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  4. The ICNARC model is predictive of hospital mortality in critically ill patients supported by acute dialysis
 
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The ICNARC model is predictive of hospital mortality in critically ill patients supported by acute dialysis

Journal
Clinical Nephrology
Journal Volume
77
Journal Issue
5
Pages
392-399
Date Issued
2012
Author(s)
Chen J.-C.
Wang W.-J.
VIN-CENT WU  orcid-logo
TAO-MIN HUANG  
Lai C.-Y.
Ko W.-J.
Cheng M.-H.
Cheng M.-H.
Ko S.-W.
DOI
10.5414/CN107174
URI
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84861499974&doi=10.5414%2fCN107174&partnerID=40&md5=8dc4d9a7bd058b54bc1d77b0ec126cb2
https://scholars.lib.ntu.edu.tw/handle/123456789/588530
Abstract
Aims: To compare prediction power between ICNARC model and RIFLE classification in postoperative patients receiving acute dialysis. Material and method: Between January 2002 and December 2008, 529 patients received acute dialysis during their ICU stay were enrolled. Patients' demographic, clinical and laboratory variables were analyzed as predictors of mortality. The RIFLE logistic regression and the ICNARC model on ICU admission were evaluated to predict the patient's hospital mortality. Results: Hospital mortality for the study group was 29.3%. Between two score systems, the ICNARC model showed better mortality prediction in this patient group by using the area under the receiver operating characteristic curve (ICNARC 0.836, RIFLE 0.702, p < 0.05). Multiple logistic regression analysis indicated that age, surgery category, metastatic carcinoma, ventilator use, and previous history of hypertension were also affecting factors for hospital mortality. Conclusions: The RIFLE classification and the ICNARC model were both correlated with mortality in critically ill patient with acute dialysis. However, the ICNARC model was a better mortality predictor compared to the RIFLE classification. ? 2012 Dustri-Verlag Dr. K. Feistle.
SDGs

[SDGs]SDG3

Other Subjects
adult; aged; area under the curve; article; correlation analysis; critically ill patient; dialysis; female; human; intensive care national audit and research center model; major clinical study; male; metastasis; mortality; named inventories, questionnaires and rating scales; patient identification; prediction; receiver operating characteristic; ventilator; Aged; APACHE; Chi-Square Distribution; Critical Illness; Female; Health Status Indicators; Hospital Mortality; Humans; Intensive Care Units; Kidney Diseases; Logistic Models; Male; Middle Aged; Postoperative Complications; Prognosis; Renal Dialysis; Risk Assessment; Risk Factors; ROC Curve; Survival Analysis; Taiwan
Type
journal article

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