Literature DB >> 3111789

A comparison of methods to predict mortality of intensive care unit patients.

S Lemeshow, D Teres, J S Avrunin, H Pastides.   

Abstract

This paper presents results of the first study explicitly designed to compare three methods for predicting hospital mortality of ICU patients: the Acute Physiology Score (APS), the Simplified Acute Physiology Score (SAPS), and the Mortality Prediction Model (MPM). With respect to sensitivity, specificity, and total correct classification rates, these methods performed comparably on a cohort of 1,997 consecutive ICU admissions. In these patients from a single hospital, the APS overestimated and the SAPS underestimated the probability of hospital mortality. The MPM probabilities most closely matched the observed outcomes. Each method holds considerable promise for assessing the severity of illness of critically ill patients. The MPM should be particularly useful for comparing ICU performance, since it is independent of ICU treatment and can be calculated at the time a patient is admitted.

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Year:  1987        PMID: 3111789     DOI: 10.1097/00003246-198708000-00001

Source DB:  PubMed          Journal:  Crit Care Med        ISSN: 0090-3493            Impact factor:   7.598


  16 in total

1.  A new scoring system for disease intensity in a surgical intensive care unit.

Authors:  P Lehmkuhl; S Jeck-Thole; I Pichlmayr
Journal:  World J Surg       Date:  1989 May-Jun       Impact factor: 3.352

Review 2.  Scoring and outcome audit systems relevant to emergency medicine.

Authors:  M Waters; P Nightingale
Journal:  Arch Emerg Med       Date:  1990-03

3.  Evaluation of paediatric intensive care in a regional centre.

Authors:  J McAloon; P Crean; J Jenkins; G McClure
Journal:  Arch Dis Child       Date:  1991-09       Impact factor: 3.791

4.  The performance of SAPS II in a cohort of patients admitted to 99 Italian ICUs: results from GiViTI. Gruppo Italiano per la Valutazione degli interventi in Terapia Intensiva.

Authors:  G Apolone; G Bertolini; R D'Amico; G Iapichino; A Cattaneo; G De Salvo; R M Melotti
Journal:  Intensive Care Med       Date:  1996-12       Impact factor: 17.440

5.  Measuring health and health state preferences among critically ill patients.

Authors:  X Badia; A Díaz-Prieto; M Rué; D L Patrick
Journal:  Intensive Care Med       Date:  1996-12       Impact factor: 17.440

6.  Contribution of non-neurologic disturbances in acute physiology to the prediction of intensive care outcome after head injury or non-traumatic intracranial haemorrhage.

Authors:  M M Niskanen; A Kari; J A Hernesniemi; M P Vapalahti; E Iisalo; L Kaukinen; V Rauhala; E Saarela; P Nikki
Journal:  Intensive Care Med       Date:  1994-11       Impact factor: 17.440

7.  European attitudes towards ethical problems in intensive care medicine: results of an ethical questionnaire.

Authors:  J L Vincent
Journal:  Intensive Care Med       Date:  1990       Impact factor: 17.440

Review 8.  Trends from the United States with end of life decisions in the intensive care unit.

Authors:  D Teres
Journal:  Intensive Care Med       Date:  1993       Impact factor: 17.440

9.  Characterization of intensive care unit patients using a model based on the presence or absence of organ dysfunctions and/or infection: the ODIN model.

Authors:  J Y Fagon; J Chastre; A Novara; P Medioni; C Gibert
Journal:  Intensive Care Med       Date:  1993       Impact factor: 17.440

10.  Microalbuminuria: An inexpensive, non invasive bedside tool to predict outcome in critically ill patients.

Authors:  Surupa Basu; S Chaudhuri; M Bhattacharyya; T K Chatterjee; S Todi; A Majumdar
Journal:  Indian J Clin Biochem       Date:  2010-05-27
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