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Clinical characteristics of pathogens in children with community-acquired pneumonia were analyzed via targeted next-generation sequencing detection

作者
Junhua Zhao,Mingfeng Xu,Zheng Tian,Yu Wang
出处
期刊:PeerJ [PeerJ, Inc.]
卷期号:13: e18810-e18810 被引量:8
标识
DOI:10.7717/peerj.18810
摘要

Background The primary purpose of this study was to detect the pathogen species using targeted next-generation sequencing (tNGS) to investigate the characteristics of community-acquired pneumonia (CAP)-related pathogens in children in Xiantao city, Hubei province, China. Methods A total of 1,527 children with CAP were prospectively recruited from our hospital between May 2022 and February 2023. Information on age and sex was collected from the medical records. Pathogen detection was performed using standard detection methods and tNGS. Results The positive coincidence rate of standard detection methods and tNGS were 61.95% (946/1,527) and 97.05% (1,482/1,527), respectively. Among the 1,482 children with CAP, the numbers of bacteria, virus, chlamydia, and mycoplasma infection were 1,188, 975, 321, and 1, respectively. Co-existing species showed high prevalence in CAP, and the prevalence of children infected with only one pathogen was 20.31%. The numbers of children infected with two and three pathogens were the highest, accounting for 29.22% and 25.17%, respectively. Among the 44 pathogens detected using tNGS, 17 species of bacteria, 25 species of viruses, one species of chlamydia, and one species of mycoplasma were documented. Among all infectious pathogens, the top five were Haemophilus influenzae , Acinetobacter baumannii, Streptococcus pneumoniae , human herpes virus type 5 (HHV-5), and Mycoplasma pneumoniae . The results showed that pathogenic infections in children with CAP were related to age but not to gender. Conclusion The infection pathogens in children with CAP were complex and the incidence of co-existence was observed to be high. The pathogens involved in CAP were closely related to the age of the child. In addition, tNGS was shown to better identify pathogens than the standard detection method, which is crucial for improving the accuracy of early CAP diagnosis and initiating appropriate treatment in a timely manner, ultimately enhancing treatment outcomes.

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