Literature DB >> 1569623

Comparison of APACHE II, TRISS, and a proposed 24-hour ICU point system for prediction of outcome in ICU trauma patients.

M J Vassar1, C L Wilkerson, P J Duran, C A Perry, J W Holcroft.   

Abstract

The APACHE II system for predicting outcomes in critically ill patients is now being used to evaluate quality of care for patients in surgical intensive care units, including trauma patients. The trauma data, however, on which the APACHE outcomes are based, were derived from only 364 ICU trauma patients. We compared the outcome predictions by APACHE II, TRISS, and a proposed 24-hour ICU point system in 1,000 ICU patients. [table: see text] p less than 0.025 by unpaired t test for predictive power of ICU point system versus APACHE II. Values of more than 15.5 represent poor agreement between the outcomes estimated from the model and the observed outcomes; a low value represents good agreement. The APACHE system significantly overestimated the risk of death in the lower ranges of predicted risk and underestimated the deaths in the higher ranges. Although TRISS was not developed for ICU trauma patients, it tended to perform better than APACHE II in our sample. The 24-hour ICU point system performed well, with accurate agreement between the outcomes estimated from the model and the observed outcomes.

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Year:  1992        PMID: 1569623     DOI: 10.1097/00005373-199204000-00014

Source DB:  PubMed          Journal:  J Trauma        ISSN: 0022-5282


  10 in total

1.  Evaluation of trauma care: validation of the TRISS method in an Italian ICU.

Authors:  U Corbanese; C Possamai; L Casagrande; P Bordino
Journal:  Intensive Care Med       Date:  1996-09       Impact factor: 17.440

2.  Aspergillus infections in transplant and non-transplant surgical patients.

Authors:  Stephen Davies; Christopher Guidry; Amani Politano; Laura Rosenberger; Matthew McLeod; Tjasa Hranjec; Robert Sawyer
Journal:  Surg Infect (Larchmt)       Date:  2014-05-05       Impact factor: 2.150

3.  Using an Artificial Neural Networks (ANNs) Model for Prediction of Intensive Care Unit (ICU) Outcome and Length of Stay at Hospital in Traumatic Patients.

Authors:  Changiz Gholipour; Fakher Rahim; Abolghasem Fakhree; Behrad Ziapour
Journal:  J Clin Diagn Res       Date:  2015-04-01

4.  Epidemiologic aspects and results of applying the TRISS methodology in a Spanish trauma intensive care unit (TICU).

Authors:  J R Suárez-Alvarez; J Miquel; F J Del Río; P Ortega
Journal:  Intensive Care Med       Date:  1995-09       Impact factor: 17.440

5.  Does it Matter if we get it right? Impact of appropriateness of empiric antimicrobial therapy among surgical patients.

Authors:  Stephen W Davies; Jimmy T Efird; Christopher A Guidry; Tjasa Hranjec; Rosemarie Metzger; Brian R Swenson; Robert G Sawyer
Journal:  Shock       Date:  2014-09       Impact factor: 3.454

6.  The ability of two scoring systems to predict in-hospital mortality of patients with moderate and severe traumatic brain injuries in a Moroccan intensive care unit.

Authors:  Hicham Nejmi; Houssam Rebahi; Aziz Ejlaidi; Taoufik Abouelhassan; Mohamed Abdenasser Samkaoui
Journal:  Indian J Crit Care Med       Date:  2014-06

7.  Performance assessment of the SOFA, APACHE II scoring system, and SAPS II in intensive care unit organophosphate poisoned patients.

Authors:  Yong Hwan Kim; Jung Hoon Yeo; Mun Ju Kang; Jun Ho Lee; Kwang Won Cho; SeongYoun Hwang; Chong Kun Hong; Young Hwan Lee; Yang Weon Kim
Journal:  J Korean Med Sci       Date:  2013-11-26       Impact factor: 2.153

8.  Acute Physiology and Chronic Health Evaluation (APACHE) III Score compared to Trauma-Injury Severity Score (TRISS) in Predicting Mortality of Trauma Patients.

Authors:  Parvin Darbandsar Mazandarani; Kamran Heydari; Hamidreza Hatamabadi; Parvin Kashani; Yasin Jamali Danesh
Journal:  Emerg (Tehran)       Date:  2016

9.  Clustering of trauma patients based on longitudinal data and the application of machine learning to predict recovery.

Authors:  Kostas Stoitsas; Saurabh Bahulikar; Leonie de Munter; Mariska A C de Jongh; Maria A C Jansen; Merel M Jung; Marijn van Wingerden; Katrijn Van Deun
Journal:  Sci Rep       Date:  2022-10-10       Impact factor: 4.996

10.  Acute Physiology and Chronic Health Evaluation II and Simplified Acute Physiology Score II in predicting hospital mortality of neurosurgical intensive care unit patients.

Authors:  Sang-Kyu Park; Hyoung-Joon Chun; Dong-Won Kim; Tai-Ho Im; Hyun-Jong Hong; Hyeong-Joong Yi
Journal:  J Korean Med Sci       Date:  2009-06-12       Impact factor: 2.153

  10 in total

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