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

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，但目前我们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