comparison of apache ii and saps ii scoring systems in prediction of critically ill patients’ outcome

introduction: using physiologic scoring systems for identifying high-risk patients for mortality has been considered recently. this study was designed to evaluate the values of acute physiology and chronic health evaluation ii (apache ii) and simplified acute physiologic score (saps ii) models in prediction of 1-month mortality of critically ill patients. methods: the present prospective cross sectional study was performed on critically ill patients presented to emergency department during 6 months. data required for calculation of the scores were gathered and performance of the models in prediction of 1-month mortality were assessed using stata software 11.0. results: 82 critically ill patients with the mean age of 53.45 ± 20.37 years were included (65.9% male). their mortality rate was 48%. mean saps ii (p < 0.0001) and apache ii (p = 0.0007) scores were significantly higher in dead patients. area under the roc curve of saps ii and apache ii for prediction of mortality were 0.75 (95% ci: 0.64 - 0.86) and 0.72 (95% ci: 0.60 - 0.83), respectively (p = 0.24). the slope and intercept of saps ii were 1.02 and 0.04, respectively. in addition, these values were 0.92 and 0.09 for apache ii, respectively. conclusion: the findings of the present study showed that apache ii and saps ii had similar value in predicting 1-month mortality of patients. discriminatory powers of the mentioned models were acceptable but their calibration had some amount of lack of fit, which reveals that apache ii and saps ii are partially perfect.