title: Risk prediction models for contrast induced nephropathy: systematic review.
abstract: OBJECTIVE
  To look at the available literature on validated prediction models for contrast induced nephropathy and describe their characteristics.
  
  
  METHODS
  Systematic review.
  
  
  METHODS
  Medline, Embase, and CINAHL (cumulative index to nursing and allied health literature) databases.
  
  
  METHODS
  Databases searched from inception to 2015, and the retrieved reference lists hand searched. Dual reviews were conducted to identify studies published in the English language of prediction models tested with patients that included derivation and validation cohorts. Data were extracted on baseline patient characteristics, procedural characteristics, modelling methods, metrics of model performance, risk of bias, and clinical usefulness. Eligible studies evaluated characteristics of predictive models that identified patients at risk of contrast induced nephropathy among adults undergoing a diagnostic or interventional procedure using conventional radiocontrast media (media used for computed tomography or angiography, and not gadolinium based contrast).
  
  
  RESULTS
  16 studies were identified, describing 12 prediction models. Substantial interstudy heterogeneity was identified, as a result of different clinical settings, cointerventions, and the timing of creatinine measurement to define contrast induced nephropathy. Ten models were validated internally and six were validated externally. Discrimination varied in studies that were validated internally (C statistic 0.61-0.95) and externally (0.57-0.86). Only one study presented reclassification indices. The majority of higher performing models included measures of pre-existing chronic kidney disease, age, diabetes, heart failure or impaired ejection fraction, and hypotension or shock. No prediction model evaluated its effect on clinical decision making or patient outcomes.
  
  
  CONCLUSIONS
  Most predictive models for contrast induced nephropathy in clinical use have modest ability, and are only relevant to patients receiving contrast for coronary angiography. Further research is needed to develop models that can better inform patient centred decision making, as well as improve the use of prevention strategies for contrast induced nephropathy.
authors: Division of Nephrology, St Michael's Hospital, University of Toronto, Toronto, Canada.
authors: Samuel A
authors: SA
authors: Silver
authors: Department of Paediatrics, Mount Sinai Hospital, University of Toronto, Toronto, Canada.
authors: Prakesh M
authors: PM
authors: Shah
authors: Division of Nephrology, Stanford University School of Medicine, Palo Alto, CA, USA.
authors: Glenn M
authors: GM
authors: Chertow
authors: Division of Nephrology, St Michael's Hospital, University of Toronto, Toronto, Canada harelz@smh.ca.
authors: Shai
authors: S
authors: Harel
authors: Division of Nephrology, St Michael's Hospital, University of Toronto, Toronto, Canada Li Ka Shing Knowledge Institute of St Michael's Hospital, Toronto, ON, M5C 2T2, Canada.
authors: Ron
authors: R
authors: Wald
authors: Division of Nephrology, St Michael's Hospital, University of Toronto, Toronto, Canada Li Ka Shing Knowledge Institute of St Michael's Hospital, Toronto, ON, M5C 2T2, Canada harelz@smh.ca.
authors: Ziv
authors: Z
authors: Harel
mesh_terms: D058186:Acute Kidney Injury / Q000139:chemically induced* / Q000453:epidemiology; D000367:Age Factors; D000740:Anemia / Q000453:epidemiology; D000792:Angiography; D003287:Contrast Media / Q000009:adverse effects*; D003661:Decision Support Techniques; D003920:Diabetes Mellitus / Q000453:epidemiology; D006333:Heart Failure / Q000453:epidemiology; D006801:Humans; D006973:Hypertension / Q000453:epidemiology; D015233:Models, Statistical; D051436:Renal Insufficiency, Chronic / Q000453:epidemiology; D018570:Risk Assessment; D012307:Risk Factors; D012737:Sex Factors; D014057:Tomography, X-Ray Computed
chemical_list: D003287:Contrast Media