Use of traditional Chinese medicine for the treatment and prevention of COVID-19 and rehabilitation of COVID-19 patients: An evidence mapping study.

Background: The potential effectiveness of traditional Chinese medicine (TCM) against "epidemic diseases" has highlighted the knowledge gaps associated with TCM in COVID-19 management. This study aimed to map the matrix for rigorously assessing, organizing, and presenting evidence relevant to TCM in COVID-19 management. Methods: In this study, we used the methodology of evidence mapping (EM). Nine electronic databases, the WHO International Clinical Trials Registry Platform (ICTRP) Search Portal, ClinicalTrials.gov, gray literature, reference lists of articles, and relevant Chinese conference proceedings, were searched for articles published until 23 March 2022. The EndNote X9, Rayyan, EPPI, and R software were used for data entry and management. Results: In all, 126 studies, including 76 randomized controlled trials (RCTs) and 50 systematic reviews (SRs), met our inclusion criteria. Of these, only nine studies (7.14%) were designated as high quality: four RCTs were assessed as "low risk of bias" and five SRs as "high quality." Based on the research objectives of these studies, the included studies were classified into treatment (53 RCTs and 50 SRs, 81.75%), rehabilitation (20 RCTs, 15.87%), and prevention (3 RCTs, 2.38%) groups. A total of 76 RCTs included 59 intervention categories and 57 efficacy outcomes. All relevant trials consistently demonstrated that TCM significantly improved 22 outcomes (i.e., consistent positive outcomes) without significantly affecting four (i.e., consistent negative outcomes). Further, 50 SRs included nine intervention categories and 27 efficacy outcomes, two of which reported consistent positive outcomes and two reported consistent negative outcomes. Moreover, 45 RCTs and 38 SRs investigated adverse events; 39 RCTs and 30 SRs showed no serious adverse events or significant differences between groups. Conclusion: This study provides evidence matrix mapping of TCM against COVID-19, demonstrating the potential efficacy and safety of TCM in the treatment and prevention of COVID-19 and rehabilitation of COVID-19 patients, and also addresses evidence gaps. Given the limited number and poor quality of available studies and potential concerns regarding the applicability of the current clinical evaluation standards to TCM, the effect of specific interventions on individual outcomes needs further evaluation.

Use of traditional Chinese medicine for the treatment and prevention of COVID-19 and rehabilitation of COVID-19 patients: An evidence mapping study

Background: The potential effectiveness of traditional Chinese medicine (TCM) against "epidemic diseases” has highlighted the knowledge gaps associated with TCM in COVID-19 management. This study aimed to map the matrix for rigorously assessing, organizing, and presenting evidence relevant to TCM in COVID-19 management. Methods: In this study, we used the methodology of evidence mapping (EM). Nine electronic databases, the WHO International Clinical Trials Registry Platform (ICTRP) Search Portal, ClinicalTrials.gov, gray literature, reference lists of articles, and relevant Chinese conference proceedings, were searched for articles published until 23 March 2022. The EndNote X9, Rayyan, EPPI, and R software were used for data entry and management. Results: In all, 126 studies, including 76 randomized controlled trials (RCTs) and 50 systematic reviews (SRs), met our inclusion criteria. Of these, only nine studies (7.14%) were designated as high quality: four RCTs were assessed as "low risk of bias” and five SRs as "high quality.” Based on the research objectives of these studies, the included studies were classified into treatment (53 RCTs and 50 SRs, 81.75%), rehabilitation (20 RCTs, 15.87%), and prevention (3 RCTs, 2.38%) groups. A total of 76 RCTs included 59 intervention categories and 57 efficacy outcomes. All relevant trials consistently demonstrated that TCM significantly improved 22 outcomes (i.e., consistent positive outcomes) without significantly affecting four (i.e., consistent negative outcomes). Further, 50 SRs included nine intervention categories and 27 efficacy outcomes, two of which reported consistent positive outcomes and two reported consistent negative outcomes. Moreover, 45 RCTs and 38 SRs investigated adverse events;39 RCTs and 30 SRs showed no serious adverse events or significant differences between groups. Conclusion: This study provides evidence matrix mapping of TCM against COVID-19, demonstrating the potential efficacy and safety of TCM in the treatment and prevention of COVID-19 and rehabilitation of COVID-19 patients, and also addresses evidence gaps. Given the limited number and poor quality of available studies and potential concerns regarding the applicability of the current clinical evaluation standards to TCM, the effect of specific interventions on individual outcomes needs further evaluation.

Data-Driven Building Energy Consumption Prediction Model Based on VMD-SA-DBN

Prediction of building energy consumption using mathematical modeling is crucial for improving the efficiency of building energy utilization, assisting in building energy consumption planning and scheduling, and further achieving the goal of energy conservation and emission reduction. In consideration of the non-linear and non-smooth characteristics of building energy consumption time series data, a short-term, hybrid building energy consumption prediction model combining variational mode decomposition (VMD), a simulated annealing (SA) algorithm, and a deep belief network (DBN) is proposed in this study. In the proposed VMD-SA-DBN model, the VMD algorithm decomposes the time series into different modes to reduce the fluctuation of the data. The SA-DBN prediction model is built for each mode separately, and the DBN network structure parameters are optimized by the SA algorithm. The prediction results of each model are aggregated and reconstructed to obtain the final prediction output. The validity and prediction performance of the proposed model is evaluated on a publicly available dataset, and the results show that the proposed new model significantly improves the accuracy and stability of building energy consumption prediction compared with several typical machine learning methods. The mean absolute percent error (MAPE) of the VMD-SA-DBN model is 63.7%, 65.5%, 46.83%, 64.82%, 44.1%, 36.3%, and 28.3% lower than that of the long short-term memory (LSTM), gated recurrent unit (GRU), VMD-LSTM, VMD-GRU, DBN, SA-DBN, and VMD-DBN models, respectively. The results will help managers formulate more-favorable low-energy emission reduction plans and improve building energy efficiency.

From Health Campaign to Interpersonal Communication: Does Traditional Diet Culture Hinder the Communication of the Chinese Gongkuai Campaign?

Interpersonal communication is beneficial in promoting individuals' tendency to accept health-campaign-targeted behavior. Based on the protective action decision model, this study investigated the key factors underlying individual's interpersonal communication on the Gongkuai campaign, which was carried out during Coronavirus disease 2019 (COVID-19). The main goal of the Gongkuai campaign was to change traditional communal eating habits and reduce public health risks. An online questionnaire survey involving 618 respondents was conducted in China after the 2020 Gongkuai campaign propagated, and the data were analyzed by using the structural equation modeling technique. The results indicated that health campaign exposure is a critical determinant of perceived campaign-related knowledge and health risk perception, which are significant predictors of interpersonal communication. Meanwhile, campaign-related knowledge can elicit risk perception. Furthermore, campaign exposure influenced interpersonal communication in ways that traditional diet culture did not predict. Risk perception was also unaffected by traditional diet culture. It is worth noting that individuals' agreement with traditional diet culture does not hinder health campaign-generated interpersonal communication in the context of public health crisis. Based on the findings, theoretical and policy implications for motivating interpersonal communication were discussed, and research limitations were pointed out.

Identification of a recombinant equine coronavirus in donkey, China.

Equine coronavirus (ECoV) was first identified in the USA and has been previously described in several countries. In order to test the presence of ECoV in China, we collected 51 small intestinal samples from donkey foals with diarrhoea from a donkey farm in Shandong Province, China between August 2020 and April 2021. Two samples tested positive for ECoV and full-length genome sequences were successfully obtained using next-generation sequencing, one of which was further confirmed by Sanger sequencing. The two strains shared 100% sequence identity at the scale of whole genome. Bioinformatics analyses further showed that the two Chinese strains represent a novel genetic variant of ECoV and shared the highest sequence identity of 97.05% with the first identified ECoV strain - NC99. In addition, it may be a recombinant, with the recombination region around the NS2 gene. To our knowledge, this is the first documented report of ECoV in China, highlighting its risk to horse/donkey breeding. In addition, its potential risk to public health also warrants further investigation.

Thymosin α1 therapy in critically ill patients with COVID-19: A multicenter retrospective cohort study.

BACKGROUND: COVID-19 characterized by refractory hypoxemia increases patient mortality because of immunosuppression effects. This study aimed to evaluate the efficacy of immunomodulatory with thymosin α1 for critical COVID-19 patients. METHODS: This multicenter retrospective cohort study was performed in 8 government-designated treatment centers for COVID-19 patients in China from Dec. 2019 to Mar. 2020. Thymosin α1 was administrated with 1.6 mg qd or q12 h for >5 days. The primary outcomes were the 28-day and 60-day mortality, the secondary outcomes were hospital length of stay and the total duration of the disease. Subgroup analysis was carried out according to clinical classification. RESULTS: Of the 334 enrolled COVID-19 patients, 42 (12.6%) died within 28 days, and 55 (16.5%) died within 60 days of hospitalization. There was a significant difference in the 28-day mortality between the thymosin α1 and non-thymosin α1-treated groups in adjusted model (P = 0.016), without obvious differences in the 60-day mortality and survival time in the overall cohort (P > 0.05). In the subgroup analysis, it was found that thymosin α1 therapy significantly reduced 28-day mortality (Hazards Ratios HR, 0.11, 95% confidence interval CI 0.02-0.63, P=0.013) via improvement of Pa02/FiO2 (P = 0.036) and prolonged the hospital length of stay (P = 0.024) as well as the total duration of the disease (P=0.001) in the critical type patients, especially those aged over 64 years, with white blood cell >6.8×109/L, neutrophil >5.3×109/L, lymphocyte < 0.73 × 109/L, PaO2/FiO2 < 196, SOFA > 3, and acute physiology and chronic health evaluation (APACHE) II > 7. CONCLUSION: These results suggest that treatment with thymosin α1 can markedly decrease 28-day mortality and attenuate acute lung injury in critical type COVID-19 patients.

Clinical manifestation, outcomes in pregnant women with COVID-19 and the possibility of vertical transmission: a systematic review of the current data.

Objectives To assess perinatal outcomes of COVID-19 infections during pregnancy and the possibility of vertical transmission. Methods An analysis was performed using Stata 15.0, and Q-test was used to evaluate the heterogeneity of the included studies. Results The most common symptoms were found to be fever (64.78%), cough (59.81%) and shortness of breath or dyspnea (23.86%). Of this 88.73% patients demonstrated typical COVID-19 signs on chest CT or X-ray. Intubation was carried out in 35.87% of patients, and 4.95% of mothers were admitted to the intensive care unit, where the rate of maternal death was <0.01% and that of premature delivery was 25.32%. The rate of the birth weight being <2,500 g was 30.65% and that of Neonatal intensive care unit (NICU) admission was 24.41%. Positive nasopharynx swabs or sputum from newborns was <0.01%. Conclusions Pregnant patients with COVID-19 most commonly presented with fever, cough, shortness of breath and dyspnea, most of which possessed imaging manifestations. The risk of intubation and admission to intensive care unit were high. The risk of premature delivery was higher, leading to a high risk of NICU admission and low neonatal birthweight. Vertical transmission of SARS-CoV-2 from mother to child was found to be unlikely.