A Dynamic Predictive Model for the Progression of Chronic Kidney Disease to Kidney Failure
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چکیده
BACKGROUND: Predicting the progression of CKD is important for treatment decisions and for informing patient provider communication. We have previously developed a highly accurate static prediction model for the progression of CKD that used one time values. In this analysis, we describe a dynamic prediction model for CKD progression that includes changes in laboratory variables between visits as additional predictors of outcome.
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تاریخ انتشار 2016