Imperial College London
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Professor Mark Gilchrist

Faculty of Medicine, Department of Infectious Disease

Professor of Practice
 
 
 
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Contact

 

m.gilchrist

 
 
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Location

 

Commonwealth BuildingHammersmith Campus

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Summary

 

Publications

Citation

BibTex format

@article{Boyd:2020:10.1016/j.jgar.2020.07.010,
author = {Boyd, SE and Vasudevan, A and Moore, LSP and Brewer, C and Gilchrist, M and Costelloe, C and Gordon, AC and Holmes, AH},
doi = {10.1016/j.jgar.2020.07.010},
journal = {Journal of Global Antimicrobial Resistance},
pages = {826--831},
title = {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},
url = {http://dx.doi.org/10.1016/j.jgar.2020.07.010},
volume = {22},
year = {2020}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - 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.
AU  - Boyd,SE
AU  - Vasudevan,A
AU  - Moore,LSP
AU  - Brewer,C
AU  - Gilchrist,M
AU  - Costelloe,C
AU  - Gordon,AC
AU  - Holmes,AH
DO  - 10.1016/j.jgar.2020.07.010
EP  - 831
PY  - 2020///
SN  - 2213-7165
SP  - 826
TI  - 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
T2  - Journal of Global Antimicrobial Resistance
UR  - http://dx.doi.org/10.1016/j.jgar.2020.07.010
UR  - https://www.ncbi.nlm.nih.gov/pubmed/32712381
UR  - http://hdl.handle.net/10044/1/82879
VL  - 22
ER  -
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