194
Views
10
CrossRef citations to date
0
Altmetric
Research Article

Urinary α-GST and π-GST for prediction of dialysis requirement or in-hospital death in established acute kidney injury

, , , , &
Pages 709-717 | Received 10 Jul 2011, Accepted 09 Oct 2011, Published online: 21 Nov 2011
 

Abstract

Context: Urinary α-glutathione S-transferase (α-GST) and π-glutathione S-transferase (π-GST) are promising proximal and distal tubular leakage markers for early detection of acute kidney injury (AKI).

Objective: To examine the performance of these markers for predicting the composite of dialysis requirement or in-hospital death in patients with an established diagnosis of AKI.

Materials and methods: Prospective cohort study of 245 adults with AKI. A single urinary α-GST and π-GST measurement was obtained at time of nephrology consultation.

Results: Overall, urinary π-GST performed better than α-GST for prediction of dialysis requirement (AUC 0.59 vs. 0.56), and the composite outcome (AUC 0.58 vs. 0.56). In subgroup analyses, π-GST displayed better discrimination for prediction of dialysis requirement in patients with baseline eGFR <60 mL/min/1.73 m2 (AUC 0.61) and oliguria (AUC 0.72). Similarly, α-GST performed better in patients with stage-1 (AUC 0.66) and stage-2 AKI (AUC 0.80).

Conclusions: In patients with an established diagnosis of AKI, a single urinary π-GST measurement performed better than α-GST at predicting dialysis requirement or death, but neither marker had good prognostic discrimination.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 65.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 527.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.