key: cord-311353-ozqfsuh8 authors: Sun, Chun-Yang; Sun, Ya-Lei; Li, Xin-Min title: The role of Chinese medicine in COVID-19 pneumonia: A systematic review and meta-analysis date: 2020-07-08 journal: Am J Emerg Med DOI: 10.1016/j.ajem.2020.06.069 sha: doc_id: 311353 cord_uid: ozqfsuh8 INTRODUCTION: Chinese medicine (CM) has been used to treat Novel Coronavirus 2019 (COVID-19) pneumonia in China. This meta-analysis was conducted to evaluate the clinical efficacy and safety of CM in the treatment of COVID-19 pneumonia. METHODS: Randomized controlled trials (RCTs) involving CM in the treatment of COVID-19 pneumonia were identified from Cochrane Central Register of Controlled Trials, PubMed, EMBASE, Chinese National Knowledge Infrastructure, Chinese Biomedical Database, Wanfang Database and VIP Information Database. The methodological quality of trials was evaluated with Cochrane Hanadbook criteria, and the Cochrane Collaboration's Review Manager 5.3 software was used for meta-analysis. RESULTS: A total of 7 valid studies involving 681 patients were included. The meta-analysis exhibited in comparison to conventional treatment, CM combined with conventional treatment significantly improved clinical efficacy (RR = 1.21, 95% CI [1.08,1.36]), and significantly increased viral nucleic acid negative conversion rate (RR = 1.49, 95% CI [1.13,1.97]). CM also prominently reduced pulmonary inflammation (RR = 1.27, 95% CI [1.12,1.44]), and improved host immune function (WBC, MD = 0.92, 95% CI [0.07,1.76]; LYM, MD = 0.33, 95% CI [0.08,0.57]; LYM%, MD = 2.90, 95% CI [2.09,3.71]; CRP, MD = −12.66, 95% CI [−24.40, −0.92]). Meanwhile, CM did not increase the incidence of adverse reactions (RR = 1.17, 95% CI [0.39,3.52]). CONCLUSION: According to the allocated data, CM has demonstrated clinical efficacy and safety on COVID-19 pneumonia, which need to be confirmed by high quality, multiple-center, large sample randomized controlled trials. Novel Coronavirus disease 2019 pneumonia is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which firstly appeared in Wuhan, China [1] [2] . It is highly infectious and spreads through respiratory droplets and contact [3] . It is characterized by acute onset, severe symptoms, such as dyspnea and multi-organ dysfunction [4] . The World Health Organization listed this pneumonia epidemic of Wuhan, China, as a public health emergency of international concern [5] . The world is now facing a pandemic of COVID-19, for which no proven specific therapies are available, other than supportive care. On January 20, 2020, National Health Commission of the People's Republic of China announced that COVID-19 would be classified as category A infectious disease [6] . At the same time, Chinese medicine experts quickly reached a consensus on Chinese medicine (CM) therapy. As medical therapy, CM treatment was written in "Diagnosis and Treatment of Pneumonia Infected by 2019-nCoV (trial implementation 7th Edition)" published by National Health Commission of the People's Republic of China [7] . However, compared with conventional treatment, there is no high-level evidence to support the effectiveness of CM treatment. Therefore, the meta-analysis method will be used to systematically review the clinical efficacy and safety of CM for COVID-19 pneumonia. This analysis is expected to obtain meaningful conclusions and provide a high level of evidence-based medicine evidence. Studies meeting the following criteria were included: (1) randomized controlled trials (RCTs) using CM (including Chinese herbal medicine, Chinese patent medicine and Chinese medicine injections) to treat COVID-19 pneumonia regardless of J o u r n a l P r e -p r o o f meta-analysis. If two or more homogeneous studies are available, we will use aggregated data for meta-analysis. If the data are not available for quantitative analysis, we will report result by qualitative description. For dichotomous outcomes, we calculated the risk ratio (RR), 95% confidence intervals (CI) and P values. For continuous variable, we calculated the mean difference (MD), 95% CI and P values. We used the inverse variance method to calculate pooled MD values and the Mantel-Haenszel estimator to calculate RR. Studies will be evaluated for heterogeneity using I squared and chi-squared test. If I 2 >50%, or P0.05, the studies will be considered heterogeneous, and the pooling model will choose a random effects model, otherwise fixed effects model will be used. The funnel plot will be used to evaluate publication bias. 716 unique citations were identified from electronic database. After duplicates removed, 697 literature remained. By reading titles and abstracts, 42 articles were downloaded. A total of 42 articles were retrieved for further assessment, among which 35 were further excluded, for the reasons: wrong patient population; self-control; retrospective studies. In total, seven [9] [10] [11] [12] [13] [14] [15] RCTs met the inclusion criteria and were subjected to data extraction ( Figure 1 ). All studies included involved seven RCTs with 681 patients. Of the seven RCTs, two RCTs [9, 13] reported clinical effective rate, seven RCTs [9] [10] [11] [12] [13] [14] [15] recorded incidence of adverse reactions, three RCTs [10, 11, 14] reported viral nucleic acid negative conversion rate, four RCTs [10, [12] [13] [14] recorded remission rate of pulmonary inflammation (chest CT). There were three RCTs [9, 13, 14] reported white blood cell count (WBC), three RCTs [9, 10, 14] reported lymphocyte count (LYM), two RCTs [9, 13] reported lymphocyte ratio (LYM%), four RCTs [9, 10, 12, 14] reported C-reactive proteins, and two RCTs [12, 14] reported interleukin-6. The comparison of baseline characteristics showed there were no significant differences in gender, age, or disease duration between the treatment and control groups (P>0.05). The characteristics of the studies are illustrated in Table 1 J o u r n a l P r e -p r o o f For the eligible studies, three studies [9, 12, 15] The clinical effective rate was tested in two RCTs involved 273 patients. The efficacy criteria were predominantly based on reduction of clinical symptoms and could be divided into three grades: cured, remarkable recovery, unrecovered. The rate calculated by this formula: (number of cured patients+number of remarkable recovery patients)/total number×100% [16] . Heterogeneity test results(P=0.39, I 2 =0%) indicated that there were no statistical significant difference between the studies, and the fixed effect model was selected for meta-analysis. As can be observes in Figure Taking incidence of adverse reactions into consideration (including seven RCTs, 681patients), we noted there is high heterogeneity between studies(P=0.03, I 2 =62%). Therefore, it was decided to choose the random effect model for meta-analysis. The chest CT findings were typical of findings for COVID-19 pneumonia [17, 18] . Figure 6 ). The results indicated that, compared with conventional treatment alone, combined therapy with CM can significantly reduce pulmonary inflammation (chest CT). [27] [28] [29] . These immunological markers may be of importance due to their correlation with disease severity in COVID-19. There are no specific pharmacological interventions discovered for treatment of COVID-19 pneumonia so far. The World Health Organization recommended that potential antiviral medicines should be developed [30] . However, the development of potential antiviral medicines may take months, even years. In consideration of these limitations, the application of Chinese medicine could be promoted. showed that CM has excellent outcomes in the treatment of COVID-19, bringing new hope for the control of COVID-19 pneumonia [9] [10] [11] [12] [13] [14] [15] . The results of this meta-analysis are encouraging. In terms of clinical effective rate, viral nucleic acid negative conversion rate, remission rate of pulmonary inflammation, and biochemical markers, CM exhibited superior performance. Meanwhile, CM has therapeutic safety. As the first meta-analysis evaluating the efficacy and safety of CM for the treatment of COVID-19 pneumonia, the wide extent of literature screening and the introduction of statistical analysis methods have ensured the validity of this review, as well as providing a rational conclusion. It is critical for clinicians to accurately determine the severity of a patients condition. 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