Medicine
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This research aimed to examine the effectiveness of artificial intelligence applications in asthma and chronic obstructive pulmonary disease (COPD) outpatient treatment support in terms of patient health and public costs. The data obtained in the research using semiotic analysis, content analysis and trend analysis methods were analyzed with strengths, weakness, opportunities, threats (SWOT) analysis. In this context, 18 studies related to asthma, COPD and artificial intelligence were evaluated. ⋯ Malicious use, commercial data leaks and data security issues stand out among the threats. Although artificial intelligence applications provide great convenience in the outpatient treatment process for asthma and COPD diseases, precautions must be taken on a global scale and with the participation of international organizations against weaknesses and threats. In addition, there is an urgent need for accreditation for the practices to be carried out in this regard.
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This integrated study combines bioinformatics, machine learning, and Mendelian randomization (MR) to discover and validate molecular biomarkers for sepsis diagnosis. Methods include differential expression analysis, weighted gene co-expression network analysis (WGCNA) for identifying sepsis-related modules and hub genes, and functional enrichment analyses to explore the roles of hub genes. Machine learning algorithms identify 3 diagnostic genes - CD177, LDHA, and MCEMP1 - consistently highly expressed in sepsis patients. ⋯ Correlations between diagnostic genes and immune cell infiltration are observed. MR analysis reveals a positive causal relationship between MCEMP1 and sepsis risk. In conclusion, this study presents potential sepsis diagnostic biomarkers, highlighting the genetic association of MCEMP1 with sepsis for insights into early diagnosis.
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To comprehensively analyze the psychological health status of operating room nurses and identify influencing factors. The research compares psychological health differences based on nurses' years of experience, specifically examining depression and anxiety scores. A detailed assessment was conducted, focusing on nurses with varying experience levels. ⋯ The results indicate that the duration of work, previous experience in disaster relief, and nurses' perception of occupational benefits were the main factors influencing the psychological health status of operating room nurses (P < .05). Healthcare institutions are recommended to implement targeted interventions based on nurses' experience levels, addressing specific psychological health needs. Future research should delve into specific subgroups, conduct long-term tracking, expand the scope of influencing factors, assess the effectiveness of intervention measures, and explore cross-cultural aspects.
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Meta Analysis
Effectiveness of Bairui granules in the treatment of respiratory tract infections: A systematic review and meta-analysis.
Respiratory tract infections (RTIs) are characterized by a high mortality rate and clinical incidence. Bairui granules (BG), which employ a method of heat elimination and detoxification, have demonstrated benefits in the treatment of infectious respiratory diseases. ⋯ The effectiveness of treating RTIs using BG alone or in combination with WT was determined to be superior to using WT alone, with no serious adverse effects observed. However, additional RCTs are essential to further confirm the findings of this study.
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Managing postoperative pain effectively with an opioid-free regimen following laparoscopic surgery (LS) remains a significant challenge. Intraperitoneal instillation of ropivacaine has been explored for its potential to reduce acute postoperative pain, but its efficacy and safety are still under debate. This study aimed to evaluate the efficacy and safety of intraperitoneal instillation of ropivacaine for acute pain management following laparoscopic digestive surgery. ⋯ The registration number at PROSPERO was CRD42021279238.