EuroSCORE II model - Evidencio
EuroSCORE II model
Calculates the predicted operative mortality for patients undergoing cardiac surgery (c-index: 0.81). The EuroSCORE II model is an improved version of the previously published EuroSCORE I additive model (1999) and the EuroSCORE I logistic model (2003).  
Research authors: Nashef SA, Roques F, Sharples LD, Nilsson J, Smith C, Goldstone AR, Lockowandt U.
Version: 1.18
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  • Cardiology
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Predicted mortality following cardiac surgery:

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The EuroSCORE II model was published in 2012 by Nashef et al and has been validated by the EuroSCORE Project Group as well as users worldwide.1 Previous versions of the EuroSCORE model were the additive EuroSCORE I model2 published by Roques et al in 1999 and the logistic EuroSCORE I model3 published by the same group in 2003. 

In the EuroSCORE II study by Nashef et al (2012), risk-adjusted mortality ratio (RAMR = observed/predicted) for the previous EuroSCORE I additive model was 0.67 and for the previous logistic model 0.53. This suggests that the original EuroSCORE I is now no longer appropriately calibrated, although both the old logistic and additive EuroSCORE I models were found to retain good discrimination.1 

Model performance: 
Calibration of the EuroSCORE II model was tested by applying the final model to the validation data set which contained 5553 patients of whom 232 died in hospital (4.18%). The model-predicted mortality for this data set is 3.95% (slight underprediction). The area under the ROC curve (discriminative power) was 0.81 (95% CI: 0.78–0.83), indicating good discrimination and a trend towards slightly but not significantly better discrimination than the older models.1 


Sources:
1Nashef S, Roques F, Sharples L et al. EuroSCORE II. Eur J Cardiothorac Surg. 2012;41(4): 734-45. 
2Roques F, Nashef SA, Michel P, et al. Risk factors and outcome in European cardiac surgery. Eur J Cardiothorac Surg (1999) 15(6): 816-23.
3Roques F, Michel P, Goldstone AR, Nashef SA. The logistic EuroSCORE. Eur Heart J. 2003 May;24(9):882-3

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