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Performance evaluation of mNGS in pathogen diagnosis of skin and soft tissue infections and its optimization effect
Xuyang Li1, Jiaao Fang1, Dongqin Li1
1Department of Dermatology, First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Background:
Skin and soft tissue infections (SSTIs), often caused by polymicrobial pathogens, pose diagnostic challenges due to the limitations of conventional methods, including low sensitivity and prolonged turnaround time. This diagnostic gap has perpetuated empirical antibiotic use in clinical practice. Metagenomic next-generation sequencing (mNGS), with its unbiased pathogen detection capability, offers a transformative approach for rapid and precise microbial identification in SSTIs.
Objective:
To evaluate the clinical utility of mNGS compared to conventional microbiological testing in guiding antibiotic stewardship for complex SSTIs.
Methods:
A retrospective cohort study was conducted at the First Affiliated Hospital of Zhengzhou University from April 2023 to May 2025, enrolling 69 patients with clinically diagnosed complex SSTIs. All patients underwent concurrent mNGS testing, conventional bacterial culture, and pathological examination. The diagnostic performance of mNGS was systematically compared with culture methods, with emphasis on culture-negative cases and polymicrobial infections. The impact of mNGS-guided antibiotic adjustments was assessed.
Results:
mNGS demonstrated significantly higher pathogen detection rates than conventional culture (P < 0.001), with a concordance of 37.5% between the two methods. Among 24 culture-negative patients, mNGS identified pathogens in 20 cases (83.3% detection rate). For polymicrobial infections (n = 20), culture detected pathogens in only 2 cases, whereas mNGS successfully identified multiple pathogens in the majority. Antibiotic therapy was adjusted based on mNGS results in 11.9% (8/69) of patients.
Conclusion:
mNGS substantially improves pathogen detection in complex SSTIs compared to conventional methods. Beyond diagnostic accuracy, its clinical value lies in enabling targeted antibiotic therapy, thereby optimizing antimicrobial stewardship and potentially reducing healthcare costs.
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