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Comparison of Diagnostic Algorithms for Detecting Toxigenic Clostridium difficile in Routine Practice at a Tertiary Referral Hospital in Korea

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dc.contributor.author김희정-
dc.date.accessioned2017-10-26T07:18:00Z-
dc.date.available2017-10-26T07:18:00Z-
dc.date.issued2016-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/151853-
dc.description.abstractSince every single test has some limitations for detecting toxigenic Clostridium difficile, multistep algorithms are recommended. This study aimed to compare the current, representative diagnostic algorithms for detecting toxigenic C. difficile, using VIDAS C. difficile toxin A&B (toxin ELFA), VIDAS C. difficile GDH (GDH ELFA, bioM?rieux, Marcy-l'Etoile, France), and Xpert C. difficile (Cepheid, Sunnyvale, California, USA). In 271 consecutive stool samples, toxigenic culture, toxin ELFA, GDH ELFA, and Xpert C. difficile were performed. We simulated two algorithms: screening by GDH ELFA and confirmation by Xpert C. difficile (GDH + Xpert) and combined algorithm of GDH ELFA, toxin ELFA, and Xpert C. difficile (GDH + Toxin + Xpert). The performance of each assay and algorithm was assessed. The agreement of Xpert C. difficile and two algorithms (GDH + Xpert and GDH+ Toxin + Xpert) with toxigenic culture were strong (Kappa, 0.848, 0.857, and 0.868, respectively). The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of algorithms (GDH + Xpert and GDH + Toxin + Xpert) were 96.7%, 95.8%, 85.0%, 98.1%, and 94.5%, 95.8%, 82.3%, 98.5%, respectively. There were no significant differences between Xpert C. difficile and two algorithms in sensitivity, specificity, PPV and NPV. The performances of both algorithms for detecting toxigenic C. difficile were comparable to that of Xpert C. difficile. Either algorithm would be useful in clinical laboratories and can be optimized in the diagnostic workflow of C. difficile depending on costs, test volume, and clinical needs.-
dc.description.statementOfResponsibilityopen-
dc.languageEnglish-
dc.publisherPublic Library of Science-
dc.relation.isPartOfPLOS ONE-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/2.0/kr/-
dc.subject.MESHAdult-
dc.subject.MESHAlgorithms-
dc.subject.MESHBacterial Proteins/analysis*-
dc.subject.MESHBacterial Toxins/analysis*-
dc.subject.MESHBacteriological Techniques-
dc.subject.MESHChild-
dc.subject.MESHClostridium difficile/isolation & purification*-
dc.subject.MESHEnterocolitis, Pseudomembranous/diagnosis*-
dc.subject.MESHEnterocolitis, Pseudomembranous/microbiology-
dc.subject.MESHEnterotoxins/analysis*-
dc.subject.MESHEnzyme-Linked Immunosorbent Assay-
dc.subject.MESHFemale-
dc.subject.MESHGlutamate Dehydrogenase/analysis*-
dc.subject.MESHHumans-
dc.subject.MESHMale-
dc.subject.MESHPolymerase Chain Reaction-
dc.subject.MESHRepublic of Korea-
dc.subject.MESHTertiary Care Centers-
dc.titleComparison of Diagnostic Algorithms for Detecting Toxigenic Clostridium difficile in Routine Practice at a Tertiary Referral Hospital in Korea-
dc.typeArticle-
dc.publisher.locationUnited States-
dc.contributor.collegeCollege of Medicine-
dc.contributor.departmentDept. of Laboratory Medicine-
dc.contributor.googleauthorHee-Won Moon-
dc.contributor.googleauthorHyeong Nyeon Kim-
dc.contributor.googleauthorMina Hur-
dc.contributor.googleauthorHee Sook Shim-
dc.contributor.googleauthorHeejung Kim-
dc.contributor.googleauthorYeo-Min Yun-
dc.identifier.doi10.1371/journal.pone.0161139-
dc.contributor.localIdA01219-
dc.relation.journalcodeJ02540-
dc.identifier.eissn1932-6203-
dc.identifier.pmid27532104-
dc.contributor.alternativeNameKim, Hee Jung-
dc.contributor.affiliatedAuthorKim, Heejung-
dc.citation.volume11-
dc.citation.number8-
dc.citation.startPagee0161139-
dc.identifier.bibliographicCitationPLOS ONE, Vol.11(8) : e0161139, 2016-
dc.date.modified2017-10-24-
dc.identifier.rimsid46178-
dc.type.rimsART-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Laboratory Medicine (진단검사의학교실) > 1. Journal Papers

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