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A Novel Metabolic Signature To Predict the Requirement of Dialysis or Renal Transplantation in Patients with Chronic Kidney Disease

Zacharias, Helena, Altenbuchinger, Michael, Schultheiss, U. T., Samol, Claudia, Kotsis, F., Poguntke, I., Sekula, P., Krumsiek, J., Kottgen, A., Spang, Rainer, Oefner, Peter J. and Gronwald, Wolfram (2019) A Novel Metabolic Signature To Predict the Requirement of Dialysis or Renal Transplantation in Patients with Chronic Kidney Disease. Journal of Proteome Research.

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Other URL: https://pubs.acs.org/doi/10.1021/acs.jproteome.8b00983


Abstract

Identification of chronic kidney disease patients at risk of progressing to end-stage renal disease (ESRD) is essential for treatment decision-making and clinical trial design. Here, we explored whether proton nuclear magnetic resonance (NMR) spectroscopy of blood plasma improves the currently best performing kidney failure risk equation, the so-called Tangri score. Our study cohort comprised ...

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Item type:Article
Date:12 March 2019
Institutions:Medicine > Institut für Funktionelle Genomik > Lehrstuhl für Funktionelle Genomik (Prof. Oefner)
Medicine > Institut für Funktionelle Genomik > Lehrstuhl für Statistische Bioinformatik (Prof. Spang)
Identification Number:
ValueType
30817158PubMed ID
10.1021/acs.jproteome.8b00983DOI
Keywords:chronic kidney disease; kidney failure risk equation; metabolomics
Dewey Decimal Classification:600 Technology > 610 Medical sciences Medicine
Status:Published
Refereed:Yes, this version has been refereed
Created at the University of Regensburg:Partially
Item ID:39785
Owner only: item control page
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