How does EuroSCORE II perform in UK cardiac surgery; an analysis of 23 740 patients from the Society for Cardiothoracic Surgery in Great Britain and Ireland National Database

Objective The original EuroSCORE models are poorly calibrated for predicting mortality in contemporary cardiac surgery. EuroSCORE II has been proposed as a new risk model. The objective of this study was to assess the performance of EuroSCORE II in UK cardiac surgery. Design A cross-sectional analysis of prospectively collected multi-centre clinical audit data, from the Society for Cardiothoracic Surgery in Great Britain and Ireland Database. Setting All NHS hospitals, and some UK private hospitals performing adult cardiac surgery. Patients 23 740 procedures at 41 hospitals between July 2010 and March 2011. Main outcome measures The main outcome measure was in-hospital mortality. Model calibration (Hosmere-Lemeshow test, calibration plot) and discrimination (area under receiver operating characteristic curve) were assessed in the overall cohort and clinically defined sub-groups. Results The mean age at procedure was 67.1 years (SD 11.8) and 27.7% were women. The overall mortality was 3.1% with a EuroSCORE II predicted mortality of 3.4%. Calibration was good overall but the model failed the Hosmere-Lemeshow test (p=0.003) mainly due to overprediction in the highest and lowest-risk patients. Calibration was poor for isolated coronary artery bypass graft surgery (Hosmere-Lemeshow, p < 0.001). The model had good discrimination overall (area under receiver operating characteristic curve 0.808, 95% CI 0.793 to 0.824) and in all clinical sub-groups analysed. Conclusions EuroSCORE II performs well overall in the UK and is an acceptable contemporary generic cardiac surgery risk model. However, the model is poorly calibrated for isolated coronary artery bypass graft surgery and in both the highest and lowest risk patients. Regular revalidation of EuroSCORE II will be needed to identify calibration drift or clinical inconsistencies, which commonly emerge in clinical prediction models.