J Res Med Sci
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Aluminum phosphate (ALP) poisoning has a high mortality rate (MR) secondary to cardiogenic shock. Recently, extracorporeal membrane oxygenation (ECMO) showed a successful result in this issue. We conducted a systematic review and meta-analysis to compare the MR of patients with ALP poisoning who underwent ECMO versus those with conventional treatment. ⋯ ECMO reduced the MR of ALP-poisoned patients; however, it is a highly invasive and complicated procedure.
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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.
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The data on the association between alcohol intake and sleep quality in a community-based setting are lacking. This study examined overall sleep difficulty according to alcohol habits among Korean adults. ⋯ Alcohol consumption is associated with increased sleep difficulties, especially in younger adults and women, underscoring the need for targeted interventions and in-depth research on the effects of alcohol on sleep.
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The study aimed to detect the association between insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2) and interleukin-6 (IL-6) polymorphisms among type 2 diabetes mellitus (T2DM). ⋯ The current study indicated that IGF2BP2 rs4402960 and IL-6 rs1800795 polymorphism were highly significantly associated with the increased risk of obese T2DM among the Saudi Arabian population and presented a genetic model to screen the high-risk individuals with further validations.
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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.