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Prediction model of renal recovery by recursive partitioning analysis.

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posted on 2016-05-06, 05:30 authored by Hans U. Gerth, Michele Pohlen, Dennis Görlich, Gerold Thölking, Martin Kropff, Wolfgang E. Berdel, Hermann Pavenstädt, Marcus Brand, Philipp Kümpers

Prediction model developed by recursive partitioning analysis to estimate the risk class of renal recovery based on two split variables: mode of extracorporeal therapy (HCO-HD vs. conv. HD) and serum uric acid values (<10.4 mg/dl vs. ≥10.4 mg/dl) before therapy initiation. With the application of HCO therapy, the rate of renal recovery doubled from 29% to 64% of patients. Further assessment of uric acid values predicts the probability of renal recovery more precisely, resulting in a medium-risk class (40.0% renal recovery) or low-risk class (71.9% renal recovery).

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