An In-hospital Mortality Risk Model for Patients Undergoing Coronary Artery Bypass Grafting in China

Abstract

Background: To meet the demand of increasing surgical volume and changing of patient's risk profiles of coronary artery bypass grafting in China, we developed a new risk model that predicts in-hospital mortality.

Methods: The analysis included patients who underwent coronary artery bypass grafting between January 2013 and December 2016 at 87 hospitals in the Chinese Cardiac Surgery Registry. Patients in years 2013 to 2015 were randomly divided into training (n = 31,297 [75%]) and test (n = 10,432 [25%]) samples; 2016 patients (n = 15047) comprised the validation sample. Demographic and clinical risk factors were identified. The Harrell C statistic was used to evaluate model discrimination, and the Hosmer-Lemeshow goodness-of-fit test was used to assess calibration.

Results: The 56,776 patients were a mean age of 61.8 (SD, 8.8) years, and 24.6% were women. Overall, in-hospital mortality was 2.1%. The final model included 21 risk factors represented by 16 unique variables. The model achieved good discrimination, with a C statistic of 0.79 (95% confidence interval [CI], 0.77-0.80) in the training sample, 0.79 (95% CI, 0.76-0.82) in the test sample, and 0.78 (95% CI, 0.76-0.81) in the validation sample. Model calibration was good according to the Hosmer-Lemeshow test (P > .05 in the 3 samples). Compared with the European System for Cardiac Operative Risk Evaluation 2011 revision (EuroSCORE II) and the Sino(Chinese) System for Coronary artery bypass grafting Operative Risk Evaluation (SinoSCORE), the model had better discrimination and calibration.

Conclusions: We developed and evaluated a model with 16 risk factors that predicted in-hospital mortality risk after coronary artery bypass grafting in China. This updated model may help surgeons and hospitals better identify high-risk patient.