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Objective: To identify risk factors and develop multivariate prediction model for short-term mortality after valve surgery in east China.Methods: 1254 patients undergoing valve surgery from January 2014 to December 2015 in a single hospital were included.The included patients were observed for 30 days and a multivariate logistic regression analysis was undertaken to identify independent risk factors for short-term mortality.A prediction model was developed with independent variables according to multivariate logistic regression for patients in east China.The receiver operating characteristic(ROC)curve was performed to verified reliability of the model.Results: A total of 25(2.0%)short-term deaths were recorded.Six preoperative independent variables were identified had relative connection with short-term mortality including NYHA 4(OR=9,72,P=0.001),smoking history(OR=3.33,P=0.006),poor ejection fraction(OR=5.43,P<0.001),previous cardiac surgery(OR=9.72,P=0.001),moderate or severe tricuspid regurgitation(OR=2.85,P=0.016),concomitant CABG(OR=4.94,P=0.013).On the basis of these variables,a prediction model was built.The ROC of the model was 0.80.Conclusion: Independent risk factors of short-term mortality of patients undergoing valve surgery were identified.Based on multivariate logistic regression analysis,we built a preoperative risk assessment model of short-term mortality for the population of east China.This model can help the surgeons to quantitatively evaluate surgical risk for patients with heart valve disease.