Analysis of the mental health status of hospital staff during the COVID-19 pandemic.

BACKGROUND: Medical work is a complex and interpersonally sensitive job; clinicians interact with patients, colleagues and society-at-large daily, and they are under pressure from a variety of sources. The doctor-patient relationship is of particular concern. OBJECTIVE: To investigate the current mental health status of hospital staff and related influencing factors during the coronavirus disease 2019 (COVID-19) pandemic. METHODS: The Symptom Checklist-90 (SCL-90) and Generalized Anxiety Disorder Scale-7 (GAD-7) were used to survey the current mental health status of hospital employees. The resulting qualitative data was described in the form of frequency and percentage (%), and the quantitative data were expressed as mean±standard deviation (X¯±S). RESULTS: A total of 1,074 employees of The Third Xiangya Hospital of Central South University participated in the mental health survey, of whom 77.47% were women. The SCL-90 score was 133.89±48.87, and the three highest scoring factors were depression, somatisation and obsessions, with factor scores of 19.10±8.14, 16.78±6.21 and 16.27±6.39, respectively. The GAD-7 score was 3.74±4.17 for women and 2.14±3.55 for men. The number of women with anxiety disorders was higher compared with men. CONCLUSION: The mental health status of hospital workers with different demographic characteristics varied greatly during the COVID-19 pandemic. Active attention needs to be paid to the mental health status of hospital staff.

NVAS: A non-interactive verifiable federated learning aggregation scheme for COVID-19 based on game theory.

The continued spread of COVID-19 seriously endangers the physical and mental health of people in all countries. It is an important method to establish inter agency COVID-19 detection and prevention system based on game theory through wireless communication and artificial intelligence. Federated learning (FL) as a privacy preserving machine learning framework has received extensive attention. From the perspective of game theory, FL can be regarded as a process in which multiple participants play games against each other to maximize their own interests. This requires that the user's data is not leaked during the training process. However, existing studies have proved that the privacy protection capability of FL is insufficient. In addition, the existing way of realizing privacy protection through multiple rounds of communication between participants increases the burden of wireless communication. To this end, this paper considers the security model of FL based on game theory, and proposes our scheme, NVAS, a non-interactive verifiable privacy-preserving FL aggregation scheme in wireless communication environments. The NVAS can protect user privacy during FL training without unnecessary interaction between participants, which can better motivate more participants to join and provide high-quality training data. Furthermore, we designed a concise and efficient verification algorithm to ensure the correctness of model aggregation. Finally, the security and feasibility of the scheme are analyzed.

NVAS: A non-interactive verifiable federated learning aggregation scheme for COVID-19 based on game theory☆

The continued spread of COVID-19 seriously endangers the physical and mental health of people in all countries. It is an important method to establish inter agency COVID-19 detection and prevention system based on game theory through wireless communication and artificial intelligence. Federated learning (FL) as a privacy preserving machine learning framework has received extensive attention. From the perspective of game theory, FL can be regarded as a process in which multiple participants play games against each other to maximize their own interests. This requires that the user's data is not leaked during the training process. However, existing studies have proved that the privacy protection capability of FL is insufficient. In addition, the existing way of realizing privacy protection through multiple rounds of communication between participants increases the burden of wireless communication. To this end, this paper considers the security model of FL based on game theory, and proposes our scheme, NVAS, a non-interactive verifiable privacy-preserving FL aggregation scheme in wireless communication environments. The NVAS can protect user privacy during FL training without unnecessary interaction between participants, which can better motivate more participants to join and provide high-quality training data. Furthermore, we designed a concise and efficient verification algorithm to ensure the correctness of model aggregation. Finally, the security and feasibility of the scheme are analyzed.

[Exploration and example interpretation of real-world herbal prescription classification based on similarity matching algorithm].

In observational studies, herbal prescriptions are usually studied in the form of "similar prescriptions". At present, the classification of prescriptions is mainly based on clinical experience judgment, but there are some problems in manual judgment, such as lack of unified criteria, labor consumption, and difficulty in verification. In the construction of a database of integrated traditional Chinese and western medicine for the treatment of coronavirus disease 2019(COVID-19), our research group tried to classify real-world herbal prescriptions using a similarity matching algorithm. The main steps include 78 target prescriptions are determined in advance; four levels of importance labeling shall be carried out for the drugs of each target prescription; the combination, format conversion, and standardization of drug names of the prescriptions to be identified in the herbal medicine database; calculate the similarity between the prescriptions to be identified and each target prescription one by one; prescription discrimination is performed based on the preset criteria; remove the name of the prescriptions with "large prescriptions cover the small". Through the similarity matching algorithm, 87.49% of the real prescriptions in the herbal medicine database of this study can be identified, which preliminarily proves that this method can complete the classification of herbal prescriptions. However, this method does not consider the influence of herbal dosage on the results, and there is no recognized standard for the weight of drug importance and criteria, so there are some limitations, which need to be further explored and improved in future research.

Virological features and pathogenicity of SARS-CoV-2 Omicron BA.2.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron BA.2 was a dominant circulating SARS-CoV-2 variant worldwide. Recent reports hint that BA.2 is similarly potent regarding antibody evasion but may be more transmissible than BA.1. The pathogenicity of BA.2 remains unclear and is of critical public health significance. Here we investigated the virological features and pathogenicity of BA.2 with in vitro and in vivo models. We show that BA.2 is less dependent on transmembrane protease serine 2 (TMPRSS2) for virus entry in comparison with BA.1 in vitro. In K18-hACE2 mice, BA.2 replicates more efficiently than BA.1 in the nasal turbinates and replicates marginally less efficiently in the lungs, leading to decreased body weight loss and improved survival. Our study indicates that BA.2 is similarly attenuated in lungs compared with BA.1 but is potentially more transmissible because of its better replication at the nasal turbinates.

Perceived stress and life satisfaction during COVID-19 pandemic: the mediating role of social adaptation and the moderating role of emotional resilience.

The present study mainly focused on college students during the COVID-19 outbreak and aimed to develop and examine a moderated mediation model between perceived stress and life satisfaction, with social adaptation during COVID-19 as a mediator, and emotional resilience as a moderator. A sample of 1032 college students participated in this study and completed questionnaires regarding perceived stress, social adaptation during COVID-19, emotional resilience, and life satisfaction. Findings indicated that 1) social adaptation during COVID-19 partially mediated the association between perceived stress and life satisfaction; and 2) emotional resilience moderated the relationship between perceived stress and social adaptation during COVID-19 as well as perceived stress and life satisfaction. These two relationships became stronger for college students with lower levels of emotional resilience. The results were discussed to illuminate the mechanism in relation to theoretical and practical implication for improving college students' life satisfaction during the period of the COVID-19 outbreak.

Multi-Criteria Decision Analysis In Healthcare: Scientometric And Bibliometric Analysis

IntroductionMulti-criteria decision analysis (MCDA) is a useful tool in complex decision-making situations and has been used in medical fields to evaluate treatment options and drug selection. We aimed to provide valuable insights on the use of MCDA in health care through examining the research focus of existing studies, major fields, major applications, most productive authors and countries, and most common journals in the domain using a scientometric and bibliometric analysis.MethodsPublications related to MCDA in health care were identified by searching the Web of Science Core Collection on 14 July 2021. Three bibliometric software programs (VOSviewer, Bibliometrix, and CiteSpace) were used to conduct the analysis.ResultsA total of 410 publications were identified from 196 academic journals (average yearly growth rate of 32% from 1999 to 2021), with 23,637 co-cited references by 871 institutions from 70 countries or regions. The USA was the most productive country (n=80), while the Universiti Pendidikan Sultan Idris (n=16), Université de Montréal (n= 13), and Syreon Research Institute (n=12) were the most productive institutions. The biggest nodes in every cluster of author networks were Aos Alaa Zaidan, Mireille Goetghebeur, and Zoltan Kalo. The top journals in terms of number of articles (n=17) and citations (n=1,673) were Value in Health and the Journal of Medical Systems, respectively. The research hotspots mainly included the analytic hierarchy process (AHP), decision-making, health technology assessment, and healthcare waste management. In the recent literature there was more emphasis on coronavirus disease 2019 (COVID-19) and fuzzy Technique for Order Preference by Similarities to Ideal Solution (TOPSIS). Big data, telemedicine, TOPSIS, and the fuzzy AHP, which are well-developed and important themes, may be the trends in future research.ConclusionsThis study provides a holistic picture of the MCDA-related literature published in health care. MCDA has a broad application in different topic areas and would be helpful for practitioners, researchers, and decision makers working in health care when faced with complex decisions. It can be argued that the door is still open for improving the role of MCDA in health care, both in its technologies and its application.

Effectiveness of Lianhua Qingwen Capsule in Treatment of Asymptomatic COVID-19 Patients: A Randomized, Controlled Multicenter Trial.

Background: Asymptomatic patients are unneglected sources in propagating transmission chain due to their high viral loads. However, treatments available based on symptoms seem not applicable to asymptomatic patients. In this study, the authors want to estimate the effectiveness of Lianhua Qingwen (LH) capsule on asymptomatic coronavirus disease 2019 (COVID-19) patients. Methods: A randomized controlled trial (RCT) was performed to explore the effectiveness and safety of LH capsule in treating asymptomatic COVID-19 patients. Patients were randomized to control group (isolated observation) and treatment group (LH, 4 capsules, thrice daily) for 14 days. The primary endpoints were the rate and time of nucleic acid turning negative during the isolation observation. Results: A total of 120 participants were included in the full analysis set (60 each in the control and treatment groups). Data showed that the rate of nucleic acid turning negative during the isolation observation in the treatment group was higher than that in the control group (rate difference: 21.66%, 95% confidence interval [CI]: 4.34 to 37.27, p = 0.0142). Patients in the treatment group have a shorter time of nucleic acid turning negative (7.5 vs. 14.5 days, p = 0.018). Moreover, the rate of clinical symptoms appearance in the treatment group was lower compared with that in the control group (rate difference: -31.67, 95% CI: -46.83 to -13.82, p = 0.0005). The proportion of confirmed mild and common cases in the treatment group was also lower (35.00% vs. 66.67%, p = 0.0005). No serious adverse events were documented. Conclusions: In this study, the authors illustrated that LH capsule is beneficial to asymptomatic COVID-19 patients. Considering the lack of interventions for treating asymptomatic COVID-19 patients at this stage, LH capsule could be considered as a choice. Chinese Clinical Trial Registry: ChiCTR2100042066.

Knowledge Mapping of Multicriteria Decision Analysis in Healthcare: A Bibliometric Analysis.

Objective: Multicriteria decision analysis (MCDA) is a useful tool in complex decision-making situations, and has been used in medical fields to evaluate treatment options and drug selection. This study aims to provide valuable insights into MCDA in healthcare through examining the research focus of existing studies, major fields, major applications, most productive authors and countries, and most common journals in the domain. Methods: A bibliometric analysis was conducted on the publication related to MCDA in healthcare from the Web of Science Core Collection (WoSCC) database on 14 July 2021. Three bibliometric software (VOSviewer, R-bibliometrix, and CiteSpace) were used to conduct the analysis including years, countries, institutes, authors, journals, co-citation references, and keywords. Results: A total of 410 publications were identified with an average yearly growth rate of 32% (1999-2021), from 196 academic journals with 23,637 co-citation references by 871 institutions from 70 countries/regions. The United States was the most productive country (n = 80). Universiti Pendidikan Sultan Idris (n = 16), Université de Montréal (n = 13), and Syreon Research Institute (n = 12) were the top productive institutions. A A Zaidan, Mireille Goetghebeur and Zoltan Kalo were the biggest nodes in every cluster of authors' networks. The top journals in terms of the number of articles (n = 17) and citations (n = 1,673) were Value in Health and Journal of Medical Systems, respectively. The extant literature has focused on four aspects, including the analytic hierarchy process (AHP), decision-making, health technology assessment, and healthcare waste management. COVID-19 and fuzzy TOPSIS received careful attention from MCDA applications recently. MCDA in big data, telemedicine, TOPSIS, and fuzzy AHP is well-developed and an important theme, which may be the trend in future research. Conclusion: This study uncovers a holistic picture of the performance of MCDA-related literature published in healthcare. MCDA has a broad application on different topics and would be helpful for practitioners, researchers, and decision-makers working in healthcare to advance the wheel of medical complex decision-making. It can be argued that the door is still open for improving the role of MCDA in healthcare, whether in its methodology (e.g., fuzzy TOPSIS) or application (e.g., telemedicine).

Access to Epidemic Information and Life Satisfaction under the Period of COVID-19: the Mediating Role of Perceived Stress and the Moderating Role of Friendship Quality.

The present study mainly focused on college students amidst the COVID-19 outbreak and aimed to develop and examine a moderated mediation model between access to epidemic information and life satisfaction. Friendship quality as a moderator, and perceived stress as a mediator. A sample of 1032 college students participated in this study and completed questionnaires regarding access to epidemic information, perceived stress, friendship quality, and life satisfaction. Findings indicated that 1) access to epidemic information was strongly related to life satisfaction; 2) perceived stress acts as a mediator in the positive relationship between access to epidemic information and life satisfaction; 3) friendship quality moderated the relationship between access to epidemic information and perceived stress as well as perceived stress and life satisfaction, and such that there was a stronger association between access to epidemic information and perceived stress for college students with high friendship quality. But the relationship between perceived stress and life satisfaction became weaker for college students with high friendship quality. The results illuminate the mechanism to theoretical and practical implications for improving college students' life satisfaction during the pandemic.

Bacillus Calmette-Guérin-induced trained immunity protects against SARS-CoV-2 challenge in K18-hACE2 mice.

SARS-CoV-2 has been confirmed in over 450 million confirmed cases since 2019. Although several vaccines have been certified by the WHO and people are being vaccinated on a global scale, it has been reported that multiple SARS-CoV-2 variants can escape neutralization by antibodies, resulting in vaccine breakthrough infections. Bacillus Calmette-Guérin (BCG) is known to induce heterologous protection based on trained immune responses. Here, we investigated whether BCG-induced trained immunity protected against SARS-CoV-2 in the K18-hACE2 mouse model. Our data demonstrate that i.v. BCG (BCG-i.v.) vaccination induces robust trained innate immune responses and provides protection against WT SARS-CoV-2, as well as the B.1.617.1 and B.1.617.2 variants. Further studies suggest that myeloid cell differentiation and activation of the glycolysis pathway are associated with BCG-induced training immunity in K18-hACE2 mice. Overall, our study provides the experimental evidence that establishes a causal relationship between BCG-i.v. vaccination and protection against SARS-CoV-2 challenge.

Retrospective analysis of laboratory data from 19,275 hair samples submitted for drug abuse/misuse analysis from February 2019 to June 2021.

Drug abuse/misuse is now a major global problem affecting public health as well as economic and social stability. This study presents a retrospective view of the prevalence of drugs in hair. Reasons for hair testing include the need for law enforcement to test suspicious individuals and the need for employers in specific industries to test their employees. Toxicology analysis results were reviewed for a total of 19,275 hair samples requested for drug abuse/misuse analysis at the Academy of Forensic Science over 29 months from February 2019 to June 2021. Drugs and their metabolites in hair samples were analyzed by liquid chromatography - tandem mass spectrometry. In the study, the 19,275 hair samples were screened for a total of 62 illegal drugs, which were divided into three categories: illegal-drugs (I), medication (II), and new psychoactive substances (III). These three categories contain 11, 29 and 22 drugs respectively. In these hair samples, 4852 (25.2 %) tested positive for one or more drugs. Among them, the positive rate of category I was the highest (48.7 %), followed by category II (28.5 %), and category III (22.7 %). Over all, the positive rate of male users (26.2 %) was higher than that of female users (23.7 %), and most of them were young people (25-44 years old). Illegal-drugs (morphine, etc.) had the highest positive rate. Under the influence of some certain factors, the drug abuse situation will also undergo corresponding changes. The results can provide a scientific knowledge database which can help in the prevention of drug abuse.

Appropriateness of Antibiotic Prescriptions in Chinese Primary Health Care and the Impact of the COVID-19 Pandemic: A Typically Descriptive and Longitudinal Database Study in Yinchuan City.

Background: The appropriateness of antibiotic prescriptions in primary care has not been well evaluated in China in recent years. Furthermore, the impact of coronavirus disease 2019 (COVID-19) on antibiotic prescriptions has not yet been investigated in China. We aimed to assess the appropriateness of antibiotic prescriptions and to evaluate the potential association between the COVID-19 pandemic and antibiotic prescriptions in primary care settings of Yinchuan, a city in China. Methods: This study included 155 primary care institutions and 10,192,713 outpatient visits. Outpatient prescriptions were classified as appropriate, potentially appropriate, inappropriate, or not linked to any diagnosis for antibiotic use following a validated evaluation scheme. Interrupted time-series analyses were performed to assess the effects of the COVID-19 pandemic on antibiotic prescriptions in Chinese primary care facilities. Results: During the study period, 1,287,678 (12.6%, 95% confidence interval [12.6-12.7]) of 10,192,713 outpatient visits in primary care resulted in antibiotic prescriptions. Among 1,287,678 antibiotic prescriptions, 653,335 (50.7% [50.6-50.9]) were inappropriate, 463,081 (36.0% [35.8-36.1]) were potentially appropriate, 171,056 (13.3% [13.1-13.5]) were appropriate, and 206 could not be linked to any diagnosis. Furthermore, patient, physician, and institutional factors were associated with inappropriate antibiotic prescriptions; there was an overall decreasing trend in the proportions of inappropriate antibiotic prescriptions, with the highest level in 2017 (67.1% [66.8-67.5]) and the lowest in 2021 (40.8% [40.3-41.3]). A total of 1,416,120 individual antibiotics were prescribed, of which 1,087,630 (76.8%) were broad-spectrum and 777,672 (54.9%) were classified in the World Health Organization's "Watch" category. In addition, the COVID-19 pandemic was associated with changes of -2.8% (-4.4 to -1.3) in the level and 0.3% (0.2-0.3) in the monthly trend of antibiotic prescription rates, as well as changes of -5.9% (-10.2 to -1.5) in the level and 1.3% (1.0-1.6) in the monthly trend of the proportions of inappropriate antibiotic prescriptions. Conclusion: More than half of the antibiotic prescriptions were inappropriate during the study period in primary care in Yinchuan. The COVID-19 pandemic may be associated with a decrease in the overall and inappropriate use of antibiotics in primary care settings in China.

Computation of Antigenicity Predicts SARS-CoV-2 Vaccine Breakthrough Variants.

It has been reported that multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) including Alpha, Beta, Gamma, and Delta can reduce neutralization by antibodies, resulting in vaccine breakthrough infections. Virus-antiserum neutralization assays are typically performed to monitor potential vaccine breakthrough strains. However, experiment-based methods took several weeks whether newly emerging variants can break through current vaccines or therapeutic antibodies. To address this, we sought to establish a computational model to predict the antigenicity of SARS-CoV-2 variants by sequence alone. In this study, we firstly identified the relationship between the antigenic difference transformed from the amino acid sequence and the antigenic distance from the neutralization titers. Based on this correlation, we obtained a computational model for the receptor-binding domain (RBD) of the spike protein to predict the fold decrease in virus-antiserum neutralization titers with high accuracy (~0.79). Our predicted results were comparable to experimental neutralization titers of variants, including Alpha, Beta, Delta, Gamma, Epsilon, Iota, Kappa, and Lambda, as well as SARS-CoV. Here, we predicted the fold of decrease of Omicron as 17.4-fold less susceptible to neutralization. We visualized all 1,521 SARS-CoV-2 lineages to indicate variants including Mu, B.1.630, B.1.633, B.1.649, and C.1.2, which can induce vaccine breakthrough infections in addition to reported VOCs Beta, Gamma, Delta, and Omicron. Our study offers a quick approach to predict the antigenicity of SARS-CoV-2 variants as soon as they emerge. Furthermore, this approach can facilitate future vaccine updates to cover all major variants. An online version can be accessed at http://jdlab.online.

Dynamics and Decoupling Analysis of Carbon Emissions from Construction Industry in China

The construction industry is the backbone of most countries, but its carbon emissions are huge and growing rapidly, constraining the achievement of global carbon-peaking and carbon-neutrality goals. China’s carbon emissions are the highest in the world, and the construction industry is the largest contributor. Due to significant differences between provinces in pressure, potential, and motivation to reduce emissions, the “one-size-fits-all”emission reduction policy has failed to achieve the desired results. This paper empirically investigates the spatial and temporal evolution of carbon emissions in China’s construction industry and their decoupling relationship with economic growth relying on GIS tools and decoupling model in an attempt to provide a basis for the formulation of differentiated construction emission reduction policies and plans in China. The study shows that, firstly, the changes in carbon emissions and carbon intensity in the provincial construction industry are becoming increasingly complex, with a variety of types emerging, such as declining, “inverted U-shaped”, growing, “U-shaped”, and smooth fluctuating patterns. Secondly, the coefficient of variation is higher than 0.65 for a long time, indicating high spatial heterogeneity. However, spatial agglomeration and correlation are low, with only a few cluster-like agglomerations formed in the Pearl River Delta, Yangtze River Delta, Bohai Bay, Northeast China, and Loess and Yunnan–Guizhou Plateau regions. Thirdly, most provinces have not reached peak carbon emissions from the construction industry, with 25% having reached peak and being in the plateau stage, respectively. Fourthly, the decoupling relationship between carbon emissions from the construction industry and economic growth, as well as their changes, is increasingly diversified, and most provinces are in a strong and weak decoupling state. Moreover, a growing number of provinces that have achieved decoupling are moving backward to re-coupling, due to the impact of economic transformation and the outbreaks of COVID-19, with the degraded regions increasingly concentrated in the northeast and northwest. Fifthly, we classify China’s 30 provinces into Leader, Intermediate, and Laggard policy zones and further propose differentiated response strategies. In conclusion, studying the trends and patterns of carbon-emission changes in the construction industry in different regions, revealing their spatial differentiation and correlation, and developing a classification management strategy for low carbonized development of the construction industry help significantly improve the reliability, efficiency, and self-adaptability of policy design and implementation.

In-Silico Analysis of Monoclonal Antibodies against SARS-CoV-2 Omicron.

Omicron was designated by the WHO as a VOC on 26 November 2021, only 4 days after its sequence was first submitted. However, the impact of Omicron on current antibodies and vaccines remains unknown and evaluations are still a few weeks away. We analysed the mutations in the Omicron variant against epitopes. In our database, 132 epitopes of the 120 antibodies are classified into five groups, namely NTD, RBD-1, RBD-2, RBD-3, and RBD-4. The Omicron mutations impact all epitopes in NTD, RBD-1, RBD-2, and RBD-3, with no antibody epitopes spared by these mutations. Only four out of 120 antibodies may confer full resistance to mutations in the Omicron spike, since all antibodies in these three groups contain one or more epitopes that are affected by these mutations. Of all antibodies under EUA, the neutralisation potential of Etesevimab, Bamlanivimab, Casirivimab, Imdevima, Cilgavimab, Tixagevimab, Sotrovimab, and Regdanvimab might be dampened to varying degrees. Our analysis suggests the impact of Omicron on current therapeutic antibodies by the Omicron spike mutations may also apply to current COVID-19 vaccines.

Efficacy and Safety of Lianhua Qingke Tablets in the Treatment of Mild and Common-Type COVID-19: A Randomized, Controlled, Multicenter Clinical Study.

BACKGROUND: Lianhua Qingke (LH) tablets is an effective traditional Chinese medicine against various viral infections, especially in relieving coughing. However, its effects on COVID-19 are unknown. METHODS: To examine the therapeutic effectiveness of LH tablets in COVID-19 patients with mild and common types, a randomized, multicenter, controlled study was carried out. COVID-19 cases were randomized to undergo routine treatment with or without LH tablets (4 tablets, three times a day) for 14 days. The primary endpoints were the rate of achieving clinical symptom resolution and the corresponding time. RESULTS: There were 144 participants in the full analysis set (72 each in the LH and control groups). The LH group participants had elevated symptom alleviation rate at 14 days compared with control cases (FAS: 98.61% vs. 84.72%, p = 0.0026). In comparison with control group participants, the LH group participants had reduced median time to clinical symptom alleviation (median: 4 vs. 7 days, p < 0.0001). Higher resolution rates of coughing (98.44% vs. 84.51%, p = 0.0045) and expectoration (100% vs. 82.35%, p = 0.0268) were observed in the LH group. Times to recovery of fever (median: 2 vs. 3 days, p = 0.0007), coughing (median: 4 vs. 7 days, p < 0.0001), and expectoration (median: 3 vs. 6 days, p < 0.0001) were also notably shorter in the LH group. Moreover, the LH group had elevated improvement rates in chest computed tomography signs (FAS: 86.11% vs. 72.22%, p = 0.0402) and clinical cure at day 28 (FAS: 83.33% vs. 68.06%, p = 0.0326). However, no differences were found in the laboratory test and viral assay. Serious adverse events were not detected. CONCLUSION: These preliminary findings indicate LH tablets may be effective in symptomatic COVID-19, especially in relieving coughing. This trial was registered in Chinese Clinical Trial Registry (ChiCTR2100042069).

Family Cohesion and Sleep Disturbances During COVID-19: the Mediating Roles of Security and Stress.

Despite the increase in proximity to one's family amid university closures during the COVID-19 pandemic, the mechanisms underlying how family cohesion influenced students' sleep remain understudied. Using a large sample of college students in China (N = 1,178) during the COVID-19 pandemic, the current study examined the serial mediating roles of sense of security and perceived stress on the effect of family cohesion on sleep disturbance. Generalized linear modeling serial mediation analysis with 1,000 resampled bootstrapping methods showed that sense of security and perceived stress were negatively and positively associated with sleep disturbance, respectively. Furthermore, sense of security and perceived stress fully mediated the indirect effect of family cohesion on sleep disturbances. Implications and conclusions are discussed.