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

Arabi Y, Haddad S, Goraj R, Al-Shimemeri A, Al-Malik S - Crit Care (2002)

Bottom Line: Predicted mortality by all systems was not significantly different from actual mortality [SMR for MPM II0: 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 II24 (C-statistic: 14.71, P = 0.06).The local performance of MPM II24 in addition to its ease-to-use makes it an attractive model for mortality prediction in Saudi Arabia.

View Article: PubMed Central - HTML - PubMed

Affiliation: Consultant ICU Program Director, Critical Care Fellowship, King Fahad National Guard Hospital, Riyadh, Saudi Arabia. yaseenarabi@yahoo.com

ABSTRACT

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 II0: 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 II24 (C-statistic: 14.71, P = 0.06). Discrimination was best for MPM II0 (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 II0 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.

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Receiver operating characteristic (ROC) curves for the four systems.
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Figure 2: Receiver operating characteristic (ROC) curves for the four systems.

Mentions: Figure 2 shows the receiver operating characteristic (ROC) curves for the four systems. The corresponding areas under the curves were as follows: MPM II0, 0.85; MPM II24, 0.84; APACHE II, 0.83; SAPS II, 0.79. These reflect the better discriminative power of the first three systems than that of SAPS II.


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

Arabi Y, Haddad S, Goraj R, Al-Shimemeri A, Al-Malik S - Crit Care (2002)

Receiver operating characteristic (ROC) curves for the four systems.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC111184&req=5

Figure 2: Receiver operating characteristic (ROC) curves for the four systems.
Mentions: Figure 2 shows the receiver operating characteristic (ROC) curves for the four systems. The corresponding areas under the curves were as follows: MPM II0, 0.85; MPM II24, 0.84; APACHE II, 0.83; SAPS II, 0.79. These reflect the better discriminative power of the first three systems than that of SAPS II.

Bottom Line: Predicted mortality by all systems was not significantly different from actual mortality [SMR for MPM II0: 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 II24 (C-statistic: 14.71, P = 0.06).The local performance of MPM II24 in addition to its ease-to-use makes it an attractive model for mortality prediction in Saudi Arabia.

View Article: PubMed Central - HTML - PubMed

Affiliation: Consultant ICU Program Director, Critical Care Fellowship, King Fahad National Guard Hospital, Riyadh, Saudi Arabia. yaseenarabi@yahoo.com

ABSTRACT

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 II0: 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 II24 (C-statistic: 14.71, P = 0.06). Discrimination was best for MPM II0 (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 II0 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.

Show MeSH
Related in: MedlinePlus