A Risk Prediction Model of Readmission for Chinese Patients after Coronary Artery Bypass Grafting

Abstract

Background: Predictive models can be used to assess the risk of readmission for patients after coronary artery bypass grafting (CABG). However, the majority of the existing prediction models have been developed based on data of western population. Our objective was to develop and validate a risk prediction model for Chinese patients after CABG. Methods: This study was conducted among 1983 patients who underwent CABG in Wuhan Asian Heart Hospital from January 2017 to October 2019. Pearson's chi-squared and multivariate logistic regression were performed to investigate the risk factors of readmission after CABG. The area under the ROC curve and Hosmer-Lemeshow test were used to validate the discrimination and calibration of the model, respectively. Results: Six risk factors were predictive of readmission: age≥65 years (odds ratio [OR] = 2.19; 95% confidence interval [CI]: 1.11-4.34; P = 0.024),  female (OR = 2.46; 95%CI: 1.26-4.80; P = 0.008), private insurance (OR = 4.23; 95%CI: 1.11-16.11; P = 0.034), diabetes (OR = 2.351; 95%CI: 1.20-4.59; P = 0.012), hypertension (OR = 2.33; 95%CI: 1.16-4.66; P = 0.017), and congenital heart disease (OR = 6.93;95%CI: 2.04-23.52; P = 0.002). The area under the curve c-statistic was 0.876 in the derivation sample and 0.865 in the validation sample. Hosmer-Lemeshow test: P=0.561. Conclusion: The risk prediction model in our study can be used to predict the risk of readmission in Chinese patients after CABG.