Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
12
pubmed:dateCreated
2010-11-30
pubmed:abstractText
With the recognition of several serious outbreaks of Clostridium difficile infection in the industrialized world coupled with the development of new testing technologies for detection of this organism, there has been renewed interest in the laboratory diagnosis of C. difficile infection. Two factors seem to have driven much of this interest. First, the recognition that immunoassays for detection of C. difficile toxins A and B, for many years the most widely used tests for C. difficile infection diagnosis, were perhaps not as sensitive as previously believed at a time when attributed deaths to C. difficile infections were showing a remarkable rise. Second, the availability of FDA-approved commercial and laboratory-developed PCR assays which could detect toxigenic strains of C. difficile provided a novel and promising testing approach for diagnosing this infection. In this point-counterpoint on the laboratory diagnosis of C. difficile infection, we have asked two experts in C. difficile infection diagnosis, Ferric Fang, who has recently published two articles in the Journal of Clinical Microbiology advocating the use of PCR as a standalone test (see this author's references 12 and 28), and Mark Wilcox, who played a key role in developing the IDSA/SHEA guidelines on Clostridium difficile infection (see Wilcox and Planche's reference 1), along with his colleague, Tim Planche, to address the following question: what is the current role of algorithmic approaches to the diagnosis of C. difficile infection?
pubmed:commentsCorrections
http://linkedlifedata.com/resource/pubmed/commentcorrection/20980568-10666429, http://linkedlifedata.com/resource/pubmed/commentcorrection/20980568-12574274, http://linkedlifedata.com/resource/pubmed/commentcorrection/20980568-17804652, http://linkedlifedata.com/resource/pubmed/commentcorrection/20980568-18032627, http://linkedlifedata.com/resource/pubmed/commentcorrection/20980568-18256226, http://linkedlifedata.com/resource/pubmed/commentcorrection/20980568-18977696, http://linkedlifedata.com/resource/pubmed/commentcorrection/20980568-19348118, http://linkedlifedata.com/resource/pubmed/commentcorrection/20980568-19710274, http://linkedlifedata.com/resource/pubmed/commentcorrection/20980568-19853666, http://linkedlifedata.com/resource/pubmed/commentcorrection/20980568-19864479, http://linkedlifedata.com/resource/pubmed/commentcorrection/20980568-19900734, http://linkedlifedata.com/resource/pubmed/commentcorrection/20980568-19923482, http://linkedlifedata.com/resource/pubmed/commentcorrection/20980568-19929371, http://linkedlifedata.com/resource/pubmed/commentcorrection/20980568-20071552, http://linkedlifedata.com/resource/pubmed/commentcorrection/20980568-20307191, http://linkedlifedata.com/resource/pubmed/commentcorrection/20980568-231071, http://linkedlifedata.com/resource/pubmed/commentcorrection/20980568-9502463
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
1098-660X
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
48
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
4347-53
pubmed:dateRevised
2011-7-28
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
What is the current role of algorithmic approaches for diagnosis of Clostridium difficile infection?
pubmed:affiliation
Microbiology, Leeds Teaching Hospitals and University of Leeds, Old Medical School, Leeds General Infirmary, Leeds LS1 3EX, W. Yorkshire, United Kingdom. mark.wilcox@leedsth.nhs.uk
pubmed:publicationType
Journal Article