Prognostic scoring helps doctors, patients and their families to weigh the risks and benefits of medical care and clarifies their expectations.
Objective: We aimed to analyze the risk stratification performance of the EuroSCORE system because of its common use in Lithuania.
Design: EuroSCORE performance is assessed in terms of sensitivity, specificity, accuracy and area under the receiver operating characteristic (ROC) curve (AUC). Logistic regression is carried out for modeling categorical data and odds ratio calculations of being a non-survivor case for each EuroSCORE risk group.
Results: The study was completed on 1002 patients. Mean score for EuroSCORE was 4.77 +/- 2.8; ROC curve of 0.71; accuracy was 65.5%; 65.4% sensitivity and 67.2% specificity.
Conclusions: EuroSCORE created a moderately predictive area under the ROC curve for our patient population. Probability of non-survival by logistic regression model for each EuroSCORE risk group is statistically significantly higher compared to the lower risk group. Predictions available from prognostic scoring systems could be useful in decision making when there is uncertainty in whether to carry out surgery or not.