Assessment of performance of four mortality prediction systems in a Saudi Arabian intensive care unit

INTRODUCTION: The purpose of this study is to assess the performance of Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) II, Mortality Probability Model MPM II(0) and MPM II(24) systems in a major tertiary care hospital in Riyadh, Saudi Arabia. METHODS: The following data were collected prospectively on all consecutive patients admitted to the Intensive Care Unit between 1 March 1999 and 31 December 2000: demographics, APACHE II and SAPS II scores, MPM variables, ICU and hospital outcome. Predicted mortality was calculated using original regression formulas. Standardized mortality ratio (SMR) was computed with 95% confidence intervals (CI). Calibration was assessed by calculating Lemeshow–Hosmer goodness-of-fit C statistics. Discrimination was evaluated by calculating the Area Under the Receiver Operating Characteristic Curves (ROC AUC). RESULTS: Predicted mortality by all systems was not significantly different from actual mortality [SMR for MPM II(0): 1.00 (0.91–1.10), APACHE II: 1.00 (0.8–1.11), SAPS II: 1.09 (0.97–1.21), MPM II(24) 0.92 (0.82–1.03)]. Calibration was best for MPM II(24) (C-statistic: 14.71, P = 0.06). Discrimination was best for MPM II(0) (ROC AUC:0.85) followed by MPM II(24) (0.84), APACHE II (0.83) then SAPS II (0.79). CONCLUSIONS: In our ICU population: 1) Overall mortality prediction, estimated by standardized mortality ratio, was accurate, especially for MPM II(0) and APACHE II. 2) MPM II(24) has the best calibration. 3) SAPS II has the lowest calibration and discrimination. The local performance of MPM II(24) in addition to its ease-to-use makes it an attractive model for mortality prediction in Saudi Arabia.