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Predicting mortality among critically ill patients with acute kidney injury treated with renal replacement therapy: Development and validation of new prediction models.

Authors :
Li DH
Wald R
Blum D
McArthur E
James MT
Burns KEA
Friedrich JO
Adhikari NKJ
Nash DM
Lebovic G
Harvey AK
Dixon SN
Silver SA
Bagshaw SM
Beaubien-Souligny W
Source :
Journal of critical care [J Crit Care] 2020 Apr; Vol. 56, pp. 113-119. Date of Electronic Publication: 2019 Dec 18.
Publication Year :
2020

Abstract

Purpose: Severe acute kidney injury (AKI) is associated with a significant risk of mortality and persistent renal replacement therapy (RRT) dependence. The objective of this study was to develop prediction models for mortality at 90-day and 1-year following RRT initiation in critically ill patients with AKI.<br />Methods: All patients who commenced RRT in the intensive care unit for AKI at a tertiary care hospital between 2007 and 2014 constituted the development cohort. We evaluated the external validity of our mortality models using data from the multicentre OPTIMAL-AKI study.<br />Results: The development cohort consisted of 594 patients, of whom 320(54%) died and 40 (15% of surviving patients) remained RRT-dependent at 90-day Eleven variables were included in the model to predict 90-day mortality (AUC:0.79, 95%CI:0.76-0.82). The performance of the 90-day mortality model declined upon validation in the OPTIMAL-AKI cohort (AUC:0.61, 95%CI:0.54-0.69) and showed modest calibration. Similar results were obtained for mortality model at 1-year.<br />Conclusions: Routinely collected variables at the time of RRT initiation have limited ability to predict mortality in critically ill patients with AKI who commence RRT.<br />Competing Interests: Declaration of Competing Interest The authors declare that they have no competing interests<br /> (Copyright © 2019 Elsevier Inc. All rights reserved.)

Details

Language :
English
ISSN :
1557-8615
Volume :
56
Database :
MEDLINE
Journal :
Journal of critical care
Publication Type :
Academic Journal
Accession number :
31896444
Full Text :
https://doi.org/10.1016/j.jcrc.2019.12.015