Abstract:Objective To establish a predictive model for acute coronary syndrome(ACS) based on Hs-CRP, HMGB1 and Myo. Methods One hundred ACS patients(ACS group) and 89 healthy subjects(control group) were enrolled in the study. Blood lipids(TC, TG, HDL and LDL), myocardial injury markers(CK-MB, TnT, Myo, hs-TnT and BNP), inflammatory factors(HMGB1 and hs-CRP), polymorphic particles and fasting blood glucose levels were measured and compared between two groups. Logistic regression was used to establish a predictive model for ACS. Results The CK-MB, TnT, Myo, hs-TnT, HMGB1, BNP and hs-CRP levels in ACS group were significantly higher than those in control group(P<0.05). Logistic regression analysis showed that hs-CRP, HMGB1 and CK-MB were the risk factors for ACS(OR=1.95,95%CI: 1.322.55; OR=7.44,95%CI: 6.518.14; OR=3.51,95%CI: 2.334.59), and Myo was the protective factor of ACS(OR=0.17,95%CI: 0.100.35). A predictive model was established based on hs-CRP, HMGB1 and Myo. The area under curve(AUC) of the model was 0.9063, and the positive predictive value and the negative predictive value were 95.24% and 81.82%, respectively. Conclusion Serum hs-CRP, HMGB1 and Myo are of value in early diagnosis of patients with acute coronary syndrome.