JOURNAL ARTICLE
Clinical application of targeted next-generation sequencing utilizing bronchoalveolar lavage fluid in thoracic surgery ICU patients with suspected pulmonary infections.
Published In: Journal of Applied Microbiology, 2025, v. 136, n. 1. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Guo, Xiaobo; Xie, Nianlin; Xi, Xiaotong; Li, Pei; Jia, Jianbo; Chen, Lianhong; Ren, Mingzhi; Wang, Yaping; Zhang, Peipei; Deng, Wanglong; Wang, Yan; Jing, Pengyu; Ding, Ran; Gu, Zhongping 3 of 3
Abstract
This article evaluates the diagnostic value of targeted next-generation sequencing (tNGS) for identifying pathogens in bronchoalveolar lavage fluid (BALF) from thoracic surgery intensive care unit (ICU) patients with suspected pulmonary infections. In a prospective study of 50 patients, tNGS demonstrated a significantly higher positive detection rate (96%) and sensitivity (95.83%) compared to traditional pathogen detection (TPD) methods, which include culture and loop-mediated isothermal amplification assays (68% positive rate, 68.75% sensitivity). tNGS identified a broader spectrum of pathogens, including bacteria, fungi, DNA viruses, and RNA viruses, and showed particular strength in detecting mixed and atypical infections. The study concludes that tNGS is a rapid, sensitive, and cost-effective diagnostic tool that can enhance pathogen detection and potentially improve clinical management of pulmonary infections in thoracic surgery ICU settings.
Additional Information
- Source:Journal of Applied Microbiology. 2025/01, Vol. 136, Issue 1, p1
- Document Type:Article
- Subject Area:Biology
- Publication Date:2025
- ISSN:1364-5072
- DOI:10.1093/jambio/lxae313
- Accession Number:182905278
- Copyright Statement:Copyright of Journal of Applied Microbiology is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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