WeChat Mini Program
Old Version Features

益赛普联合塞来昔布治疗强直性脊柱炎的临床疗效观察

Chinese Journal of Clinical Rational Drug Use(2018)

Cited 5|Views7
Abstract
目的 观察益赛普联合塞来昔布治疗强直性脊柱炎的临床疗效.方法 选取收治的强直性脊柱炎患者70例,随机分为观察组和对照组,每组35例.对照组应用柳氮磺胺吡啶联合塞来昔布治疗,观察组应用益赛普联合塞来昔布治疗.观察比较2组患者治疗后实验室指标(红细胞沉降率、C反应蛋白水平)变化、治疗效果及不良反应发生情况.结果 治疗后2组红细胞沉降率、C反应蛋白水平指标均得以改善,观察组改善程度较对照组更为明显(P<0.05);观察组患者治疗总有效率为94.29%,高于对照组的74.29% (P <0.05);观察组不良反应发生率为5.71%,低于对照组的22.86% (P <0.05).结论 益赛普与塞来昔布联合治疗强直性脊柱炎,有助于快速改善患者临床症状,治疗有效率较高,且不良反应发生率低,值得临床推广应用.
More
上传PDF
Bibtex
收藏
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
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