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COVID-19 is a severe acute respiratory syndrome caused by a novel coronavirus, SARS-CoV- 2.COVID-19 is now a pandemic, and is not yet fully under control.As the surface spike protein (S) mediates the recognition between the virus and cell membrane and the process of cell entry, it plays an important role in the course of disease transmission.The study on the S protein not only elucidates the structure and function of virus-related proteins and explains their cellular entry mechanism, but also provides valuable information for the prevention, diagnosis and treatment of COVII)-19.Concentrated on the S protein of SARS-CoV-2, this review covers four aspects: (1 ) The structure of the S protein and its binding with angiotensin converting enzyme II (ACE2) , the specific receptor of SARS-CoV-2, is introduced in detail.Compared with SARS-CoV, the receptor binding domain (RBD) of the SARS-CoV- 2 S protein has a higher affinity with ACE2, while the affinity of the entire S protein is on the contrary.(2) Currently, the cell entry mechanism of SARS-CoV-2 meditated by the S protein is proposed to include endosomal and non-endosomal pathways.With the recognition and binding between the S protein and ACE2 or after cell entry, transmembrane protease serine 2(TMPRSS2) , lysosomal cathepsin or the furin enzyme can cleave S protein at S1/S2 cleavage site, facilitating the fusion between the virus and target membrane.(3) For the progress in SARS-CoV-2 S protein antibodies, a collection of significant antibodies are introduced and compared in the fields of the target, source and type.(4) Mechanisms of therapeutic treatments for SARS-CoV-2 varied.Though the antibody and medicine treatments related to the SARS-CoV-2 S protein are of high specificity and great efficacy, the mechanism, safety, applicability and stability of some agents are still unclear and need further assessment.Therefore, to curb the pandemic, researchers in all fields need more cooperation in the development of SARS-CoV-2 antibodies and medicines to face the great challenge.Copyright © Palaeogeography (Chinese Edition).All right reserved.
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Aim To explore the myocardial damage, abnormal electrocardiogram characteristics of patients infected with SARS-CoV-2 Omicron variant in Zhuhai. Methods 84 patients with SARS-CoV-2 Omicron variant (Omicron variant group) admitted to the Fifth Affiliated Hospital of Sun Yat-sen University from January 13 to March 20, 2022 were included, and 88 patients with non SARS-CoV-2 Omicron variant (non-Omicron variant group) from January 17 to February 17, 2020 were included. A retrospective study was conducted to compare myocardial damage, abnormal electrocardiogram and clinical characteristics between the two groups. Results The mean age of patients in Omicron variant group was smaller than that in non-Omicron variant group [(36. 6±15. 6) years vs. (49. 8±14. 3) years, P<0. 01], and the proportion of patients with body temperature, systolic blood pressure and fever at admission was lower than that of non-Omicron variant group (P<0. 05). The neutrophil / lymphocyte ratio [(2. 93 (3. 03, 5. 81) vs. 7. 06 (2. 32, 11. 27), P<0. 001], interleukin-2 (IL-2) and interleukin-6 (IL-6) levels in Omicron variant group were significantly lower than those in non-Omicron variant group (P<0. 01). Cardiac troponin I (cTnI) was negative in Omicron variant group, and the concentrations of cTnI, creatine kinase-MB isozyme (CK-MB) and N-terminal pro-brain natriuretic peptide (NT-proB-NP) and the proportion of patients with elevated levels were significantly lower than those of non-Omicron variant group (P<0. 01). The incidence of abnormal electrocardiogram in Omicron variant group was also significantly lower than that in non-Omicron variant group (25. 0% vs. 42. 0%, P = 0. 001), sinus tachycardia, atrial premature beats and T wave changes were the main symptoms. Atrial premature beats, T wave changes, ST segment depression and bundle branch block were the main symptoms in non-Omicron variant group. Conclusions The patients infected with SARS-CoV-2 Omicron variant in Zhuhai may not have obvious myocardial damage because most of the patients have been vaccinated with COVID-19 vaccine. The incidence of abnormal electrocardiogram is also significantly lower than that of non-Omicron variant group, mainly sinus tachycardia, atrial premature beats and T wave changes. © 2022, Editorial Office of Chinese Journal of Arteriosclerosis. All rights reserved.
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Objectives: Various interventions were used to control the COVID-19 pandemic and protect population health, including vaccination, medication and nonpharmaceutical interventions (NPIs). This study aims to examine the cost-effectiveness of different combinations of NPIs (including social distancing, mask wearing, tracing-testing-isolation, mass testing, and lockdown), oral medicine (Paxlovid), and vaccination (including two-dose and three-dose vaccination) under the Delta and Omicron pandemic in China. Method(s): We constructed a Markov model using a SIRI structure with a one-week cycle length over one-year time horizon to estimate the cost-effectiveness of different combinations in China from societal perspective. Effectiveness of interventions, disease transition probabilities and costs were from published data, quality-adjusted life years (QALYs) gained and incremental cost-effectiveness ratios (ICER) and net monetary benefits were calculated for one-year time horizon. One-way and probabilistic sensitivity analyses were performed to test the robustness of the model. Scenario analysis was developed to examine different situations under the Omicron pandemic. Result(s): Under the Delta pandemic, implementing the combination of social distancing, mask wearing, mass testing and three-dose vaccination was the optimal strategy, with cost at $11165635.33 and utility of 94309.94 QALYs, and had 60% probability of being cost-effective compared with other strategies. Three-dose vaccination combinations were better than two-dose combinations. Under the Omicron pandemic, antigen testing was better than nucleic testing by avoiding cross infections;second, adding Paxlovid or lockdown to the combined intervention strategies could increase limited health outcomes at huge cost and thus were not cost-effective;last, encouraging patients to stay at home can save societal costs compared with concentrated quarantine at hospitals. Conclusion(s): Three-dose vaccination and self-quarantine of asymptomatic and mild cases can save total costs. Under the Omicron pandemic outbreak, antigen testing is a better way to control the pandemic, and adding Paxlovid or lockdown to intervention combinations is not cost-effective.Copyright © 2023
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Doctor's effort of active stress coping is a key factor for keeping stability of healthcare system in the COVID pandemic. The Internet hospital breaks through the boundaries and expands external resources of the physical hospital, but brings doctors stress and challenges. However, it is not clear how Internet hospital innovation affects doctors' active stress coping effort. To address this question, based on conservation of resource theory (COR), we explore the issue and examine the model through a face-to-face situational investigation of 174 doctors from 66 Internet hospitals with complete online service functions in China. The results show that the personal characteristics and energy resources provided by platform-based hospital will promote doctors to actively respond to stress. The increase in object and condition resources will lead to doctors' avoidance of coping with stress in the short term, but help doctors to actively cope with stress in the long term. We extend the COR theory by considering platform-based feature of Internet hospital and suggest that hospital should continue to promote technological innovation for its long-term benefits. This study contributes to the growing literature on platform-based healthcare innovation and its non-economic benefits for healthcare professionals.
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To understand the influence of coronavirus disease control policies on changes in characteristics of particulate matter smaller than 2.5 μm (PM2.5), concentrations of various PM2.5 components in Jinan city before and after implementation of the epidemic control measures during the 2020 Spring Festival were studied using online monitoring data. Standardized multiple linear regression was used to analyze the contribution of meteorological factors to the variations in concentrations of PM2.5 components. After the epidemic control measures were implemented, the concentrations of PM2.5 components in the area decreased significantly, and the rate at which the daily average concentration was exceeded decreased by 24.8%. The concentrations of all PM2.5 components decreased to various degrees, with those of trace elements (TE), elemental carbon (EC), and nitrate (NO3−) having decreased significantly by 50.3%, 46.8%, and 31.5%, respectively. In terms of component proportions, those of TE and EC decreased after the epidemic control measures were initiated whereas those of ammonium (NH4+), organic matter (OM), sulfate (SO4 2− ), and mineral dust increased;the proportion of NO3 − changed slightly, and the total proportion of secondary ions SO4 2−, NO3−, and NH4 + increased by 14.3%. Comparison of the proportions of PM2.5 components showed that after the epidemic control measures were implemented, the proportions of NO3 − and EC in PM2.5 that cause a light pollution level decreased whereas those of OM, SO4 2−, and NH4 + increased. This indicated that people traveled less, motor vehicle emissions decreased, work at construction sites stopped, and NO3 − proportion was greatly reduced while epidemic control measures were in place. However, afterward, decrease in concentrations of PM2.5 components and increase in secondary transformation of volatile organic compounds led to an increase in OM concentration. Compared with those before the epidemic control measures were implemented, the NO2/SO2 and NO3– /SO4 2− ratios fell significantly, and their average values decreased by 30.0% and 14.0%, respectively, indicating that the contribution of mobile sources (e.g., automobile exhaust) to pollution had decreased during the epidemic control period. Under the influence of the control measures, the OC concentration also decreased for excellent, good, and mild pollution levels;however, the secondary organic carbon concentration increased, indicating that secondary conversions did not decrease under the epidemic control conditions. Standardized multiple linear regression analyses of meteorological factors showed that changes in the height of the boundary layer contributed the most (46.5%) to changes in concentrations of PM2.5 components before the epidemic control measures were implemented;afterward, humidity was the primary factor governing the increase in these concentrations. © 2022, The Science Press. All rights reserved.
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Recently, innovations in the Internet-of-Medical- Things (IoMT), information and communication technologies, and Machine Learning (ML) have enabled smart healthcare. Pooling medical data into a centralised storage system to train a robust ML model, on the other hand, poses privacy, ownership, and regulatory challenges. Federated Learning (FL) overcomes the prior problems with a centralised aggregator server and a shared global model. However, there are two technical challenges: FL members need to be motivated to contribute their time and effort, and the centralised FL server may not accurately aggregate the global model. Therefore, combining the blockchain and FL can overcome these issues and provide high-level security and privacy for smart healthcare in a decentralised fashion. This study integrates two emerging technologies, blockchain and FL, for healthcare. We describe how blockchain-based FL plays a fundamental role in improving competent healthcare, where edge nodes manage the blockchain to avoid a single point of failure, while IoMT devices employ FL to use dispersed clinical data fully. We discuss the benefits and limitations of combining both technologies based on a content analysis approach. We emphasise three main research streams based on a systematic analysis of blockchain-empowered (i) IoMT, (ii) Electronic Health Records (EHR) and Electronic Medical Records (EMR) management, and (iii) digital healthcare systems (internal consortium/secure alerting). In addition, we present a novel conceptual framework of blockchain-enabled FL for the digital healthcare environment. Finally, we highlight the challenges and future directions of combining blockchain and FL for healthcare applications. IEEE
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COVID-19 is the latest and most severe epidemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Besides the respiratory system, the effects of SARS-CoV-2 on central and peripheral nervous systems have been recognized by more and more people. Clinically, patients with COVID-19 have been reported from mild anosmia and hypoesthesia to acute necrotizing hemorrhagic encephalopathy and Guillain-Barre syndrome. In order to facilitate clinicians to recognize the nerve injury of COVID-19 patients and give timely treatment to these patients, this paper reviews the latest research progress on the possible pathways of nerve injury, clinical manifestations and pathogenesis of COVID-19 patients.Copyright © 2020 by the Chinese Medical Association.
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The2022Nobel Prize in Physiology or Medicine was awarded to Swedish biologist Svante Paabo forhis decisive contribution to paleoanthropogenomics and human origins.There are various theories about theorigin of human beings,and the current mainstream view is:out of the African doctrine.In other words,ancienthumans had about three times of migrations.The first time wasHomo erectus,the second was Neanderthals andDenisovans,and the third was the ancestors of modern humans.All migrated from Africa to Eurasia.Whilepioneering a new discipline,paleoanthropogenomics,Svante Paabo has been refining the"Out of Africa Theory".With the help of various biological techniques,he delved into the origin of human beings from the perspective ofgenomics and found that some genetic imprints from ancient humans were retained in our bodies.For example,the STAT2gene and TLR gene associated with immunity,the EPAS1gene that contributes to hypoxic respirationand the six genes of chromosome3are highly positively correlated with the incidence of COVID-19.Thisresearch means that we can go back to the root of certain diseases,rather than limiting our eyes to the genesthemselves,and exploring where a gene comes from will be a new way of studying diseases.We summarized hisinnovations in related biotechnology in the process of research,his exploration of ancient humans based onmitochondrial and nuclear genes and related results,and introduced some genes derived from ancient humans andtheir related information
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Nigella sativa is known for the safety profile, containing a wealth of useful antiviral compounds. The main protease (Mpro, 3CLpro) of severe acute respiratory syndrome 2 (SARS-CoV-2) is being considered as one of the most attractive viral target, processing the polyproteins during viral pathogenesis and replication. In the current investigation we analyzed the potency of active component, thymoquinone (TQ) of Nigella sativa against SARS-CoV-2 Mpro. The structures of TQ and Mpro was retrieved from PubChem (CID10281) and Protein Data Bank (PDB ID 6MO3) respectively. The Mpro and TQ were docked and the complex was subjected to molecular dynamic (MD) simulations for a period 50ns. Protein folding effect was analyzed using radius of gyration (Rg) while stability and flexibility was measured, using root means square deviations (RMSD) and root means square fluctuation (RMSF) respectively. The simulation results shows that TQ is exhibiting good binding activity against SARS-CoV-2 Mpro, interacting many residues, present in the active site (His41, Cys145) and also the Glu166, facilitating the pocket shape. Further, experimental approaches are needed to validate the role of TQ against virus infection. The TQ is interfering with pocket maintaining residues as well as active site of virus Mpro which may be used as a potential inhibitor against SARS-CoV-2 for better management of COVID-19.
Subject(s)
COVID-19 Drug Treatment , Nigella sativa , Benzoquinones , Coronavirus 3C Proteases , Cysteine Endopeptidases/chemistry , Cysteine Endopeptidases/metabolism , Nigella sativa/metabolism , SARS-CoV-2 , Viral Proteins/chemistry , Viral Proteins/metabolismABSTRACT
Our niche method independently estimates hourly commuter rail station-to-station origin-destination (OD) matrix data each day from ticket sales and activation data from four sales channels (paper/mobile tickets, mail order, and onboard sales) by extending well-established transportation modelling methodologies. This algorithm's features include: (1) handles multi pack pay-per-ride fare instruments not requiring electronic validation, like ten-trip paper tickets "punched" onboard by railroad conductors;(2) correctly infers directionality for direction-agnostic ticket-types;(3) estimates unlimited ride ticket utilization patterns sufficiently precisely to inform vehicle assignment/scheduling;(4) provides integer outputs without allowing rounding to affect control totals nor introduce artifacts;(5) deals gracefully with cliff-edge changes in demand, like the COVID19 related lockdown;and (6) allocates hourly traffic to each train-start based on passenger choice. Our core idea is that the time of ticket usage is ultimately a function of the time of sale and ticket type, and mutual transformation is made via probability density functions ("patterns") given sufficient distribution data. We generated pre-COVID daily OD matrices and will eventually extend this work to post-COVID inputs. Results were provided to operations planners using visual and tabular interfaces. These matrices represent data never previously available by any method;prior OD surveys required 100,000 respondents, and even then could neither provide daily nor hourly levels of detail, and could not monitor special event ridership nor specific seasonal travel such as summer Friday afternoons.
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To know the current status of family health and negative psychology of primary and secondary school students, and to explore the correlation between them during the prevention and control of COVlD-19. From January 1 5 to 30, in 2022, a total of 1 9 343 urban and rural primary and secondary school students in X city were selected. The short form of the family health scaee, center for epidemiologica survey-depression scaee and student burnout inventory for junior midde school students were used to conduct a cross-sectional survey. The Pearson correlation was used to analyze the relationship between the family health and negative psychology. The family health of primary and secondary school students is at the medium level or above, and more than half of students may/must be depressed. There are significant differences in study burnout n different learning stages and epidemic management in different places of residence. It is recommended that family members and schools staff should give more psychological and social secondary school students to reduce the negative impact of COVID-19 on them. © 2022, Editorial department of Chinese Medical Ethics. All rights reserved.
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Virtual reality (VR) is gaining popularity these days for a variety of reasons, the most prominent of which is the Covid-19 scenario. This article outlines a strategy for restoring people's lives and allowing them to work from home, as well as bringing people together on a common platform to cheer them up. At Chulalongkorn University, the work technique was used to create a virtual three-dimensional (3D) chemistry lab. Many tactics were adopted and carried out step by step to provide a genuine experience of the lab when creating a virtual lab. Using Unity, a cross-platform game engine, the 3D model was then used to create an immersive and interactive VR experience. The final output is an immersive and interactive virtual reality environment with information constructed using Unity. © 2022 IEEE.
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Commercial sharing services (CSSs) provide consumers with temporary access to products or services. Consumers can use CSSs to communicate an identity by renting products from specific brands. Applying the theory of the extended self, we proposed an attachment-based account of CSS usage. Across four studies, we found consistent evidence that consumers were less likely to rent the products of their strongly attached brands via CSSs because these brands were regarded as part of their extended selves, and thus sharing these products with others would contaminate the self. However, this effect was mitigated when consumers' psychological ownership of the shared product was augmented. Our findings reveal that psychological ownership can replace the role of actual ownership in the sharing context, rendering profound implications for understanding the relationships among self, brand, and product in sharing services.
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Nitrogen dioxide (NO2) is an important target for monitoring atmospheric quality. Deriving ground-level NO2 concentrations with much finer resolution, it requires high-resolution satellite tropospheric NO2 column as input and a reliable estimation algorithm. This paper aims to estimate the daily ground-level NO2 concentrations over China based on machine learning models and the TROPOMI NO2 data with high spatial resolution. In this study, four tree-based algorithm machine learning models, decision trees (DT), gradient boost decision tree (GBDT), random forest (RF) and extra-trees (ET), were used to estimate ground-level NO2 concentrations. In addition to considering many influencing factors of the ground-level NO2 concentrations, we especially introduced simplified temporal and spatial information into the estimation models. The results show that the extra-trees with spatial and temporal information (ST-ET) model has great performance in estimating ground-level NO2 concentrations with a cross-validation R-2 of 0.81 and RMSE of 3.45 mu g/m(3) in test datasets. The estimated results for 2019 based on the ST-ET model achieves a satisfactory accuracy with a cross-validation R-2 of 0.86 compared with the other models. Through time-space analysis and comparison, it was found that the estimated high-resolution results were consistent with the ground observed NO2 concentrations. Using data from January 2020 to test the prediction power of the models, the results indicate that the ST-ET model has a good performance in predicting ground-level NO2 concentrations. Taking four ground-level NO2 concentrations hotspots as examples, the estimated ground-level NO2 concentrations and ground-based observation data during the coronavirus disease (COVID-19) pandemic were lower compared with the same period in 2019. The findings offer a solid solution for accurately and efficiently estimating ground-level NO2 concentrations by using satellite observations, and provide useful information for improving our understanding of the regional atmospheric environment.
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With the increasing exhaustion of global resources, various countries have explored bioeconomy as an economic model that can cope with environmental, climate，resource problems and food security crisis. China recently released the " 14th Five-Year Plan for Bioeconomy Development", raising the bioeconomy to the level of national strategic development for the first time. Based on the innovation of life science and biotechnology, emerging industries have come into being in bioeconomy including biomedicine, bioagriculture, biomanufacturing and bioenergy. Bioeconomy is an economic development model with great potential for sustainable development in the future. This paper summarizes the evolution law of the global bioeconomy, the development of the bioeconomy worldwide and the industrial development of Chinese bioeconomy. Moreover, under the complex situation in a time of unprecedented global changes in a century and the COVID-19 epidemic, the relevant countermeasures to cope with challenges and suggestions on Chinese future are put forward. © 2022, China Biotechnology Press. All rights reserved.
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Corona virus disease 2019 is an acute infectious disease caused by SARS-CoV-2 infection and has entered the state of global pandemic. Spike protein ( S protein) , a key protein that mediates SARS-CoV-2 to infect host cells, has the characteristics of specific receptor binding and membrane fusion, playing an important role in host tropism and virulence. The spontaneous closed and open conformation of S protein trimer is crucial for receptor binding and initiation of conformational changes in membrane fusion, and its unique furin recognition site may be a crucial factor leading to high infectivity. Therefore, to study the structure and function of SARS-CoV-2 S protein and its receptor has important implications for invasion mechanisms of SARS- CoV-2 and the development of relevant targeted drugs.
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The rapid development of artificial intelligence techniques is significantly promoting the resolution of various important decision-making issues such as material distribution, generation line optimization scheduling, and path planning. Currently, SARS-CoV-2 is raging over the world, and it is valuable to propose a vaccine distribution strategy to utilize limited vaccine resources rationally. In this paper, we aim to propose an optimal vaccine distribution strategy based on deep reinforcement learning(DRL) approaches. An End-to-End vaccine distribution model is proposed by combining the Deep Reinforcement Learning model and LinUCB algorithm to get an optimistic strategy of allocation. Experiment results demonstrated that vaccine distribution strategies based on this model show a strong capacity to control the epidemic and ensure stable government revenue compared with baseline strategies. © 2021 IEEE.
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COVID-19 is a severe acute respiratory syndrome caused by a novel coronavirus, SARS-CoV- 2.COVID-19 is now a pandemic, and is not yet fully under control.As the surface spike protein (S) mediates the recognition between the virus and cell membrane and the process of cell entry, it plays an important role in the course of disease transmission.The study on the S protein not only elucidates the structure and function of virus-related proteins and explains their cellular entry mechanism, but also provides valuable information for the prevention, diagnosis and treatment of COVII)-19.Concentrated on the S protein of SARS-CoV-2, this review covers four aspects: (1 ) The structure of the S protein and its binding with angiotensin converting enzyme II (ACE2) , the specific receptor of SARS-CoV-2, is introduced in detail.Compared with SARS-CoV, the receptor binding domain (RBD) of the SARS-CoV- 2 S protein has a higher affinity with ACE2, while the affinity of the entire S protein is on the contrary.(2) Currently, the cell entry mechanism of SARS-CoV-2 meditated by the S protein is proposed to include endosomal and non-endosomal pathways.With the recognition and binding between the S protein and ACE2 or after cell entry, transmembrane protease serine 2(TMPRSS2) , lysosomal cathepsin or the furin enzyme can cleave S protein at S1/S2 cleavage site, facilitating the fusion between the virus and target membrane.(3) For the progress in SARS-CoV-2 S protein antibodies, a collection of significant antibodies are introduced and compared in the fields of the target, source and type.(4) Mechanisms of therapeutic treatments for SARS-CoV-2 varied.Though the antibody and medicine treatments related to the SARS-CoV-2 S protein are of high specificity and great efficacy, the mechanism, safety, applicability and stability of some agents are still unclear and need further assessment.Therefore, to curb the pandemic, researchers in all fields need more cooperation in the development of SARS-CoV-2 antibodies and medicines to face the great challenge. © Palaeogeography (Chinese Edition).All right reserved.
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Wuhan Tianhe International Airport (WUH) was suspended to contain the spread of COVID-19, while Shanghai Hongqiao International Airport (SHA) saw a tremendous flight reduction. Closure of a major international airport is extremely rare and thus represents a unique opportunity to straightforwardly observe the impact of airport emissions on local air quality. In this study, a series of statistical tools were applied to analyze the variations in air pollutant levels in the vicinity of WUH and SHA. The results of bivariate polar plots show that airport SHA and WUH are a major source of nitrogen oxides. NOx, NO2 and NO diminished by 55.8%, 44.1%, 76.9%, and 40.4%, 33.3% and 59.4% during the COVID-19 lockdown compared to those in the same period of 2018 and 2019, under a reduction in aircraft activities by 58.6% and 61.4%. The concentration of NO2, SO2 and PM2.5 decreased by 77.3%, 8.2%, 29.5%, right after the closure of airport WUH on 23 January 2020. The average concentrations of NO, NO2 and NOx scatter plots at downwind of SHA after the lockdown were 78.0%, 47.9%, 57.4% and 62.3%, 34.8%, 41.8% lower than those during the same period in 2018 and 2019. However, a significant increase in O3 levels by 50.0% and 25.9% at WUH and SHA was observed, respectively. These results evidently show decreased nitrogen oxides concentrations in the airport vicinity due to reduced aircraft activities, while amplified O3 pollution due to a lower titration by NO under strong reduction in NOx emissions. © 2022
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Background: To examine the outcomes heterogeneity of clinical trial protocols of coronavirus disease 2019 (COVID-19) to prioritize the establishment of a core outcome set. Methods: Databases of the International Committee of Medical Journal Editors - accepted clinical trial registry platforms were searched on February 14, 2020 and May 31, 2020. Randomized controlled trials and non-randomized controlled trials of COVID-19 were considered. Patient condition was classified as common, severe, or critical. Interventions included traditional Chinese medicine and Western medicine. We excluded trials that involved discharged patients, psychological intervention, and complications of COVID-19. The general information and outcomes, outcome measurement instruments, and measurement times were extracted. The results were analyzed by descriptive analysis. Results: In all, 19 registry platforms were searched. A total of 97 protocols were selected from among 160 protocols for the first search. For protocols of traditional Chinese medicine clinical trials, 76 outcomes from 16 outcome domains were reported, and almost half (34/76, 44.74%) of the outcomes were reported only once;the most frequently reported outcome was time taken for severe acute respiratory syndrome coronavirus 2 RNA to become negative. Twenty-seven (27/76, 35.53%) outcomes provided one or more outcome measurement instruments. Ten outcomes provided one or more measurement time frame. For protocols of Western medicine clinical trials, 126 outcomes from 17 outcome domains were reported;almost half (62/126, 49.21%) of the outcomes were reported only once;the most frequently reported outcome was proportion of patients with negative severe acute respiratory syndrome coronavirus 2. Twenty-seven outcomes provided one or more outcome measurement instruments. Forty (40/126, 31.75%) outcomes provided one or more measurement time frame. There were > 40 duplicated outcomes between the clinical trials protocols of traditional Chinese medicine and western medicine protocols. All of them were included in the Delphi survey when developing core outcome set for COVID-19. A total of 1,027 protocols were selected from 2,741 protocols for the second search. Forty-two new outcomes and 47 new outcome measurement instruments were reported. Conclusion: Outcome reporting in clinical trial protocols of COVID-19 is inconsistent. Thus, establishing a core outcome set is necessary for diagnosis and management.