Literature DB >> 21195582

Cross-validation of a modified score to predict mortality in cancer patients admitted to the intensive care unit.

Joseph L Nates1, Marylou Cárdenas-Turanzas, Joe Ensor, Chris Wakefield, Susannah Kish Wallace, Kristen J Price.   

Abstract

PURPOSE: The aim of this study was to cross-validate an automated and customized severity of illness score as a means of predicting death among adult cancer patients admitted to the intensive care unit (ICU).
MATERIALS AND METHODS: We conducted a retrospective study of ICU discharges between January 1, 2001, and December 31, 2005, in a university comprehensive cancer center. We randomly selected training and validation samples in 2 ICU groups (medical and surgical patients). We used logistic regression to calculate the probabilities of death in the ICU and in-hospital death in training samples and applied these probabilities to the validation samples to calculate sensitivity and specificity, construct curves, and determined the areas under the receiver operating characteristic curve (AUC).
RESULTS: We included 6880 patients. In predicting ICU mortality, the AUC was 0.77 (95% confidence interval [CI], 0.73-0.82) for the medical validation group and 0.8207 (95% CI, 0.7304-0.9109) for the surgical validation group. For in-hospital mortality, the AUCs for the groups of medical and surgical patients were 0.73 (95% CI, 0.69-0.76) and 0.77 (95% CI, 0.73-0.80), respectively.
CONCLUSIONS: The modified Sequential Organ Failure Assessment score is a good and valid predictor of cancer patients' risk of dying in the ICU and/or hospital despite the modifications needed to automate the score using existing electronic data.
Copyright © 2011 Elsevier Inc. All rights reserved.

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Year:  2010        PMID: 21195582     DOI: 10.1016/j.jcrc.2010.10.016

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


  4 in total

1.  Evaluating High-Dimensional Machine Learning Models to Predict Hospital Mortality Among Older Patients With Cancer.

Authors:  Edmund M Qiao; Alexander S Qian; Vinit Nalawade; Rohith S Voora; Nikhil V Kotha; Lucas K Vitzthum; James D Murphy
Journal:  JCO Clin Cancer Inform       Date:  2022-06

2.  Validity of a Modified Sequential Organ Failure Assessment Score Using the Richmond Agitation-Sedation Scale.

Authors:  Eduard E Vasilevskis; Pratik P Pandharipande; Amy J Graves; Ayumi Shintani; Ryosuke Tsuruta; E Wesley Ely; Timothy D Girard
Journal:  Crit Care Med       Date:  2016-01       Impact factor: 7.598

3.  Validation of computerized automatic calculation of the sequential organ failure assessment score.

Authors:  Andrew M Harrison; Hemang Yadav; Brian W Pickering; Rodrigo Cartin-Ceba; Vitaly Herasevich
Journal:  Crit Care Res Pract       Date:  2013-07-09

4.  Comparison of a modified Sequential Organ Failure Assessment Score using RASS and FOUR.

Authors:  Gabriel Piñeiro Telles; Isabella Bonifácio Brige Ferreira; Rodrigo Carvalho de Menezes; Thomas Azevedo do Carmo; Paula Lins David Pugas; Lara Freitas Marback; Maria B Arriaga; Kiyoshi F Fukutani; Licurgo Pamplona Neto; Sydney Agareno; Kevan M Akrami; Nivaldo Menezes Filgueiras Filho; Bruno B Andrade
Journal:  PLoS One       Date:  2020-02-21       Impact factor: 3.240

  4 in total

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