在中枢神经系统感染中优化元基因组下一代测序:基于CSF参数的诊断模型
Xiao-Guang Cao1, Xiong-Feng Zhu2, Jun-Xi Ni2
1Department of Emergency Medical Center, the First Affiliated Hospital of University of Science and Technology of China (Anhui Provincial Hospital), Hefei, Anhui, China.
Frontiers in cellular and infection microbiology
|February 5, 2026
概括
脑脊液 (CSF) 细胞数和蛋白质水平可以预测疑似中枢神经系统 (CNS) 感染的元基因组下一代测序 (mNGS) 阳性. 这种预测模型可以帮助优化mNGS测试策略,特别是在资源有限的环境中.
科学领域:
- 神经科学是一个神经科学.
- 传染性疾病 传染性疾病
- 分子诊断学 分子诊断
背景情况:
- 中枢神经系统 (CNS) 感染带来了诊断挑战,通常需要先进的分子技术,如元基因组下一代测序 (mNGS).
- 常规的脑脊液 (CSF) 生物化学参数很容易获得,但它们与mNGS导致中枢神经系统感染的关联尚未完全阐明.
- 优化使用mNGS,一个敏感但昂贵的诊断工具,至关重要,特别是在资源有限的环境中.
研究的目的:
- 评估在疑似中枢神经系统感染的患者中标准的CSF生化标志物和mNGS发现之间的相关性.
- 开发和验证使用CSF参数来指导mNGS测试策略的预测模型.
- 提高中枢神经系统感染诊断的诊断产量和成本效益.
主要方法:
- 对110名疑似中枢神经系统感染的患者的回顾性分析,比较CSF分析和mNGS结果.
- 使用后勤回归来确定mNGS阳性的独立预测因素,重点关注CSF细胞数量和蛋白质度.
- 开发了一个预测性名录,并在内部 (10倍交叉验证,引导) 和外部 (40名患者) 验证.
主要成果:
- mNGS在56.36%的病例中检测到感染,明显高于CSF培养 (6.36%).
- 与mNGS阴性病例相比,mNGS阳性患者的CSF细胞数量,蛋白质水平和度显著增加,葡萄糖水平降低.
- 结合CSF细胞计数和蛋白质的预测模型表现良好,在导出队列中,曲线下的面积 (AUC) 为0.782,在外部验证队列中为0.763.
结论:
- 在疑似中枢神经系统感染时,CSF细胞数量和蛋白质度是mNGS阳性的强有力的预测指标.
- 开发的预测模型显示了一致的诊断性能和临床实用性.
- 该模型可以帮助临床医生做出有关mNGS测试的明智决策,从而优化诊断工作流程,特别是在资源有限的医疗机构.
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