Comparison of two multiplex PCR tests for common pathogen detection in hospitalized children with acute respiratory infection
DOI:
https://doi.org/10.3855/jidc.17999Keywords:
Pediatric acute respiratory infections, pathogens, multiplex PCR, virusAbstract
Introduction: Multiplex PCR methods have significantly improved the diagnosis of acute respiratory tract infections (ARTIs) in children. The ResP-CE System coupled with capillary electrophoresis is a highly specialized, automated, and expensive technology for detecting common pathogens in ARTIs. The XYRes-MCA System, a remarkably less expensive multiplex PCR instrument, employs hybridization for the detection of ARTI pathogens. Both methods detect 9 common microorganisms in ARTIs, i.e., RSV, FLUAV, FLUBV, ADV, PIV, HMPV, HBOV, HCOV, and MP. In this study, we aimed to compare the performance of these two methods in the detection of pathogens from sputum specimens collected from children with ARTIs.
Methodology: Sputum specimens were collected from 237 hospitalized children with ARTIs. Nucleic acid was extracted on an automated workstation. The ResP-CE and XYres-MCA systems were applied to detect pathogens from the samples, and the test result agreement between the two methods was evaluated using Kappa statistics.
Results: The ResP-CE and XYres-MCA identified pathogens, single or in combination, in 151 (63.7%) and 171 (72.1%) of 237 samples, respectively. Approximately 85% of positive samples identified by either method contained a single pathogen. Moderate to almost perfect concordance between the two methods was found in detecting the following 7 pathogens: RSV, FLUAV, FLUBV, PIV, HMPV, HBOV, and MP.
Conclusions: These two methods are comparable in detecting common pathogens of ARTIs in children. As XYres-MCA analysis is more cost-effective, it could play an important role in diagnosing ARTIs in children in less economically developed regions.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Le Wang, Suzhen Sun, Dianping You, Fang Chen, Yinghui Guo, Xianping Zeng, Weijian Wang, Shuo Yang

This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).