4.6 Article

Growth Patterns of Clostridium difficile - Correlations with Strains, Binary Toxin and Disease Severity: A Prospective Cohort Study

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PLOS ONE
卷 11, 期 9, 页码 -

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PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0161711

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资金

  1. Antibacterial Europe ASPIRE Research awards by Pfizer International Operations
  2. Swiss National Science Foundation grant [PBBSP3-134499]
  3. Swiss National Science Foundation (SNF) [PBBSP3-134499] Funding Source: Swiss National Science Foundation (SNF)

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A broad spectrum of symptoms has been associated with C. difficile infection (CDI). Several studies indicate that toxin-production correlates with growth rates of C. difficile. This study aimed to correlate growth rates of C. difficile with disease severity and strain characteristics. From 01/2003 to 10/2011, strains from a prospective cohort of all inpatients with CDI at the University Hospital Basel, Switzerland were analyzed regarding binary toxin, presence of the tcdC deletion and ribotype. Isothermal microcalorimetry was performed to determine growth rates, quantified by the Gompertz function. Ordered logistic regression models were used to correlate disease severity with strain features and clinical characteristics. Among 199 patients, 31 (16%) were infected with binary toxin-producing strains, of which the tcdC gene-deletion nt117 was detected in 9 (4%). Disease severity was classified as mild in 130 patients (65.3%), as severe in 59 patients (29.7%) and as severe/complicated in 10 patients (5.0%). Growth rates were inversely associated with disease severity in univariable (OR 0.514, 95% CI 0.29-0.91, p = 0.023) and multivariable analyses (OR 0.51, 95% CI 0.26-0.97, p = 0.040). While none of the strain characteristics such as presence of the tcdC gene deletion or binary toxin predicted CDI severity, growth rates were inversely correlated with disease severity. Further investigations are needed to analyze growth-regulators and respective correlations with the level of toxin production in C. difficile, which may be important determinants of disease severity.

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