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ArticleClinical rheumatology2025

Clinical value of metagenomic next-generation sequencing in patients with connective tissue diseases co-infections: a single-center study from southern hospital in China.

Yuan-Yuan Xiao, Ai-Ling Lu, Han-You Mo, Zhen-Dong He, Jia-Le Wen, Xuan Yin

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Article in Clinical rheumatology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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6 authors.

Yuan-Yuan XiaoDepartment of Rheumatology, Guilin Medical University, Guilin, Guangxi, China.
Ai-Ling LuDepartment of Rheumatology, Guilin Medical University, Guilin, Guangxi, China.
Han-You MoDepartment of Rheumatology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China. mohanyou@hotmail.com.ORCID http://orcid.org/0000-0001-5482-5014
Zhen-Dong HeDepartment of Rheumatology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
Jia-Le WenDepartment of Rheumatology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
Xuan YinDepartment of Rheumatology, Guilin Medical University, Guilin, Guangxi, China.

Funding

National Natural Science Foundation of China 81760298Natural Science Foundation of Guangxi Zhuang Autonomous Region 2021JJA140699the First Afliated Hospital of Guangxi Medical University (Grant No. YYZS2023005).
6 · The paper itself

Abstract

objectivesThis study aimed to assess the clinical value of metagenomic next-generation sequencing (mNGS) in patients with connective tissue diseases (CTDs) co-infections, thereby establishing a foundation for early infection identification and the development of anti-infective regimens.

methodsThis retrospective study analyzed 304 CTD patients with suspected infections at the First Affiliated Hospital of Guangxi Medical University between October 2020 and April 2024. The study compared the diagnostic efficacy between mNGS and conventional microbiological testing (CMT), examined pathogen detection rates across different periods and pathogen types, and evaluated the clinical outcomes of mNGS-guided antimicrobial regimen adjustments.

resultsAmong the 180 confirmed infections (Group I), mNGS demonstrated superior diagnostic performance compared to conventional microbiological testing (CMT). mNGS exhibited significantly higher sensitivity (89.6% vs. 57.0%; OR = 6.5, 95% CI: 3.7-11.0, p < 0.001), with a specificity of 81.5%, positive predictive value (PPV) of 97.2%, and negative predictive value (NPV) of 52.4%. mNGS outperformed CMT in detecting bacterial and viral pathogens (p < 0.05). Viral infections were the most common. Compared to prior studies, mNGS exhibited improved pathogen detection rates. mNGS-guided treatment optimization significantly enhanced clinical outcomes, with higher cure rates, lower mortality, and shorter hospital stays.

conclusionCurrent evidence suggests that while mNGS demonstrates superior diagnostic performance over CMT for detecting infections in CTD patients, their combined use provides optimal pathogen identification accuracy and enhanced clinical management. Key Points • This is the larger-scale retrospective study of mNGS application in patients with CTDs co-infections following the Coronavirus Disease 2019 (COVID-19). • We found that the distribution of pathogens and positivity rates have changed in recent years, especially after the COVID-19. • The clinical value of mNGS was further demonstrated through its impact of mNGS results on antibiotic regimens and the analysis of negative samples.

Indexed as

Bacterial InfectionsCoinfectionConnective Tissue DiseasesHigh-Throughput Nucleotide SequencingMetagenomicsVirus DiseasesAdultAgedChinaCOVID-19FemaleHumansMaleMiddle AgedRetrospective StudiesClinical valueConnective tissue diseasesInfectionsMetagenomic next-generation sequencingPathogens

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.