Abstract: Objective To investigate the independent risk factors of major adverse cardiac events (MACEs) in patients with acute coronary syndrome (ACS) 1 year after percutaneous coronary intervention (PCI), and to establish a risk prediction model.Methods A retrospective study was conducted. A total of 271 ACS patients diagnosed in one tertiary gradeA hospital in Weifang receiving 1-year postoperative follow-up were divided into model group(n=190) and validation group (n=81) and the model group was sub-divided into MACE group (n=61) and non-MACE group(n=129). The risk factors in MACE group and non-MACE group were compared and the risk prediction model was established. The prediction effect was assessed using the area under the ROC curve, and 81 patients in validation group were selected to validate the prediction effect of the model.Results Univariate and multivariate analysis showed that left main artery disease, hypertension, smoking history, number of stents implanted, low density lipoprotein, neutrophils and hemoglobin were independent risk factors for MACEs. The predictive model was P=e^x/(1+e^x), X=-7.476+2.352×left main disease+2.061×hypertension +1.479× smoking history +1.036×number of stent implantation +3.526×low-density lipoprotein +1.096×neutrophil-0.487×hemoglobin. The area under ROC curve of this model was 0.718 [95%CI (0.629~0.807), P< 0.001]; the sensitivity 62.3%; the specificity 79.7%; and the Jorden index 0.420. The area under ROC curve was 0.756 [95%CI (0.682~0.830), P<0.001] and the sensitivity, specificity and accuracy were 89.5%, 85.0% and 81.4% respectively.Conclusion The prediction model constructed in this study has a good effect, which can identify the risk factors of MACEs in patients with ACS 1 year after PCI, and provide reference for clinical medical staff to carry out risk management.

Key words: acute coronary syndrome, PCI postoperative, MACE, risk factor, risk prediction model