Benchmarking the prognostic performance of EUROSCORE II with the original EuroSCORE in cardiac surgery patients
Background and Goal of the Study: The European System for Cardiac Operative Risk Evaluation (EuroSCORE) is one of the most documented preoperative risk algorithms for assessing operative morbidity and mortality following cardiac surgery, which has been recently refined to EuroSCORE II, in order to improve the performance of the original EuroSCORE. Aim of this study was to comparably assess the applicability of the updated EuroSCORE II model with the logistic (log) and additive (add) versions of the initial EuroSCORE, in cardiac surgical population, on the basis of morbidity and mortality.

Materials and Methods: Data from a total of 1058 consecutive patients (aged 63.9 ± 9.1 years, male to female ratio: 3.7/1) admitted to our post-cardiac surgery intensive care unit (ICU) following cardiosurgical procedure, were included in this data analysis study. EuroSCORE add, EuroSCORE log and EuroSCORE II were calculated for each participant. The study endpoints were operative mortality (30-day) and morbidity assessed by length of intensive care unit stay (ICU-LOS), using 2-days as cut-off point. For statistical purposes Mann-Whitney test and ROC curve analysis were used as appropriate.
Results: Overall ICU mortality of the study population was 3.3% (n=35). Univariate analysis revealed a significant augmentation (p=0.000) of the studied parameters in patients with ICU-LOS > 2 days and in those with poor outcome. Data from ROC curve analysis are presented in the Table.
Conclusion(s): The findings of the present study substantiate that EuroScore log, EuroSCORE add and EuroSCORE II models, confer noteworthy prognostic value when applied to adult cardiac surgical population, being more pronounced in terms of mortality. The updated EuroSCORE ΙI risk model seems to confer superior discriminatory performance compared to the original EuroSCORE. Thus, the implementation of EuroSCORE II in cardiac ICU could possibly contribute towards risk stratification, mortality prediction and identification of patients who are at increased risk for prolonged ICU stay.