title: A 5-item prediction rule to identify severe renal dysfunction in patients with acute stroke.
abstract: OBJECTIVE
  Although patients with severe renal dysfunction who receive iodinated contrast are at high risk of CIN, contrast-enhanced CT scans are often obtained without prior knowledge of kidney function in patients with acute stroke. We aimed to develop a tool to identify patients with acute stroke at a high risk of CIN in the absence of a recent GFR.
  
  
  METHODS
  We used the RCSN (9872 patients) and OSA (2544 patients) for our derivation and validation cohort, respectively. A multivariable logistic regression model was performed to develop a predictive tool to identify severe renal dysfunction (defined as a GFR < 30 mL/min/1.73 m(2)).
  
  
  RESULTS
  The overall prevalence of severe renal dysfunction was 4.9% and 5.2% in the derivation and validation cohort, respectively. The prediction rule was designed as follows: (age in years) + (5 points for women) + (5 points for history of diabetes mellitus) + (15 points for preadmission insulin use) + (10 points for history of hypertension). The prevalence of severe renal dysfunction is negligible in patients with a total score of ≤70 (≤0.005%-0.7%) but increases with higher Renal Risk Scores (eg, scores 71-80: 2.1%-2.2%; scores 91-100: 6.6%-7.1%; scores 111-120: 15.9%-28.1%).
  
  
  CONCLUSIONS
  The Renal Risk Score is a validated tool that helps clinicians select which patients with stroke can safely proceed to contrast-enhanced brain imaging without waiting for laboratory evidence of good renal function.
authors.affiliation: Division of Neurology, Department of Medicine, University Health Network, University of Toronto, Toronto, Canada. m.d.i.vergouwen@umcutrecht.nl
authors.forename: M D I
authors.initials: MD
authors.lastname: Vergouwen
authors.forename: J
authors.initials: J
authors.lastname: Fang
authors.forename: L K
authors.initials: LK
authors.lastname: Casaubon
authors.forename: M K
authors.initials: MK
authors.lastname: Kapral
authors.forename: M
authors.initials: M
authors.lastname: Stamplecoski
authors.forename: A
authors.initials: A
authors.lastname: Robertson
authors.forename: F L
authors.initials: FL
authors.lastname: Silver
mesh_terms: D000367:Age Factors; D003287:Contrast Media / Q000009:adverse effects*; D048909:Diabetes Complications; D005260:Female; D005919:Glomerular Filtration Rate; D006801:Humans; D006973:Hypertension / Q000150:complications; D007328:Insulin / Q000627:therapeutic use; D007455:Iodine / Q000009:adverse effects*; D007674:Kidney Diseases / Q000139:chemically induced* / Q000150:complications / Q000175:diagnosis*; D008297:Male; D015233:Models, Statistical; D016017:Odds Ratio; D011859:Radiography; D018570:Risk Assessment; D020521:Stroke / Q000150:complications / Q000000981:diagnostic imaging*
chemical_list: D003287:Contrast Media; D007328:Insulin; D007455:Iodine