title: Comparison of Two Risk Models in Predicting the Incidence of Contrast-Induced Nephropathy after Percutaneous Coronary Intervention.
abstract: OBJECTIVE
  We sought to compare 2 contrast-induced nephropathy (CIN) risk prediction models in a validation cohort using a consensus definition.
  
  
  BACKGROUND
  Contrast-induced nephropathy (CIN) is independently associated with mortality following percutaneous coronary intervention (PCI). Multiple prediction models for the development of CIN have been published using heterogeneous outcome definitions.
  
  
  METHODS
  We analyzed 5,540 patients who underwent PCI from January 2005 to June 2012 at a single academic medical center. The primary outcome was development of CIN, defined as an increase in serum creatinine of ≥0.5 mg/dl or a relative increase of ≥25% from baseline. Receiver operator characteristic (ROC) curves were used to evaluate the discriminatory power of Mehran and WBH prediction models.
  
  
  RESULTS
  The mean age of our cohort was 68 ± 12 years. The mean baseline creatinine was 1.2 ± 0.53 mg/dl (eGFR 73 ± 27 ml/min). The mean contrast volume used was 212 ± 92 ml. CIN occurred in 436 patients (7.9%). The Mehran risk score demonstrated better discrimination than the William Beaumont Hospital (WBH) risk score to predict the occurrence of CIN (c statistic: 0.82 vs. 0.73, respectively). Mortality at 30 days was approximately 8 times higher among patients with CIN as compared to those without (14.7% vs. 1.8% P < 0.01).
  
  
  CONCLUSIONS
  In an independent validation cohort, the Mehran risk model demonstrates greater discriminatory power than the WBH model in predicting the incidence of CIN. Mortality was significantly higher in patients who developed CIN after PCI.
authors.affiliation: Hospital de Clinicas de Porto Alegre and Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil. gustavon.araujo@gmail.com.
authors.forename: Gustavo N
authors.initials: GN
authors.lastname: Araujo
authors.affiliation: Hospital de Clinicas de Porto Alegre and Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.
authors.forename: Marco V
authors.initials: MV
authors.lastname: Wainstein
authors.affiliation: University of Washington, Seattle, Washington.
authors.forename: James M
authors.initials: JM
authors.lastname: McCabe
authors.affiliation: Sutter Medical Center, Sacramento, California.
authors.forename: Pei-Hsiu
authors.initials: PH
authors.lastname: Huang
authors.affiliation: Downstate Medical Center and State University of New York, New York, New York.
authors.forename: Usha S
authors.initials: US
authors.lastname: Govindarajulu
authors.affiliation: Lahey Clinic Medical Center and Tufts University School of Medicine, Burlington, Massachusetts.
authors.forename: Frederic S
authors.initials: FS
authors.lastname: Resnic
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D003287:Contrast Media / Q000009:adverse effects*; D003327:Coronary Disease / Q000175:diagnosis / Q000453:epidemiology / Q000628:therapy; D003404:Creatinine / Q000032:analysis; D005260:Female; D006801:Humans; D007674:Kidney Diseases / Q000139:chemically induced / Q000175:diagnosis / Q000401:mortality; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D010043:Outcome and Process Assessment, Health Care; D062645:Percutaneous Coronary Intervention / Q000009:adverse effects / Q000379:methods; D011237:Predictive Value of Tests; D011379:Prognosis; D012372:ROC Curve; D018570:Risk Assessment / Q000379:methods*; D012307:Risk Factors; D014481:United States / Q000453:epidemiology
chemical_list: D003287:Contrast Media; D003404:Creatinine