Real-world experience of Fuzheng Yiqing granule as chemoprophylaxis against COVID-19 infection among close contacts: A prospective cohort study.

BACKGROUND: The objective of the current study was to evaluate whether the use of traditional Chinese medicine, Fuzheng Yiqing granule (FZYQG), was associated with a reduced infection risk of COVID-19 in close contacts. RESEARCH DESIGN AND METHODS: This was a prospective cohort study across 203 quarantine centres for close contacts and secondary contacts of COVID-19 patients in Yangzhou city. FZYQG group was defined as quarantined individuals who voluntarily took FZYQG; control group did not take FZYQG. The primary outcome was the coronavirus test positive rate during quarantine period. Logistic regression with propensity score inverse probability weighting was used for adjusted analysis to evaluate independent association between FZYQG and test positive rate. RESULTS: From July 13, 2021 to September 30, 2021, 3438 quarantined individuals took FZYQG and 2248 refused to take the granule. Test positive rate was significantly lower among quarantined individuals who took FZYQG (0.29% vs. 1.73%, risk ratio 0.17, 95% confidence interval (CI): 0.08-0.34, p < 0.001). On logistic regression, odds for test positive were decreased in FZYQG group (odds ratio: 0.16, 95% CI: 0.08-0.32, p < 0.001). CONCLUSIONS: Close and secondary contacts of COVID-19 patients who received FZYQG had a lower test positive rate than control individuals in real-world experience. TRIAL REGISTRATION: This study has been registered on Chinese Clinical Trial Registry (ChiCTR2100049590) on August 5, 2021.

Combination of Hua Shi Bai Du granule (Q-14) and standard care in the treatment of patients with coronavirus disease 2019 (COVID-19): A single-center, open-label, randomized controlled trial.

OBJECTIVE: To evaluate the efficacy and safety of Hua Shi Bai Du Granule (Q-14) plus standard care compared with standard care alone in adults with coronavirus disease (COVID-19). STUDY DESIGN: A single-center, open-label, randomized controlled trial. SETTING: Wuhan Jinyintan Hospital, Wuhan, China, February 27 to March 27, 2020. PARTICIPANTS: A total of 204 patients with laboratory-confirmed COVID-19 were randomized into the treatment group and control group, consisting of 102 patients in each group. INTERVENTIONS: In the treatment group, Q-14 was administered at 10 g (granules) twice daily for 14 days, plus standard care. In the control group, patients were provided standard care alone for 14 days. MAIN OUTCOME MEASURE: The primary outcome was the conversion time for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral assay. Adverse events were analyzed in the safety population. RESULTS: Among the 204 patients, 195 were analyzed according to the intention-to-treat principle. A total of 149 patients (71 vs. 78 in the treatment and control groups, respectively) tested negative via the SARS-CoV-2 viral assay. There was no statistical significance in the conversion time between the treatment group and control group (Full analysis set: Median [interquartile range]: 10.00 [9.00-11.00] vs. 10.00 [9.00-11.00]; Mean rank: 67.92 vs. 81.44; P = 0.051). The recovery time for fever was shorter in the treatment group than in the control group. The disappearance rate of symptoms like cough, fatigue, and chest discomfort was significantly higher in the treatment group. In chest computed tomography (CT) examinations, the overall evaluation of chest CT examination after treatment compared with baseline showed that more patients improved in the treatment group. There were no significant differences in the other outcomes. CONCLUSION: The combination of Q-14 and standard care for COVID-19 was useful for the improvement of symptoms (such as fever, cough, fatigue, and chest discomfort), but did not result in a significantly higher probability of negative conversion in the SARS-CoV-2 viral assay. No serious adverse events were observed. TRIAL REGISTRATION: ChiCTR2000030288.

Association between early treatment with Qingfei Paidu decoction and favorable clinical outcomes in patients with COVID-19: A retrospective multicenter cohort study.

The coronavirus disease 2019 (COVID-19) epidemic has been almost controlled in China under a series of policies, including "early diagnosis and early treatment". This study aimed to explore the association between early treatment with Qingfei Paidu decoction (QFPDD) and favorable clinical outcomes. In this retrospective multicenter study, we included 782 patients (males, 56 %; median age 46) with confirmed COVID-19 from 54 hospitals in nine provinces of China, who were divided into four groups according to the treatment initiation time from the first date of onset of symptoms to the date of starting treatment with QFPDD. The primary outcome was time to recovery; days of viral shedding, duration of hospital stay, and course of the disease were also analyzed. Compared with treatment initiated after 3 weeks, early treatment with QFPDD after less than 1 week, 1-2 weeks, or 2-3 weeks had a higher likelihood of recovery, with adjusted hazard ratio (HR) (95 % confidence interval [CI]) of 3.81 (2.65-5.48), 2.63 (1.86-3.73), and 1.92 (1.34-2.75), respectively. The median course of the disease decreased from 34 days to 24 days, 21 days, and 18 days when treatment was administered early by a week (P < 0.0001). Treatment within a week was related to a decrease by 1-4 days in the median duration of hospital stay compared with late treatment (P<0.0001). In conclusion, early treatment with QFPDD may serve as an effective strategy in controlling the epidemic, as early treatment with QFPDD was associated with favorable outcomes, including faster recovery, shorter time to viral shedding, and a shorter duration of hospital stay. However, further multicenter, prospective studies with a larger sample size should be conducted to confirm the benefits of early treatment with QFPDD.

Current state and future perspective of cardiovascular medicines derived from natural products.

The contribution of natural products (NPs) to cardiovascular medicine has been extensively documented, and many have been used for centuries. Cardiovascular disease (CVD) is the leading cause of morbidity and mortality worldwide. Over the past 40 years, approximately 50% of newly developed cardiovascular drugs were based on NPs, suggesting that NPs provide essential skeletal structures for the discovery of novel medicines. After a period of lower productivity since the 1990s, NPs have recently regained scientific and commercial attention, leveraging the wealth of knowledge provided by multi-omics, combinatorial biosynthesis, synthetic biology, integrative pharmacology, analytical and computational technologies. In addition, as a crucial part of complementary and alternative medicine, Traditional Chinese Medicine has increasingly drawn attention as an important source of NPs for cardiovascular drug discovery. Given their structural diversity and biological activity NPs are one of the most valuable sources of drugs and drug leads. In this review, we briefly described the characteristics and classification of NPs in CVDs. Then, we provide an up to date summary on the therapeutic potential and the underlying mechanisms of action of NPs in CVDs, and the current view and future prospect of developing safer and more effective cardiovascular drugs based on NPs.

[TCMATCOV--a bioinformatics platform to predict efficacy of TCM against COVID-19].

There is urgent need to discover effective traditional Chinese medicine(TCM) for treating coronavirus disease 2019(COVID-19). The development of a bioinformatic tool is beneficial to predict the efficacy of TCM against COVID-19. Here we deve-loped a prediction platform TCMATCOV to predict the efficacy of the anti-coronavirus pneumonia effect of TCM, based on the interaction network imitating the disease network of COVID-19. This COVID-19 network model was constructed by protein-protein interactions of differentially expressed genes in mouse pneumonia caused by SARS-CoV and cytokines specifically up-regulated by COVID-19. TCMATCOV adopted quantitative evaluation algorithm of disease network disturbance after multi-target drug attack to predict potential drug effects. Based on the TCMATCOV platform, 106 TCM were calculated and predicted. Among them, the TCM with a high disturbance score account for a high proportion of the classic anti-COVID-19 prescriptions used by clinicians, suggesting that TCMATCOV has a good prediction ability to discover the effective TCM. The five flavors of Chinese medicine with a disturbance score greater than 1 are mainly spicy and bitter. The main meridian of these TCM is lung, heart, spleen, liver, and stomach meridian. The TCM related with QI and warm TCM have higher disturbance score. As a prediction tool for anti-COVID-19 TCM prescription, TCMATCOV platform possesses the potential to discovery possible effective TCM against COVID-19.

[Analysis of the Puzzle between Acupuncture Community and Acupuncture Clinical Trials].

Recently a number of acupuncture clinical trial projects mainly conducted by conventional scientists have generated many negative results. A large meta-analysis of patient-level acupuncture data for the treatment of chronic pain conditions have demonstrated that the effects of verum acupuncture on pain improvement have statistically significant, but small, differences compared with sham-acupuncture procedures and no difference between acupuncture points and non-points. These conclusions have puzzled the acupuncture community and made confusion for acupuncture research and practices. The purpose of this paper was to compare differences between acupuncture clinical practices and the trial studies, which include "acupuncture technical principles", "acupuncture clinical trial design", and "acupuncture practice based on the theory of traditional Chinese medicine". These factors contribute to the puzzle between the acupuncture community/practice and acupuncture clinical trials, which can be improved in future studies.

[Professor MA Ji-xing and Acupuncture Scientification at the Primary Stage of Establishment of the People's Republic of China].

In the initial stage (1950s) of the establishment of the People's Republic of China, the Pavlov's theory played an important influence on Chinese biology and medical science fields. At that time, many schools or colleges of traditional Chinese medicine were set up one after another, the first edition of teaching materials or textbook was complete, and a lot of advanced training courses and training classes were developed. In that specific period of "acupuncture scientification", Mr. MA Ji-xing, a professor from China Academy of Traditional Chinese Medicine, is a representative scholar who employed Pavlov's theory to make a scientific explanation about the underlying physiological mechanisms of acupuncture-moxibustion therapy. For example, he employed nerve network or nerve system to explain topical acupuncture stimulation and distal stimulation to induce local effect or distal curative effect, employed the cutaneous-visceral reflex to explain the therapeutic effect of acu-moxibustion for visceral disorders, used the viscera-cutaneous reflex to explain the tender point (sensitized region) or Ashi-point, used the "predominant factor mechanism" or excitation transfer of the stimulated non-sensitized cutaneous region close to the diseased locus to explain the pain-relief of acupuncture stimulation, used the stimulation strength, duration, frequency and distance (to the locus) to explain the needling reinforcing or reducing effect, and so on and so forth. He wrote many articles and books about acupuncturology, one of which was named Jianyao Zhenjiu Xue (Concise Acupuncturology), a well-known demonstration teaching material for advanced training courses, inducing a significant influence on the acu-moxibustion field in both academic field and clinical practice. Looking back this period of history may provide a helpful reference for current research on academic development of acupuncturology.

Comparsion analysis of data mining models applied to clinical research in traditional Chinese medicine.

OBJECTIVE: To help researchers selecting appropriate data mining models to provide better evidence for the clinical practice of Traditional Chinese Medicine (TCM) diagnosis and therapy. METHODS: Clinical issues based on data mining models were comprehensively summarized from four significant elements of the clinical studies: symptoms, symptom patterns, herbs, and efficacy. Existing problems were further generalized to determine the relevant factors of the performance of data mining models, e.g. data type, samples, parameters, variable labels. Combining these relevant factors, the TCM clinical data features were compared with regards to statistical characters and informatics properties. Data models were compared simultaneously from the view of applied conditions and suitable scopes. RESULTS: The main application problems were the inconsistent data type and the small samples for the used data mining models, which caused the inappropriate results, even the mistake results. These features, i.e. advantages, disadvantages, satisfied data types, tasks of data mining, and the TCM issues, were summarized and compared. CONCLUSION: By aiming at the special features of different data mining models, the clinical doctors could select the suitable data mining models to resolve the TCM problem.

Syndrome classification based on manifold ranking for viral hepatitis.

Treatment determination based on syndrome differentiation is the key of Chinese medicine. A feasible way of improving the clinical therapy effectiveness is needed to correctly differentiate the syndrome classifications based on the clinical manifestations. In this paper, a novel data mining method based on manifold ranking (MR) is proposed to explore the relation between syndromes and symptoms for viral hepatitis. Since MR could take the symptom data with expert differentiation and the symptom data without expert differentiation into the task of syndrome classification, the clinical information used for modeling the syndrome features is greatly enlarged so as to improve the precise of syndrome classification. In addition, the proposed method of syndrome classification could also avoid two disadvantages in previous methods: linear relation of the clinical data and mutually exclusive symptoms among different syndromes. And it could help exploit the latent relation between syndromes and symptoms more effectively. Better performance of syndrome classification is able to be achieved according to the experimental results and the clinical experts.