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目的探讨研究急诊不典型心肌梗死患者的快速识别方法,以免延误最佳治疗时机。方法回顾分析2012年6月1日至2015年12月31日我院急诊救治的354例初诊不典型急性心肌梗死(AMI)患者的临床资料,对患者的病史、临床症状、心电图、生活习惯等进行数据统计和分析。并对患者年龄、首次诊断时间、医师的专业程度、梗死部位、合并其他疾病等因素行误诊率卡方单因素分析,在此基础上,对可能影响诊断准确率的5个因素行LOGISTC多因素回归分析。结果 354例患者由于症状不典型早期误诊39例,误诊率11.02%;根据单因素和多因素分析结果,年龄、合并其他疾病、医师水平、首诊时间、发生心肌梗死部位均显著影响诊断准确率,均具有统计学意义(p<0.05)。结论不典型急诊心肌梗死患者的早期临床症状多样,诊断时应在掌握全面信息时进行诊断,包括了解患者病史、临床症状、心电图表现、行心肌酶检查等,从而尽早进行急诊处理,减少梗死面积和心肌受损,提高疗效、改善患者预后。
Objective To study the rapid identification of emergency patients with atypical myocardial infarction in order to avoid the delay of the best timing of treatment. Methods The clinical data of 354 patients with newly diagnosed atypical acute myocardial infarction (AMI) admitted to our hospital from June 1, 2012 to December 31, 2015 were retrospectively analyzed. The patient’s medical history, clinical symptoms, electrocardiogram, living habits, etc. Data statistics and analysis. The factors of misdiagnosis rate, such as patient’s age, first diagnosis time, physician’s specialty degree, infarction location and other diseases were analyzed by univariate analysis. Based on this, five factors that may affect the accuracy of diagnosis were analyzed by LOGISTC multi- regression analysis. Results Among the 354 patients, 39 cases were misdiagnosed due to atypical symptoms and the rate of misdiagnosis was 11.02%. According to the results of univariate and multivariate analysis, the accuracy of diagnosis was significantly affected by age, combined with other diseases, physician level, first visit time and myocardial infarction , All with statistical significance (p <0.05). Conclusions The clinical manifestations of patients with atypical acute myocardial infarction are diverse and should be diagnosed at the time of full information, including understanding the patient’s medical history, clinical symptoms, electrocardiogram, and myocardial enzymes examination, so as to conduct emergency treatment as soon as possible and reduce infarct size And myocardial damage, improve efficacy, improve patient prognosis.