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

Abstract Background 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.