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mNGS-based dynamic pathogen monitoring for accurate diagnosis and treatment of severe pneumonia caused by fungal infections

Authors :
Zhen Li
Changcheng Wu
Li-An Tang
Yinjie Liang
Ruhan A
Debin Huang
Chuanyi Ning
Wenling Wang
Wenjie Tan
Source :
Biosafety and Health, Vol 5, Iss 3, Pp 138-143 (2023)
Publication Year :
2023
Publisher :
Elsevier, 2023.

Abstract

Metagenomic next-generation sequencing (mNGS) has been widely applied to identify pathogens associated with infectious diseases. However, limited studies have explored the use of mNGS-based dynamic pathogen monitoring in intensive care unit patients with severe pneumonia. Here, we present a clinical case of an 86-year-old male patient with severe pneumonia caused by a fungal infection. During the clinical treatment, four mNGS analyses were performed within two consecutive weeks. Various respiratory fungal pathogens, including Candida orthopsilosis, Candida albicans, and Aspergillus fumigatus were detected by mNGS of bronchoalveolar lavage fluid (BALF). Based on conventional pathogen identification and clinical symptoms, the patient was diagnosed with severe pneumonia caused by a fungal infection. The abundance of fungal species decreased gradually in response to antifungal and empirical therapies, and the fungal infections were effectively controlled. In summary, our results demonstrated that mNGS could effectively identify pathogens in patients with severe pneumonia. Additionally, dynamic pathogen monitoring based on mNGS could assist in the precise diagnosis of complex infections and may facilitate rapid induction of the most appropriate therapy.

Details

Language :
English
ISSN :
25900536
Volume :
5
Issue :
3
Database :
Directory of Open Access Journals
Journal :
Biosafety and Health
Publication Type :
Academic Journal
Accession number :
edsdoj.004ad39d3a9b43d4be85a97eb76111d6
Document Type :
article
Full Text :
https://doi.org/10.1016/j.bsheal.2023.04.004