Comparison of the Luminex xTAG respiratory viral panel with in-house nucleic acid amplification tests for diagnosis of respiratory virus infections.
J Clin Microbiol 2008;
46:3056-62. [PMID:
18632902 DOI:
10.1128/jcm.00878-08]
[Citation(s) in RCA: 124] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
Detection of respiratory viruses using sensitive real-time nucleic acid amplification tests (NATs) is invaluable for patient and outbreak management. However, the wide range of potential respiratory virus pathogens makes testing using individual real-time NATs expensive and laborious. The objective of this study was to compare the detection of respiratory virus targets using the Luminex xTAG respiratory viral panel (RVP) assay with individual real-time NATs used at the Provincial Laboratory of Public Health, Calgary, Alberta, Canada. The study included 1,530 specimens submitted for diagnosis of respiratory infections from December 2006 to May 2007. Direct-fluorescent-antigen-positive nasopharyngeal samples were excluded from this study. A total of 690 and 643 positives were detected by RVP and in-house NATs, respectively. Kappa correlation between in-house NATs and RVP for all targets ranged from 0.721 to 1.000. The majority of specimens missed by in-house NATs (96.7%) were positive for picornaviruses. Samples missed by RVP were mainly positive for adenovirus (51.7%) or respiratory syncytial virus (27.5%) by in-house NATs and in general had low viral loads. RVP allows for multiplex detection of 20 (and differentiation between 19) respiratory virus targets with considerable time and cost savings compared with alternative NATs. Although this first version of the RVP assay has lower sensitivity than in-house NATs for detection of adenovirus, it has good sensitivity for other targets. The identification of picornaviruses and coronaviruses and concurrent typing of influenza A virus by RVP, which are not currently included in our diagnostic testing algorithm, will improve our diagnosis of respiratory tract infections.
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