潘盼.急性呼吸窘迫综合征的临床表型[J].内科急危重症杂志,2022,28(5):353-356
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| DOI：10.11768/nkjwzzzz20220501 |
| 中文关键词: 急性呼吸窘迫综合征 表型 大数据 人工智能 精准治疗 |
| 英文关键词: |
| 基金项目:国家重点研发课题（No:2021YFC0122500） |
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| 摘要点击次数: 1028 |
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| 中文摘要: |
| 急性呼吸窘迫综合征(ARDS)在新冠肺炎疫情背景下再度成为公众关注焦点。纵观ARDS发展史，结合新冠肺炎治疗经验，我们深刻意识到ARDS的传统认知存在局限，因技术手段的束缚只能从单一临床表现或某个生物学现象/分子在特定时空维度下去解释复杂的ARDS。而临床数据信息化的建立、组学技术的发展及机器学习算法的完善，使重新认识ARDS成为可能，即ARDS临床表型的概念。ARDS表型分为内表型和外表型，内外表型的联合将能够实时动态连续的反映患者的临床病情变化和对治疗的反应。这将为形成智能化、个体化、精准化的ARDS治疗体系，使ARDS诊断、预后、治疗的临床辅助决策支持成为可能。 |
| 英文摘要: |
| Acute respiratory distress syndrome (ARDS) has once again become the focus of the public attention in the backgrounds of the COVID-19 epidemic. Throughout the history of ARDS combined with the lessons learned from the COVID-19 treatment, we have a deep understanding of the limitations of traditional knowledge. Due to the constraints of technology, the complicated ARDS can only be explained from a single clinical manifestation or a certain biological phenomenon/molecule in a specific time and space dimension. With the establishment of clinical data informatization, the development of omics technology and the improvement of machine learning algorithms, it is possible and necessary to re-understand ARDS. The concept of the clinical phenotype of ARDS is proposed. ARDS phenotype is divided into phenotype and endotype. The combination of phenotype and endotype will be able to reflect the patient's clinical condition changes and treatment response dynamically and continuously in real time. It will provide a series of algorithms and applications have been developed to form an intelligent, individualized, and precise ARDS treatment system to achieve clinical decision support for ARDS diagnosis, prognosis, and treatment. |
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