AbstractBackground and aim of the study
To compare four risk scores with regard to their validity to predict in-hospital mortality after heart valve surgery in a multicenter patient population of China.Materials and methods
From January 2009 to December 2012, data from 12,412 consecutive patients older than 16 years who underwent heart valve surgery at four cardiac surgical centers were collected and scored according to the EuroSCORE II, Ambler risk score, NYC risk score, and STS risk score. The patients were divided into two subgroups according to the types of valve procedures, and the performance of the four risk scores for each group was assessed. Calibration was assessed by the Hosmer–Lemeshow (H-L) test. Discrimination was tested by calculating the area under the receiver operating characteristic (ROC) curve.Results
Observed mortality was 2.09% overall. The EuroSCORE II, Ambler score, and NYC score overpredicted observed mortality (Hosmer–Lemeshow: P = 0.002, P < 0.0001, and P < 0.0001, respectively) and the STS score underpredicted observed mortality (Hosmer–Lemeshow: P = 0.001). The discriminative power in the entire cohort for in-hospital mortality was highest for the STS score (0.735), followed by the EuroSCORE II score (0.704), NYC score (0.693), and Ambler score (0.674). Meanwhile, the STS score and EuroSCORE II give an accurate prediction in patients undergoing single valve surgery compared with the Ambler score and NYC score. However, all four risk scores give an imprecise prediction in patients undergoing multiple valve surgery.Conclusions
Both the STS score and Euroscore II, especially the STS score, were suitable for individual operative risk in Chinese patients undergoing single valve surgery compared with the Ambler score and NYC score, however, all four risk scores were not suitable for prediction in Chinese patients undergoing multiple valve surgery. Therefore, the creation of a new model which accurately predicts outcomes in patients undergoing multiple valve surgery is possibly required in China.