Abstract: Objective:To learn about the risk factors for postoperative pulmonary infection in children with congenital heart disease and to construct a risk prediction model.Methods:A retrospective analysis was conducted on the clinical data of 256 children with congenital heart disease,who received treatment in Hunan Children′s Hospital between May 2023 and May 2024.Based on whether pulmonary infection occurred,the children were divided into pulmonary infection group(29 cases) and no infection group(227 cases).Logistic regression was used to analyze the risk factors for postoperative pulmonary infection,and a nomogram prediction model was constructed.The receiver operating characteristic (ROC) curve was plotted to analyze the predictive value of the model for postoperative pulmonary infection in these children.Results:Among the 256 children with congenital heart disease,29 developed pulmonary infection,with an infection rate of 11.33%（29/256）.Multivariate Logistic regression analysis showed that age <3 years,heart function grade≥ Ⅲ,extracorporeal circulation time >100 minutes,complex congenital heart disease,and surgical time > 150 minutes were independent risk factors for postoperative pulmonary infection(all P<0.05).The calibration curve indicated that the constructed nomogram model had good consistency,with a C index of 0.832［95%CI（0.816，0.859）］ and an area under the ROC curve(AUC) of 0.882［95%CI（0.835，0.898）］,suggesting that the nomogram model had good calibration and discrimination.Conclusion:The nomogram prediction model,which is constructed based on independent risk factors for postoperative pulmonary infection in children with congenital heart disease,is helpful to identify the children with high risk of postoperative pulmonary infection and reduce the incidence of postoperative pulmonary infection.It has certain clinical application value.

Key words: Congenital heart disease, Pulmonary infection, Risk factors, Prediction model, Nomogram