A Risk Prediction Model of Readmission after coronary artery bypass grafting (CABG) in China

Abstract

Abstract Background At present, there is no risk prediction model suitable for the Chinese population after coronary artery bypass grafting (CABG), this study aims to analyze the risk factors related to readmission after CABG and to construct a risk prediction model of readmission for patients with CABG in China. Methods A total of 1983 patients who had undergone CABG at Wuhan Asian Heart Hospital from 2017 to 2019 were selected to collect general patient information. Univariate analysis was performed on the data of 825 patients in the modeling group to determine potential risk factors, and then independent risk factors of readmission after CABG were determined by multivariate logistic regression. Hosmer-Lemeshow （H-L） test, calibration curve and the area under the receiver operating characteristic （ROC） curve are used to test the calibration and discrimination of the model. Results Six preoperative variables （age≥65, female, Private insurance, diabetes, hypertension level2,3, congenital heart disease）were independent risk factors of readmission after CABG. Our risk prediction model has high application value （the area under the ROC curve of the modeling group is 0.876, and of the validation group is 0.865, H-L test: P=0.561〉0.05）. Conclusion The risk prediction model in our study can be used to predict the risk of readmission in CABG patients in clinical work, providing a basis for more effective perioperative treatment and care to prevent patients from being readmitted to hospital.