JOURNAL OF SHANDONG UNIVERSITY (HEALTH SCIENCES) ›› 2013, Vol. 51 ›› Issue (1): 46-.

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Data analysis for the positive rate of selective coronary artery angiography and the risk factors in coronary artery stenosis

FU Shen-shen1, LI Da-qing1, LI Ji-fu1, LIU Bin2, YANG Min1, SHAO Na1   

  1. 1. Department of Cardiology; 2. Department of Radiology, Qilu Hospital of Shandong University, Jinan 250012, China
  • Received:2012-01-21 Online:2013-01-10 Published:2013-01-10

Abstract:

Objective   To evaluate the detection rate of coronary stenosis with coronary angiography (CAG) and analyze the coronary risk factors associated with the coronary stenosis, in order to provide a basis for increasing the CAG-positive detection rate. Methods   The data of patients with CAG test collected from March 2008 to December 2008 in Qilu Hospital of Shandong University were analyzed to observe the positive rate of LM, LAD, LCX and RCA. Chi-square test was used in the categorical data. Multinomial logistic regression analysis was used to evaluate the risk factors related to the coronary stenosis. A discriminate predicting score and receiver operating characteristic curve (ROC) analysis were performed to evaluate the predictive diagnostic sensitivity and specificity. Results   The diameter of coronary artery stenosis (CAS) > 25% was diagnosed as the positive event, and the positive rate of CAG was 64.21%. The positive rate of men with age ≤ 59 was 56.19%, and 32.47% for women with age ≤ 59. The negative rate of women was higher compared with the men. The risk factors associated with CAS were gender, age, diabetes, hypertension, smoking and the blood biochemical indicators including A/G, TBA, TG, HDL, GLU, Cr, FIB and HGB (P<0.05). The sensitivity and specificity were 54.40% and 89.90% based on the predicting score in the discriminate regression and ROC analysis. Conclusion   The risk factors associated with CAS can enhance the detection rate of coronary artery stenosis (CAS).

Key words: Coronary angiography; Coronary stenosis; Positive rate; Risk factors; Prediction

CLC Number: 

  • R543.3
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