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作 者:黄晶晶 黄素芳 王荃 刘雨晨 张可心 盛晓萱 刘诗雅 Huang Jingjing;Huang Sufang;Wang Quan;Liu Yuchen;Zhang Kexin;Sheng Xiaoxuan;Liu Shiya(Department of Emergency,Tongji Hospital,Tongji Medical College,Huazhong University of Science and Technology,Wuhan 430030,China)
机构地区:[1]华中科技大学同济医学院附属同济医院急诊科,湖北武汉430030 [2]华中科技大学同济医学院护理学院
出 处:《护理学杂志》2024年第18期28-31,共4页Journal of Nursing Science
摘 要:目的了解中青年急性心肌梗死患者的院前症状和就医特征,为医护人员开展针对性健康教育以改善患者就医延迟提供参考。方法根据纳入及排除标准,从医院的医疗大数据平台提取200例中青年急性心肌梗死患者的电子病历数据,对其电子病历中的非结构化文本信息进行文本挖掘,使用词频分析和可视化方法分析患者院前症状和就医情况。结果胸痛和胸闷是中青年急性心肌梗死患者的典型和特异症状,大汗、乏力、心慌等是次常见和次强相关的院前症状。148例患者选择当地就诊后寻求进一步诊治而转诊上级医院。结论中青年急性心肌梗死患者就医前有不同程度的典型症状或非典型症状,患者就医情况与病情有关。医疗大数据平台在操作便利性、数据获取能力方面展现出独特优势,但数据质量需提高。Objective To understand the pre-hospital symptoms and medical-seeking characteristics of young and middle-aged patients with acute myocardial infarction,so as to provide a reference for medical staff conducting targeted health education to improve patient delays in seeking medical attention.Methods Adhering to inclusion and exclusion criteria,electronic medical records of 200 young and middle-aged acute myocardial infarction patients were extracted from the hospital′s medical big data platform.Text mining was performed on the unstructured textual information within the electronic medical records,then frequency analysis and visualization techniques were employed to analyze patients′pre-hospital symptoms and medical-seeking behavior.Results Chest pain and tightness were identified as the typical and specific symptoms of young and middle-aged patients with acute myocardial infarction,while profuse sweating,fatigue,and palpitations were among the less common but strongly related pre-hospital symptoms.A total of 148 patients sought local medical attention and were subsequently referred to higher-level hospitals for further diagnosis and treatment.Conclusion The young and middle-aged patients with acute myocardial infarction exhibit varying degrees of typical and atypical symptoms prior to seeking medical care,and their medical-seeking behavior is related to the severity of their condition.The medical big data platform demonstrates unique advantages in terms of operational convenience and data acquisition capabilities,however,the quality of data still requires improvment.
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