JOURNAL ARTICLE
RESEARCH SUPPORT, NON-U.S. GOV'T
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Confocal scanning laser microscopy evidence of biofilms in patients with chronic rhinosinusitis.

Laryngoscope 2007 July
OBJECTIVES: The recent detection of bacterial biofilms on the sinus mucosa of patients with chronic rhinosinusitis (CRS) has implicated biofilms in the pathogenesis of this condition. Electron microscopy has been the main modality used to document the presence of biofilms on sinus tissue, however, it has inherent problems associated with tissue preparation and sampling. Recently, Confocal Scanning Laser Micrsocopy (CSLM) has emerged as a noninvasive, nondestructive technique for the analysis of biofilms. This study used CSLM as the means of investigating biofilm presence in CRS patients.

STUDY DESIGN AND METHODS: A prospective study comparing the presence of bacterial biofilms on the sinus mucosa of CRS and control patients was conducted using CSLM. Thirty eight CRS patients undergoing endoscopic sinus surgery and nine control patients were enrolled in this study. Demographic and clinical information was recorded from each patient and intraoperatively, sinus culture specimens and mucosal samples were obtained for microbiologic and microscopic examination.

RESULTS: Using previously documented CSLM criteria, bacterial biofilms were found in 17 (44%) of the 38 CRS patients. No biofilm structures were evident in any of the controls. Patients having undergone previous sinus surgery seemed to have a higher incidence of biofilms compared with the incidence for those undergoing their first procedure. The difference however was not statistically significant. No correlation between positive bacterial cultures and biofilm presence was observed.

CONCLUSIONS: The CSLM detection of biofilms in CRS patients and their absence in controls further supports the hypothesis that biofilms may play a role in the pathogenesis of CRS. This study's lower reported incidence of biofilms compared with that of previous studies might reflect the increased accuracy of biofilm detection with CSLM.

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