Liu Nanyang, Zhang Tingting, Ma Lina, Wang Huican, Cao Yu, Yang Yang, Pei Hui, Li Hao
Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing.
College of First Clinical Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong Province, P.R. China.
Medicine (Baltimore). 2020 Aug 14;99(33):e21614. doi: 10.1097/MD.0000000000021614.
As of June 2020, more than 7 million cases of coronavirus disease (COVID-2019) have been reported worldwide. At present, there is no vaccine or antiviral for the novel coronavirus pneumonia. Lianhua Qingwen (LQ), a Chinese medicine formula, has been authorized by the Chinese government for treating COVID-2019. This systematic review and meta-analysis will evaluate the efficacy and safety of LQ on patients with COVID-19.
Two independent reviewers will search the following databases of the China Biology Medicine disc, China National Knowledge Infrastructure, China Science and Technology Periodical Database, Wanfang database, Embase, PubMed, and Cochrane Library from the date of conception to June 1, 2020. We will use the MeSH/Emtree terms, combining free-text words that were properly adjusted for the different databases in all of the search strategies. We will take primary clinical symptoms, total efficacy, and adverse event into consideration for our primary outcomes. As secondary outcomes, we will estimate the chest computed tomography manifestations, the rate of conversion to severe cases, and secondary clinical symptoms. We will evaluate the quality of including studies through the risk of bias assessment tool provided by the Cochrane Collaboration. Fixed-or random-effect model will be utilized to calculate the overall pooled risk estimates. Forest plots will be generated to prove the pooled results. Sensitivity analysis will be carried out to identify sources of heterogeneity. The Begg rank correlation test and Egger linear regression test will be used to explore publication bias.
This systematic review and meta-analysis will compare the primary and secondary outcomes at baseline and endpoint in the treatment and control groups to investigate the efficacy and safety of LQ for treatment COVID-2019.
Data from this study will provide strong evidence for clinical decision if the findings are positive.PROSPERO registration number: CRD42020190757.
截至2020年6月，全球报告的冠状病毒病（COVID-19）病例已超过700万例。目前，新型冠状病毒肺炎尚无疫苗或抗病毒药物。连花清瘟（LQ），一种中药配方，已获中国政府批准用于治疗COVID-19。本系统评价和荟萃分析将评估连花清瘟对COVID-19患者的疗效和安全性。
两名独立的评价者将检索中国生物医学光盘数据库、中国知网、维普数据库、万方数据库、Embase、PubMed和Cochrane图书馆等数据库，检索时间从概念形成之日至2020年6月1日。在所有检索策略中，我们将使用医学主题词表（MeSH）/Emtree术语，并结合针对不同数据库适当调整的自由文本词。我们将主要临床症状、总疗效和不良事件作为主要结局。作为次要结局，我们将评估胸部计算机断层扫描表现、重症转化率和次要临床症状。我们将通过Cochrane协作网提供的偏倚风险评估工具来评估纳入研究的质量。将采用固定效应或随机效应模型来计算总体合并风险估计值。将生成森林图以证明合并结果。将进行敏感性分析以识别异质性来源。将使用Begg秩相关检验和Egger线性回归检验来探讨发表偏倚。
本系统评价和荟萃分析将比较治疗组和对照组在基线和终点的主要和次要结局，以研究连花清瘟治疗COVID-19的疗效和安全性。
如果研究结果为阳性，本研究的数据将为临床决策提供有力证据。
CRD42020190757。
