What is the current role of algorithmic approaches for diagnosis of Clostridium difficile infection?

目前算法方法在艰难梭菌感染诊断中发挥着怎样的作用?

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Abstract

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?

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