Performance of Four Risk Algorithms in Predicting Intermediate Survival in Patients Undergoing Aortic Valve Replacement

Abstract

Objective

Several risk models exist to predict operative outcomes after cardiac surgery and are used in selecting patients for alternative procedures such as transcatheter valve implantation. We sought to evaluate the performance of the Society of Thoracic Surgeons Predicted Risk of Mortality (STS-PROM) model in accurately identifying patients at high risk for aortic valve replacement (AVR).

Methods

Three hundred and ninety four consecutive patients who underwent isolated AVR from January 1, 2001, to July 1, 2007, at a tertiary care center were analyzed using the STS database. Patients were stratified into tertiles according to operative surgical risk calculated by the four models [STS-PROM, European system for cardiac operative risk evaluation (EuroSCORE), Ambler, and Providence]. Vital status at 1 year was determined using the National Death Index and Social Security Death Index.

Results

There were 310 low-risk patients, 56 intermediate-risk patients, and 28 high-risk patients with respect to the STS-PROM. The predicted risk of death for the low-risk, intermediate-risk, and high-risk groups were 2.4% ± 1.1%, 6.9% ± 1.4%, 15.8% ± 7.6% (P < 0.001) with respect to the STS-PROM model. Actual operative mortality for each respective group was 1.94%, 5.36%, 14.29% (P < 0.001) and 1-year mortality was 3.23%, 12.50%, 21.43% (P < 0.001), respectively.

Conclusions

High-risk patients have significantly high mortality after AVR. The STS-PROM accurately predicts operative mortality and can be used to predict 1-year survival as well. This risk model may be preferentially used instead of the EuroSCORE.