| 周丹丹,方丽.基于呼吸道微生物组学的重症肺炎发病机制与诊疗策略研究进展[J].安徽医药,待发表. |
| 基于呼吸道微生物组学的重症肺炎发病机制与诊疗策略研究进展 |
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| 投稿时间：2026-07-03 录用日期：2026-08-03 |
| DOI： |
| 中文关键词: 重症肺炎 呼吸道微生物组 人工智能 精准治疗 |
| 英文关键词: |
| 基金项目:贵州省科技计划项目(黔科合基础-ZK[2021]一般445) |
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| 摘要点击次数: 63 |
| 全文下载次数: 0 |
| 中文摘要: |
| 重症肺炎发病急、死亡率高，传统单一病原体的诊疗思路存在明显局限。近年来，高通量测序有力推动了呼吸道微生物组学研究，尤其是结合机器学习算法的宏基因组下一代测序技术，不仅可实现菌株级水平的多种病原体同时检测，还能够构建动态的重症肺炎风险评估模型，在抗生素靶向治疗与微生态精准干预方面展现出巨大的应用潜力。本文梳理了呼吸道微生物组在重症肺炎发病机制及诊疗中的研究进展，同时指出未来应发展时空监测技术，建立免疫?微生物组动态预测模型，并探索代谢通路的定向干预，以期推动诊疗从经验模式向精准生态重塑转变。 |
| 英文摘要: |
| Severe pneumonia strikes quickly and kills many people, and the classical diagnostic and therapeutic approaches that focus on single pathogen have obvious shortcomings. Over the past few years, high-throughput sequencing has greatly promoted the research on the respiratory microbiome, especially a combination of machine learning algorithms and metagenomic next-generation sequencing technique can not only detect a variety of pathogens all at once and further identify them at the strain level but also establish the dynamic risk assessment models for severe pneumonia, thus sharing a great value of applications in both antibiotic targeted therapy and precise intervention of microecology. This article reviewed the research progress of the respiratory microbiome in the pathogenesis, diagnosis and treatment of severe pneumonia. It also pointed out that in the future, it will be necessary to develop spatiotemporal monitoring technologies, establish dynamic prediction models of the immune-microbiome, and explore targeted intervention of metabolic pathways, in order to promote the transformation of the diagnosis and treatment of severe pneumonia from an empirical model to a precise ecological remodeling. |
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