| Literature DB >> 29676136 |
Feng-Wen Yang1, Jia-Han Zou2, Yuan Wang2, Chong-Xiang Sun2, Long Ge3, Jin-Hui Tian3, Jun-Hua Zhang1.
Abstract
To assess the clinical efficacy of Chinese medical injection (CMI) for heart failure by using network Meta-analysis method. The relative randomized controlled trials (RCTs) of CMI for heart failure were retrieved from China National Knowledge Infrastructure (CNKI), WanFang Database, Chinese Biomedical Literature Database (SinoMed), PubMed, Cochrane Library and EMbase in July 2017. RCTs on the comparison of two kinds of CMIs for heart failure were included. Two researchers independently completed the literature screening, data extraction and quality evaluation according to the pre-determined inclusion and exclusion criteria, and the results were crossed checked. The data were analyzed by Win Bugs, and STATA software was used for plotting. Finally, 13 RCTs were included, involving 5 kinds of CMIs and 1 538 patients. According to the quality evaluation, the appropriate random dividing methods were reported in only two RCTs, double-blindness was used in only one RCT, and even none of the RCTs mentioned allocation concealment. Network Meta-analysis showed that Shenmai injection had the greatest effect in the clinical efficacy for patients with heart failure, which was followed by Shenfu Injection. However, Shenfu Injection was most effective in improving the patients' left ventricular ejection fraction (LVEF), which was followed by Shenmai Injection. Therefore, Shenfu Injection and Shenmai Injection had certain advantages in treating heart failure. However, due to the limited sample size and the poor literature quality, more studies were required to verify the strength of evidence. We suggest that further studies shall pay more attention to the improvement of the methodological quality, increase the follow-up period, and strengthen the observation of cardiovascular end points. Copyright© by the Chinese Pharmaceutical Association.Entities:
Keywords: Chinese medical injection ; heart failure ; network Meta-analysis
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Year: 2018 PMID: 29676136 DOI: 10.19540/j.cnki.cjcmm.2018.0049
Source DB: PubMed Journal: Zhongguo Zhong Yao Za Zhi ISSN: 1001-5302