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Comparative Study
. 2025 Apr 8:15:1530486.
doi: 10.3389/fcimb.2025.1530486. eCollection 2025.

A retrospective analysis comparing metagenomic next-generation sequencing with conventional microbiology testing for the identification of pathogens in patients with severe infections

Fei Hou  1   2 , Yanting Qiao  3 , Yuanyuan Qiao  3 , Ya Shi  3 , Mingrui Chen  3 , Min Kong  1   2 , Xiaohang Hu  2 , Liqing Jiang  2 , Xiaowei Liu  3
Affiliations
Comparative Study

A retrospective analysis comparing metagenomic next-generation sequencing with conventional microbiology testing for the identification of pathogens in patients with severe infections

Fei Hou et al. Front Cell Infect Microbiol. .

Abstract

Introduction: The application value of metagenomic next-generation sequencing (mNGS) in detecting pathogenic bacteria was evaluated to promote the rational and accurate use of antibiotics. A total of 180 patients with severe infections were included in this study.

Methods: Based on their different symptoms, bronchoalveolar lavage fluid (BALF) or blood samples were collected for conventional microbiological testing (CMT) and mNGS.

Results: The results indicated that the etiological diagnosis rate of mNGS (78.89%) was significantly higher than that of CMT (20%) (p<0.001). Notably, mNGS exhibited greater sensitivity towards rare pathogens such as Chlamydia pneumoniae, Mycobacterium tuberculosis complex, and Legionella pneumophila, which were undetectable by CMT. Additionally, 64 cases underwent blood culture, BALF culture, and mNGS testing. Analysis revealed that the positive rate of blood culture (3.1%) was lower than that of BALF (25%), and the positive rate of CMT from both types was significantly lower than that of mNGS (89.1%) (p<0.001). In this study, 168 mNGS results were accepted, and 116 patients had their antibiotic therapy adjustment based on mNGS. Paired analysis indicated that white blood cell count (WBC), procalcitonin (PCT), C-reactive protein (CRP), and neutrophil (NEU) percentage provided valuable therapeutic guidance. The survival rate of patients was 55.36%, influenced by patient physical condition and age.

Discussion: Our data indicated that mNGS had significant auxiliary value in the clinical diagnosis and treatment for critically ill patients, especially for those with negative CMT results and clinically undefined infections. mNGS could broaden the detection scope, especially for special pathogens, and improve the detection rate, providing powerful assistance for early clinical diagnosis and treatment.

Keywords: blood; bronchial alveolar lavage fluid; conventional microbiological testing; detection of pathogens; metagenomic next-generation sequencing; severe infections.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Flow diagram.
Figure 2
Figure 2
Concordance of samples between mNGS and CMTs. (A) The positive rates of pathogen identification between mNGS and CMT in BALF (85.94%, 110/128 vs 21.86%, 28/128) (p<0.001) and blood (61.54%, 32/52 vs 15.38%, 8/52) (p<0.001). (B) Concordance of diagnosis between mNGS and CMT. 36 cases (21.4%, 36/168) were both positive, 26 cases (15.5%, 26/168) were negative for both methods, and 106 cases (63.1%, 106/168) were positive by mNGS only. (C) There were 3 cases (10.7%) were matched, 18 cases (64.3%) were partially matched, and 7 cases (25%) were completely mismatched in BALF. 3 cases (33.3%) were matched, 5 cases (55.6%) were partially matched, and 1 case (11.1%) was mismatched in Blood.
Figure 3
Figure 3
Comparative analysis of laboratory indicators before and after treatment. Statistical significance was determined using a paired t-test. (A) WBC, white blood cell, p=0.0028; (B) PCT, procalcitonin, p=0.0156; (C) CRP, C-reactive protein, p<0.0001; (D) NEU, neutrophils, p<0.0001.
Figure 4
Figure 4
Three-month survival rate analysis. (A) Patients were well previously vs Patients underlying medical conditions (p=0.0278). (B) ≥65 vs <65 (p=0.0002).
See this image and copyright information in PMC

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