Brit J Hosp Med
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Aims/Background In light of the increased utilization of digital technology among the elderly population, understanding the relationship between e-health literacy, self-identity, social capital, and educational participation motivation has become crucial. This study aims to investigate these relationships and explore the mediating effects of self-identity and social capital on the elderly population. By shedding light on these aspects, the study seeks to contribute to the existing knowledge base and inform intervention strategies to enhance the elderly individuals' overall well-being and engagement with digital health resources. ⋯ Specifically, self-identity and social capital acted as complete mediators, with a mediating effect value of 0.61, between e-health literacy and educational participation motivation. Additionally, the chained mediating effect of self-identity and social capital was also significant. Conclusion This study demonstrated that e-health literacy and educational participation motivation are closely intertwined, with self-identity and social capital acting as the mediators in this association, in the elderly population, providing valuable guidance for enhancing the health and quality of life and offering insightful references for the development and implementation of relevant policies.
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Aims/Background Previous literature has indicated that sarcopenia is related to poor outcomes after radical resection for colorectal cancer (CRC). However, its effect on the postoperative clinical outcomes of CRC remains controversial. This study aimed to elucidate the predictive value of sarcopenia for postoperative complications and survival in CRC patients. ⋯ Sarcopenia was an independent risk factor for poor DFS (hazard ratio (HR) = 1.404; p = 0.016) and OS (HR = 1.290; p = 0.021). Conclusion In CRC patients undergoing radical surgery, sarcopenia is an independent risk factor for postoperative complications. Sarcopenia may be a predictive factor for the prognosis and survival of CRC patients undergoing radical resection.
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Aims/Background Coronary heart disease (CHD) and atrial fibrillation (AF) exhibit a close relationship, yet the existing body of research predominantly relies on observational study methodologies, posing challenges in establishing causal relationships. The objective of our study is to investigate the causal linkages between coronary atherosclerosis (CAAs), angina pectoris, myocardial infarction (MI), and AF. Methods This study utilizes a two-sample Mendelian randomization (TSMR) methodology, leveraging genetic variation as a means of evaluating causality. ⋯ Results The results of our study suggest a genetic predisposition in which CAAs, angina, and MI may enhance susceptibility to AF, while AF may reciprocally elevate the risk of CAAs. Conclusion In light of these findings, it is recommended that patients with CHD undergo regular cardiac rhythm monitoring, and that patients with AF receive anticoagulant and antiplatelet therapy whenever feasible. This study posits a practical implication for clinical practice.
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Aims/Background To investigate the application value of a machine learning model in predicting mild depression associated with migraine without aura (MwoA). Methods 178 patients with MwoA admitted to the Department of Neurology of the First Affiliated Hospital of Anhui University of Traditional Chinese Medicine from March 2022 to March 2024 were selected as subjects. According to their inpatient medical records, 38 patients were selected as the validation group by random number method, and the remaining 140 patients were included in the modelling group. ⋯ The receiver operating characteristic (ROC) analysis results showed that the area under the curve of the established prediction model for MwoA patients with mild depression in the modelling group and the validation group was 0.982 and 0.901, respectively, the sensitivity was 0.978 and 0.857, respectively, and the specificity was 0.892 and 0.929, respectively. Conclusion Gender, course of disease, seizure frequency, headache duration, MIDAS score, and HIT-6 score are independent influencing factors for mild depression in patients with MwoA. The model displays good performance for the prediction of mild depression in patients with MwoA.
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Aims/Background Immunohistochemistry (IHC) is the main method to detect human epidermal growth factor receptor 2 (Her-2) and Ki-67 expression levels. However, IHC is invasive and cannot reflect their expression status in real-time. This study aimed to build radiomics models based on visceral adipose tissue (VAT)'s 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) imaging, and to evaluate the relationship between radiomics features of VAT and positive expression of Her-2 and Ki-67 in gastric cancer (GC). ⋯ Three wavelet transform features were correlated with Her-2 expression status (p all < 0.001), and one wavelet transform feature was correlated with the expression status of Ki-67 (p = 0.042). Conclusion 18F-FDG PET/CT-based radiomics models of VAT demonstrate good performance in predicting Her-2 and Ki-67 expression status in patients with GC. Radiomics features can be used as imaging biomarkers for GC.