| Summary: | Objective To establish and validate a risk prediction model for severe pneumonia following cardiopulmonary bypass (CPB) in children with congenital heart disease. Methods All the children diagnosed with congenital heart disease and treated with CPB surgery in the Department of Thoracic Surgery, Children's hospital of Chongqing Medical University from October 2014 to December 2017 were assigned into the modeling group (n=1 415), while those treated from December 2017 to October 2018 were enrolled into the validation group (n=393). The independent risk factors for severe pneumonia after surgery were screened using univariate and multivariate Logistic regression analysis, and the corresponding nomogram prediction model was constructed according to the regression coefficients. The receiver operating characteristic (ROC) curve and calibration curve were used respectively to evaluate the discriminant validity and calibration of the prediction model. Results The following 5 indicators were revealed to be the independent risk factors for severe pneumonia after CPB surgery: age, weight, preoperative hospital stay, score of Risk Adjustment in Congenital Heart Surgery-1 (RACHS-1) and time of cardiopulmonary bypass. Based on them, an individualized prediction model was established. The area under the curve (AUC) of the prediction model was 0.943 (95%CI: 0.929-0.954) and 0.925 (95%CI: 0.894-0.949) for the modeling and validation groups, indicating good discriminant validity. The P value of the calibration test was 0.592 and 0.256 for the 2 groups. Conclusion Our established individualized prediction model can be well used to evaluate the risk of severe pneumonia in children with congenital heart disease after CPB.
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