• Journal of critical care · Feb 2016

    Comparative Study

    Using patient admission characteristics alone to predict mortality of critically ill patients: A comparison of 3 prognostic scores.

    • Kwok M Ho, Teresa A Williams, Yusra Harahsheh, and Thomas L Higgins.
    • Department of Intensive Care, Royal Perth Hospital, Perth, Australia; School of Population Health, University of Western Australia, Perth, Australia; School of Veterinary & Life Sciences, Murdoch University, Perth, Australia. Electronic address: kwok.ho@health.wa.gov.au.
    • J Crit Care. 2016 Feb 1; 31 (1): 21-5.

    PurposeThis study compared the performance of 3 admission prognostic scores in predicting hospital mortality.Materials And MethodsPatient admission characteristics and hospital outcome of 9549 patients were recorded prospectively. The discrimination and calibration of the predicted risks of death derived from the Simplified Acute Physiology Score (SAPS III), Admission Mortality Prediction Model (MPM0 III), and admission Acute Physiology and Chronic Health Evaluation (APACHE) II were assessed by the area under the receiver operating characteristic curve and a calibration plot, respectively.Measurements And Main ResultsOf the 9549 patients included in the study, 1276 patients (13.3%) died after intensive care unit admission. Patient admission characteristics were significantly different between the survivors and nonsurvivors. All 3 prognostic scores had a reasonable ability to discriminate between the survivors and nonsurvivors (area under the receiver operating characteristic curve for SAPS III, 0.836; MPM0 III, 0.807; admission APACHE, 0.845), with best discrimination in emergency admissions. The SAPS III model had a slightly better calibration and overall performance (slope of calibration curve, 1.03; Brier score, 0.09; Nagelkerke R(2), 0.297) compared to the MPM0 III and admission APACHE II model.ConclusionsAll 3 intensive care unit admission prognostic scores had a good ability to predict hospital mortality of critically ill patients, with best discrimination in emergency admissions.Copyright © 2015 Elsevier Inc. All rights reserved.

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