title: The ICNARC model is predictive of hospital mortality in critically ill patients supported by acute dialysis.
abstract: OBJECTIVE
  To compare prediction power between ICNARC model and RIFLE classification in postoperative patients receiving acute dialysis.
  
  
  METHODS
  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.
authors.affiliation: Department of Internal Medicine, Taoyuan General Hospital, Department of Health, Executive Yuan, Taoyuan, Taiwan.
authors.forename: Jui-Chang
authors.initials: JC
authors.lastname: Chen
authors.forename: Wei-Jie
authors.initials: WJ
authors.lastname: Wang
authors.forename: Vin-Cent
authors.initials: VC
authors.lastname: Wu
authors.forename: Tao-Min
authors.initials: TM
authors.lastname: Huang
authors.forename: Chun-Ying
authors.initials: CY
authors.lastname: Lai
authors.forename: Wen-Je
authors.initials: WJ
authors.lastname: Ko
authors.forename: Hau-Shin
authors.initials: HS
authors.lastname: Wu
authors.forename: Mei-Hua
authors.initials: MH
authors.lastname: Cheng
authors.forename: Sheng-Wen
authors.initials: SW
authors.lastname: Ko
mesh_terms: D018806:APACHE; D000368:Aged; D016009:Chi-Square Distribution; D016638:Critical Illness; D005260:Female; D006305:Health Status Indicators; D017052:Hospital Mortality; D006801:Humans; D007362:Intensive Care Units; D007674:Kidney Diseases / Q000209:etiology / Q000401:mortality* / Q000628:therapy*; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D011183:Postoperative Complications / Q000209:etiology / Q000401:mortality* / Q000628:therapy*; D011379:Prognosis; D012372:ROC Curve; D006435:Renal Dialysis / Q000009:adverse effects / Q000401:mortality*; D018570:Risk Assessment; D012307:Risk Factors; D016019:Survival Analysis; D013624:Taiwan / Q000453:epidemiology