肺部感染病原体识别中的NGS与传统方法比较

Comparison of NGS and Traditional Methods in Identifying Pathogens Causing Lung Infections

摘要: 肺部感染在免疫缺陷及老年患者中病死率高。传统检测方法存在周期长(48~72小时)、敏感性低、苛养菌检出困难及诊断窗口期等局限，导致治疗延误。高通量测序技术(next-generation sequencing, NGS)通过无偏倚检测总核酸，实现细菌、病毒、真菌和寄生虫同步识别，使病原体检出率提升20%~30%，对混合感染、罕见病原体及抗生素预处理样本优势显著，检测时效缩至24~48小时。其敏感性优于传统方法，但低生物量样本仍受宿主核酸干扰；特异性依赖严格生物信息学分析，需结合临床区分致病菌与定植菌。该技术使病毒检出率提升28%，显著提高免疫抑制患者罕见病原识别能力；耐药基因检测灵敏度优于传统测序，但存在同源病毒分型误差及成本高昂问题。NGS通过快速精准诊断优化临床决策：提前指导靶向治疗使重症患者28天生存率提升30%，并推动抗生素精准使用。临床应用仍面临宿主核酸干扰、15%耐药基因沉默现象、成本高及标准化缺失等挑战。未来发展需采用分层诊断策略(高危患者首选宏基因组测序)，推动CRISPR等多技术融合，依托医保政策支持协同价值。开发超低量测序、动态耐药库及解读系统，将促进该技术成为感染性疾病精准诊疗核心工具。

Abstract: Pulmonary infections have a high mortality rate in immunocompromised and elderly patients. Traditional diagnostic methods have limitations such as long turnaround times (48~72 hours), low sensitivity, difficulty in detecting fastidious bacteria, and diagnostic window periods, which can lead to treatment delays. High-throughput sequencing technology enables unbiased detection of total nucleic acids, achieving simultaneous identification of bacteria, viruses, fungi, and parasites. This improves pathogen detection rates by 20%~30%, with significant advantages for mixed infections, rare pathogens, and antibiotic-pretreated samples, reducing detection time to 24~48 hours. Its sensitivity surpasses traditional methods, but low-biological-mass samples remain susceptible to host nucleic acid interference; specificity depends on rigorous bioinformatics analysis and requires clinical differentiation between pathogenic and colonizing bacteria. This technology increases viral detection rates by 28%, significantly enhancing the identification of rare pathogens in immunocompromised patients; antibiotic resistance gene detection sensitivity surpasses traditional sequencing, but it faces issues such as homologous viral typing errors and high costs. NGS optimizes clinical decision-making through rapid and accurate diagnosis: early guidance on targeted therapy improves the 28-day survival rate of critically ill patients by 30% and promotes the precise use of antibiotics. Clinical applications still face challenges such as host nucleic acid interference, 15% gene silencing of drug resistance, high costs, and a lack of standardization. Future development requires a stratified diagnostic strategy (metagenomic sequencing as the first choice for high-risk patients), the integration of multiple technologies such as CRISPR, and the support of medical insurance policies to leverage synergistic value. The development of ultra-low-volume sequencing, dynamic resistance databases, and interpretation systems will promote this technology as a core tool for precision diagnosis and treatment of infectious diseases.