title: Discriminative Power of EuroSCORE in Predicting Morbidity and Prolonged Hospital Stay in an Iranian Sample Population.
abstract: BACKGROUND
  The EuroSCORE is a simple and rigorous risk stratification model and is, thus, commonly used in predicting the early and late outcomes of cardiac surgery across the world. We aimed to assess the discriminative power of the EuroSCORE model to predict postoperative morbidity and total prolonged length of stay in hospital (LOS) and Intensive Care Unit (ICU) stay in an Iranian group of cardiac surgical population.
  
  
  METHODS
  In a prospective study, the additive EuroSCORE model was applied to 570 patients undergoing isolated coronary artery bypass grafting (CABG) at Tehran Heart Center. The discrimination power of the EuroSCORE model was tested by the area under the receiver operating characteristic (ROC) curve and the calibration by comparing the observed and predicted outcomes across the risk spectrum assessed using the Hosmer-Lemeshow goodness-of-fit test.
  
  
  RESULTS
  The mean age was 59.03 ± 0.73 years and 429 out of the 570 (75.3%) patients were men. The overall morbidity rate was 47.5%. The observed morbidity in the high-risk patients (EuroSCORE > 6) was significantly greater than that in the low-risk patients (EuroSCORE ≤ 6). Furthermore, 51.2% of the patients had LOS beyond 14 days. Both prolonged LOS (> 14 days) and prolonged ICU stay (> 72 hours) were more prevalent in the high-risk group than in the low-risk group. The discriminative power of the EuroSCORE in predicting morbidity, prolonged LOS, and ICU stay was poor with an area under the ROC curve of 0.617, 0.598, and 0.581, respectively. However, this risk score showed good calibrations for morbidity (p value = 0.119), prolonged LOS (p value = 0.958), and prolonged ICU stay (p value = 0.620).
  
  
  CONCLUSIONS
  The EuroSCORE provided inappropriate discrimination in predicting early morbidity and prolonged LOS and ICU stay in our study population. Creating a revised model may enable us to accurately predict outcomes in Iranian CABG patients.
authors.affiliation: Tehran Heart Center, Tehran University of Medical Sciences, Tehran, Iran.
authors.forename: Mahdi
authors.initials: M
authors.lastname: Najafi
authors.affiliation: Tehran Heart Center, Tehran University of Medical Sciences, Tehran, Iran.
authors.forename: Mehrdad
authors.initials: M
authors.lastname: Sheikhvatan
authors.affiliation: Tehran Heart Center, Tehran University of Medical Sciences, Tehran, Iran.
authors.forename: Mahmood
authors.initials: M
authors.lastname: Sheikhfathollahi
keywords: Coronary artery bypass • Risk assessment • ROC curve