The Effect of Different Ventilation Modes on the Outcomes of Patients Infected with Coronavirus Disease 2019 (COVID-19): a Protocol of Systematic Review and Network Meta-Analysis

Background: Coronavirus disease 2019 (COVID-19) outbreak has spread around the world, the high mortality rate and strong infectious cause surging global patients diagnosed patients and death while in response to the outbreak, a myriad of scientic research workers and researchers have made unremitting efforts, but effective treatments are still limited, even may say that there is no specic treatment. So a large number of patients with severe patients need treatment for respiratory support, in particular, based on various realistic factors, different way of ventilation is widely used in clinical, which kind of ventilation way is the best one of the most effective ventilation strategy is not clear, so we planned a network meta-analysis to evaluate different ventilation methods on new crown the ecacy and safety of patients, expect to nd an optimal ventilation strategy. Methods and analysis: Two authors will independently search the electronic databases, preprints databases, Clinical Study Registration website and COVID-19 research related project database from December 1, 2019 to November 5, 2020. The primary outcomes are 1) All-cause mortality; 2) Transmission of COVID-19 to health care workers and other people; 3) Length of hospital stay; 4) Length of ICU stay. A systemic review and a network meta-analysis based on Bayesian framework will be performed to assess the effect of different ventilation modes on the outcomes of patients infected with COVID-19. The Grading of Recommendations Assessment, Development and Evaluation System (GRADE) will be used to evaluate the quality of evidence. Discussion: COVID-19 has spread around the world and become a global public health security problem. With limited treatment available, a large number of critically ill patients need ventilator support treatment, and the demand for ventilators has increased sharply. To our knowledge, this study will be the rst systematic review and NMA to analyze the ecacy and safety of different ventilation modes in patients with COVID-19. This study expected to obtain the best choice of ventilation mode for COVID-19 patients based on high quality evidence. Ethics and dissemination: Ethical approval is not required owning to it is a literature-based study. The nal conclusion will be disseminated through peer-reviewed publication.

Transmission of COVID-19 to health care workers and other people; 3) Length of hospital stay; 4) Length of ICU stay. A systemic review and a network meta-analysis based on Bayesian framework will be performed to assess the effect of different ventilation modes on the outcomes of patients infected with COVID-19. The Grading of Recommendations Assessment, Development and Evaluation System (GRADE) will be used to evaluate the quality of evidence.
Discussion: COVID-19 has spread around the world and become a global public health security problem.
With limited treatment available, a large number of critically ill patients need ventilator support treatment, and the demand for ventilators has increased sharply. To our knowledge, this study will be the rst systematic review and NMA to analyze the e cacy and safety of different ventilation modes in patients with COVID-19. This study expected to obtain the best choice of ventilation mode for COVID-19 patients based on high quality evidence.
Ethics and dissemination: Ethical approval is not required owning to it is a literature-based study. The nal conclusion will be disseminated through peer-reviewed publication. November 2020, more than 48 million novel coronavirus infections had been diagnosed and over 1.22 million deaths had been con rmed worldwide [1] . In response to the outbreak, despite the tremendous efforts of scientists around the world and a total of 2,462 registered studies [2] , effective treatments are still limited and no speci c treatment has been found. Therefore, a large number of patients need ventilator support treatment. A large number of studies are under way on the effects of different ventilation modes on COVID-19 patients. Recent studies on ventilation therapy have shown that early tracheotomy improves prognosis in patients with COVID-19 [3][4][5] , but some previous studies have shown that early tracheotomy does not improve mortality, but reduces the incidence of pulmonary complications [6,7] . In addition, as a result of the COVID-19 pandemic, there has been a surge in demand for ventilator equipment, we need to use all kinds of ventilators more rationally. Therefore, we plan to conduct this network meta-analysis to acquire the best choice between non-invasive ventilation, tracheotomy and invasive ventilation in the early stage of COVID-19 patients, further analyze whether different ventilation parameter settings have an impact on patient outcomes, and nd the optimal choice.

Objective
The purpose of this study is to investigate the effect of different modes of ventilation on outcome in COVID-19 patients through NMA and systematic review.

Method
The protocol of this review was rst registered with the International Prospective Register of Systematic Reviews (PROSPERO), and Reporting Items for Systematic Reviews and Meta-Analysis Protocols (PRISMA-P) statement (Supplement S1) [8] was followed while conducting and reporting the protocol of this systematic review and network meta-analysis (http://www.prisma-statement.org).

Eligibility Criteria
Type of study The review will include randomized controlled trials (RCTs), case control study and cohort study that were reported in English or Chinese without any regional restrictions, irrespective of publication status and publication year. Case report, animal experiment, vitro cell experiment, expert experience, conference article, review, communication letter, comment and duplication publication will be excluded.

Type Of Patients
Patients with con rmed COVID-19 infection and hypoxemic respiratory failure (despite oxygen therapy) in any setting that has capacity for non-invasive ventilation (NIV) or invasive ventilation.

Type Of Control Group
Control treatments included early noninvasive or invasive ventilation, tracheotomy, sham operative ventilation. Studies comparing the therapeutic effects of different ventilation modes will also be included.

Type Of Outcome Measures
Studies that reported one or more of the following outcomes will be included.

Type Of Language
We will only include only English or Chinese literature.

Search Method
Two authors will independently search the electronic databases Web of Science, Embase, and the Cochrane Central Register of Controlled Trials (CENTRAL), Medline through Pubmed from December 1, 2019 to November 9, 2020. We will search the Chinese electronic databases: Chinese National Knowledge Infrastructure (CNKI), Wanfang Database, VIP Database, Chinese Biomedical Literature Database (CBM), and we will also search World Health Organization (WHO) Clinical Trials Registry, Chinese clinical registry, ClinicalTrials.gov, ProQuest Central, SciFinder, the Virtual Health Library, LitCovid, WHO covid-19 website, Centers for Disease Control (CDC) covid-19 website, Eurosurveillance, China CDC Weekly. We will also search bioRxiv (preprints), medRxiv (preprints), chemRxiv (preprints), and SSRN (preprints), Chinese Medical Journal Net (preprints), and ChinaXiv (preprints).
A subject-speci c search strategy (Supplement S2) was developed in Pubmed/Medline and applied as the basic search strategy in the other electronic databases. We also scanned the reference lists and citations of the included trials and any relevant systematic reviews, referring to further literature. If necessary, we contacted trial authors to obtain additional information.

Data Collection
Two investigators independently extracted the data of all included studies using a standard data exaction form prepared by authors, on which they recorded the rst author, publication year, study design, ventilation modes, population characteristics, and reported outcomes of interest. If necessary, we contacted the authors of included studies by email to obtain additional data missing from the published paper. If additional information could not be obtained in this manner, we extracted data and information from the gures. At each step of data extraction, we resolved any differences between the investigators by discussion or consulting an arbiter.

Study Selection
Two authors independently scanned the title and abstract of the identi ed records to exclude uncorrelated studies and accessed the full-text articles for eligibility. We resolved any disagreements regarding inclusion of the study by discussion or by consulting an arbiter. The study selection procedure will be performed according to the PRSIMA ow chart ( Figure. 1).

Risk-of-bias In Individual Studies
Two authors will respectively assess the risk-of-bias of all included studies, using the Cochrane risk-ofbias tool. We will appraise each study in terms of selection bias (random sequence generation and allocation concealment), performance bias (blinding of participants and personnel), detection bias (blinding of outcome assessment), attrition bias (incomplete outcome data), selective reporting bias and other bias. Each component was judged as low risk-of-bias (green), high risk-of-bias (red), or unclear riskof-bias (yellow).

Quality Assessment
The Grading of Recommendations Assessment, Development and Evaluation System (GRADE) will be used to evaluate the quality of the evidence for primary outcomes [9] . Two reviewers will independently assess the quality of evidence using GRADE software, the quality of evidence will be divided into four levels: high, medium, low and very low, according the GRADE standards. For a speci c study, the quality will be assessed according to the risk of bias, inconsistency, indirectness, imprecision and publication bias.

Assessment Of Similarity And Consistency
The assessment of similarity and consistency will be conducted to get a reliable and valid result. At present, it is di cult to determine similarity by statistical analysis, so we will evaluate the similarity of included studies by analyzing clinical and methodological characteristics, patient characteristics, experimental design, and interventions. We will use the z-test to check for consistency, and calculate the P-value to check for inconsistencies between direct and indirect comparisons and a P-value greater than 0.05(P > 0.05) is considered to be consistent between the direct comparison and the indirect comparison, on the contrary, there is inconsistency.
Network Meta-analysis Data synthesis and statistical analysis will be performed using R3.6.3 (https://www.r-project.org/) with the Bayesian framework in this NMA. For continuous outcomes, standard mean difference (SMD) with 95% con dence intervals (CIs) or a weighted mean difference (WMD) with 95%CIs will be applied to analyze the e cacy data, while risk ratio (RR) with 95% CIs will be used for dichotomous data. WMD will be used for the same units or for the same measurement method while SMD will be used for different scale or assessment tools.
The contribution of each study to the nal effect will be assessed and demonstrated by mapping the netheat map. P value will be used to measure the accuracy of different ventilation modes over the control group and different ventilation modes were ranked by P value. P value equal to 100 percent, it will be considered as the best treatment for patients, while P value equal to 0 percent, it will be considered the worst treatment. The results of the NMA will be shown using forest maps, the ranking results of different ventilation modes will be displayed by using the surface under the cumulative sorting curve analysis, and the network evidence plot will be applied to present the comparison between different interventions.

Assessment Of Heterogeneity
For the heterogeneity of clinical and methodological heterogeneity, the sources of heterogeneity will be assessed by careful assessment of participant characteristics, study design, randomization, blinding, interventions, and outcomes of all included studies. The I 2 statistics was used to report statistical heterogeneity, which was classi ed by applying the Cochrane Handbook of Systematic Reviews of Interventions. When I 2 > 50%, obvious heterogeneity existed, on the contrary, when I 2 < 50%, heterogeneity is considered acceptable. Furthermore, if I 2 > 50%, several subgroup analyses and sensitivity analyses were conducted to evaluate the source of heterogeneity and to assess the subpopulation of patients that could probably obtain bene ts from the intervention. The nal NMA will be performed after the removal of studies that produce primary or unacceptable sources of heterogeneity. Lastly, if the source of heterogeneity cannot be explored after subgroup analyses and sensitivity analyses, a narrative review will be provided.

Meta-regression, Subgroup Analysis And Sensitivity Analysis
The network meta-regression will be conducted to explore the sources of heterogeneity by using random effects models. We will also perform subgroup analyses based on the following items.

NIV or invasive ventilation
For all outcomes, we will rst include all the trials regardless of peer reviewed or non-peer reviewed, and then we will conduct sensitivity analysis limited to peer reviewed researches. Sensitivity analysis will be conducted to explore the source of heterogeneity and ensure that a stable and accuracy conclusion can be obtained.

Patients and public involvement
All data were extracted from the literature and there will be no patients and public will be directly included in this systemic review and network meta-analysis.

Discussion
COVID-19 has spread around the world and become a global public health security problem. With limited treatment available, a large number of critically ill patients need ventilator support treatment, and the demand for ventilators has increased sharply. Although some studies have advocated early tracheotomy as a way to reduce the need for ventilators, more conservative and safe ventilate strategies may be chosen as opposed to conventional treatment, given the potential for increased viral load in the air, increased risk of cross-infection, viral transmission, and infection by medical personnel.
Compared with traditional meta-analysis, NMA can simultaneously integrate and compare the results of direct and indirect comparison of multiple interventions, and can help evaluate the e cacy and safety of various ventilation modes in patients with COVID-19. NMA analysis framework consists of Bayesian method and frequency method, the Bayesian method based on the observation data of transcendental frequency distribution and the combined effect of the distribution (likelihood), the combination of the a posteriori probability distribution to obtain merger effect. Compared with the frequency method, the Bayesian framework can form the frame of decision-making support decision, to overcome the defect of the frequency method in parameter estimation. [10] Therefore, in our review, the synthesis and analysis of valid data will be carried out under the Bayesian framework. For each individual study, we will rigorously analyze inclusion criteria and quality scores for each study based on GRADE assessment results.
To our knowledge, this study will be the rst systematic review and NMA to analyze the e cacy and safety of different ventilation modes in patients with COVID-19. Based on the available evidence, this NMA is expected to provide a ranking of the e cacy and safety of different ventilation patterns in the treatment of patients infected with COVID-19. In addition, the results of this NMA study will likely assist patients, clinicians, and researchers in selecting the most appropriate ventilation patterns and modes for patients with COVID-19 infection. Finally, it is our sincere hope that the results of this NMA will provide the best possible ventilation model for decision making in response to COVID-19.

Supplementary Files
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