慢加急性肝衰竭预后评估模型及相关炎症指标的研究进展  

Progress on prognostic evaluation models and related inflammatory indicators of acute-on-chronic liver failure

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作  者:李江 郝彦琴[2] Li Jiang;Hao Yanqin(First Clinical Medical College,Shanxi Medical University,Taiyuan,Shanxi 030001,China;Department of Infectious Diseases,First Hospital of Shanxi Medical University,Taiyuan,Shanxi 030001,China)

机构地区:[1]山西医科大学第一临床医学院,山西太原030001 [2]山西医科大学第一医院感染病科,山西太原030001

出  处:《中国药物与临床》2025年第7期455-462,共8页Chinese Remedies & Clinics

基  金:山西省基础研究计划项目(20210302123436)。

摘  要:慢加急性肝衰竭(ACLF)是一种严重的肝损伤性疾病,治疗棘手、花费高、死亡风险高,早期预测预后具有重要临床意义。目前,临床上常用的预后评估模型有Child-Pugh(CTP)评分、终末期肝病模型(MELD)、MELD-Na评分及中国重度乙型肝炎研究小组-慢加急性肝衰竭(COSSH-ACLF)评分等,鉴于其存在主观性以及ACLF复杂多变的发病机制等特性,上述传统预后模型的应用受到限制。近年来的研究表明,系统性炎症反应在ACLF的疾病进展中起关键作用,且炎症反应的程度与患者的预后密切相关,基于此,国内外多项研究提出一系列血清学相关的炎症指标作为新的预后评估工具。本文总结现有的常规预后模型及其特点,以及新型炎症指标在ACLF预后评估中的应用前景。Acute-on-chronic liver failure(ACLF)is a severe liver disease marked by difficult treatment,high costs,and a significant mortality risk.Early prognosis prediction holds significant clinical importance.Currently,commonly used prognostic assessment models in clinical practice:such as the Child-Pugh(CTP)score,model for end-stage liver disease(MELD),MELD-Na score,and the Chinese Group on severe hepatitis B-acute-onchronic liver failure(COSSH-ACLF)score:face limitations in application due to their subjective components and the complex,heterogeneous pathogenesis of ACLF.Recent studies have highlighted the pivotal role of systemic inflammatory responses in ACLF progression,with the degree of inflammatory response being closely linked to patient prognosis.Based on this understanding,numerous domestic and international studies have proposed a series of serological inflammatory indicators as novel prognostic assessment tools.This review aims to summarize existing conventional prognostic models and their characteristics,as well as explore the potential application of emerging inflammatory indicators in the prognostic evaluation of ACLF.

关 键 词:肝功能衰竭 炎症 预后 

分 类 号:R575.3[医药卫生—消化系统]

 

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