标题：早发急性心肌梗死患者预后影响因素研究

      作者：李美红，朱强锋，陈赛勇，李晓苏
    (北京大学深圳医院心血管内科，广东 深圳 518036)

      卷次： 2013年24卷9期

      【摘要】 目的 探讨早发急性心肌梗死患者预后影响因素，为采取针对性的干预措施提供参考依据。方法 采用
自编问卷收集2010年9月至2011年9月在我院心内科收治的153例早发急性心肌梗死患者的临床资料，采用多因素
Logistic回归分析找出早发急性心肌梗死患者预后影响因素。结果 早发急性心肌梗死患者预后不良率占
17.65%。多因素Logistic回归分析结果显示，B型钠利尿肽水平高(OR=23.086)、高敏肌钙蛋白Ｉ水平高(OR=
5.95)、血清胱抑素C水平高(OR=4.024)、超敏C-反应蛋白水平高(OR=5.185)、N末端B型脑钠尿肽前体水平高
(OR=4.380)和有早发心梗家族史(OR=3.338)是早发急性心肌梗死患者预后欠佳危险因素。结论 早发急性心肌
梗死患者预后总体欠佳，预后受诸多因素影响，应针对各种危险因素采取针对性的措施干预患者病情，改善患者
的预后。

      【关键词】 急性心肌梗死；预后；影响因素

      【中图分类号】 R542.2+2 【文献标识码】 A 【文章编号】 1003—6350（2013）09—1280—03


Study on the influence factors of early acute myocardial infarction.
LI Mei-hong, ZHU Qiang-feng, CHEN Sai-yong,
LI Xiao-su. Department of Cardiology, Peking University Shenzhen Hospital, Shenzhen 518036, Guangdong, CHINA

【Abstract】 Objective To investigate the influential factors of early acute myocardial infarction in order to
provide reference for the specific intervention measures. Methods The clinical data of 153 patients with early acute
myocardial infarction who were treated in the Department of Cardiology in our hospital from September 2010 to Sep-
tember 2011 were collected by the self-made questionnaire. The influential factors of early acute myocardial infarction
were analyzed by binary logistic regression analysis. Results The rate of poor prognosis was 17.65%. Binary logistic
regression analysis showed that high B-type natriuretic peptide (OR=23.086) level, high sensitivity troponin I level
(OR=5.95), high Serum Cys level (OR=4.024), high high sensitivity C-reaction protein level (OR=5.185), high
NT-proBNP level (OR=4.380) and family history of premature heart attack (OR=3.338) were the risk factors of early
acute myocardial infarction. Conclusion The prognosis of patients with early acute myocardial infarction is poor
generally, which is affected by various factors. We should take countermeasures to intervene the disease and improve
the prognosis.

      【Key words】 Acute myocardial infarction; Prognosis; Influence factors