J Korean Acad Adult Nurs.  2005 Aug;17(3):464-473.

Comparison of Predict Mortality Scoring Systems for Spontaneous Intracerebral Hemorrhage Patients

Affiliations
  • 1Eulji University Hospital.
  • 2School of Nursing, Eulji University. kek@eulji.ac.kr

Abstract

PURPOSE
The purpose of this study was to evaluate and compare the predictive ability of three mortality scoring systems; Acute Physiology and Chronic Health Evaluation(APACHE) III, Simplified Acute Physiology Score(SAPS) II, and Mortality Probability Model(MPM) II in discriminating in-hospital mortality for intensive care unit(ICU) patients with spontaneous intracerebral hemorrhage. METHODS: Eighty-nine patients admitted to the ICU at a university hospital in Daejeon Korea were recruited for this study. Medical records of the subject were reviewed by a researcher from January 1, 2003 to March 31, 2004, retrospectively. Data were analyzed using SAS 8.1. General characteristic of the subjects were analyzed for frequency and percentage. RESULTS: The results of this study were summarized as follows. The values of the Hosmer-Lemeshow's goodness-of-fit test for the APACHE III, the SAPS II and the MPM II were chi-square H=4.3849 p=0.7345, chi-square H= 15.4491 p=0.0307, and chi-square H=0.3356 p=0.8455, respectively. Thus, The calibration of the MPM II found to be the best scoring system, followed by APACHE III. For ROC curve analysis, the areas under the curves of APACHE III, SAPS II, and MPM II were 0.934, 0.918 and 0.813, respectively. Thus, the discrimination of three scoring systems were satisfactory. For two-by-two decision matrices with a decision criterion of 0.5, the correct classification of three scoring systems were good. CONCLUSION: Both the APACHE III and the MPM II had an excellent power of mortality prediction and discrimination for spontaneous intracerebral hemorrhage patients in ICU.

Keyword

Intensive care; Mortality prediction; Acute Physiology and Chronic Health Evaluation (APACHE); Simplified acute physiology score; Morality probability model
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