J Res Med Sci
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Malaria, transmitted by Plasmodium parasites and anopheline mosquitoes, continues to be a leading cause of global disease and death. This retrospective investigation from 2018 to 2023 examines the epidemiological attributes of malaria in Saravan, southeastern Iran. It seeks to evaluate the prevalence, transmission causes, local population impact, and health system effects. ⋯ The findings emphasize the persistent malaria challenges in Saravan, accentuating the urgent need to strengthen prevention and control strategies. Reducing disease burden demands focused approaches, including improving prevention and treatment programs, enhancing surveillance systems, developing health infrastructures, and implementing localized therapies, especially considering recent climatic and rainfall patterns.
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Proteinuria is a key indicator of kidney damage in diabetic nephropathy, and its severity correlates with the progression of the disease. In diabetic patients, it is crucial to identify reliable predictors for proteinuria and its severity for early detection and management of kidney damage. ⋯ Overall, this study suggests that some routine laboratory parameters may be associated with proteinuria and its severity in patients with T2DM. NLR, in particular, showed this association in our study, promising future studies evaluating this association and whether it can help as a predictor or not.
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The diagnosis of chronic rhinosinusitis (CRS) is a crucial and challenging entity in bone marrow transplantation candidates. We aimed to evaluate the diagnostic accuracy of the Sino-Nasal Outcome Test (SNOT-22) and Lund-Kennedy endoscopic score for the diagnosis of CRS in bone marrow transplantation candidates. ⋯ The Lund-Kennedy endoscopy score could diagnose CRS in bone marrow transplantation candidates with satisfactory accuracy, whereas SNOT-22 lacks enough accuracy to be employed as an independent sino-nasal assessment modality in these patients.
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The initial assessment of trauma is a time-consuming and challenging task. The purpose of this research is to examine the diagnostic effectiveness and usefulness of machine learning models paired with radiomics features to identify blunt traumatic liver injury in abdominal computed tomography (CT) images. ⋯ The artificial intelligence models used in this study have great potential to improve patient care by assisting radiologists and other physicians in diagnosing and staging trauma-related liver injuries. These models can help prioritize positive studies, allow more rapid evaluation, and identify more severe injuries that may require immediate intervention.
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Diabetic cardiomyopathy (DCM) is a severe complication among patients with Type 2 diabetes, significantly increasing heart failure risk and mortality. Despite various implicated mechanisms, effective DCM treatments remain elusive. This study aimed to construct a comprehensive competing endogenous RNA (ceRNA) network in DCM using bioinformatics analysis. ⋯ The identified hub genes and ceRNA network components provide valuable insights into DCM biology and offer potential diagnostic biomarkers and therapeutic targets for further investigation. Further experimental validation and clinical studies are warranted to translate these findings into clinical applications.