Clinical value of macrogenome next-generation sequencing on infections

Author:

Han Benfa1,Zhang Xiaoli1,Li Xiuxi1,Chen Mei1,Ma Yanlin2,Zhang Yunxia1,Huo Song1

Affiliation:

1. Department of Infectious Diseases, Southern Central Hospital of Yunnan Province, The First People’s Hospital of HongHe State , Honghe , 661000, Yunnan , China

2. Department of Pharmaceutical, Southern Central Hospital of Yunnan Province, The First People’s Hospital of HongHe State , Honghe , 661000, Yunnan , China

Abstract

Abstract Intracranial infection (ICI) is a frequent and serious complication after neurosurgery. Macrogenome next-generation sequencing (mNGS) technology can provide reference for clinical diagnosis and treatment of ICI. This work aimed to explore the application value of mNGS technology in analyzing the clinical characteristics of human immunodeficiency virus (HIV) infection and ICI after neurosurgery. A total of 60 patients with ICI were enrolled as the research objects, all patients underwent routine cerebrospinal fluid analysis and traditional pathogen detection, followed by mNGS genome analysis. Using clinical diagnosis of ICI as the gold standard, the sensitivity, specificity, positive predictive value, and negative predictive value for both detection methods were calculated. Receiver operating characteristic curves were constructed to assess the area under the curve (AUC) for evaluating the clinical value of mNGS in suspected intracranial infectious pathogen diagnosis. Results showed a positivity rate of 71.67% (43 cases) with mNGS compared to 28.33% (17 cases) with traditional pathogen detection methods, demonstrating a significant difference (P < 0.05). The sensitivity of mNGS for detecting ICIs was 83.7%, significantly higher than the 34.88% observed with traditional methods (P < 0.05). The pathogen detection rate of mNGS was higher than traditional methods (P = 0.002), with an AUC of 0.856 (95% CI: 0.638–0.967), significantly greater than the AUC of 0.572 (95% CI: 0.350–0.792) for traditional methods (P < 0.05). mNGS successfully identified microorganisms such as Cryptococcus, Propionibacterium, Staphylococcus, Corynebacterium, Micrococcus, and Candida associated with ICIs. These findings underscore the clinical applicability of mNGS technology in analyzing the characteristics of HIV infection and ICI post-neurosurgical procedures. This technology enables more accurate diagnosis and treatment of ICIs, providing valuable insights for developing effective therapeutic strategies.

Publisher

Walter de Gruyter GmbH

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3