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

Content Provider	Springer Nature : BioMed Central
Author	Arabi, Yaseen Haddad, Samir Goraj, Radoslaw Al-Shimemeri, Abdullah Al-Malik, Salim
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.
Related Links	https://ccforum.biomedcentral.com/counter/pdf/10.1186/cc1477.pdf
Ending Page	9
Page Count	9
Starting Page	1
File Format	HTM / HTML
ISSN	13648535
DOI	10.1186/cc1477
Journal	Critical Care
Issue Number	2
Volume Number	6
Language	English
Publisher	BioMed Central
Publisher Date	2002-03-13
Access Restriction	Open
Subject Keyword	Intensive Critical Care Medicine Emergency Medicine intensive care mortality prediction severity of illness
Content Type	Text
Resource Type	Article
Subject	Critical Care and Intensive Care Medicine
Journal Impact Factor	8.8/2023
5-Year Journal Impact Factor	10.4/2023

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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