Literature DB >> 29643194

Quantitative Thresholds Enable Accurate Identification of Clostridium difficile Infection by the Luminex xTAG Gastrointestinal Pathogen Panel.

Sixto M Leal1,2, Elena B Popowitch3, Kara J Levinson3, Teny M John4, Bethany Lehman4, Maria Bueno Rios4, Peter H Gilligan3,5, Melissa B Miller3,5.   

Abstract

Clostridium difficile colonizes the gastrointestinal (GI) tract, resulting in either asymptomatic carriage or a spectrum of diarrheal illness. If clinical suspicion for C. difficile is low, stool samples are often submitted for analysis by multiplex molecular assays capable of detecting multiple GI pathogens, and some institutions do not report this organism due to concerns for high false-positive rates. Since clinical disease correlates with organism burden and molecular assays yield quantitative data, we hypothesized that numerical cutoffs could be utilized to improve the specificity of the Luminex xTAG GI pathogen panel (GPP) for C. difficile infection. Analysis of cotested liquid stool samples (n = 1,105) identified a GPP median fluorescence intensity (MFI) value cutoff of ≥1,200 to be predictive of two-step algorithm (2-SA; 96.4% concordance) and toxin enzyme immunoassay (EIA) positivity. Application of this cutoff to a second cotested data set (n = 1,428) yielded 96.5% concordance. To determine test performance characteristics, concordant results were deemed positive or negative, and discordant results were adjudicated via chart review. Test performance characteristics for the MFI cutoff of ≥150 (standard), MFI cutoff of ≥1,200, and 2-SA were as follows (respectively): concordance, 95, 96, and 97%; sensitivity, 93, 78, and 90%; specificity, 95, 98, and 98%; positive predictive value, 67, 82, and 81%;, and negative predictive value, 99, 98, and 99%. To capture the high sensitivity for organism detection (MFI of ≥150) and high specificity for active infection (MFI of ≥1,200), we developed and applied a reporting algorithm to interpret GPP data from patients (n = 563) with clinician orders only for syndromic panel testing, thus enabling accurate reporting of C. difficile for 95% of samples (514 negative and 5 true positives) irrespective of initial clinical suspicion and without the need for additional testing.
Copyright © 2018 American Society for Microbiology.

Entities:  

Keywords:  Clostridium difficile; community-associated infections; quantitative thresholds; syndromic panels; two-step algorithm

Mesh:

Substances:

Year:  2018        PMID: 29643194      PMCID: PMC5971534          DOI: 10.1128/JCM.01885-17

Source DB:  PubMed          Journal:  J Clin Microbiol        ISSN: 0095-1137            Impact factor:   5.948


  34 in total

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Journal:  J Clin Microbiol       Date:  2017-06-14       Impact factor: 5.948

2.  Evaluation of diagnostic tests for Clostridium difficile infection.

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4.  Point-Counterpoint: What Is the Optimal Approach for Detection of Clostridium difficile Infection?

Authors:  Ferric C Fang; Christopher R Polage; Mark H Wilcox
Journal:  J Clin Microbiol       Date:  2017-01-11       Impact factor: 5.948

Review 5.  Nosocomial diarrhea: evaluation and treatment of causes other than Clostridium difficile.

Authors:  Christopher R Polage; Jay V Solnick; Stuart H Cohen
Journal:  Clin Infect Dis       Date:  2012-06-14       Impact factor: 9.079

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Authors:  N M Sullivan; S Pellett; T D Wilkins
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Review 7.  Diagnosis of Clostridium difficile infection: an ongoing conundrum for clinicians and for clinical laboratories.

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Review 8.  Clostridium difficile infection: epidemiology, diagnosis and understanding transmission.

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Journal:  Clin Infect Dis       Date:  2013-07-10       Impact factor: 9.079

Review 10.  Asymptomatic Clostridium difficile colonization: epidemiology and clinical implications.

Authors:  Luis Furuya-Kanamori; John Marquess; Laith Yakob; Thomas V Riley; David L Paterson; Niki F Foster; Charlotte A Huber; Archie C A Clements
Journal:  BMC Infect Dis       Date:  2015-11-14       Impact factor: 3.090

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2.  Biographical Feature: Peter H. Gilligan, Ph.D., D(ABMM), F(AAM).

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3.  A high-throughput and multiplex microsphere immunoassay based on non-structural protein 1 can discriminate three flavivirus infections.

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Journal:  PLoS Negl Trop Dis       Date:  2019-08-23

4.  Clinical evaluation of a non-purified direct molecular assay for the detection of Clostridioides difficile toxin genes in stool specimens.

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  4 in total

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