Table 1_tNGS-based detection of respiratory pathogens in a single center: associations with age, gender, season, and co-infections.docx

Background<p>Respiratory tract infections represent a significant global health challenge. Conventional diagnostic methods frequently fail to detect complex infections or novel pathogens. This study employed Targeted Next-Generation Sequencing to achieve an unbiased and comprehensive identific...

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Hlavní autor: Qingling Wang (485692) (author)
Další autoři: Dan Wu (5969) (author), Yanzi Zhang (6306962) (author), Qian Zeng (2866592) (author), Juan Wang (115708) (author), Xin Lv (770855) (author)
Vydáno: 2025
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Shrnutí:Background<p>Respiratory tract infections represent a significant global health challenge. Conventional diagnostic methods frequently fail to detect complex infections or novel pathogens. This study employed Targeted Next-Generation Sequencing to achieve an unbiased and comprehensive identification of respiratory pathogens, as well as to conduct analysis of pathogen distribution across age, gender and seasons.</p>Methods<p>We conducted a retrospective analysis of clinical samples, including throat swabs, sputum, and bronchoalveolar lavage fluid, obtained from symptomatic patients. The analysis utilized targeted next-generation sequencing in conjunction with bioinformatics. Statistical assessments were performed to evaluate associations with age, gender, season, and co-infections, primarily employing Chi-square tests.</p>Results<p>A high pathogen detection rate of 97.08% was achieved among 20059 individuals. Bacteria were the most frequently detected pathogens, accounting for 49.62%, followed by viruses at 43.31%, and special pathogens at 7.07%. Significant age-related differences in pathogen profiles were observed. Although no overall gender effect was detected, variations specific to certain pathogens were noted. Clear seasonal trends emerged for key pathogens. Co-infections were highly prevalent, with bacterial-viral combinations being the most common, affecting 49.03% of patients, which exceeded the rate of bacterial infections alone at 15.69%.</p>Conclusion<p>Targeted next-generation sequencing serves as a robust tool for elucidating the intricate spectrum and epidemiology of respiratory pathogens. This study underscores significant associations with patient age, seasonal variations, and the prevalence of co-infections, providing essential insights for targeted clinical and public health interventions in response to respiratory tract infections.</p>