Metagenomic next-generation sequencing vs. conventional detection methods for detecting the pulmonary infections

Area of Science:

• Medical Microbiology
• Genomics
• Infectious Diseases

Background:

• Untreated lung infections lead to fatalities, often due to delayed diagnosis or antibiotic overuse.
• Accurate and early pathogen identification is crucial for effective pulmonary infection management.

Purpose of the Study:

• To compare the diagnostic efficacy of metagenomic next-generation sequencing (mNGS) against conventional methods for detecting infectious pathogens in pulmonary infections.
• To evaluate the sensitivity and detection rates of mNGS for both single and mixed infections.

Main Methods:

• A retrospective study analyzed pathogens from 104 patients using bronchoalveolar lavage fluid, pleural effusions, and sputum samples.
• Pathogen profiles were determined using both conventional detection methods and mNGS analysis.
• Detection rates and sensitivity of each method were statistically analyzed.

Main Results:

• mNGS demonstrated significantly higher sensitivity (89.42%) compared to conventional methods (56.73%), a 32.69% improvement.
• mNGS detected mixed infections with 85.29% efficacy, far exceeding conventional methods' 17.65% rate.
• The study confirmed mNGS as a more sensitive diagnostic tool for pulmonary infections.

Conclusions:

• mNGS offers superior sensitivity for diagnosing pulmonary infections, presenting a valuable clinical tool.
• Combining mNGS with other detection techniques can enhance pulmonary infection detection rates and guide treatment.
• Optimizing sample collection timing and antibiotic administration is important for mNGS effectiveness, especially with bronchoalveolar lavage fluid.