Abstract
Background:
COVID-9 has become a global pandemic with severe health issues around the world. However, there is still no effective drug to treat the disease, and many studies have shown that moxibustion plays a positive role in adjuvant treatment of COVID-19. Therefore, this meta-analysis is designed to evaluate the efficacy of moxibustion for COVID-19.
Methods:
The relevant randomized controlled trials will be systematically retrieved from the electronic database, including PubMed, Embase, Cochrane Clinical Trials Database, Web of Science, and China National Knowledge Infrastructure, without restrictions on publication status and language. Two reviewers will independently review all included studies and assess the risk of bias. Two reviewers will independently extract data from the included studies based on a pre-designed standardized form. Any disagreements will be resolved by consensus. The meta-analysis will be performed with RevMan (V5.3.5) software.
Result:
The results of this study will be published in a peer-reviewed journal.
Conclusion:
This ongoing meta-analysis will provide up-to-date evidence of the efficacy of moxibustion for patients with COVID-19.
Registration:
The meta-analysis has been prospectively registered in PROSPERO (CRD42020211910).
Keywords: moxibustion, COVID-19, systematic review, meta-analysis, protocol
1. Introduction
COVID-19 is an infection caused by the SARS-CoV-2 virus, initially identified in the city of Wuhan, China, in December 2019. Since then, the virus has spread to the continents, causing a major pandemic.[1] COVID-9 has become a global pandemic with severe health issues around the world.[2] Epidemiological investigations have shown that main symptoms of COVID-19 are fever, dry cough, and fatigue, with a small number of patients suffering from nasal congestion, sore throat, runny nose, myalgia, and diarrhea.[3] Moxibustion, as a common treatment of traditional Chinese medicine (TCM), played the auxiliary role of TCM in the treatment of Severe Acute Respiratory Syndrome (SARS) in 2003.[4] Therefore, in China, where COVID-19 was first popular, moxibustion is also used as an adjuvant therapy for COVID-19. Although many studies have shown that moxibustion plays a positive role in adjuvant treatment of COVID-19,[5–8] there is no systematic review on the efficacy of moxibustion in the treatment of COVID-19. Therefore, the study we are going to conduct is a systematic review and meta-analysis of the efficacy of moxibustion in the treatment of COVID-19.
2. Methods
We will conduct the systematic review according to preferred reporting items for systematic review and meta-analysis protocols 2015 statement.[9] This meta-analysis has been registered in PROSPERO (CRD42020211910) for quality control.
2.1. Study inclusion criteria
2.1.1. Types of studies
Randomized controlled trials of COVID-19 treated with moxibustion will be included and pooled in the assessment. Non randomized controlled clinical studies and clinical case reports will be reported.
2.1.2. Participants
Patients diagnosed with COVID-19, without gender, race, educational status, and age restrictions.
2.1.3. Types of interventions
The intervention of the experimental group should include moxibustion, which can be carried out alone, or combined with other kinds of therapies. The control group will receive any kind of treatment without moxibustion (Western medicine, placebo or regular treatment).
2.1.4. Outcomes
In this meta-analysis, the primary outcomes assessed is the total clinical response rate, and the diagnostic criteria included Cured: the disappearance of the main symptoms, the normal body temperature, the disappearance of lung rales, the re-examination of chest X-ray showed the absorption of lung lesions, and the return of white blood cell count to normal; Effective: the main symptoms were relieved, lung rhombus was improved, chest X-ray showed that the lung lesions were not completely absorbed, and the white blood cell count was improved; Invalid: no improvement or aggravation of symptoms, signs, chest X-ray examination and abnormal white blood cell count. Total clinical effective rate = (number of cured cases + number of effective cases)/total number of cases 100%; Secondary outcome measures: antipyretic time, cough duration, rhombus disappearance time, imaging transition time, serum C-reactive protein level after treatment.[10]
2.2. Search strategy
Two independent reviewers (ZLW and JZ) will search PubMed, Embase, Cochrane Clinical Trials Database, Web of Science, and China National Knowledge Infrastructure. The search strategy in PubMed is as follows:
#1 “moxibustion” [Title/Abstract] OR “moxa” [Title/Abstract] OR “acupoint” [Title/Abstract] OR “TCM”[Title/Abstract] OR “ Traditional Chinese medicine” [Title/Abstract]
#2 “COVID-19” [MeSH Terms] OR “2019 novel coronavirus infection” [Title/Abstract] OR “COVID19” [Title/Abstract] OR “coronavirus disease 2019” [Title/Abstract] OR“coronavirus disease-19” [Title/Abstract] OR “2019-nCoV disease” [Title/Abstract] OR “2019 novel coronavirus disease” [Title/Abstract] OR “2019-nCoV infection”[Title/Abstract] OR “ 2019-nCoV ” [Title/Abstract] OR “ nCoV ” [Title/Abstract] OR “ SARS-CoV∗ ” [Title/Abstract] OR “ SARSCov2 ” [Title/Abstract] OR “SARS-CoV ” [Title/Abstract] OR “ 2019 coronavirus ” [Title/Abstract]
#3 “randomized controlled trial” [Publication Type] OR “controlled clinical trial” [Publication Type] OR “Single-Blind Method” [Text Word] OR “Double-Blind Method”[Text Word] OR “random allocation” [Text Word] OR “allocation” [Text Word] OR “ randomized controlled trials” [Text Word]
#4 #1 AND #2 AND #3
2.3. Data collection and management
2.3.1. Study selection
After literature retrieval, the literature records will be imported into EndNoteX9 software for management. We will first exclude duplication, and then 2 authors (XY and JFM) will independently evaluate the literature search for relevant abstracts and titles based on pre-defined inclusion criteria. A third author will arbitrate any disagreement between the 2 authors. If the full text is not available, we will try to contact the appropriate author. The selection process will be presented in a preferred reporting items for systematic review and meta-analysis protocols flow diagram (Fig. 1).
2.3.2. Data extraction
Two authors (CC and DQD) will select the literature and extract the data according to the retrieval strategy. The title of the study, the name of the first author, the year of publication, the journal; the participants’ information: gender, age, study design, sample size, diagnostic criteria, intervention and outcome indicators will be independently extracted from the included study by the 2 reviewers in a standardized form, they will also cross-check the results, and the differences will be resolved by recommending a third author (ZL W).
2.3.3. Dealing with missing data
We will attempt to obtain missing data by contacting the corresponding author. If it fails, we will analyze it based on available data.
2.3.4. Risk of bias assessment
Through the RevMan v5.3 software built-in risk bias assessment tool provided by Cochrane Collaboration Network; the risk bias assessment will be carried out for the included study. The evaluation contents include random sequence generation, allocation concealment, blinding of participants and personnel, blinding of outcome assessment, incomplete outcome data, selective reporting and other risk bias. According to the performance of the included literature in the above evaluation items, if all key domains are graded as low risk, this study will be graded as low risk; if 1 or more key domains are graded as high risk, this study will be graded as high risk; if 1 or more key domains are graded as unclear risk, this study will be graded as unclear risk.
2.3.5. Assessment of quality of evidence
We will use Grading of Recommendations Assessment, Development and Evaluation (GRADE) system for rating overall quality of evidence supporting selected primary and secondary outcomes. This work will be completed by 2 researchers (ZLW and JZ). If there are different opinions, they can be solved through discussion.
2.3.6. Date synthesis
Data synthesis will be performed with RevMan v5.3. For dichotomous data, we will calculate the date and present it by the relative risks with 95% confidence intervals. For continuous data, we will calculate the effect size using the mean differences or standardized mean difference with 95% confidence intervals. Heterogeneity will be assessed by I2. It is acknowledged that I2 < 25% indicates negligible heterogeneity, 25%≤I2 < 50% indicates mild heterogeneity, 50%≤I2 < 75% moderate heterogeneity, and I2 ≥75% high heterogeneity. Fixed- and random-effects models will be used when I2 ≤50% and I2 > 50%, respectively. The results will be presented as forest plots.
2.3.7. Subgroups and sensitivity analysis
If data are available, we will conduct a subgroup analysis according to different interventions, controls, durations of treatment, and outcome measures. We will conduct a sensitivity analysis to assess the robustness of the meta-analysis results. Sensitivity analysis is used to analyze research quality, method elements, publishing type, and publishing language and so on. If there is a high degree of heterogeneity, meta-analysis will be repeated to exclude low-quality or small sample studies.
2.3.8. Assessment of publication biases
The funnel plots in RevMan V.5.3 will be used to detect publication bias if >10 studies are included in the meta-analysis.
2.3.9. Ethics and dissemination
There is no need for this study to require ethical approval and informed consent because it is based on published literatures. The results of this meta-analysis will be submitted to a peer-reviewed journal for publication and information sharing.
3. Discussion
Due to the lack of specific drugs, COVID-19 in many countries around the world has not been effectively controlled since the outbreak in 2019. In China, moxibustion has played a role in preventing and treating plague since ancient times.[11] Previous studies have shown that moxibustion plays a good auxiliary role in the treatment of common pneumonia and SARS.[4,12] At the beginning of the outbreak in China, the World Federation of Acupuncture and moxibustion Societies issued guidelines on moxibustion intervention in COVID-19.[13] It is recommended to use moxibustion as an adjuvant treatment of COVID-19. Moxibustion has contributed to the prevention and treatment of COVID-19 in China. At present, China has achieved remarkable results in epidemic prevention, but the situation in other countries is still grim. Therefore, we will systematically review the role of moxibustion in the adjuvant therapy of COVID-19 and provide reference for the global fight against the epidemic.
Author contributions
ZLW, JZ, and YXM contributed to conceiving and designing the experiments; DQD, FJM, XY and CC gave some suggestions for modification. All authors have read and approved the manuscript.
Data curation: Juan Zhang, Xiao Yan.
Funding acquisition: Yu-xia Ma.
Methodology: Dong-qing Du, Feng-jun Ma.
Software: Dong-qing Du, Feng-jun Ma, Xiao Yan, Chen Chen.
Supervision: Yu-xia Ma.
Visualization: Chen Chen.
Writing – original draft: Zhi-lei Wang.
Writing – review & editing: Zhi-lei Wang, Yu-xia Ma.
Footnotes
Abbreviations: CIs = confidence intervals, CNKI = China National Knowledge Infrastructure, CRP = C-reactive protein, MD = mean differences, PRISMA-P = preferred reporting items for systematic review and meta-analysis protocols, RCT = randomized controlled trials, RR = relative risk, SMD = standardized mean difference, TCM = traditional Chinese medicine, WFAS = World Federation of Acupuncture and moxibustion Societies.
How to cite this article: Wang Zl, Zhang J, Du Dq, Ma Fj, Yan X, Chen C, Ma Yx. Adjuvant therapeutic effects of moxibustion on COVID-19: a protocol for systematic review and meta-analysis. Medicine. 2020;99:46(e23198).
This research was supported by the National Natural Science Foundation of China, Nos. 81774402. The funding body had no role in the design of the study and collection and analysis of data and in writing manuscript.
The authors have no conflicts of interest to disclose.
Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.
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