Applying metagenomic next-generation sequencing to analyze infections in immunosuppressed patients with chronic kidney disease: A single-center retrospective study
DOI:
https://doi.org/10.3855/jidc.20713Keywords:
Chronic kidney disease, immunodeficiency, infection, metagenomic next-generation sequencingAbstract
Introduction: This retrospective study evaluated the diagnostic value and clinical application of metagenomic next-generation sequencing (mNGS) for detecting infections in immunosuppressed CKD patients.
Methodology: Data from immunosuppressed CKD patients who were suspected of having an infection and admitted to Jinling Hospital from 2018–2022 were retrospectively analyzed. The patients were divided into the conventional microbiological testing (CMT)-confirmed infection group (Group I), clinically diagnosed infection group (Group II), and exclusion of infection group (Group III), and the efficiencies of microbiological detection with mNGS and CMT were compared.
Results: In the 303 patients included in this study, 2 (1, 3) types of immunosuppressants were used for a median duration of 7 (2, 50) months. In Group I, 38.79% of the mNGS results were completely consistent with the CMT results, 27.88% were partially consistent, and 33.33% were inconsistent. In Group II, 57.69% of the infecting pathogens were detected by mNGS. Furthermore, 2 patients in Group III had positive NGS results. mNGS outperformed CMT in terms of the time to a positive test and the detection of mixed or rare microbial pathogens (p < 0.05). The sensitivity and accuracy of the detection of infectious pathogens were greater for mNGS than for CMT (p = 0.014).
Conclusions: mNGS can improve the sensitivity and accuracy of infectious pathogen detection in immunosuppressed CKD patients. mNGS is a promising emerging technique for detecting pathogens in CKD patients, with potential benefits in speed and sensitivity, and may provide more diagnostic evidence for the detection of mixed, opportunistic, and rare infectious pathogens.
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Copyright (c) 2025 Zhe Li, Shuhua Zhu, Jing Jiang, Yang Wang, Yuchao Zhou, Shutian Xu, Shijun Li

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Funding data
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Nanjing General Hospital of Nanjing Military Command
Grant numbers 22JCYYYB8, 2023JCYJYB126

