Arch Iran Med
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Today, cardiovascular disease (CVD) is the most important cause of death around the world. In this study, our main aim was to predict CVD using some of the most important indicators of this disease and present a tree-based statistical framework for detecting CVD patients according to these indicators. ⋯ Given the superior performance of the GLMM tree compared with the standard tree and the lack of significant difference with the GLMM, using this model is suggested due to its simpler interpretation and fewer assumptions. Using updated statistical models for more accurate CVD prediction can result in more precise frameworks to aid in proactive patient detection planning.
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Infective endocarditis (IE), a severe and economically impactful condition, lacks substantial epidemiological data in the North Africa and Middle East (NAME) region. This study focused on analyzing the trends and burden of IE in NAME from 1990 to 2019, taking into account factors like age, gender, and socio-demographic index (SDI). ⋯ This study highlights the changing epidemiology of IE in the NAME region, recommending the establishment of multidisciplinary IE registries, antibiotic prophylaxis guidelines for healthcare-associated IE, and strategies to control antimicrobial resistance as key mitigation measures.
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Acute appendicitis is known as the most common diagnosis of acute abdomen leading to surgery. Therefore, timely diagnosis is of special importance. This study was conducted with the aim of pathological assessment of the appendix in appendectomies performed in children to determine the rate of negative appendectomies and the predictors of negative appendectomy and to evaluate the paraclinical tools used in the diagnosis of acute appendicitis. ⋯ A relatively significant number of accidental and negative appendectomies are performed. More careful investigation and the use of expectant and medical treatment instead of surgery, especially in females and young children, can be effective in improving diagnostic accuracy and preventing negative appendectomies.