The goal of this study is to summarize valvular surgery data from the Chinese Cardiac Surgery Registry (CCSR) and compare it to the most recent data from the Society of Thoracic Surgeons (STS). From 2016 to 2018, a total of 34,386 cases of the seven most common valvular surgical procedures was obtained from the CCSR. We calculated the proportions of different procedures in the CCSR cohort (n = 34,386) as well as the change in operation volume for each procedure. We also compiled rates of postoperative in-hospital mortality and five major complications across all procedures. All of the results were compared to the STS data. The CCSR and STS data showed divergent trends in valvular heart disease features and operation volume. Although the proportion of MV repair in the CCSR (13.7%) data was lower than in the STS data (23.2%), it demonstrated a substantial upward trend. In terms of operation volume, the CCSR data showed an upward trend, but the STS data showed a downward trend. CCSR procedures showed lower mortality (2% vs. 2.6%), reoperation (2.8% vs. 4.3%), and permanent stroke (0.5% vs. 1.6%) rates than STS procedures but higher rates of prolonged ventilation (22.4% vs. 10.4%) and renal failure (5.6% vs. 3.2%). Valvular surgery quality in China’s leading cardiac hospitals is roughly comparable to that in the United States. China, on the other hand, has some shortcomings that need improvement.

Aims To characterize surgical valvular heart diseases (VHDs) in China and disclose regional variations in VHD surgeries by analyzing the data derived from the Chinese Cardiac Surgery Registry (CCSR). Methods and results From January 2016 to December 2018, we consecutively collected the demographic information, clinical characteristics and outcomes of 38,131 adult patients undergoing valvular surgery in China. We sought to assess the quality of VHD surgery by examining in-hospital deaths of all patients from 7 geographic regions. Using a hierarchical generalized linear model, we calculated the risk-standardized mortality rate (RSMR) of each region. By comparing VHD characteristics and RSMRs, we pursued an investigation into regional variations. The mean age was 54.4 ± 12.4 years, and 47.2% of the patients were females. Among cases, the number of aortic valve surgeries was 9361 (24.5%), which was less than that of mitral valve surgeries (n = 14,506, 38.0%). The number of concurrent aortic and mitral valve surgeries was 6984 (18.3%). A total of 4529 surgical VHD patients (11.9%) also underwent coronary artery bypass grafting (CABG) surgery. The overall in-hospital mortality rate was 2.17%. The lowest RSMR, 0.91%, was found in the southwest region, and the highest RSMR, 3.99%, was found in the northeast. Conclusion Although the overall valvular surgical mortality rate in large Chinese cardiac centers was in line with high-income countries, there were marked regional variations in the characteristics and outcomes of surgical VHD patients across China.

Background: To preferably evaluate and predict the risk for in-hospital mortality in elderly patients receiving cardiac valvular surgery, we developed a new prediction model using least absolute shrinkage and selection operator (LASSO)-logistic regression and machine learning (ML) algorithms. Methods: Clinical data including baseline characteristics and peri-operative data of 7163 elderly patients undergoing cardiac valvular surgery from January 2016 to December 2018 were collected at 87 hospitals in the Chinese Cardiac Surgery Registry (CCSR). Patients were divided into training (N = 5774 [80%]) and testing samples (N = 1389 [20%]) according to their date of operation. LASSO-logistic regression models and ML models were used to analyze risk factors and develop the prediction model. We compared the discrimination and calibration of each model and EuroSCORE II. Results: A total of 7163 patients were included in this study, with a mean age of 69.8 (SD 4.5) years, and 45.0% were women. Overall, in-hospital mortality was 4.05%. The final model included seven risk factors: age, prior cardiac surgery, cardiopulmonary bypass duration time (CPB time), left ventricular ejection fraction (LVEF), creatinine clearance rate (CCr), combined coronary artery bypass grafting (CABG) and New York Heart Association (NYHA) class. LASSO-logistic regression, linear discriminant analysis (LDA), support vector classification (SVC) and logistic regression (LR) models had the best discrimination and calibration in both training and testing cohorts, which were superior to the EuroSCORE II. Conclusions: The mortality rate for elderly patients undergoing cardiac valvular surgery was relatively high. LASSO-logistic regression, LDA, SVC and LR can predict the risk for in-hospital mortality in elderly patients receiving cardiac valvular surgery well.