中国全科医学 ›› 2026, Vol. 29 ›› Issue (06): 790-801.DOI: 10.12114/j.issn.1007-9572.2025.0176

• 综述与专论 • 上一篇    

急性心肌梗死患者炎症反应研究进展

王立娜1, 雷警输2, 李奎宝3, 王睿颖2, 李新苗2, 王芳芳2, 郭晓荣2, 牛瑞浩2, 赵伟2, 周芳芳2, 赵京晶2, 李忠佑1,*()   

  1. 1.100044 北京市,北京大学人民医院心血管内科 急性心肌梗死早期预警和干预北京市重点实验室
    2.065201 河北省廊坊市,河北燕达医院心血管内科
    3.100013 北京市,首都医科大学附属北京朝阳医院心血管内科
  • 收稿日期:2025-06-24 修回日期:2025-08-19 出版日期:2026-02-20 发布日期:2026-01-05
  • 通讯作者: 李忠佑

  • 作者贡献:

    王立娜、雷警输、李奎宝、李忠佑提出文章思路,负责文章命题及设计;王立娜负责文章书写、文献汇总、文章框架设定等实施;王睿颖、李新苗、王芳芳、郭晓荣、牛瑞浩、赵伟、周芳芳、赵京晶负责数据收集、采集,文献汇总、总结等;王立娜负责论文起草;王立娜、雷警输、李奎宝、李忠佑负责最终版本修订,对论文负责。

  • 基金资助:
    河北省卫生健康委员会课题(20220967)

Review on Inflammatory Response in Patients with Acute Myocardial Infarction

WANG Lina1, LEI Jingshu2, LI Kuibao3, WANG Ruiying2, LI Xinmiao2, WANG Fangfang2, GUO Xiaorong2, NIU Ruihao2, ZHAO Wei2, ZHOU Fangfang2, ZHAO Jingjing2, LEE CHONGYOU1,*()   

  1. 1. Department of Cardiology/Beijing Key Laboratory of Early Prediction and Intervention of Acute Myocardial Infarction, Peking University People's Hospital, Beijing 100044, China
    2. Department of Cardiology, Hebei Yanda Hospital, Langfang 065201, China
    3. Department of Cardiology, Beijing Chao-yang Hospital, Capital Medical University, Beijing 100013, China
  • Received:2025-06-24 Revised:2025-08-19 Published:2026-02-20 Online:2026-01-05
  • Contact: LEE CHONGYOU

摘要: 炎症反应在急性心肌梗死(AMI)患者的发病机制和预后中起着关键作用,甚至胜于传统危险因素对AMI的影响,但缺乏对AMI患者炎症反应病理生理机制、临床意义和目前循证医学证据的系统总结。本文梳理相关文献,全面探讨了炎症反应在AMI患者中的作用机制、相关炎症衍生指标、临床意义和目前研究证据的汇总。本文表明AMI初始阶段为炎症反应在罪犯病变内产生早期反应激增,是最具破坏性的阶段,后续阶段多种免疫细胞和细胞因子协同作用参与心肌修复和愈合。因此AMI患者存在复杂的炎症网络机制,可能成为AMI治疗新的突破口,但目前对免疫机制在心脏重塑中的作用是不完整和不全面的,最大的困境是起初促炎和有害的细胞也可显示出强大的愈合特性,使得研究甚至产生相反的结果,因此目前AMI患者的抗炎治疗循证医学证据并不充分。或许将来基于人工智能辅助的炎症表型分型"机器学习",联合多维度炎症指标,识别单独个体中免疫细胞的特定作用,可实现炎症调控从理论到临床的突破,破解心血管残余风险困局。本文能够为AMI患者抗炎治疗深入开展提供借鉴。

关键词: 心肌梗死, 急性心肌梗死, 炎症, 人工智能, 残余风险, 预后, 综述

Abstract:

Inflammatory response plays a crucial role in the pathogenesis and prognosis of acute myocardial infarction (AMI) patients, even surpassing the influence of traditional risk factors on AMI. However, there is a lack of systematic summary of the pathophysiological mechanisms, clinical impaction, and current evidence-based medicine of inflammatory response in AMI patients. We reviewed the relevant literature and comprehensively explores the mechanism of inflammatory response in AMI patients, related inflammatory derived indicators, clinical significance, and a summary of current research evidence. We exposed that the initial stage of AMI is characterized by a rapid increase in inflammatory response, which is the most destructive stage. In the subsequent stage, multiple immune cells and cytokines work together to participate in myocardial repair and healing. Therefore, AMI patients have a complex inflammatory network mechanism, which may become a new breakthrough for AMI treatment. However, our current understanding of the role of immune mechanisms in cardiac remodeling is incomplete. The biggest challenge is that initially pro-inflammatory and harmful cells can also exhibit strong healing characteristics, leading to research even producing opposite results. Therefore, the current evidence-based medicine for anti-inflammatory treatment of AMI patients is not sufficient. Perhaps in the future, machine learning based on artificial intelligence assisted inflammation phenotype typing, combined with multidimensional inflammation indicators, can identify the specific roles of immune cells in individuals, achieving a breakthrough in inflammation regulation from theory to clinical practice and solving the dilemma of residual cardiovascular risk. This article can provide reference for the in-depth development of anti-inflammatory treatment for AMI patients.

Key words: Myocardial infarction, Acute myocardial infarction, Inflammation, Artificial intelligence, Residual risk, Prognosis, Review

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