Next-generation sequencing in the etiological diagnosis of severe childhood pneumonia

Pneumonia is the leading cause of death for children, particularly those aged 3-5 years old. The majority of the 740,000 annual global deaths of children under five years old occurred in developing countries in 2019. Severe childhood pneumonia (SCAP) causes death and disability in children, as it may trigger pleural effusion, respiratory failure, bacteremia and multiple organ failure. Traditional pathogen detection techniques including microscopy, culture and polymerase chain reaction (PCR) feature narrow detection coverage, lengthy detection cycles and low sensitivity. These defects frequently lead to undetermined infectious etiology, forcing clinicians to administer empirical broad-spectrum antibiotics. Metagenomic next-generation sequencing (mNGS) has emerged as an innovative, high-throughput, untargeted detection technology in recent years, which greatly promotes the etiological diagnosis of infectious diseases. Published meta-analyses show that the pathogen detection rate of mNGS using bronchoalveolar lavage fluid (BALF) samples collected from children can reach 85.83%, which is markedly higher than the 49.97% detection rate of conventional testing approaches. This review systematically elaborates how mNGS reconstructs the cognition of pathogen spectrum in children with severe pneumonia: this technology accurately identifies complex mixed infection patterns, detects pathogens that cannot be captured by traditional testing, and redefines the clinical boundary between microbial colonization and invasive infection. Combined with latest clinical research data, this paper analyzes the core value of mNGS in optimizing treatment schemes, reducing irrational antibiotic use and realizing precision therapy for severe pneumonia in children. Meanwhile, the current limitations and future development directions of this technology are discussed.