Chrome Extension
WeChat Mini Program
Use on ChatGLM

不同P2Y12受体抑制剂对ACS患者血浆中sLRP-1、Fib的影响

Chinese Journal of Evidence-Bases Cardiovascular Medicine(2020)

承德医学院附属医院 | 河北省隆化县医院 | 河北省承德市中医院

Cited 1|Views8
Abstract
目的 探讨替格瑞洛与氯吡格雷对急性冠脉综合征(ACS)患者血浆可溶性低密度脂蛋白受体相关蛋白1(sLRP-1)和纤维蛋白原(Fib)的影响.方法 选择2019年1月~7月于承德医学院附属医院心内科被确诊为ACS患者150例,采用随机数表法将患者分为氯吡格雷组和替格瑞洛组.两组患者均常规给予口服阿司匹林肠溶片、阿托伐他汀钙片,皮下注射低分子肝素钙注射液;其中,氯吡格雷组入院即刻给予300 mg负荷量,随后75 mg(1/d);替格瑞洛组入院即刻予180 mg负荷量,随后90 mg(2/d).采用Sysmex CS5100全自动血凝分析仪检测患者Fib水平;采用酶联免疫吸附实验(ELISA)法检测患者血浆中sLRP-1的水平.结果 重复测量设计的方差分析显示,治疗前、后1个月和3个月两组患者sLRP-1(μg/ml:5.09±0.38、4.05±0.26、2.89±0.15;5.06±0.41、3.98±0.23、2.32±0.17)和Fib(g/L:4.35±0.27、4.03±0.16、3.55±0.16;4.42±0.31、4.06±0.17、3.04±0.10)水平的主效应有差别(P均<0.05);不考虑治疗时间,替格瑞洛组和氯比格雷组患者sLRP-1、Fib的主效应有差别(P均<0.05);且治疗时间和药物分组间存在交互作用(P均<0.05).多变量方差分析显示,治疗后1个月,两组间Fib、sLRP-1水平比较差异无统计学意义(P均>0.05);治疗后3个月,替格瑞洛组Fib、sLRP-1水平显著低于氯吡格雷组(P均<0.05).结论 对于ACS患者,替格瑞洛较氯吡格雷可能有更强的抗炎作用和血栓抑制作用.
More
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Related Papers
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined