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山东大学学报 (医学版) ›› 2023, Vol. 61 ›› Issue (1): 86-93.doi: 10.6040/j.issn.1671-7554.0.2022.1086

• 公共卫生与管理学 • 上一篇    

急性心肌梗死智能辅助诊断模型构建及应用

林杨,颜豪森,陈琦,陈裕玺,王玖   

  1. 滨州医学院公共卫生与管理学院, 山东 烟台 264003
  • 发布日期:2023-01-10
  • 通讯作者: 王玖. E-mail:mswj@163.com
  • 基金资助:
    全国统计科学研究项目(2020LY070)

Construction of intelligent auxiliary diagnostic model for acute myocardial infarction

LIN Yang, YAN Haosen, CHEN Qi, CHEN Yuxi, WANG Jiu   

  1. School of Public Health and Management, Binzhou Medical University, Yantai 264003, Shandong, China
  • Published:2023-01-10

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摘要： 目的 探讨利用患者临床表现和常规实验室检测指标构建急性心肌梗死智能辅助诊断模型及应用,为基层医院急性心肌梗死(AMI)计算机辅助诊断提供参考依据。 方法 回顾性分析烟台市某三甲医院2018—2020年心肌梗死可疑患者207例,经金标准冠状动脉造影诊断后,心肌梗死确诊患者107例(病例组),非心肌梗死患者100例(对照组)。在单因素分析基础上,采用Lasso-Logistic回归方法建立模型,采用10折交叉验证法进行验证。 结果 肌酸激酶同工酶、C反应蛋白、心电图异常、持续性的胸骨后或心前区压榨性疼痛、恶心呕吐作为AMI诊断的独立影响因素构建预测模型,ROC曲线下面积(AUC)为0.903, 95%CI为0.896~0.944,敏感度、特异度分别为0.910、0.794,10折交叉验证AUC为0.825。 结论 本模型在诊断正确率得到保障的情况下,模型指标易获取、费用节省,适用于早期筛检疾病及二次心梗监测。

关键词: 急性心肌梗死, 辅助诊断, 基层医院, 诊断费用

Abstract: Objective To explore the use of patients clinical manifestations and conventional laboratory test indexes to construct an intelligent auxiliary diagnostic model of acute myocardial infarction(AMI)and its application, so as to provide reference to computer-aided diagnosis of AMI in primary hospitals. Methods The clinical data of 207 suspected AMI patients treated in a tertiary hospital in Yantai during 2018 and 2020 were retrospectively analyzed. After diagnosis by gold standard coronary angiography, 107 patients were confirmed to have AMI(case group)while 100 had not(control group). Based on single factor analysis, Lasso-logistic regression was used to establish a model, which was verified with 10-fold cross-validation. Results Creatine kinase isoenzyme, C-reactive protein, ECG abnormalities, persistent retrosternal or precordial crushing pain, nausea and vomiting were used as independent influencing factors for the diagnosis of AMI to construct the prediction model. The area under the receiver operating characteristic curve(AUC), 95%CI, sensitivity and specificity were 0.903, 0.896-0.944, 0.910 and 0.794, respectively. The AUC of 10-fold cross-validation was 0.825. Conclusion If correct diagnosis is guaranteed, the indicators of this model are easily accessible and cost-saving, and are suitable for early screening of AMI and monitoring of secondary infarction.

Key words: Acute myocardial infarction, Auxiliary diagnosis, Primary hospital, Diagnostic costs

中图分类号: 

  • R542.2
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