Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 5 de 5
Filter
1.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-313350

ABSTRACT

Background: Bedside lung ultrasound (LUS) has emerged as a useful and non-invasive tool to detect lung involvement and monitor changes in patients with coronavirus disease 2019(COVID-19). While the clinical significance of LUS-score in patients with COVID-19 remains unknown. We aimed to investigate the prognostic value of LUS-score in patients with COVID-19.MethodsLUS protocol consisted of 12 scanning zones and was performed in 280 consecutive patients with COVID-19. LUS-score based on B-lines, pleural line abnormalities and lung consolidation was evaluated. The primary outcome was a combination of severe acute respiratory distress syndrome (ARDS), and mortality.ResultsCompared with patients in the lowest LUS-score group, those in the highest LUS-score group were more likely to have a lower lymphocyte%, higher levels of D-dimer, C-reactive protein, hypersensitive troponin I and creatine kinase muscle-brain, more invasive mechanical ventilation therapy, higher incidence of ARDS, and higher mortality. After a median follow-up of 14 days, 37 patients progressed to the poor outcome. Compared with event-free survivors, patients with adverse event presented higher rate of bilateral involved, more involved zones and B-lines, pleural lines abnormalities and consolidation, and higher LUS-score. The Cox models adding LUS-score as a continuous variable (hazard ratio [HR]: 1.05, 95% confidence intervals [CI]: 1.02~1.08;P < 0.001;Akaike Information Criterion [AIC] =272;C-index = 0.903) or as a categorical variable (HR: 10.76, 95% CI: 2.75~42.05;P = 0.001;AIC =272;C-index = 0.902) were found to predict poor outcome more accurately than the basic model (AIC =286;C-index = 0.866). LUS-score cutoff >12 would predict adverse events with specificity and sensitivity of 90.5% and 91.9%, respectively.ConclusionsLUS-score is a powerful predictor of adverse events in patients with COVID-19, and is important for risk stratification in COVID-19 patients.

2.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-313349

ABSTRACT

Background: Bedside lung ultrasound (LUS) has emerged as a useful and noninvasive tool to detect lung involvement and monitor changes in patients with coronavirus disease 2019 (COVID-19). However, the clinical significance of the LUS score in patients with COVID-19 remains unknown. We aimed to investigate the prognostic value of the LUS score in patients with COVID-19. Methods: : The LUS protocol consisted of 12 scanning zones and was performed in 280 consecutive patients with COVID-19. The LUS score based on B-lines, lung consolidation and pleural line abnormalities was evaluated. Results: : The median time from admission to LUS examinations was 7 days (interquartile range [IQR] 3-10). Patients in the highest LUS score group were more likely to have a lower lymphocyte percentage (LYM%);higher levels of D-dimer, C-reactive protein, hypersensitive troponin I and creatine kinase muscle-brain;more invasive mechanical ventilation therapy;higher incidence of ARDS;and higher mortality than patients in the lowest LUS score group. After a median follow-up of 14 days [IQR, 10-20 days], 37 patients developed ARDS, and 13 died. Patients with adverse outcomes presented a higher rate of bilateral involvement;more involved zones and B-lines, pleural line abnormalities and consolidation;and a higher LUS score than event-free survivors. The Cox models adding the LUS score as a continuous variable (hazard ratio [HR]: 1.05, 95% confidence intervals [CI]: 1.02~1.08;P < 0.001;Akaike Information Criterion [AIC] =272;C-index = 0.903) or as a categorical variable (HR: 10.76, 95% CI: 2.75~42.05;P = 0.001;AIC =272;C-index = 0.902) were found to predict poor outcomes more accurately than the basic model (AIC =286;C-index = 0.866). An LUS score cut-off >12 predicted adverse outcomes with a specificity and sensitivity of 90.5% and 91.9%, respectively. Conclusions: : The LUS score devised by our group performs well at predicting adverse outcomes in patients with COVID-19 and is important for risk stratification in COVID-19 patients.

3.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-312504

ABSTRACT

The COVID-19 pandemic is the most serious catastrophe since the Second World War. To more accurately observe the epidemic under the influence of policies and provide policy adjustments before the official presidential transition in the United States, we use a three-layer superimposed Long-Short-Term-Memory (LSTM) model to predict the epidemic development trend to mid-January, 2021. The proposed model provides more accuracy and stability relative to Susceptible-Exposed-Infective-Recovered (SEIR), modified stacked au-to-encoder, and single-layer LSTM models. The performance effects of the measures in China and five countries with severe epidemics are analysed and summarised. The model shows that the error rate of China, five countries and the world is less than 1.4%. According to forecasts, the epidemic situations in the United States, India, and Brazil, caused by untimely, inappropriate policies, lax regulations and insufficient public cooperation, remain very severe, with cases continuing to increase by tens of thousands. The number of cumulative confirmed cases worldwide will exceed 84.58 million by mid-January, 2021;however, the mortality rate will gradually decrease. Based on analysis of measures (including China’s effective prevention and control policies), we found that there are performed tremendous different efficiency even using same positive policy for different countries because of various cooperation between people and governments. It is essential to maintain self-protection to prevent the epidemic from deterioration or regenerating, especially, wearing mask and maintaining a safe distance.

4.
Proc Natl Acad Sci U S A ; 118(38)2021 09 21.
Article in English | MEDLINE | ID: covidwho-1397979

ABSTRACT

Global containment of COVID-19 still requires accessible and affordable vaccines for low- and middle-income countries (LMICs). Recently approved vaccines provide needed interventions, albeit at prices that may limit their global access. Subunit vaccines based on recombinant proteins are suited for large-volume microbial manufacturing to yield billions of doses annually, minimizing their manufacturing cost. These types of vaccines are well-established, proven interventions with multiple safe and efficacious commercial examples. Many vaccine candidates of this type for SARS-CoV-2 rely on sequences containing the receptor-binding domain (RBD), which mediates viral entry to cells via ACE2. Here we report an engineered sequence variant of RBD that exhibits high-yield manufacturability, high-affinity binding to ACE2, and enhanced immunogenicity after a single dose in mice compared to the Wuhan-Hu-1 variant used in current vaccines. Antibodies raised against the engineered protein exhibited heterotypic binding to the RBD from two recently reported SARS-CoV-2 variants of concern (501Y.V1/V2). Presentation of the engineered RBD on a designed virus-like particle (VLP) also reduced weight loss in hamsters upon viral challenge.


Subject(s)
COVID-19 Vaccines/immunology , COVID-19/prevention & control , Protein Engineering/methods , SARS-CoV-2/metabolism , Spike Glycoprotein, Coronavirus/genetics , Animals , Antibodies, Viral/immunology , Antigens, Viral , Binding Sites , COVID-19/virology , COVID-19 Vaccines/economics , Humans , Immunogenicity, Vaccine , Mice , Mice, Inbred BALB C , Models, Molecular , Protein Binding , Protein Conformation , Saccharomycetales/metabolism , Vaccines, Subunit
5.
British Journal of Educational Technology ; : 1, 2021.
Article in English | Academic Search Complete | ID: covidwho-1276547

ABSTRACT

This research consisted of two studies to investigate how the Chinese rural educational system supported students' online learning and to determine the factors that influenced students' online learning quality (satisfaction and cognitive and social presence) during the COVID‐19 pandemic. Study 1, based on interviews with three curriculum officers, seven principals and 30 course teachers, found that great efforts were made to realize digital equity and education for all students. The necessity of providing resources and support to teachers and students (facilitating conditions) was recognized, along with the importance of teachers' online course design and organization and the facilitation of discourse (teaching presence and social presence). Based on the findings of Study 1 and the literature review, a conceptual model of facilitating conditions and teaching presence reported to influence students' online learning quality was generated. In Study 2, 1,409 students from three rural primary schools were surveyed to test the conceptual model. The results indicated that facilitating conditions influenced students' online learning quality through enhanced technology self‐efficacy and perceived usefulness. Teaching presence directly and positively predicted students' online learning quality. This research highlights the importance of creating a learning community and providing technology access and support to ensure online learning opportunities and quality for rural students. Practitioner notes What is already known about this topic Chinese students from rural or migrant schools have fewer opportunities to access computers and the Internet, lower frequencies of online activity and technology self‐efficacy and less training and parental and teacher support. Providing support and resources to encourage and facilitate technology use among teachers and students in rural and underdeveloped schools is of great importance. Identifying the factors that contribute to online learning quality among rural school students to tackle the transition to online learning is necessary. What this paper adds The rural government and schools have made great efforts to ensure digital equity and education for all students, despite family conditions. Facilitating purposeful interactions and providing timely feedback is critical for effective learning in online teaching. Facilitating conditions represented by available support and resources and teaching presence influence students' online learning quality in rural areas. Implications for practice and/or policy Providing digital equipment and resources to all students is the first step towards distance learning. Providing opportunities to improve teachers' digital competency is critical for providing quality online instruction. Providing students timely assistance and useful and learner‐friendly technologies to enhance their satisfaction and social and cognitive presence is necessary. Online instructors should create a friendly online learning environment, facilitate active discussion and purposeful reflection and create opportunities to promote students' open communication, group cohesion and meaning construction. What is already known about this topic Chinese students from rural or migrant schools have fewer opportunities to access computers and the Internet, lower frequencies of online activity and technology self‐efficacy and less training and parental and teacher support. Providing support and resources to encourage and facilitate technology use among teachers and students in rural and underdeveloped schools is of great importance. Identifying the factors that contribute to online learning quality among rural school students to tackle the transition to online learning is necessary. What this paper adds The rural government and schools have made great efforts to ensure digital equity and education for all students, despite family conditions. Facilitating purposeful interactions and providing timely feedback is critical for effective learning in online teaching. Facilitating onditions rep esented by available support and resources and teaching presence influence students' online learning quality in rural areas. Implications for practice and/or policy Providing digital equipment and resources to all students is the first step towards distance learning. Providing opportunities to improve teachers' digital competency is critical for providing quality online instruction. Providing students timely assistance and useful and learner‐friendly technologies to enhance their satisfaction and social and cognitive presence is necessary. Online instructors should create a friendly online learning environment, facilitate active discussion and purposeful reflection and create opportunities to promote students' open communication, group cohesion and meaning construction. [ABSTRACT FROM AUTHOR] Copyright of British Journal of Educational Technology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

SELECTION OF CITATIONS
SEARCH DETAIL