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 II0 and MPM II24 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 IIo: 1.00 (0.91-1.10), APACHE II: 1.00 (0.8-1.11), SAPS II: 1.09 (0.97-1.21), MPM II24 0.92 (0.82-1.03)]. Calibration was best for MPM 1121 (C-statistic: 14.71, P = 0.06). Discrimination was best for MPM IIo (ROC AUC:0.85) followed by MPM II24 (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 IIo and APACHE II. 2) MPM II24 has the best calibration. 3) SAPS II has the lowest calibration and discrimination. The local performance of MPM II24 in addition to its ease-to-use makes it an attractive model for mortality prediction in Saudi Arabia.