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已发表论文
支气管肺泡灌洗液的宏基因组学下一代测序可提高下呼吸道感染病原体检测率并优化抗菌药物使用：一项回顾性研究
Authors Ma X, Zhang Q, Ji X, Xia Y , Cao J, Xu X
Received 3 October 2025
Accepted for publication 9 December 2025
Published 13 December 2025 Volume 2025:18 Pages 6611—6632
DOI https://doi.org/10.2147/IDR.S572028
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Oliver Planz
Xiangsong Ma,1 Qinqin Zhang,1,2 Xuelian Ji,1 Yun Xia,1 Ju Cao,1 Xiuyu Xu1
1Department of Laboratory Medicine, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People’s Republic of China; 2Department of Laboratory Medicine, People’s Hospital of Mingshan District, Ya’an, Sichuan, 625100, People’s Republic of China
Correspondence: Xiuyu Xu, Department of Laboratory Medicine, the First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuzhong District, Chongqing, 400016, People’s Republic of China, Email xuxiuyu85@126.com
Purpose: With the advancement of metagenomic next-generation sequencing (mNGS), its role in diagnosing lower respiratory tract infections (LRTIs) has expanded rapidly. LRTIs remain a major global health burden, particularly in critically ill patients where diagnosis is challenging. Routine microbiological testing (RMT), including culture, microscopy, antigen detection, and PCR—are limited by low sensitivity, long turnaround times, and restricted pathogen coverage. This study assesses the diagnostic performance of mNGS in LRTIs, with emphasis on pathogen detection and resistance gene prediction, and compares it with traditional methods to clarify its clinical benefits and limitations.
Methods: This retrospective study included 367 hospitalized patients with suspected LRTIs. All patients underwent mNGS testing, which was compared with traditional diagnostic methods. We also used mNGS to explore the pathogen spectrum characteristics in critically ill patients with pneumonia and evaluated its applicability in predicting antimicrobial resistance genes and adjusting antibiotic treatment.
Results: For patients diagnosed with LRTIs, mNGS demonstrated superior microbial detection efficacy, particularly for bacteria and fungi, relative to culture (bacteria: 56.58% vs 17.37%, P < 0.0001; fungi: 49.65% vs 16.78%, P < 0.0001) and PCR (65.14% vs 45.14%, P < 0.05). In contrast to the non-severe pneumonia group, the detection rate of Enterococcus faecium was highest in the severe pneumonia group (P < 0.001), and the severe pneumonia group had more mixed infections (P < 0.001). In addition, mNGS showed high accuracy in predicting antibiotic resistance genes, with 90.57% agreement with antibiotic susceptibility testing (AST) results. Based on the mNGS results, 97.82% of patients underwent active adjustment to their antibiotic treatment regimen.
Conclusion: mNGS is an effective tool for diagnosing LRTIs, with significantly higher pathogen detection rates than traditional methods. mNGS also demonstrates high accuracy in predicting antimicrobial resistance, providing crucial support for clinical treatment decisions.
Keywords: LRTIs, mNGS, diagnosis, pathogens, antimicrobial resistance
1Department of Laboratory Medicine, the First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, People’s Republic of China; 2Department of Laboratory Medicine, People’s Hospital of Mingshan District, Ya’an, Sichuan, 625100, People’s Republic of China
Correspondence: Xiuyu Xu, Department of Laboratory Medicine, the First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuzhong District, Chongqing, 400016, People’s Republic of China, Email xuxiuyu85@126.com
Purpose: With the advancement of metagenomic next-generation sequencing (mNGS), its role in diagnosing lower respiratory tract infections (LRTIs) has expanded rapidly. LRTIs remain a major global health burden, particularly in critically ill patients where diagnosis is challenging. Routine microbiological testing (RMT), including culture, microscopy, antigen detection, and PCR—are limited by low sensitivity, long turnaround times, and restricted pathogen coverage. This study assesses the diagnostic performance of mNGS in LRTIs, with emphasis on pathogen detection and resistance gene prediction, and compares it with traditional methods to clarify its clinical benefits and limitations.
Methods: This retrospective study included 367 hospitalized patients with suspected LRTIs. All patients underwent mNGS testing, which was compared with traditional diagnostic methods. We also used mNGS to explore the pathogen spectrum characteristics in critically ill patients with pneumonia and evaluated its applicability in predicting antimicrobial resistance genes and adjusting antibiotic treatment.
Results: For patients diagnosed with LRTIs, mNGS demonstrated superior microbial detection efficacy, particularly for bacteria and fungi, relative to culture (bacteria: 56.58% vs 17.37%, P < 0.0001; fungi: 49.65% vs 16.78%, P < 0.0001) and PCR (65.14% vs 45.14%, P < 0.05). In contrast to the non-severe pneumonia group, the detection rate of Enterococcus faecium was highest in the severe pneumonia group (P < 0.001), and the severe pneumonia group had more mixed infections (P < 0.001). In addition, mNGS showed high accuracy in predicting antibiotic resistance genes, with 90.57% agreement with antibiotic susceptibility testing (AST) results. Based on the mNGS results, 97.82% of patients underwent active adjustment to their antibiotic treatment regimen.
Conclusion: mNGS is an effective tool for diagnosing LRTIs, with significantly higher pathogen detection rates than traditional methods. mNGS also demonstrates high accuracy in predicting antimicrobial resistance, providing crucial support for clinical treatment decisions.
Keywords: LRTIs, mNGS, diagnosis, pathogens, antimicrobial resistance