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A 5-item prediction rule to identify severe renal dysfunction in patients with acute stroke
M D I Vergouwen1, J Fang, L K Casaubon
1Division of Neurology, Department of Medicine, University Health Network, University of Toronto, Toronto, Canada. m.d.i.vergouwen@umcutrecht.nl
Background And Purpose:
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.
Materials And 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.
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