Literature DB >> 26621265

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

Kwok M Ho1, Teresa A Williams2, Yusra Harahsheh3, Thomas L Higgins4.   

Abstract

PURPOSE: This study compared the performance of 3 admission prognostic scores in predicting hospital mortality.
MATERIALS AND METHODS: Patient 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 RESULTS: Of 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.
CONCLUSIONS: All 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.

Entities:  

Keywords:  Outcome; Prediction; Prognosis; Risk adjustment; Severity of illness

Mesh:

Year:  2015        PMID: 26621265     DOI: 10.1016/j.jcrc.2015.10.019

Source DB:  PubMed          Journal:  J Crit Care        ISSN: 0883-9441            Impact factor:   3.425


  6 in total

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2.  Derivation and Validation of a Novel Physiological Emergency Surgery Acuity Score (PESAS): Reply.

Authors:  Naveen Sangji; David Chang; Haytham M A Kaafarani
Journal:  World J Surg       Date:  2018-05       Impact factor: 3.352

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5.  A comparison of prognostic significance of strong ion gap (SIG) with other acid-base markers in the critically ill: a cohort study.

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6.  Effect of non-linearity of a predictor on the shape and magnitude of its receiver-operating-characteristic curve in predicting a binary outcome.

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