Aim: To compile up-to-date evidence of the benefits and risks of herbal medicine for the treatment of COVID-19 symptoms.
Methods: Eleven databases, including PubMed, Cochrane Register of Controlled Trials (CENTRAL), Embase, Allied and Complementary Medicine Database (AMED), Chinese National Knowledge Infrastructure Database (CNKI), Wanfang Database, and Chinese Science and Technique Journals Database (VIP), Research Information Service System (RISS), Korean Medical database (KMBase), Korean Association of Medical Journal database (KoreaMed), and OASIS database, were searched from 15 June, 2020, until 28 March 2022. Randomized controlled trials (RCTs), published in any language, reporting the efficacy and safety outcomes of herbal medicine in patients of all ages with a PCR-confirmed diagnosis of COVID-19 were included in this analysis. Data extraction and quality assessments were performed independently.
Results: Random-effects meta-analyses showed evidence of favorable effects of treatment with herbal medicine when added to standard treatment, versus standard treatment alone, on the total effective rate (p = 0.0001), time to remission from fever (p < 0.00001), rate of remission from coughing (p < 0.0001), fatigue (p = 0.02), sputum production (p = 0.004), improvement of manifestations observed on chest computed tomography scans (p < 0.00001), incidence of progression to severe COVID-19 (p = 0.003), all-cause mortality (p = 0.003), time to a negative COVID-19 coronavirus test (p < 0.0001), and duration of hospital stay (p = 0.0003). There was no evidence of a difference between herbal medicine added to standard treatment, versus standard treatment alone, on the rate of remission from symptoms such as a fever, sore throat, nasal congestion and discharge, diarrhea, dry throat, chills, and the rate of conversion to a negative COVID-19 coronavirus test. Meta-analysis showed no evidence of a significant difference in adverse events between the two groups. There was an unclear risk of bias across the RCTs included in this analysis, indicating that most studies had methodological limitations.
Conclusion: Current evidence suggests that herbal medicine added to standard treatment has potential benefits in the treatment of COVID-19 symptoms but the certainty of evidence was low.
To address the uncertainty in the evidence for herbal medicine intervention for COVID-19 treatment, there is a need for the continuous surveillance of new evidence. This can be performed using a living systematic review (LSR) approach, where a systematic review is continually updated to incorporate newly available evidence (Elliott et al., 2017). According to the International Clinical Trials Registry Platform (ICTRP) of the WHO, >100 randomized controlled trials (RCTs) related to herbal medicine intervention have been registered worldwide, and there is the probability of more trials in the near future [World Health Organization (WHO), 2022a]. Hence, there is likely to be emerging evidence that will allow informed decisions to be made on the effectiveness of treatment using herbal medicine for the treatment of COVID-19 symptoms.
In this LSR, evidence regarding the potential effects and risks of using herbal medicine for the treatment or prevention of COVID-19 was evaluated, focusing on the following questions: 1) Is herbal medicine effective in treating patients with COVID-19? 2) Is herbal medicine effective in preventing COVID-19 infections? 3) Are there any potential adverse events or risks associated with the use of herbal medicine for the treatment of COVID-19? New evidence will be kept under surveillance and summarized quarterly. A major update will be performed if the emerging evidence impacts upon the conclusion of this review. This LSR will continuously inform the best practice for clinical treatment and clinical research of this disease.
This LSR was registered in the PROSPERO international prospective register of systematic reviews database (ID: CRD42020191711) and was reported in accordance with the reporting guideline provided in the Preferred Reporting Items Systematic Reviews and Meta-Analysis (PRISMA) statement (Moher et al., 2009). Standard methods and guidance for conducting living reviews was also followed (Akl et al., 2017; Elliott et al., 2017).
Data Sources and Searches
All sources were searched from the date of inception through to 28 March 2022. Two review authors developed the search strategy (see Supplementary Table S1) and conducted the search monthly for eligible articles. The sources included, but was not limited to the following 11 databases: PubMed, Cochrane Register of Controlled Trials (CENTRAL), Embase, Allied and Complementary Medicine Database (AMED), Chinese National Knowledge Infrastructure Database (CNKI), Wanfang Database, and Chinese Science and Technique Journals Database (VIP), Research Information Service System (RISS), Korean Medical database (KMBase), Korean Association of Medical Journal database (KoreaMed), and OASIS database.
Additional sources such as the COVID-19 Study Registry (), WHO’s COVID-19 Database (https://search.bvsalud.org/global-literature-on-novel-coronavirus-2019-ncov/), and The Institute of Medical Information (IMI) and Library, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS and PUMC) () were also searched. To identify ongoing trials, the National Institute of Health and Clinical Trials Database (http://www.clinicaltrials.gov/), WHO’s International Clinical Trials Registry Platform (https://www.who.int/ictrp/en/), and Chinese Clinical Trial Registry (http://www.chictr.org.cn/) were searched.
There were no restrictions concerning the language or publication status. The use of indexing terms such as medical subject headings (MeSH) terms, and other equivalent terms, were applied for wider coverage. All of the searches will be performed again on a monthly basis to retrieve any further eligible studies.
Types of Studies
All RCTs that included herbal medicine as a treatment for COVID-19 were eligible for inclusion. Other clinical and experimental studies such as case-control studies, cohort studies, cross-sectional studies, case reports, animal studies, and laboratory experiments were excluded. Preprint articles were also excluded because these studies can introduce bias and could undergo major changes before peer-review and publication.
Types of Participants
Patients of all ages with a PCR-confirmed diagnosis of COVID-19, regardless of sex, or ethnicity were included. Patients who used herbal medicine for other comorbidities or any other purpose were excluded to ensure the accuracy of evidence. Participants who were suspected of having COVID-19 or asymptomatic PCR-confirmed COVID-19 cases were also excluded. Trials which reported separate data on symptomatic and asymptomatic COVID-19 participants were included in this review.
Types of Interventions
All types of herbal medicine intervention by oral administration, such as herbal decoctions or a patient’s medicine were considered in this review, irrespective of the composition of herbal medicine, dose, and duration of administration. Co-intervention of standard medical treatment was also eligible so long as the co-intervention was given similarly in both intervention and comparison groups. Herbal medicine interventions in the form of single/multiple herbal extractions, herbal injections, herbal fumigation, or combinations of two or more different types of herbal medicine interventions were excluded.
Types of Comparisons
Comparison groups that received only standard medical treatment, placebo, or no treatment were included. Comparator groups that involved any type of herbal medicine were excluded.
The primary outcomes comprised of:
− Total effective rate (defined by the number of patients who were cured or where treatment was markedly effective)
− Symptom resolution
The secondary outcomes included:
− Chest radiological findings
− Progression to severe or critical COVID-19
− All-cause mortality
− Negative viral assay
− Duration of hospital stay
− Adverse events
Both primary and secondary outcomes were chosen by referring to the core outcome sets (COS) that have been registered on the Core Outcome Measures in Effectiveness Trials (COMET) database (Qiu R. et al., 2020; Jin et al., 2020; Marshall et al., 2020; Tong et al., 2020), with the consideration of applicability to patients with mild-to-critical COVID-19.
Two review authors (LA and ES) performed the literature searches and assessed the eligibility of the studies. To prevent discrepancies between daily database updates, all searches were conducted and results exported on the same day. The full text of the potentially eligible RCTs was then retrieved and screened according to the pre-defined criteria. Any discrepancies regarding the suitability of a study for inclusion in this review were discussed with a third review author (ML) until a consensus was reached.
Data Extraction and Quality Assessment
Trial design, sample size, risk of bias domains (as defined above), length of trial and follow-up, the number of participants (recruited, randomized, withdraw, completed, analyzed, and lost to follow-up), age range, sex ratio, details of the interventions and comparators (regimens), all outcome measures, study results, adverse events, and funding source data were extracted by two review authors (LA and ES) independently using a standard data extraction form. Each trial was named after the first author and year of primary publication, and any relevant secondary publications were classified under that name. The authors of the included studies were contacted for unreported data or missing data.
Subsequently, two review authors (LA and ES) individually assessed the risk of bias of the included studies using the Cochrane Collaboration’s Risk of Bias Assessment tool Version 2 (ROB 2.0) (Sterne et al., 2019). The following five domains were assessed: 1) randomization process, 2) deviations from intended interventions, 3) missing outcome data, 4) measurement of outcome, and 5) selection of the reported results. The risk of bias of each item was categorized into “low risk of bias,” “some concerns,” or “high risk of bias.” The overall risk of bias of the included studies was also assessed. Additionally, the quality of evidence was summarized using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE, ). Any disagreements over the data extraction, risk of bias, and quality of evidence in a particular study were resolved through the involvement of a third party.
All data were analyzed using Review Manager (RevMan) Version 5.3 software. The risk ratios (RRs), odds ratio (OR), or risk difference (RD) with 95% confidence intervals (CIs) were calculated for dichotomous data while the mean differences (MDs) with 95% CIs were calculated for continuous data. A narrative synthesis of the key findings from the included studies was presented according to the review questions with summary tables for study characteristics, participants, and outcome details. Quantitative synthesis was also performed to demonstrate overall effect estimates. The random-effects model was used as it incorporates heterogeneity both within and between studies. The heterogeneity levels of the eligible RCTs were assessed using I2 statistics.
A monthly surveillance for new evidence related to the potential benefits and risks of the treatment was planned. The data selection, data extraction, and quality assessment methods described in this review will be performed. The relevant meta-analyses will continuously be updated, and if significant evidence is available, the results will be published quarterly.
The diagnosis of COVID-19 was confirmed by polymerase chain reaction (PCR) for all cases in all studies and was accompanied by radiological findings of pneumonia caused by COVID-19 in some studies. The majority of standard medical treatment received by participants involved the use of lopinavir-ritonavir, arbidol, alpha-interferon nebulization, or a combination of these treatments. Five different forms of herbal medicines were evaluated. The most common form of herbal medicines was herbal decoction (12/25; 48%), followed by herbal granules (9/25; 36%), herbal oral liquid (2/25; 8%), herbal capsules (1/25; 4%), and herbal powder (1/25; 4%). All trials compared herbal medicine added to standard treatment versus standard treatment alone. Due to insufficient data, meta-analysis for several trials and outcomes could not be conducted. We wrote to the authors of those studies requesting the missing data and have yet to receive responses. The detailed study characteristics of the included trials can be found in Tables 1, 2.
TABLE 1. Study characteristics of trials conducted with herbal medicine for the treatment of COVID-19.
Risk of Bias and Certainty of Evidence
Most of the studies assessed had a concerning level of risk of bias. Of the RCTs included in this review, 16 trials performed adequate randomization using a simple randomization method (Ai et al., 2020; Qiu M. et al., 2020; Wang JB. et al., 2020; Xiong WZ. et al., 2020; Fu et al., 2020b; Sun H.-m. et al., 2020; Wang Y. et al., 2020; Ding et al., 2020; Duan et al., 2020; Hu et al., 2020; Lin et al., 2020; G-CHAMPS Collaborative Group, 2020; Yu et al., 2020; Liu J. et al., 2021; Zeng et al., 2021; Zhou et al., 2021). The specific information on the generation of randomization was absent in nine trials. Most of the trials did not report on allocation sequence concealment. Six trials were open-labeled (Sun H.-m. et al., 2020; Wang Y. et al., 2020; Hu et al., 2020; G-CHAMPS Collaborative Group, 2020; Liu J. et al., 2021; Zeng et al., 2021), one was double-blinded (Wang JB. et al., 2020), and the remaining trials did not provide information on masking. Of the seven trials with publicly accessible protocols or registrations, two trials did not report results for one or more outcomes that were pre-specified in their protocols (Hu et al., 2020; Zhou et al., 2021). The reporting bias in two trials was assessed as concerning due to selective reporting and missing outcome data (Zhao et al., 2020; Zeng et al., 2021). One trial was initially posted as a preprint and subsequently peer-reviewed and published, and no substantial discrepancies in reporting were determined between the preprint and journal publication (G-CHAMPS Collaborative Group, 2020). The full risk of bias assessments for each domain for each study and the summary of findings are available in Supplementary Tables S3, S4, and Figure 1.
Therapeutic Effect of Herbal Medicine
Total Effective Rate
Ten RCTs including 1,192 participants, reported total effective rates. Meta-analysis showed that herbal medicine added to standard treatment was more favorable compared with standard treatment alone for total effective rate (RR 1.21, 95% CI 1.10 to1.33, p = 0.0001, I2 = 63; low certainty, Figure 2).
Six RCTs including 365 participants, reported the rate of remission from fever. Meta-analysis showed no evidence of a difference between herbal medicine added to standard treatment versus standard treatment for the reduction of fever (RR 1.21, 95% CI 0.94 to 1.55, p = 0.15, I2 = 91%; low certainty, Figure 3A). In two RCTs including 72 participants, time to remission from fever, using meta-analysis, showed that herbal medicine added to standard treatment reduced time of remission from fever faster compared with standard treatment alone (MD −1.72, 95% CI −2.39 to −1.04, p < 0.00001, I2 = 0%; low certainty, Figure 3B).
FIGURE 3. Forest plot for (A) rate of remission from fever, (B) time to remission from fever, (C) rate of remission from coughing, (D) rate of remission from fatigue.
Five RCTs including 290 participants, reported the rate of remission from coughing. Meta-analysis showed that herbal medicine added to standard treatment has a significantly greater effect in alleviating coughing compared with standard treatment (RR 1.44, 95% CI 1.21 to 1.72, p < 0.0001, I2 = 0%; low certainty, Figure 3C).
Five RCTs including 242 participants, reported rates of remission from fatigue. Meta-analysis showed that herbal medicine added to standard treatment has a significantly greater effect in reducing fatigue compared with standard treatment (RR 1.27, 95% CI 1.04 to 1.54, p = 0.02, I2 = 33%; low certainty, Figure 3D).
Meta-analysis of two RCTs including 80 participants, also showed that herbal medicine added to standard treatment has a positive effect in reducing sputum production compared with standard treatment (RR 1.73, 95% CI 1.19 to 2.50, p = 0.004, I2 = 0%; low certainty). In contrast, meta-analyses showed no evidence of a significant difference between herbal medicine added to standard treatment versus standard treatment at reducing symptoms such as a sore throat (three trials, n = 31, RR 1.06, 95% CI 0.73 to 1.54, p = 0.76, I2 = 0%; low certainty), nasal congestion and discharge (two trials, n = 14, 95% CI 0.62 to 2.18, p = 0.67, I2 = 0%; low certainty), diarrhea (two trials, n = 28, RR 0.32, 95% CI 0.01 to 8.68, p = 0.0.50, I2 = 82%; very low certainty), a dry throat (two trials, n = 25, RR 0.98, 95% CI 0.65 to 1.48, p = 0.93, I2 = 0%; very low certainty), and chills (two trials, n = 60, RR 0.99, 95% CI 0.75 to 1.32, p = 0.97, I2 = 0%; low certainty). Forest plots figures are provided in Supplementary Figures 2A–F.
Chest Radiological Findings
Eleven RCTs including 1,117 participants, reported the rate of improvement of chest computed tomography (CT) scans. Meta-analysis showed that herbal medicine added to standard treatment was more favorable compared with standard treatment on improving pulmonary lesions (RR 1.23, 95% CI 1.14 to 1.32, p < 0.00001, I2 = 0%; low certainty, Supplementary Figure S3).
Progression to Severe or Critical COVID-19
Seven RCTs including 953 participants, reported the incidence of progression to severe COVID-19 following treatment. Meta-analysis showed that herbal medicine added to standard treatment probably reduced deterioration compared with standard treatment alone (RR 0.52, 95% CI 0.34 to 0.80, p = 0.003, I2 = 0%; low certainty, Supplementary Figure S4).
Four RCTs including 495 participants, reported mortality. Meta-analysis showed that herbal medicine added to standard treatment probably reduced deaths compared with standard treatment (OR 0.26, 95% CI 0.12 to 0.54, p = 0.003, I2 = 0%; very low certainty, Supplementary Figure S5).
Conversion to a Negative COVID-19 Test
Two RCTs including 162 participants, reported conversion to a negative COVID-19 test, and meta-analyses showed that herbal medicine added to standard treatment probably reduced the conversion time to a negative COVID-19 test compared with standard treatment (MD −3.14, 95% CI −4.68 to −1.60, p < 0.0001, I2 = 0%; moderate certainty, Supplementary Figure S6A). Meta-analysis of two RCTs including 404 participants, did not show a significant difference for the conversion rate to a negative COVID-19 test between herbal medicine added to standard treatment, versus standard treatment (RR 1.04, 95% CI 0.95 to 1.13, p = 0.39, I2 = 0%; moderate certainty, Supplementary Figure S6B).
Duration of Hospital Stay
Three RCTs including 161 participants, reported the duration of hospital stay. Meta-analysis showed that herbal medicine added to standard treatment reduced the length of stay compared with standard treatment (RR −3.78, 95% CI −5.85 to −1.71, p = 0.0003, I2 = 0%; low certainty, Supplementary Figure S7).
Seventeen RCTs including 1,716 participants, reported adverse effects relating to herbal medicine and standard treatment intervention. Meta-analysis showed no evidence of a significant difference between herbal medicine added to standard treatment versus standard treatment in the adverse events recorded (RD 0.00, 95% CI -0.04 to 0.03, p = 0.88, I2 = 75%; low certainty, Supplementary Figure S8). Of the 12 RCTs assessed for adverse events, no severe adverse events were determined in either group. The extracted data for all studies evaluating adverse events are available in Supplementary Table S5.
Prophylactic Effect of Herbal Medicine
There were no studies that directly addressed the prophylactic potential of herbal medicine intervention in COVID-19.
Ongoing RCTs of Herbal Medicine Intervention
The ongoing RCTs evaluating herbal medicine for the treatment and prevention of COVID-19 are provided in Supplementary Table S6. As of 28 March 2022, 48 RCTs for the treatment of COVID-19 were identified and one RCT investigating prophylaxis. These RCTs are being conducted or scheduled to start in several countries including China, United States, Singapore, and Pakistan, with expected trial completion dates by December 2022.
Summary of Main Results
This LSR and meta-analyses presents a comprehensive overview of herbal medicine trials relating to the treatment of COVID-19 up to 28 March 2022. This is the first version of this systematic review where there were 25 published RCTs, and 50 ongoing trials using many different herbal medicine interventions for the treatment and prevention of COVID-19. No studies investigating the effects of herbal medicine in preventing COVID-19 were identified. Of the 25 randomized trials included in this analysis, from a total of 2,288 participants, 1,185 participants were randomized to receive herbal medicine in addition to their standard treatment. The risk of bias of the included RCTs was overall unclear.
Eighteen meta-analyses were performed in this study. Random effects meta-analyses showed evidence of favorable effects of herbal medicine added to standard treatment, versus standard treatment alone based on the total effective rate (p = 0.0001), time to remission from fever (p < 0.00001), rate of remission from coughing (p < 0.0001), fatigue (p = 0.02), sputum production (p = 0.004), improvement in chest CT scans (p < 0.00001), incidence of progression to severe COVID-19 (p = 0.003), all-cause mortality (p = 0.003), time to a negative COVID-19 test (p < 0.0001), and duration of hospital stay (p = 0.0003). It was also determined that there was no evidence of a difference between herbal medicine added to standard treatment versus standard treatment alone on the rate of remission from symptoms such as fever, sore throat, nasal congestion and discharge, diarrhea, dry throat, and chills, as well as rate of conversion to a negative COVID-19 test. No severe adverse events were determined relating to herbal medicine interventions, and meta-analysis showed no evidence of a significant difference in the risk of adverse events between the two groups. The findings of this review showed that herbal medicine added to standard treatment may be beneficial for COVID-19 patients, but the certainty of evidence was mostly low to very low.
Overall Completeness and Applicability of Evidence
Most RCTs included in this study involved participants who were mildly to severely ill with COVID-19. However, different scales of disease severity and progression were used across the studies despite all included studies having originated from China. The severity of COVID-19 of the study participants varied between studies, and the available data was insufficient to allow an evaluation of whether the benefits of herbal medicine would differ with the severity of disease. The outcome measures of the included trials were also complex and varied widely. We selected and analyzed eight outcomes of interest based on “patient-important outcomes” and the general applicability of these outcomes to participants with mild-to-moderate or severe illness. Due to the lack of relevant data in the majority of studies, we could only include limited data for the analysis of safety outcomes. Several RCTs reporting on the outcomes selected for this current review were also excluded in the meta-analyses due to improper data presentation. Additionally, the comparison of differential treatment effects could not be conducted for the types and forms of herbal medicine due to the small number of included studies for each type of herbal medicine.
Quality of Evidence
The evidence for outcome measures was of moderate to very low certainty, with a vast majority being low to very low certainty. We downgraded the certainty of evidence for most outcomes to low or very low certainty due to the serious risk of bias for inadequate blinding, due to wide CI, or serious inconsistency in statistical heterogeneity (Supplementary Table S4). In addition, the sample size of several studies was small which may have led to higher variability and skewing of findings. Hence, the overall robustness as determined by these review findings was considered to be low.
Potential Biases in the Review Process
The primary limitation of this review was the unclear risk of bias across the included RCTs, indicating that most studies had methodological limitations. Only one study was judged to have a low risk of bias. All trials were described as “randomized controlled trials” but the reporting of most trials did not comply with the Consolidated Standards of Reporting Trials (CONSORT). Most trials did not provide the relevant information regarding allocation concealment and blinding and, several trials were open-labeled which may introduce bias to the trial results. The risk of bias across the included studies was concerning and resulted in the downgrading of the certainty of evidence. Another limitation was the reliability of the included studies which was possibly reduced due to the lack of trial registration and publicly available study protocol. Where data were missing, we tried to contact all study authors for the detailed reporting of incomplete data but we have yet to receive responses. In this review a comprehensive search was conducted to identify all completed, and ongoing trials, therefore we are confident that most of the relevant studies have been identified in this review, and further monitoring of the list of identified ongoing studies will be performed. We are also aware that excluding preprints from this review may somehow affect the outcome effect size. The evidence in preprints, however, is unstable and often undergoes major changes during peer-reviewed publication. Nevertheless, we will continue to monitor the updates in the evidence reported in preprints and their peer-reviewed publication in order to update the review accordingly.
Agreement and Disagreements With Other Studies or Reviews
To date, 21 systematic reviews have been identified that have similar findings to this current review (Liu M. et al., 2020; Ang et al., 2020; Sun CY. et al., 2020; Xiong X. et al., 2020; Fan et al., 2020; Pang et al., 2020; Zeng et al., 2020; Zhou et al., 2020; Wang H. et al., 2021; Liu M. et al., 2021; Wang Q. et al., 2021; Du et al., 2021; Fan et al., 2021; Jiang et al., 2021; Li et al., 2021; Liang et al., 2021; Luo et al., 2021; Wu et al., 2021; Yan et al., 2021; Yin et al., 2021; Zhuang et al., 2021). The treatment of COVID-19 benefits from the rapid dissemination of evidence, providing data for the synthesizing of evidence disseminated was constantly complied by systematic reviewers, resulting in a large number of systematic reviews with overlapping evidence, each article updated with the inclusion of only one or two additional studies at the time of publication. The multiplicity of systematic reviews of similar topics can confuse and mislead research end-users. Therefore, the intention in performing a LSR is to provide guidance in the form of a systematic up-to-date review. A comprehensive search (e.g., extensive database search) was performed in this review with analytical methods best suited for the evidence compiled (e.g., random-effects model instead of fixed effect model). This LSR and meta-analyses will be periodically updated with changes from each version highlighted for readers.
Implication for Practice and Research
Evidence that herbal medicine added to standard treatment of patients with COVID-19 results in important benefits, but the harms to relevant patient-important outcomes are highly uncertain, and not definitive. The evidence regarding the adverse effects of using herbal medicine interventions is also very uncertain due to inconsistent reporting of safety outcomes. Herbal medicine interventions could be recommended after their efficacy and safety concerns are adequately addressed. Amongst the included studies, there was also a lack of consistency in the outcome measurements, where the main outcomes reported varied across the studies and included many insubstantial outcomes. Despite the various challenges faced by COVID-19 clinical research, optimal trial designs of substantial sample size, randomization or blinding methods, and outcome measurements with proper reporting is necessary to increase the quality of evidence. Hence, future well-designed RCTs relating to herbal medicine for the treatment of COVID-19 remains highly anticipated.
Current evidence suggests that herbal medicine added to standard treatment has potential benefits for treating COVID-19 regardless of the uncertainties. Many research gaps in the clinical studies of herbal medicine still exist and trials with more rigorous study designs are highly warranted.
Deviation From Registered Protocol
A pre-registered protocol of this LSR is available at the International prospective register of systematic reviews database (PROSPERO CRD42020191711). Considering the inconsistency and complexity of outcome measurements reported amongst the included studies, the planned outcomes list was reviewed and the main outcomes were restricted to patient-important outcomes only. We selected the patient-important outcomes based on the COS that have been registered on the Core Outcome Measures in Effectiveness Trials (COMET) database (Qiu R. et al., 2020; Jin et al., 2020; Marshall et al., 2020; Tong et al., 2020). Subsequent to the originally planned risk of bias assessment, we performed an additional assessment on the quality of evidence using the GRADEpro guideline development tool. These changes were implemented before the data analysis.
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