Recovery from acute kidney injury: Determinants and predictors

Nattachai Srisawat, Raghavan Murugan, Xiaoyan Wen, Kai Singbartl, Gilles Clermont, Somchai Eiam-Ong, John A. Kellum

Research output: Chapter in Book/Report/Conference proceedingChapter

20 Scopus citations

Abstract

Predicting recovery of renal function following acute kidney injury (AKI) is one of the top ten questions in the field of AKI research. Accurate prediction would help physicians distinguish patients with poor renal prognosis in whom further therapy is likely to be futile from those who are likely to have good renal prognosis. Proper stratification of patients with AKI is also critical to design clinical trials to target patients with poor prognosis. Unfortunately, current general clinical severity scores (APACHE, SOFA, etc.) and AKI-specific severity scores (Mehta's score, Liano's score, Chertow's score, etc.) are not the good predictors of renal recovery. Recent progress on the pathophysiology of renal injury and recovery is encouraging. Repopulation of surviving renal tubular epithelial cell with the assistance of certain renal epithelial cell and specific growth factors such as neutrophil gelatinase-associated lipocalin (NGAL), hepatocyte growth factor (HGF), epidermal growth factor, and insulin-like growth factor-1, etc., play a major role in the recovery process. Such findings provide a great opportunity to test and validate these potential biomarkers as candidate markers of renal recovery. This review will describe the current understanding of the renal recovery process, and the role of clinical severity scores and novel biomarkers such as NGAL, HGF, and cystatin C in predicting renal recovery.

Original languageEnglish (US)
Title of host publicationCardiorenal Syndromes in Critical Care
EditorsClaudio Ronco, Rinaldo Bellomo, Peter McCullough
Pages284-291
Number of pages8
DOIs
StatePublished - Apr 1 2010

Publication series

NameContributions to Nephrology
Volume165
ISSN (Print)0302-5144

All Science Journal Classification (ASJC) codes

  • Nephrology

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