Journal of Shandong University (Health Sciences) ›› 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 • Previous Articles    

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

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

CLC Number: 

  • R542.2
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