DOAJ Open Access 2023

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

Zhen Li Changcheng Wu Li-An Tang Yinjie Liang Ruhan A +4 lainnya

Abstrak

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.

Penulis (9)

Z

Zhen Li

C

Changcheng Wu

L

Li-An Tang

Y

Yinjie Liang

R

Ruhan A

D

Debin Huang

C

Chuanyi Ning

W

Wenling Wang

W

Wenjie Tan

Format Sitasi

Li, Z., Wu, C., Tang, L., Liang, Y., A, R., Huang, D. et al. (2023). mNGS-based dynamic pathogen monitoring for accurate diagnosis and treatment of severe pneumonia caused by fungal infections. https://doi.org/10.1016/j.bsheal.2023.04.004

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Informasi Jurnal
Tahun Terbit
2023
Sumber Database
DOAJ
DOI
10.1016/j.bsheal.2023.04.004
Akses
Open Access ✓