Abstract
OBJECTIVE: To investigate the clinical application value of microfluidic-based in vitro diagnostic (IVD) technology in pathogenic detection of respiratory tract infections. METHODS: A total of 300 clinical samples, including blood, bronchoalveolar lavage fluid, and pleural effusion, were collected from patients with respiratory tract infections. The samples were randomly divided into three groups: A, B, and C, with 100 cases in each group. Group A used traditional microbiological detection methods, Group B used metagenomic next-generation sequencing (mNGS) technology, and Group C used both microfluidic-based IVD technology and traditional microbiological detection methods to detect pathogenic microorganisms in the clinical samples. The positive detection rate, detection time, and detection cost were compared among the groups. The diagnostic performance of each group was compared using the Receiver Operating Characteristic (ROC) curve. RESULTS: Traditional microbiological detection identified 38 positive samples (38%), including 45 pathogens; mNGS technology identified 95 positive samples (95%), including 210 pathogens; microfluidic-based IVD technology identified 96 positive samples (96%), including 158 pathogens. Microfluidic-based IVD technology had a significantly higher positive detection rate for pathogenic microorganisms compared to traditional culture techniques (96% vs 38%, χ2 = 122.0, P < 0.01), and it was also faster and cheaper than mNGS technology. ROC analysis showed that compared to traditional microbiological culture results, microfluidic-based IVD technology had significantly increased sensitivity and specificity, similar to mNGS technology. CONCLUSION: In respiratory infectious diseases, microfluidic-based IVD technology had a higher detection rate for pathogenic microorganisms than traditional culture methods, and it had advantages in detection time and cost compared to mNGS technology. It could also detect critical drug-resistant genes of pathogens. Hence, microfluidic-based IVD technology can be a viable option for diagnosis and treatment of respiratory infectious diseases.