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The Role of Risk Prediction Models in Prevention and Management of AKI

Hodgson, Luke E., Selby, Nicholas, Huang, Tao-Min and Forni, Lui G. (2019) The Role of Risk Prediction Models in Prevention and Management of AKI Seminars in Nephrology, 39 (5). pp. 421-430.

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Abstract

Acute kidney injury is a major health care problem. Improving recognition of those at risk and highlighting those who have developed AKI at an earlier stage remains a priority for research and clinical practice. Prediction models to risk-stratify patients and electronic alerts for AKI are two approaches that could address previously highlighted shortcomings in management and facilitate timely intervention. We describe and critique available prediction models and the effects of the use of AKI alerts on patient outcomes are reviewed. Finally, the potential for prediction models to enrich population subsets for other diagnostic approaches and potential research, including biomarkers of AKI, are discussed.

Item Type: Article
Divisions : Faculty of Health and Medical Sciences > School of Biosciences and Medicine
Authors :
NameEmailORCID
Hodgson, Luke E.
Selby, Nicholas
Huang, Tao-Min
Forni, Lui G.l.forni@surrey.ac.uk
Date : September 2019
DOI : 10.1016/j.semnephrol.2019.06.002
Copyright Disclaimer : © 2019. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
Uncontrolled Keywords : Acute kidney injury; Prediction models; Electronic alerts
Depositing User : Clive Harris
Date Deposited : 27 Sep 2019 12:37
Last Modified : 27 Sep 2019 12:37
URI: http://epubs.surrey.ac.uk/id/eprint/852827

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