The importance of independent risk-factors for long-term mortality prediction after cardiac surgery

Backround The purpose of the present study was to determine independent predictors for long-term mortality after cardiac surgery. The European System for Cardiac Operative Risk Evaluation (EuroSCORE) was developed to score in-hospital mortality and recent studies have shown its ability to predict long-term mortality as well. We compared forecasts based on EuroSCORE with other models based on independent predictors. Methods Medical records of patients with cardiac surgery who were discharged alive (n = 4852) were retrospectively reviewed. Their operative surgical risks were calculated according to EuroSCORE. Patients were randomly divided into two groups: training dataset (n = 3233) and validation dataset (n = 1619). Long-term survival data (mean follow-up 5.1 years) were obtained from the National Death Index. We compared four models: standard EuroSCORE (M1); logistic EuroSCORE (M2); M2 and other preoperative, intra-operative and post-operative selected variables (M3); and selected variables only (M4). M3 and M4 were determined with multivariable Cox regression analysis using the training dataset. Results The estimated five-year survival rates of the quartiles in compared models in the validation dataset were: 94.5%, 87.8%, 77.1%, 64.9% for M1; 95.1%, 88.0%, 80.5%, 64.4% for M2; 93.4%, 89.4%, 80.8%, 64.1% for M3; and 95.8%, 90.9%, 81.0%, 59.9% for M4. In the four models, the odds of death in the highest-risk quartile was 8.4-, 8.5-, 9.4- and 15.6-fold higher, respectively, than the odds of death in the lowest-risk quartile (P < 0.0001 for all). Conclusions EuroSCORE is a good predictor of long-term mortality after cardiac surgery. We developed and validated a model using selected preoperative, intra-operative and post-operative variables that has better discriminatory ability.