文章摘要
尹丽鹤,刘 娜,方晓康,史红刚,牛 媛,刘秋武,李莹超.血清AGEs、sRAGE水平与急性脑梗死后出血性转化的相关性[J].,2021,(10):1893-1897
血清AGEs、sRAGE水平与急性脑梗死后出血性转化的相关性
Correlation between Serum AGEs and sRAGE Levels and Hemorrhagic Transformation after Acute Cerebral Infarction
投稿时间:2020-08-09  修订日期:2020-08-30
DOI:10.13241/j.cnki.pmb.2021.10.019
中文关键词: 晚期糖基化终末产物  可溶性期糖基化终末产物受体  急性脑梗死  出血性转化
英文关键词: Advanced glycation end products  Soluble receptor for advanced glycation end products  Acute cerebral infarction  Hemorrhagic transformation
基金项目:西安医学院2016青年科研基金项目(2016QN20)
作者单位
尹丽鹤 西安交通大学第一附属医院神经内科 陕西 西安710089 
刘 娜 空军军医大学附属第一医院神经内科 陕西 西安 710032 
方晓康 西安交通大学第一附属医院神经内科 陕西 西安710089 
史红刚 西安交通大学第一附属医院神经内科 陕西 西安710089 
牛 媛 西安交通大学第一附属医院神经内科 陕西 西安710089 
刘秋武 西安交通大学第一附属医院神经内科 陕西 西安710089 
李莹超 第一临床医学院临床医学科 陕西 西安 710021 
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中文摘要:
      摘要 目的:探讨血清晚期糖基化终末产物(AGEs)及可溶性期糖基化终末产物受体(sRAGE)与急性脑梗死后出血性转化(hemorrhagic transformation,HT)的相关性。方法:将2017年1月至2019年12月于我院诊治的131例急性脑梗死患者纳入研究对象,根据患者是否出现出血性转化将其分为HT组及NHT组,比较两组患者AGEs、sRAGE等实验室指标,采用多因素Logistic回归模型对影响急性脑梗死出血性转化的因素进行分析,并采用Pearson相关模型对血清中AGEs水平与sRAGE水平的相关性进行分析。结果:HT组患者合并糖尿病史、心房颤动病史比例、脑栓塞比例、梗死面积、采用抗凝治疗比例及血清中IL-1β、TNF-α、AGEs水平明显高于NHT组(均P<0.05);多因素Logistic回归分析示大梗死面积、高IL-1β、TNF-α及AGEs水平是患者出现急性脑梗死后出血性转换的保护因素(OR=0.625, 0.832, 0.874, 0.708;均P<0.05),而无抗凝治疗、高sRAGE则是患者出现急性脑梗死后出血性转换的危险因素(OR=10.901, 1.004;均P<0.05);相关性分析示血清中sRAGE水平与AGEs、IL-1β及TNF-α水平呈明显负相关(ρ=-0.852,-0.828,-0.826;均P<0.05)。结论:血清AGEs是急性脑梗死患者出现出血性转化的危险因素,而sRAGE则是保护因素,sRAGE可能通过抑制RAGE与AGEs结合,从而减少释放炎症介质,减轻血管损伤,降低HT发生风险。
英文摘要:
      ABSTRACT Objective: To explore the correlation between serum advanced glycosylation end products (AGEs) and soluble phase glycosylation end product receptors (sRAGE) and hemorrhagic transformation after acute cerebral infarction. Methods: A total of 131 patients with acute cerebral infarction diagnosed and treated in our hospital from January 2017 to December 2019 were included in the study. They were divided into HT group and NHT group according to whether hemorrhagic transformation occurred. The AGEs, sRAGE and other related laboratory indicators, using multi-factor Logistic regression model to analyze the factors affecting hemorrhagic transformation of acute cerebral infarction, and Pearson correlation model to analyze the correlation between serum AGEs and sRAGE. Results: The proportion of patients with HT group combined with diabetes history, atrial fibrillation history, cerebral embolism ratio, infarct size, the proportion of anticoagulant therapy and serum levels of IL-1β, TNF-α, and AGEs were significantly higher than those of NHT group(all P<0.05). There were no significant differences in age, gender and other general data of the two groups of patients and laboratory indicators such as PLT and TC(both P>0.05); multivariate logistic regression analysis showed large infarct size, high IL-1β, TNF-α and AGEs Level is a protective factor for hemorrhagic conversion after acute cerebral infarction (OR=0.625, 0.832, 0.874, 0.708; all P<0.05), while no anticoagulation therapy and high sRAGE are hemorrhagic conversion after acute cerebral infarction Risk factors (OR=10.901, 1.004; all P<0.05); correlation analysis showed that serum sRAGE levels were significantly negatively correlated with AGEs, IL-1β and TNF-α levels (ρ=-0.852, -0.828, -0.826; Both P<0.05). Conclusion: Serum AGEs is a risk factor for hemorrhagic conversion in patients with acute cerebral infarction, and sRAGE is a protective factor. sRAGE may inhibit the combination of RAGE and AGEs, thereby reducing the release of inflammatory mediators, vascular damage, and the risk of HT.
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