in medical care could offer significant improvements of the medical act and in biomedical research. However, there are still many limitations that should be addressed when adapting AI resources in Medicine. [ABSTRACT FROM AUTHOR]