Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/127315
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Type: Journal article
Title: Patient centred variables with univariate associations with unplanned ICU admission: a systematic review
Author: Malycha, J.
Bonnici, T.
Clifton, D.A.
Ludbrook, G.
Young, J.D.
Watkinson, P.J.
Citation: BMC Medical Informatics and Decision Making, 2019; 19(1):98-1-98-9
Publisher: Springer Nature
Issue Date: 2019
ISSN: 1472-6947
1472-6947
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Responsibility: 
James Malycha, Timothy Bonnici, David A. Clifton, Guy Ludbrook, J. Duncan Young, and Peter J. Watkinson
Abstract: Background: Multiple predictive scores using Electronic Patient Record data have been developed for hospitalised patients at risk of clinical deterioration. Methods used to select patient centred variables for inclusion in these scores varies. We performed a systematic review to describe univariate associations with unplanned Intensive Care Unit (ICU) admission with the aim of assisting model development for future scores that predict clinical deterioration. Methods: Data sources were MEDLINE, EMBASE, CINAHL, CENTRAL and the Cochrane Database of Systematic Reviews. Included studies were published since 2000 describing an association between patient centred variables and unplanned ICU admission determined using univariate analysis. Two authors independently screened titles, abstracts and full texts against inclusion and exclusion criteria. DistillerSR (Evidence Partners, Canada, Ottawa, Ontario) software was used to manage the data and identify duplicate search results. All screening and data extraction forms were implemented within DistillerSR. Study quality was assessed using an adapted version of the Newcastle-Ottawa Scale. Variables were analysed for strength of association with unplanned ICU admission. Results: The database search yielded 1520 unique studies; 1462 were removed after title and abstract review; 57 underwent full text screening; 16 studies were included. One hundred and eighty nine variables with an evaluated univariate association with unplanned ICU admission were described. Discussion: Being male, increasing age, a history of congestive cardiac failure or diabetes, a diagnosis of hepatic disease or having abnormal vital signs were all strongly associated with ICU admission. Conclusion: These findings will assist variable selection during the development of future models predicting unplanned ICU admission.
Keywords: Critical care; intensive care; ICU admission; clinical deterioration; EPR; EHR; variable selection; systematic review; predictive scores
Rights: © The Author(s). 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
DOI: 10.1186/s12911-019-0820-1
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