Treatment efficacy analysis of traditional Chinese medicine for novel coronavirus pneumonia (COVID-19): an empirical study from Wuhan, Hubei Province, China

Author:

Luo Erdan,Zhang Daiyan,Luo Hua,Liu Bowen,Zhao Keming,Zhao Yonghua,Bian Ying,Wang Yitao

Abstract

Abstract Background A novel coronavirus was identified in December, 2019 in Wuhan, China, and traditional Chinese medicine (TCM) played an active role in combating the novel coronavirus pneumonia (NCP) caused by this fast-spreading virus COVID-19. Thus, we aimed to explore TCM characteristics of clinical efficacy to NCP, as well as to optimize Qingfei Paidu decoction (QFPDD) and the recommended formulas to NCP by National Health Commission (NHC). Methods Chinese medical sciences theory and clinical application of TCM were analyzed. A total of 54 NCP patients were observed in a hospital from Wuhan, whose clinical characteristics and utilization of Chinese Medicines (CMs) were described. Paired t test was used to measure the change of patients’ hemogram during hospitalization period, indicating the effect of CMs. Multiple linear regression analysis was applied to explore the factors affecting the length of hospital stay. Network pharmacology analysis was applied to figure out the performance of NHC-recommended formulas of five disease stages at levels of compounds, targets and pathways. Result The average length of hospital stay was 8.96 days. Patients over 45 stayed 9.79 days in hospital in average, longer than 7.64 days of patients under 45. Comparing the hemograms between admission and discharge of hospital, the number of leukocytes, neutrophil, lymphocyte and platelet increased, while the numbers of erythrocytes, hemoglobin concentration and hematocrit decreased. According to the standard coefficients of regression, the factor affecting the length of stay for the most was CMs in category of invigorating spleen and removing dampness (ISRD), followed by administrating CMs, male, and cough. Thirty-two CMs were screened after deleting duplication from QFPDD and NHC-recommended formulas. Compound quercetin, luteolin, kaempferol, acacetin etc., were all involved in the treatment of various disease stages on the compound level both in generality and individuality. Conclusion TCM has a systemic theoretical understanding on the pathological evolution and a positive clinical efficacy on NCP. The CMs of ISRD improved patients’ recovery, suggesting the importance of regulating intestinal function and keeping microenvironmental balance in TCM treatment of NCP. The active compounds from QFPDD and NHC-recommended formulas contribute to recovery of varied disease progresses during TCM treating NCP.

Funder

Universidade de Macau

Publisher

Springer Science and Business Media LLC

Subject

Complementary and alternative medicine,Pharmacology

Reference30 articles.

1. Tong X, Li X, Zhao L, et al. Discussion on traditional Chinese medicine prevention and treatment strategies of coronavirus disease 2019 (COVID-19) from the perspective of “Cold-dampness Pestilence”. J Tradit Chin Med. 2020;61(06):465–70.

2. Wang Q. Manual for traditional Chinese medicine diagnosis and treatment of oovel coronavirus pneumonia. Beijing. 2020.

3. Wang Y, Qi W, Ma J, et al. Clinical features and syndrome differentiation of novel coronavirus pneumonia in traditional Chinese medicine. J Tradit Chin Med. 2020;61(04):281–5.

4. Xiang Q, Mo Z, Song E. Traditional Chinese medicine theory and clinical study on novel coronavirus pneumonia (NCP) infection. Herald Med. 2020;39(03):323–6.

5. Yong W, Feng C, Zhang L, et al. Analysis of 4 cases of COVID-19 treated by integrated traditional Chinese and western medicine in Gansu. Shanghai J Tradit Chin Med. 2020;54(03):21–4.

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