ArticleInfection and drug resistance2023
Secondary Infection Surveillance with Metagenomic Next-Generation Sequencing in COVID-19 Patients: A Cross-Sectional Study.
Article in Infection and drug resistance, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 9 citations in OpenAlex.
- SARS‑CoV‑2 Associated Shifts in the Upper Respiratory Tract Mycobiome in Non-hospitalized Cases.Mycopathologia · 2026Article
- Review
- Yield of clinical metagenomics: insights from real-world practice for tissue infections.EBioMedicine · 2025Article
- Spontaneous inferior epigastric artery hemorrhage in a COVID-19 patient with membranous nephropathy on anticoagulant therapy: a Case Report.Frontiers in medicine · 2025Article
- Clinical usefulness of metagenomic next-generation sequencing for Talaromyces marneffei diagnosis in China: a retrospective study.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2024Article
- Review
- Case Report: Diagnosis of Hemolytic Anemia from Babesia and Secondary Multi-Pathogen Pneumonia Using a Metagenomic Next-Generation Sequencing Approach.Infection and drug resistance · 2024Article
Corrections and comments
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Authors and funding
13 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Metagenomic next-generation sequencing (mNGS) is a promising tool for improving antimicrobial therapy and infection control decision-making in complex infections. Secondary infection surveillance using mNGS in COVID-19 patients has rarely been reported. Methods: Respiratory pathogen and antibiotic resistance prediction were evaluated by BALF mNGS for 192 hospitalized COVID-19 patients between December 2022 and February 2023. Results: Secondary infection was confirmed in 83.3% (160/192) of the COVID-19 patients, with bacterial infections (45%, 72/160) predominating, followed by mixed bacterial and fungal infections (20%, 32/160), and fungal infections (17.5%, 28/160). The incidence of bacterial or viral secondary infection was significantly higher in patients who were admitted to the ICU, received mechanical ventilation, or developed severe pneumonia (all p<0.05). Conclusion: mNGS can detect pathogens causing secondary infection and predict antimicrobial resistance for COVID19 patients. This is crucial for initiating targeted treatment and rapidly detect unsuspected spread of multidrug-resistant pathogens.
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