Application of a Super‐Multiplex Microfluidic qPCR System for Detection of Respiratory Pathogens in Patients With Influenza‐Like Illness

Respiratory tract infections (RTIs) pose a major diagnostic challenge, complicated by multiple microbial etiologies. Conventional low-throughput methods may underestimate the prevalence and impact of co-infections. This study aimed to evaluate a novel super-multiplex microfluidic qPCR system for comprehensive 49 target pathogens screening and co-infection analysis in patients with influenza-like illness (ILI). Throat swab samples (n = 288) were collected from febrile patients in Beijing during the spring of 2025. All samples were tested using the super-multiplex microfluidic qPCR chip, with a subset (n = 96) validated by conventional qPCR to determine analytical sensitivity, specificity, and Cohen's kappa. The assay demonstrated an overall pathogen detection rate of 66.32%. Influenza A virus (IAV) was the most prevalent pathogen, identified in 50.00% of all samples and constituting 70.69% of single infections, followed by SARS-CoV-2 (14.24%) and Epstein-Barr virus (EBV, 11.81%). Co-infections were frequent (39.27% of positive cases), predominantly dual (23.04%) and triple (10.47%) infections. Notably, IAV was implicated in 84.0% of co-infections. The microfluidic qPCR showed high concordance with conventional qPCR (sensitivity 91.07%, specificity 92.50%, κ = 0.83, indicating almost perfect agreement). This study reveals a complex respiratory pathogen landscape dominated by IAV and marked by frequent polymicrobial co-infections. The super-multiplex microfluidic qPCR chip is a reliable, high-throughput platform that effectively addresses the need for improved detection of co-infections, offering valuable insights for both clinical decision-making and public health surveillance.

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Publication Details

Journal
Journal of Medical Virology
Published
2026-07-27
DOI
https://doi.org/10.1002/jmv.71072
Primary Topic
Biosensors and Analytical Detection
Type
article
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article

Application of a Super‐Multiplex Microfluidic qPCR System for Detection of Respiratory Pathogens in Patients With Influenza‐Like Illness

Xiaoping Kang, Y Huang, Tao Jiang, Jing Li et al.
Journal of Medical Virology
Biosensors and Analytical Detection
article

Application of a Super‐Multiplex Microfluidic qPCR System for Detection of Respiratory Pathogens in Patients With Influenza‐Like Illness

Xiaoping Kang, Y Huang, Tao Jiang, Jing Li, Yi Chen, Gao Y, Ye Feng, Yuchang Li, Sen Zhang, Ganji Song
article en

Abstract

Respiratory tract infections (RTIs) pose a major diagnostic challenge, complicated by multiple microbial etiologies. Conventional low-throughput methods may underestimate the prevalence and impact of co-infections. This study aimed to evaluate a novel super-multiplex microfluidic qPCR system for comprehensive 49 target pathogens screening and co-infection analysis in patients with influenza-like illness (ILI). Throat swab samples (n = 288) were collected from febrile patients in Beijing during the spring of 2025. All samples were tested using the super-multiplex microfluidic qPCR chip, with a subset (n = 96) validated by conventional qPCR to determine analytical sensitivity, specificity, and Cohen's kappa. The assay demonstrated an overall pathogen detection rate of 66.32%. Influenza A virus (IAV) was the most prevalent pathogen, identified in 50.00% of all samples and constituting 70.69% of single infections, followed by SARS-CoV-2 (14.24%) and Epstein-Barr virus (EBV, 11.81%). Co-infections were frequent (39.27% of positive cases), predominantly dual (23.04%) and triple (10.47%) infections. Notably, IAV was implicated in 84.0% of co-infections. The microfluidic qPCR showed high concordance with conventional qPCR (sensitivity 91.07%, specificity 92.50%, κ = 0.83, indicating almost perfect agreement). This study reveals a complex respiratory pathogen landscape dominated by IAV and marked by frequent polymicrobial co-infections. The super-multiplex microfluidic qPCR chip is a reliable, high-throughput platform that effectively addresses the need for improved detection of co-infections, offering valuable insights for both clinical decision-making and public health surveillance.

Journal of Medical VirologyVol. 98(8)
Academy of Military Medical Sciences (CN), Chinese PLA General Hospital (CN)
Peace, Justice and strong institutions
Openalex Percentile: Top 17%
Biosensors and Analytical Detection
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