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Multicenter Study
. 2021 Aug;23(4):e13599.
doi: 10.1111/tid.13599. Epub 2021 Mar 25.

Clinical prediction tool for extended-spectrum beta-lactamase-producing enterobacterales as the etiology of a bloodstream infection in solid organ transplant recipients

Rebecca Wang  1 , Jennifer H Han  2 , Ebbing Lautenbach  1   3   4 , Pranita D Tamma  5 , Kerri A Thom  6   7 , Kevin Alby  8 , Emily A Blumberg  1 , Warren B Bilker  3   4 , Alissa Werzen  7 , Jacqueline Omorogbe  3 , Pam Tolomeo  3 , Judith A Anesi  1   3   4
Affiliations
Multicenter Study

Clinical prediction tool for extended-spectrum beta-lactamase-producing enterobacterales as the etiology of a bloodstream infection in solid organ transplant recipients

Rebecca Wang et al. Transpl Infect Dis. 2021 Aug.

Abstract

Background: Multidrug-resistant Gram-negative bacterial infections are increasingly common among solid organ transplant (SOT) recipients, leading to challenges in the selection of empiric antimicrobial therapy. We sought to develop a clinical tool to predict which SOT recipients are at high risk for extended-spectrum beta-lactamase (ESBL)-producing Enterobacterales (EB) bloodstream infection (BSI).

Methods: A multicenter case-control study was performed. The source population included SOT recipients with an EB BSI between 2005 and 2018. Cases were those with ESBL-EB BSI; controls were those with non-ESBL EB BSI. The population was subdivided into derivation and validation cohorts based on study site. The predictive tool was developed in the derivation cohort through iterative multivariable logistic regression analyses that maximized the area under the receiver-operating curve (AUC). External validity was assessed using the validation cohort.

Results: A total of 897 SOT recipients with an EB BSI were included, of which 539 were assigned to the derivation cohort (135, 25% ESBL-EB) and 358 to the validation cohort (221, 62% ESBL-EB). Using multivariable analyses, the most parsimonious model that was predictive of ESBL-EB BSI consisted of 10 variables, which fell into four clinical categories: prior colonization or infection with EB organisms, recent antimicrobial exposures, severity of preceding illness, and immunosuppressive regimen. This model achieved an AUC of 0.81 in the derivation cohort and 0.68 in the validation cohort.

Conclusions: Though further refinements are needed in additional populations, this tool shows promise for guiding empiric therapy for SOT recipients with EB BSI.

Keywords: bloodstream infection; enterobacterales; extended-spectrum beta-lactamase; predictive tool; transplant.

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Conflict of interest statement

CONFLICT OF INTEREST

Emily Blumberg receives research support from Takeda, Merck, and Hologic; is a member of a Data and Safety Monitoring Board (DSMB) for Amplyx; and serves as a member of the scientific advisory committee for Merck. Jennifer Han was affiliated with the University of Pennsylvania during the conduct of this research and is now employed by and holds shares in the GlaxoSmithKline group of companies. Ebbing Lautenbach is a member of a DSMB for Merck and serves as a member of the scientific advisory committees for Paratek and Shionogi. Kevin Alby serves on the scientific advisory boards for Becton Dickinson and Shionogi. Warren Bilker is a member of multiple DSMBs for Genentech. None of these conflicts are relevant to this article. All other authors report no conflicts of interest relevant to this article.

Figures

FIGURE 1
FIGURE 1
Receiver operator characteristic (ROC) curve for the predictive tool in the derivation cohort
FIGURE 2
FIGURE 2
Receiver operator characteristic (ROC) curve for the predictive tool in the validation cohort
See this image and copyright information in PMC

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