1 Introduction
Coronavirus disease 2019 (COVID-19) is a global pandemic caused by the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2).[1] [2–6] [7] [8]
At present, there is no specific cure for this disease, and the clinical management mainly depends on supportive treatment.[9] [10] [11] [12] [13]
In the fourth edition of the diagnosis and treatment guideline of COVID-19 in China, Lianhuaqingwen capsule was listed as one of the recommended medicines.[14–16] systematic review and meta-analysis . This study is necessary before further large-scale clinical studies being carried out. For clinicians, this study can provide some direction and guidance for clinical practice.
2 Methods and analysis
2.1 Study registration
This study has been registered at Open Science Framework (OSF, https://osf.io/ [17]
2.2 Inclusion and exclusion criteria
2.2.1 Study design
Randomized controlled trials (RCTs) can provide evidence about efficacy of intervention, so they will be included in this systematic review. However, the outbreak of COVID-19 is an urgent public health event, and it is difficult to carry out RCTs, so non-randomized controlled trials will also be included in this study, although non-randomized controlled trials (non-RCTs) may be more biased than RCTs.
2.2.2 Participants
Participants with a laboratory-confirmed COVID-19 diagnosis will be included in this study. There will be no limitation about kits and detection methods. Also, there will be no restriction about age, sex, and severity of disease of participants.
2.2.3 Intervention
CHM in intervention group will be included. There will be no restrictions on the types, dosage forms, doses, and methods of use of CHM.
2.2.4 Outcomes
Since there are no core outcome sets for COVID-19, it is difficult to predefined what outcomes will be included in our study. In general, any outcome that can reflect the condition will be included in this study.
2.3 Study search
Three English database including PubMed, Embase, Cochrane Library Central Register of Controlled Trials, and 4 Chinese databases including China National Knowledge Infrastructure (CNKI) database, Wanfang Data Knowledge Service Platform, the VIP information resource integration service platform (cqvip), China Biology Medicine Disc (Sino Med) will be searched from its inception to April 1, 2020 without language limitation. Preprinted website including arXiv (http://arxiv.org/ https://www.biorxiv.org/ https://f1000.com/ https://peerj.com/preprints/
A search strategy of the combination of controlled vocabulary and text words will be adopted. Boolean operators will be used to concatenate search terms. This work will be conducted by 2 authors (ZH and MY) independently. The search strategy of PubMed is presented in Table 1 .
Table 1: Example of PubMed search strategy.
2.4 Study selection
EndNote X9 will be used by 2 researchers (ZH and MY) to screen the citations independently according to the predefined inclusion and exclusion criteria. Discrepancies between 2 authors will be solved by discussion with a third author (RY). A research flow chart will be drawn to show the whole process of research selection (Fig. 1 ).
Figure 1: Flow chart of study selection.
2.5 Data extraction
Data extraction will be conducted by 2 independent authors (MY and ZH) according to a prespecified form and checked by a third author (RY). The following data will be extracted: the first author's name, publication time, country, article title, article type, interventions in experimental and control group, course of treatment, severity of disease, number of patients in each group, ages and sex of patients, outcomes and adverse effect.
2.6 Risk of bias assessment
Different risk of bias assessment tools will be used according to different types of research. The risk of bias of RCTs will be conducted using version 2 of the Cochrane risk-of-bias tool for randomized trials (RoB2).[18] [19]
2.7 Data analysis
Data analysis will be conducted using Stata 14.0, StataCorp, Texas, USA. The effect measure of binary variable will be expressed as risk ratio (RR) or odds ratio (OR) and 95% confidence interval (CI). For continuous variables, 95% CI and mean difference (MD) or standardized mean difference (SMD) will be used. The number needed to treat (NNT) will be calculated for the interpretation of results. Cochrane χ 2 and I 2 P < .05 and I 2 P > .05 and I 2 < 50%, then a fixed effect model will be used to calculate the effect size. The results of RCTs and non-RCTs will be analyzed and presented independently. Subgroup analysis will be conducted to explore the subgroup effects and investigate the source of heterogeneity. If there is a substantial heterogeneity and quantitative synthesis is not appropriate, the results will be presented in the form of tables and figures.
Publication bias and small-study effects will be evaluated by funnel plot and statistically investigated by Egger test with a P value boundary of .05.[20]
2.8 Ethics and dissemination
Meta-analysis is an analysis of previous research data and does not require ethical approval. The results of this study will be published in peer-reviewed journals.
3 Discussion
COVID is a global epidemic that has so far caused >700,000 confirmed cases and 30,000 deaths. At present, there is no effective treatment. Due to the long cycle and difficulties of new drug research and development, mining existing drugs has become the focus of research. Since there are some difficulties in carrying out clinical trials, this study will include both RCT and non-RCTs. Non-RCTs may introduce bias in the course of research, but it can provide evidence more conveniently. This means that we need to be more careful when interpreting non-RCT results. This research will comprehensively present the existing evidence of CHM in treating COVID-19, which will be of guiding significance for further research.
3.1 Amendments
If any modification is required, we will update our protocol to include any changes in the entire research process.
Author contributions
Conceptualization: Maoyi Yang, Zhipeng Hu, Rensong Yue.
Data curation: Maoyi Yang, Zhipeng Hu.
Formal analysis: Maoyi Yang, Zhipeng Hu.
Investigation: Maoyi Yang, Zhipeng Hu.
Methodology: Maoyi Yang, Zhipeng Hu.
Project administration: Rensong Yue.
Software: Maoyi Yang, Zhipeng Hu.
Visualization: Maoyi Yang, Zhipeng Hu.
Writing – original draft: Maoyi Yang.
Writing – review and editing: Rensong Yue.
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