Evaluation of a fully automatic nucleic acid amplification system for detecting four respiratory pathogens.

Background: Respiratory syncytial virus (RSV), adenovirus (ADV), human parainfluenza virus (hPIV), and Mycoplasma pneumoniae (MP) are prevalent pathogens causing acute respiratory infections (ARIs) in children. Prompt and precise detection of these pathogens is essential for early differentiation. This study sought to assess the diagnostic efficacy of a fully automatic real-time fluorescence PCR assay utilizing microfluidic technology (PCR-MT) for the rapid detection of RSV, hPIV, ADV, and MP in children in a hospital setting in Zhejiang, China.

Methods: The study was conducted on 420 children with ARIs from March to December 2022 at our hospital. Throat swab samples were collected and detected for RSV, hPIV, ADV, and MP using both PCR-capillary electrophoresis fragment analysis (PCR-CEFA) and PCR-MT. The results obtained from the PCR-MT method were compared with those from PCR-CEFA.

Results: With PCR-CEFA as the gold standard, the sensitivity and specificity of the PCR-MT method were as follows: 94.4% and 100.0% for RSV, 96.0% and 99.1% for hPIV, 100.0% and 98.6% for ADV, and 93.5% and 98.8% for MP, respectively.

Conclusion: The PCR-MT method demonstrates substantial potential for clinical application in the early diagnosis of RSV, hPIV, ADV, and MP in an outpatient setting, offering robust sensitivity and specificity.

Impact: Rapid, accurate, and convenient multiple pathogen detection technologies represent a significant area of research in the medical field. The method evaluated in this study enables simultaneous detection of four pathogens on a single chip, covering various subtypes, with results available within half an hour. Although some multi-pathogen detection chips are already commercially available, they may still have limitations such as sensitivity, specificity, and cost. Ongoing technological advancements could make pathogen detection more efficient, accurate, and economical. Continued attention to the development, validation, and optimization of these technologies in clinical practice will better serve patients.