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Value of euroscore II to predict operative mortality in infectious endocarditis surgery
Background:
Stratification of surgical risk is an important step in cardiac surgery, often based on the estimation of operative mortality. The EuroSCORE II (ES II) incorporates several factors in the calculation of mortality, but few are specific to Infectious endocarditis (IE).
Aim:
Our study is aimed to evaluate the predictive power of the Es II in the surgery of IE and to test its discriminating power according to certain specific parameters of the IE.
Methods:
55 surgical procedures were carried out between January 2000 and June 2012 (37 EI on native valves and 18 on prosthesis). The mortality observed was compared with the mortality predicted by Es II. The discriminant capacity of the Es II model was tested using the receiver operating characteristic (ROC) curve model by comparing the areas under the curve (AsC).
Results:
For our cohort The observed mortality was 30.9 % , the mortality predicted by Es II was 10.5%. in general, the EsII discriminatory capacity for mortality was satisfactory: the ROC AsC was 0,76. By analyzing the subgroups of the endocarditis, Es II lost its discriminating power: theROC AsC was: 0.64 for staphylococcal, 0.62 for the annular abscess and 0.56 for endocarditis on prosthesis.
Conclusion:
The EuroSCORE II model has a satisfactory discriminating power in the IE. However, analysis of subgroups leads to decrease in this discriminating power. Thus, some specific parameters of the IE, which do not appear in the EuroSCORE II model, should be taken into accountwhen analyzing mortality.
Related Concept Videos
Endocarditis II: Clinical Features of Infective Endocarditis
Endocarditis I: Introduction
Predicting Molecular Geometry
Endocarditis III: Medical Management
Endocarditis IV: Nursing Management
Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.

