Validating a prediction tool to determine the risk of nosocomial multidrug-resistant Gram-negative bacilli infection in critically ill patients: A retrospective case-control study
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Published version
Author(s)
Type
Journal Article
Abstract
BACKGROUND: The Singapore GSDCS score was developed to enable clinicians predict the risk of nosocomial multidrug-resistant Gram-negative bacilli (RGNB) infection in critically ill patients. We aimed to validate this score in a UK setting. METHOD: A retrospective case-control study was conducted including patients who stayed for more than 24h in intensive care units (ICUs) across two tertiary National Health Service hospitals in London, UK (April 2011-April 2016). Cases with RGNB and controls with sensitive Gram-negative bacilli (SGNB) infection were identified. RESULTS: The derived GSDCS score was calculated from when there was a step change in antimicrobial therapy in response to clinical suspicion of infection as follows: prior Gram-negative organism, Surgery, Dialysis with end-stage renal disease, prior Carbapenem use and intensive care Stay of more than 5 days. A total of 110 patients with RGNB infection (cases) were matched 1:1 to 110 geotemporally chosen patients with SGNB infection (controls). The discriminatory ability of the prediction tool by receiver operating characteristic curve analysis in our validation cohort was 0.75 (95% confidence interval 0.65-0.81), which is comparable with the area under the curve of the derivation cohort (0.77). The GSDCS score differentiated between low- (0-1.3), medium- (1.4-2.3) and high-risk (2.4-4.3) patients for RGNB infection (P<0.001) in a UK setting. CONCLUSION: A simple bedside clinical prediction tool may be used to identify and differentiate patients at low, medium and high risk of RGNB infection prior to initiation of prompt empirical antimicrobial therapy in the intensive care setting.
Date Issued
2020-09-01
Date Acceptance
2020-07-01
Citation
Journal of Global Antimicrobial Resistance, 2020, 22, pp.826-831
ISSN
2213-7165
Publisher
Elsevier
Start Page
826
End Page
831
Journal / Book Title
Journal of Global Antimicrobial Resistance
Volume
22
Copyright Statement
© 2020 The Authors. Published by Elsevier Ltd on behalf of International Society for Antimicrobial Chemotherapy. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Sponsor
National Institute for Health Research
NIHR
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/32712381
PII: S2213-7165(20)30185-5
Grant Number
NIHR200646
Subjects
Antimicrobial resistance
Bedside prediction tool
Critical care
Gram-negative bacilli
Intensive care unit
Nosocomial infection
Publication Status
Published
Coverage Spatial
Netherlands
Date Publish Online
2020-07-24