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1.
Disease Surveillance ; 37(1):17-21, 2022.
Article in Chinese | CAB Abstracts | ID: covidwho-1789478

ABSTRACT

Objective: To understand the infection status of major respiratory pathogens in pneumonia patients in the early phase of coronavirus disease 2019 (COVID-19) epidemic (January-March, 2020) in Tongzhou district of Beijing.

2.
Trop Med Infect Dis ; 7(3)2022 Mar 06.
Article in English | MEDLINE | ID: covidwho-1732224

ABSTRACT

The study of the spatial differentiation of COVID-19 in cities and its driving mechanism is helpful to reveal the spatial distribution pattern, transmission mechanism and diffusion model, and evolution mechanism of the epidemic and can lay the foundation for constructing the spatial dynamics model of the epidemic and provide theoretical basis for the policy design, spatial planning and implementation of epidemic prevention and control and social governance. Geodetector (Origin version, Beijing, China) is a great tool for analysis of spatial differentiation and its influencing factors, and it provides decision support for differentiated policy design and its implementation in executing the city-specific policies. Using factor detection and interaction analysis of Geodetector, 15 indicators of economic, social, ecological, and environmental dimensions were integrated, and 143 cities were selected for the empirical research in China. The research shows that, first of all, risks of both infection and death show positive spatial autocorrelation, but the geographical distribution of local spatial autocorrelation differs significantly between the two. Secondly, the inequalities in urban economic, social, and residential environments interact with COVID-19 spatial heterogeneity, with stronger explanatory power especially when multidimensional inequalities are superimposed. Thirdly, the spatial distribution and spread of COVID-19 are highly spatially heterogeneous and correlated due to the complex influence of multiple factors, with factors such as Area of Urban Construction Land, GDP, Industrial Smoke and Dust Emission, and Expenditure having the strongest influence, the factors such as Area of Green, Number of Hospital Beds and Parks, and Industrial NOx Emissions having unignorable influence, while the factors such as Number of Free Parks and Industrial Enterprises, Per-GDP, and Population Density play an indirect role mainly by means of interaction. Fourthly, the factor interaction effect from the infected person's perspective mainly shows a nonlinear enhancement effect, that is, the joint influence of the two factors is greater than the sum of their direct influences; but from the perspective of the dead, it mainly shows a two-factor enhancement effect, that is, the joint influence of the two factors is greater than the maximum of their direct influences but less than their sum. Fifthly, some suggestions are put forward from the perspectives of building a healthy, resilient, safe, and smart city, providing valuable reference and decision basis for city governments to carry out differentiated policy design.

3.
Transplant Proc ; 2022 Mar 02.
Article in English | MEDLINE | ID: covidwho-1713002

ABSTRACT

BACKGROUND: Collapsing glomerulopathy (CGN) secondary to HIV or COVID-19 infection mainly occurs in patients of African American descent due to APOL-1 gene mutations, but CGN is occasionally reported in white patients. CGNs are rarely reported in renal transplant biopsies and their association with idiopathic focal segmental glomerulosclerosis (FSGS) is unclear. METHODS AND RESULTS: Patient #1 was a 48-year-old Caucasian white man who had a renal transplant 8 years ago and was recently diagnosed with COVID-19 infection. Two weeks post infection, his serum creatinine (SCr) increased to 2.01 mg/dL from a baseline of 1.40 mg/dL, and he developed concomitant nephrotic range proteinuria. The first renal transplant biopsy showed FSGS. Four weeks later, his sCr level increased to 2.65 mg/dL with worsening proteinuria, and a second renal transplant biopsy revealed CGN. Patient #2 was a 32-year-old African American man whose native renal biopsy revealed primary FSGS. He received a renal transplant with initial post-transplant sCr level at 1.17 mg/dL. Four months later, his sCr and protein-to-creatinine ratio began to rise. Sequential biopsies revealed that the patient had developed recurrent FSGS, which progressed to show features of CGN. The CGN was further confirmed in his transplant kidney graft at autopsy later. CONCLUSIONS: This is the first case report of CGN in a white renal recipient with COVID-19 infection. The pathologic presentations of FSGS progressing to collapsing FSGS in our 2 renal transplant recipients suggest that FSGS and GGN may share a common pathophysiologic mechanism of podocytopathy.

4.
Buildings ; 12(3):257, 2022.
Article in English | MDPI | ID: covidwho-1699222

ABSTRACT

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.

5.
EuropePMC;
Preprint in English | EuropePMC | ID: ppcovidwho-327418

ABSTRACT

Summary Background Though case fatality rate (CFR) is widely used to reflect COVID-19 fatality risk, it’s use is limited by large temporal and spatial variation. Hospital mortality rate (HMR) is also used to assess the severity of COVID-19, but HMR data is not directly available except 35 states of USA. Alternative metrics are needed for COVID-19 severity and fatality assessment. Methods New metrics and their applications in fatality measurements and risk monitoring are proposed here. We also introduce a new mathematical model to estimate average hospital length of stay for death ( L dead ) and discharges ( L dis ). Multiple data sources were used for our analysis. Findings We propose three new metrics, hospital occupancy mortality rate (HOMR), ratio of total deaths to hospital occupancy (TDHOR) and ratio of hospital occupancy to cases (HOCR), for dynamic assessment of COVID-19 fatality risk. Estimated L dead and L dis for 501,079 COVID-19 hospitalizations in US 34 states between Aug 7, 2020 and Mar 1, 2021 were 14.0 and 18.2 days, respectively. We found that TDHOR values of 27 countries are less spatially and temporally variable and more capable of detecting changes in COVID-19 fatality risk. The dramatic changes in COVID-19 CFR observed in 27 countries during early stages of the pandemic were mostly caused by undiagnosed cases. Compared to the first week of November, 2021, the week mean HOCRs (mimics hospitalization-to-case ratio) for Omicron variant decreased 34.08% and 65.16% in the United Kingdom and USA respectively as of Jan 16, 2022. Interpretation These new and reliable measurements for COVID-19 that could be expanded as a general index to other fatal infectious diseases for disease fatality risk and variant-associated risk monitoring. Research in context Evidence before this study We searched PubMed, medRxiv, and bioRxiv for peer-reviewed articles, preprints, and research reports on risk and health care evaluation for COVID-19 using the search terms “hospital occupancy mortality rate”, “ratio of total deaths to hospital occupancy”, “ratio of hospital occupancy to case” up to Jan 20, 2022. No similar concepts or studies were found. No similar mathematical models based on “hospital occupancy mortality rate” for the estimation of hospital length of stay for deaths and discharges have been identified to date. Added value of the study Our new metrics, HOMR and TDHOR, mimic HMR for COVID-19 fatality risk assessment but utilize readily available data for many US states and countries around the world. HOCR mimics hospitalization-to-case ratio for COVID-19. We also provide evidence that explains why COVID-19 CFR has such dramatic changes at the beginning of a COVID-19 outbreak. We have additionally provided new metrics for COVID-19 fatality risk dynamic monitoring including Omicron variant and showed that these metrics provided additional information. Implications of all the available evidence The results of this study, including average hospital length of stay for deaths and discharges for over 500,000 COVID-19 hospitalizations in the US, can aid county, state, and national leaders in making informed public health decisions related to the ongoing COVID-19 pandemic. This is the first study to provide quantitative evidence to address why CFR has a such a large variation at the beginning of the COVID-19 pandemic in most countries and will hopefully encourage more countries to release hospital occupancy data, which we show is both useful and easy information to collect. The new metrics introduced by our study are effective indicators for monitoring COVID-19 fatality risk, as well as potentially fatal COVID-19 variants, and could also be expanded to other fatal infectious diseases.

6.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-311784

ABSTRACT

The global pandemic has made it more important than ever to quickly and accurately retrieve relevant scientific literature for effective consumption by researchers in a wide range of fields. We provide an analysis of several multi-label document classification models on the LitCovid dataset, a growing collection of 23,000 research papers regarding the novel 2019 coronavirus. We find that pre-trained language models fine-tuned on this dataset outperform all other baselines and that BioBERT surpasses the others by a small margin with micro-F1 and accuracy scores of around 86% and 75% respectively on the test set. We evaluate the data efficiency and generalizability of these models as essential features of any system prepared to deal with an urgent situation like the current health crisis. Finally, we explore 50 errors made by the best performing models on LitCovid documents and find that they often (1) correlate certain labels too closely together and (2) fail to focus on discriminative sections of the articles;both of which are important issues to address in future work. Both data and code are available on GitHub.

7.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-306871

ABSTRACT

Background: Accumulating evidence has revealed that coagulopathy and widespread thrombosis in the lung are common in patients with Coronavirus Disease 2019 (COVID-19). This raises questions about the efficacy and safety of systemic anticoagulation (AC) in COVID-19 patients. Method: This single-center, retrospective, cohort study unselectively reviewed 2272 patients with COVID-19 admitted to the Tongji Hospital between Jan 25 and Mar 23, 2020. Propensity score-matching between patients adjusted for potential covariates was carried out with the patients divided into two groups depending on whether or not they had received AC treatment (AC group, ³7 days of treatment;non-AC group, no treatment). This yielded 164 patients in each group. Result: In-hospital mortality of the AC group was significantly lower than that of the non-AC group (14.0% vs. 28.7%, P =0.001). Treatment with AC was associated with a significantly lower probability of in-hospital death (adjusted HR=0.273, 95% CI, 0.154 to 0.484, P <0.001). The incidence of major bleeding and thrombocytopenia in the two groups was not significantly different. Subgroup analysis showed the following factors were associated with a significantly lower in-hospital mortality in patients who had received AC treatment;severe cases (13.2% vs. 24.6%, P =0.018), critical cases (20.0% vs 82.4%, P =0.003), patients with a D-dimer level ≥0.5 μg/mL (14.8% vs. 33.8, P <0.001), and moderate (16.7% vs. 60.0%, P =0.003) or severe acute respiratory distress syndrome (ARDS) cases at admission (33.3% vs. 86.7%, P =0.004). During the hospital stay, critical cases (38.3% vs. 76.7%, P <0.001) and severe ARDS cases (36.5% vs. 76.3%, P <0.001) who received AC treatment had significantly lower in-hospital mortality. Conclusions: : AC treatment decreases the risk of in-hospital mortality, especially in critically ill patients, with no additional significant, major bleeding events or thrombocytopenia being observed. Trials registration - ChiCTR2000039855

8.
IEEE Trans Biomed Eng ; PP2022 Feb 11.
Article in English | MEDLINE | ID: covidwho-1685149

ABSTRACT

OBJECTIVE: The m6A modification is the most common ribonucleic acid (RNA) modification, playing a role in prompting the viruss gene mutation and protein structure changes in the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Nanopore single-molecule direct RNA sequencing (DRS) provides data support for RNA modification detection, which can preserve the potential m6A signature compared to second-generation sequencing. However, due to insufficient DRS data, there is a lack of methods to find m6A RNA modifications in DRS. Our purpose is to identify m6A modifications in DRS precisely. METHODS: We present a methodology for identifying m6A modifications that incorporated mapping and extracted features from DRS data. To detect m6A modifications, we introduce an ensemble method called mixed-weight neural bagging (MWNB), trained with 5-base RNA synthetic DRS containing modified and unmodified m6A. RESULTS: Our MWNB model achieved the highest classification accuracy of 97.85% and AUC of 0.9968. Additionally, we applied the MWNB model to the COVID-19 dataset; the experiment results reveal a strong association with biomedical experiments. CONCLUSION: Our strategy enables the prediction of m6A modifications using DRS data and completes the identification of m6A modifications on the SARS-CoV-2. SIGNIFICANCE: The Corona Virus Disease 2019 (COVID-19) outbreak has significantly influence, caused by the SARS-CoV-2. An RNA modification called m6A is connected with viral infections. The appearance of m6A modifications related to several essential proteins affects proteins' structure and function. Therefore, finding the location and number of m6A RNA modifications is crucial for subsequent analysis of the protein expression profile.

9.
Front Med (Lausanne) ; 8: 786414, 2021.
Article in English | MEDLINE | ID: covidwho-1626704

ABSTRACT

Objective: To explore the efficacy of anticoagulation in improving outcomes and safety of Coronavirus disease 2019 (COVID-19) patients in subgroups identified by clinical-based stratification and unsupervised machine learning. Methods: This single-center retrospective cohort study unselectively reviewed 2,272 patients with COVID-19 admitted to the Tongji Hospital between Jan 25 and Mar 23, 2020. The association between AC treatment and outcomes was investigated in the propensity score (PS) matched cohort and the full cohort by inverse probability of treatment weighting (IPTW) analysis. Subgroup analysis, identified by clinical-based stratification or unsupervised machine learning, was used to identify sub-phenotypes with meaningful clinical features and the target patients benefiting most from AC. Results: AC treatment was associated with lower in-hospital death risk either in the PS matched cohort or by IPTW analysis in the full cohort. A higher incidence of clinically relevant non-major bleeding (CRNMB) was observed in the AC group, but not major bleeding. Clinical subgroup analysis showed that, at admission, severe cases of COVID-19 clinical classification, mild acute respiratory distress syndrome (ARDS) cases, and patients with a D-dimer level ≥0.5 µg/mL, may benefit from AC. During the hospital stay, critical cases and severe ARDS cases may benefit from AC. Unsupervised machine learning analysis established a four-class clustering model. Clusters 1 and 2 were non-critical cases and might not benefit from AC, while clusters 3 and 4 were critical patients. Patients in cluster 3 might benefit from AC with no increase in bleeding events. While patients in cluster 4, who were characterized by multiple organ dysfunction (neurologic, circulation, coagulation, kidney and liver dysfunction) and elevated inflammation biomarkers, did not benefit from AC. Conclusions: AC treatment was associated with lower in-hospital death risk, especially in critically ill COVID-19 patients. Unsupervised learning analysis revealed that the most critically ill patients with multiple organ dysfunction and excessive inflammation might not benefit from AC. More attention should be paid to bleeding events (especially CRNMB) when using AC.

10.
Frontiers in medicine ; 8, 2021.
Article in English | EuropePMC | ID: covidwho-1609796

ABSTRACT

Objective: To explore the efficacy of anticoagulation in improving outcomes and safety of Coronavirus disease 2019 (COVID-19) patients in subgroups identified by clinical-based stratification and unsupervised machine learning. Methods: This single-center retrospective cohort study unselectively reviewed 2,272 patients with COVID-19 admitted to the Tongji Hospital between Jan 25 and Mar 23, 2020. The association between AC treatment and outcomes was investigated in the propensity score (PS) matched cohort and the full cohort by inverse probability of treatment weighting (IPTW) analysis. Subgroup analysis, identified by clinical-based stratification or unsupervised machine learning, was used to identify sub-phenotypes with meaningful clinical features and the target patients benefiting most from AC. Results: AC treatment was associated with lower in-hospital death risk either in the PS matched cohort or by IPTW analysis in the full cohort. A higher incidence of clinically relevant non-major bleeding (CRNMB) was observed in the AC group, but not major bleeding. Clinical subgroup analysis showed that, at admission, severe cases of COVID-19 clinical classification, mild acute respiratory distress syndrome (ARDS) cases, and patients with a D-dimer level ≥0.5 μg/mL, may benefit from AC. During the hospital stay, critical cases and severe ARDS cases may benefit from AC. Unsupervised machine learning analysis established a four-class clustering model. Clusters 1 and 2 were non-critical cases and might not benefit from AC, while clusters 3 and 4 were critical patients. Patients in cluster 3 might benefit from AC with no increase in bleeding events. While patients in cluster 4, who were characterized by multiple organ dysfunction (neurologic, circulation, coagulation, kidney and liver dysfunction) and elevated inflammation biomarkers, did not benefit from AC. Conclusions: AC treatment was associated with lower in-hospital death risk, especially in critically ill COVID-19 patients. Unsupervised learning analysis revealed that the most critically ill patients with multiple organ dysfunction and excessive inflammation might not benefit from AC. More attention should be paid to bleeding events (especially CRNMB) when using AC.

11.
Medicinal Plant ; 12(1):87-90, 2021.
Article in English | CAB Abstracts | ID: covidwho-1374717

ABSTRACT

Objectives: To collect the main active components and targets of baicalein, and to explore the relationship between their targets and COVID-19 and the treatment mechanism of potential unknown targets.

12.
Obesity (Silver Spring) ; 29(8): 1294-1308, 2021 08.
Article in English | MEDLINE | ID: covidwho-1333021

ABSTRACT

OBJECTIVE: The Action for Health in Diabetes (Look AHEAD) study previously reported that intensive lifestyle intervention (ILI) reduced incident depressive symptoms and improved health-related quality of life (HRQOL) over nearly 10 years of intervention compared with a control group (the diabetes support and education group [DSE]) in participants with type 2 diabetes and overweight or obesity. The present study compared incident depressive symptoms and changes in HRQOL in these groups for an additional 6 years following termination of the ILI in September 2012. METHODS: A total of 1,945 ILI participants and 1,900 DSE participants completed at least one of four planned postintervention assessments at which weight, mood (via the Patient Health Questionnaire-9), antidepressant medication use, and HRQOL (via the Medical Outcomes Scale, Short Form-36) were measured. RESULTS: ILI participants and DSE participants lost 3.1 (0.3) and 3.8 (0.3) kg [represented as mean (SE); p = 0.10], respectively, during the 6-year postintervention follow-up. No significant differences were observed between groups during this time in incident mild or greater symptoms of depression, antidepressant medication use, or in changes on the physical component summary or mental component summary scores of the Short Form-36. In both groups, mental component summary scores were higher than physical component summary scores. CONCLUSIONS: Prior participation in the ILI, compared with the DSE group, did not appear to improve subsequent mood or HRQOL during 6 years of postintervention follow-up.


Subject(s)
Diabetes Mellitus, Type 2 , Quality of Life , Diabetes Mellitus, Type 2/therapy , Humans , Life Style , Overweight/therapy , Weight Loss
13.
Diabetes Care ; 44(8): 1788-1796, 2021 08.
Article in English | MEDLINE | ID: covidwho-1280713

ABSTRACT

OBJECTIVE: To assess whether risk of severe outcomes among patients with type 1 diabetes mellitus (T1DM) hospitalized for coronavirus disease 2019 (COVID-19) differs from that of patients without diabetes or with type 2 diabetes mellitus (T2DM). RESEARCH DESIGN AND METHODS: Using the Premier Healthcare Database Special COVID-19 Release records of patients discharged after COVID-19 hospitalization from U.S. hospitals from March to November 2020 (N = 269,674 after exclusion), we estimated risk differences (RD) and risk ratios (RR) of intensive care unit admission or invasive mechanical ventilation (ICU/MV) and of death among patients with T1DM compared with patients without diabetes or with T2DM. Logistic models were adjusted for age, sex, and race or ethnicity. Models adjusted for additional demographic and clinical characteristics were used to examine whether other factors account for the associations between T1DM and severe COVID-19 outcomes. RESULTS: Compared with patients without diabetes, T1DM was associated with a 21% higher absolute risk of ICU/MV (RD 0.21, 95% CI 0.19-0.24; RR 1.49, 95% CI 1.43-1.56) and a 5% higher absolute risk of mortality (RD 0.05, 95% CI 0.03-0.07; RR 1.40, 95% CI 1.24-1.57), with adjustment for age, sex, and race or ethnicity. Compared with T2DM, T1DM was associated with a 9% higher absolute risk of ICU/MV (RD 0.09, 95% CI 0.07-0.12; RR 1.17, 95% CI 1.12-1.22), but no difference in mortality (RD 0.00, 95% CI -0.02 to 0.02; RR 1.00, 95% CI 0.89-1.13). After adjustment for diabetic ketoacidosis (DKA) occurring before or at COVID-19 diagnosis, patients with T1DM no longer had increased risk of ICU/MV (RD 0.01, 95% CI -0.01 to 0.03) and had lower mortality (RD -0.03, 95% CI -0.05 to -0.01) in comparisons with patients with T2DM. CONCLUSIONS: Patients with T1DM hospitalized for COVID-19 are at higher risk for severe outcomes than those without diabetes. Higher risk of ICU/MV in patients with T1DM than in patients with T2DM was largely accounted for by the presence of DKA. These findings might further guide recommendations related to diabetes management and the prevention of COVID-19.


Subject(s)
COVID-19 , Diabetes Mellitus, Type 1 , Diabetes Mellitus, Type 2 , COVID-19 Testing , Hospitalization , Humans , Intensive Care Units , Respiration, Artificial , Risk Factors , SARS-CoV-2
14.
J Psychosoc Nurs Ment Health Serv ; 59(9): 30-37, 2021 Sep.
Article in English | MEDLINE | ID: covidwho-1264594

ABSTRACT

Using Gordon's Functional Health Pattern Model, the current cross-sectional study aimed to survey physical and psychosocial responses to the coronavirus disease 2019 (COVID-19) pandemic among Chinese frontline nurses and to identify the most vulnerable groups for future reference and interventions. A self-administered online questionnaire was used to collect demographic data and stress reactions of 115 Chinese frontline nurses. The 52-item version of Gordon's Functional Health Questionnaire was used to evaluate physical, psychological, and social effects of the COVID-19 pandemic among participants. The most prevalent problems were reported in the psychological aspect, where respondents referred to altered self-image due to constant use of masks (87.8%), excessive attention to clinical signs of COVID-19 (59.2%), depression (54%), forgetfulness (40.9%), and anxiety (39.1%). The most vulnerable nurses were those who were younger, had a chronic disease, and were divorced. [Journal of Psychosocial Nursing and Mental Health Services, 59(9), 30-37.].


Subject(s)
COVID-19 , Nurses , Anxiety/epidemiology , COVID-19/epidemiology , China/epidemiology , Cross-Sectional Studies , Depression/epidemiology , Humans , Mental Health , Nurses/psychology , Pandemics , Surveys and Questionnaires
15.
Epidemiol Infect ; 148: e241, 2020 10 01.
Article in English | MEDLINE | ID: covidwho-1263436

ABSTRACT

A recently developed pneumonia caused by SARS-CoV-2 has quickly spread across the world. Unfortunately, a simplified risk score that could easily be used in primary care or general practice settings has not been developed. The objective of this study is to identify a simplified risk score that could easily be used to quickly triage severe COVID-19 patients. All severe and critical adult patients with laboratory-confirmed COVID-19 on the West campus of Union Hospital, Wuhan, China, from 28 January 2020 to 29 February 2020 were included in this study. Clinical data and laboratory results were obtained. CURB-65 pneumonia score was calculated. Univariate logistic regressions were applied to explore risk factors associated with in-hospital death. We used the receiver operating characteristic curve and multivariate COX-PH model to analyse risk factors for in-hospital death. A total of 74 patients (31 died, 43 survived) were finally included in the study. We observed that compared with survivors, non-survivors were older and illustrated higher respiratory rate, neutrophil-to-lymphocyte ratio, D-dimer and lactate dehydrogenase (LDH), but lower SpO2 as well as impaired liver function, especially synthesis function. CURB-65 showed good performance for predicting in-hospital death (area under curve 0.81, 95% confidence interval (CI) 0.71-0.91). CURB-65 ⩾ 2 may serve as a cut-off value for prediction of in-hospital death in severe patients with COVID-19 (sensitivity 68%, specificity 81%, F1 score 0.7). CURB-65 (hazard ratio (HR) 1.61; 95% CI 1.05-2.46), LDH (HR 1.003; 95% CI 1.001-1.004) and albumin (HR 0.9; 95% CI 0.81-1) were risk factors for in-hospital death in severe patients with COVID-19. Our study indicates CURB-65 may serve as a useful prognostic marker in COVID-19 patients, which could be used to quickly triage severe patients in primary care or general practice settings.


Subject(s)
Betacoronavirus , Coronavirus Infections/mortality , Pneumonia, Viral/mortality , Pneumonia/mortality , Severity of Illness Index , Adult , Aged , Aged, 80 and over , Biomarkers , COVID-19 , Female , Humans , L-Lactate Dehydrogenase/blood , Logistic Models , Male , Middle Aged , Pandemics , Prognosis , Retrospective Studies , SARS-CoV-2
16.
Mol Ther ; 29(7): 2219-2226, 2021 07 07.
Article in English | MEDLINE | ID: covidwho-1228174

ABSTRACT

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in humans. Despite several emerging vaccines, there remains no verifiable therapeutic targeted specifically to the virus. Here we present a highly effective small interfering RNA (siRNA) therapeutic against SARS-CoV-2 infection using a novel lipid nanoparticle (LNP) delivery system. Multiple siRNAs targeting highly conserved regions of the SARS-CoV-2 virus were screened, and three candidate siRNAs emerged that effectively inhibit the virus by greater than 90% either alone or in combination with one another. We simultaneously developed and screened two novel LNP formulations for the delivery of these candidate siRNA therapeutics to the lungs, an organ that incurs immense damage during SARS-CoV-2 infection. Encapsulation of siRNAs in these LNPs followed by in vivo injection demonstrated robust repression of virus in the lungs and a pronounced survival advantage to the treated mice. Our LNP-siRNA approaches are scalable and can be administered upon the first sign of SARS-CoV-2 infection in humans. We suggest that an siRNA-LNP therapeutic approach could prove highly useful in treating COVID-19 disease as an adjunctive therapy to current vaccine strategies.


Subject(s)
COVID-19/drug therapy , Drug Delivery Systems/methods , Lipids/chemistry , Nanoparticles/chemistry , RNA, Double-Stranded/administration & dosage , RNA, Small Interfering/administration & dosage , RNA, Small Interfering/genetics , SARS-CoV-2/genetics , Administration, Intravenous , Angiotensin-Converting Enzyme 2/genetics , Animals , COVID-19/metabolism , COVID-19/virology , Female , Gene Silencing , HEK293 Cells , Humans , Lung/metabolism , Male , Mice , Mice, Transgenic , RNA, Double-Stranded/genetics , RNA, Viral/genetics , Transcriptome/drug effects , Treatment Outcome
17.
Emerging Markets, Finance & Trade ; 57(6):1578-1591, 2021.
Article in English | ProQuest Central | ID: covidwho-1220251

ABSTRACT

This paper investigates the impact of stock liquidity on firm value in the time of COVID-19 pandemic. Using data from A-share listed companies in China, we calculate the firm value of Cumulative Abnormal Returns through the event study method and stock liquidity by the Amihud illiquidity. We find that significant negative relationships between stock liquidity and firm value exist in the first three days of the COVID-19 outbreak, while significant positive relationships in the following days. We also find that these negative relationships are more significant in severely impacted regions, small companies, and non-state-owned enterprises.

18.
Journal of Comparative Policy Analysis ; 23(2):262-273, 2021.
Article in English | Academic Search Complete | ID: covidwho-1201356

ABSTRACT

The COVID-19 pandemic has prompted a variety of responses from governments around the world. This research investigates national governments' fiscal policies that have been introduced to manage the COVID-19 pandemic within economic, political, and institutional contexts. It demonstrates similarities and heterogeneity in the three dimensions of fiscal policy responses to COVID-19 (the size of fiscal spending, the types and targets of fiscal policy responses) across 170 countries. [ABSTRACT FROM AUTHOR] Copyright of Journal of Comparative Policy Analysis is the property of Routledge 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.)

19.
Matter ; 2021.
Article in English | ScienceDirect | ID: covidwho-1185157

ABSTRACT

Summary Viral infections remain one of the leading causes of mortality worldwide, responsible for millions of deaths every year. The application of antiviral drugs, along with symptomatic treatment, is the primary modality of clinical antiviral therapy. Nevertheless, the severe side effects of antiviral drugs, such as gastrointestinal, hepatic, renal, and/or hematopoietic damages, can affect compliance and may even interrupt treatment. Moreover, drug resistance due to frequent viral mutations and single antiviral mechanisms often leads to therapeutic failure. The introduction of biomaterials into antiviral therapy provides distinct advantages and unique mechanisms. Antiviral biomaterials work in various ways, such as physical adsorption of viruses, binding to viruses as entry inhibitors, induction of irreversible viral deformation, interference with viral nucleic acid replication, and blockage of viral release from infected cells, among others. This review offers an overview of state-of-the-art advances in antiviral biomaterials featuring different mechanisms and discusses their challenges and opportunities in clinical translations.

20.
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