Corpus overview


Overview

MeSH Disease

Human Phenotype

Transmission

Seroprevalence
    displaying 1 - 10 records in total 11
    records per page




    COVID-19 patients upregulate toll-like receptor 4-mediated inflammatory signaling that mimics bacterial sepsis HP sepsis MESHD

    Authors: Kyung Mok Sohn; Sung-Gwon Lee; Hyeon Ji Kim; Shinhyea Cheon; Hyeongseok Jeong; Jooyeon Lee; In Soo Kim; Prashanta Silwal; Young Jae Kim; Chungoo Park; Yeon-Sook Kim; Eun-Kyeong Jo

    doi:10.1101/2020.07.17.207878 Date: 2020-07-17 Source: bioRxiv

    Observational studies of the ongoing coronavirus disease MESHD 2019 (COVID-19) outbreak suggest that a cytokine storm is involved in the pathogenesis of severe illness. However, the molecular mechanisms underlying the altered pathological inflammation MESHD in COVID-19 are largely unknown. We report here that toll-like receptor (TLR) 4-mediated inflammatory signaling molecules are upregulated in peripheral blood SERO mononuclear cells (PBMCs) from COVID-19 patients, compared with healthy controls. Among the most highly increased inflammatory mediators in severe/ critically ill MESHD patients, S100A9, an alarmin and TLR4 ligand, was found as a noteworthy biomarker, because it inversely correlated with the serum SERO albumin levels. These data support a link between TLR4 signaling and pathological inflammation MESHD during COVID-19 and contribute to develop therapeutic approaches through targeting TLR4-mediated inflammation MESHD.

    Selenium Deficiency is Associated with Mortality Risk from COVID-19

    Authors: Arash Moghaddam; Raban Arved Heller; Qian Sun; Julian Seelig; Asan Cherkezov; Linda Seibert; Julian Hackler; Petra Seemann; Joachim Diegmann; Maximilian Pilz; Manuel Bachmann; Waldemar B. Minich; Lutz Schomburg

    id:10.20944/preprints202007.0113.v1 Date: 2020-07-07 Source: Preprints.org

    SARS-CoV-2 infections MESHD underlie the current Coronavirus disease MESHD (COVID-19) pandemic and are causative for a high death toll particularly among elderly TRANS subjects and those with comorbidities. Selenium (Se) is an essential trace TRANS element of high importance for human health and particularly for a well-balanced immune response. Mortality risk from severe disease like sepsis HP sepsis MESHD or polytrauma MESHD is inversely related to Se status. We hypothesized that this relation also applies to COVID-19. Serum samples SERO (n=166) from COVID-19 patients (n=33) were collected consecutively and analysed for total Se by X-ray fluorescence and selenoprotein P (SELENOP) by a validated ELISA SERO. Both biomarkers showed the expected strong correlation (r=0.7758, p<0.001), pointing to an insufficient Se status for optimal selenoprotein expression. In comparison to reference data from a European cross sectional analysis (EPIC, n=1915), the patients showed a pronounced deficit in total serum SERO Se (mean±SD, 50.8±15.7 vs. 84.4±23.4 µg/L) and SELENOP (3.0±1.4 vs. 4.3±1.0 mg/L). A Se status below the 2.5th percentile of the reference population, i.e., [Se] < 45.7 µg/L and [SELENOP] < 2.56 mg/L was present in 43.4% and 39.2% of COVID samples, respectively. The Se status was significantly higher in samples from surviving COVID patients as compared to non-survivors (Se; 53.3±16.2 vs. 40.8±8.1 µg/L, SELENOP; 3.3±1.3 vs. 2.1±0.9 mg/L). We conclude that Se status analysis in COVID patients provides diagnostic information. However, causality remains unknown due to the observational nature of this study. Nevertheless, the findings strengthen the notion on a relevant role of Se for COVID convalescence, and support the discussion on adjuvant Se supplementation in severely diseased and Se-deficient patients.

    Tocilizumab and Thromboembolism HP Thromboembolism MESHD in COVID-19: A Retrospective Hospital-based Cohort Analysis

    Authors: Kok Hoe Chan; Bhavik Patel; Bishnu Podel; Maria E Szabela; Hamid S Shaaban; Gunwant Guron; Jihad Slim

    doi:10.21203/rs.3.rs-39943/v1 Date: 2020-07-02 Source: ResearchSquare

    Background:Tocilizumab, an IL-6 receptor antagonist has been used in patients with Coronavirus Disease MESHD 2019 (COVID-19) as an anti-cytokine agent. IL-6 also plays a complex role in hemostasis and thrombosis MESHD. We observed a transient elevation of D-dimer in our patients who received Tocilizumab, which triggered the current study.Methods:A retrospective hospital-based cohort analysis of patients with confirmed COVID-19 who received Tocilizumab during the study period of 03/15/2020 to 05/20/2020. We retrieved demographic, clinical and laboratory data, we excluded patients who were receiving therapeutic anticoagulation therapy prior to Tocilizumab administration.  Descriptive analysis was performed, the cause of death MESHD and trends of D-dimer and inflammatory markers were studied. Results: Out of the 436 confirmed COVID 19 patients admitted during the study period, 24 met the inclusion criteria. Their median age TRANS was 47.5 years old. They were 18 males TRANS and 6 females TRANS; 15 patients survived, and 9 expired. Of the group that survived, 12 received therapeutic anticoagulation. Of the 7 patients who did not receive therapeutic anticoagulation, 4 expired, 1 from sepsis HP sepsis MESHD and 3 probably from thromboembolic complications MESHD, compared to 5 deaths in the 17 patients who received therapeutic anticoagulation with 4 dying from sepsis HP sepsis MESHD, and one possibly from thromboembolic complications MESHD.Conclusions:The interplay between IL-6, IL-6 receptor antagonist and venous thromboembolism MESHD thromboembolism HP are complex. We observed a transient elevation of D-dimer in COVID-19 patients who received Tocilizumab, and a trend toward increased death secondary to thromboembolism HP thromboembolism MESHD. This observation is novel and highlights the potential thrombophilic side effects of Tocilizumab.

    A blood SERO-based comprehensive and systems-level analysis of disease stages, immune regulation and symptoms in COVID-19 patients

    Authors: Anguraj Sadanandam; Tobias Bopp; Santosh Dixit; David JHF Knapp; Chitra Priya Emperumal; Krishnaraj Rajalingam; Alan Melcher; Nagarajan Kannan

    doi:10.21203/rs.3.rs-30473/v1 Date: 2020-05-20 Source: ResearchSquare

    COVID-19 patients show significant clinical heterogeneity in presentation and outcomes that makes pandemic control and strategy difficult; optimising management requires a systems biology approach of understanding the disease. Here we sought to understand and infer complex system-wide changes in patients infected with coronaviruses ( SARS-CoV and SARS-CoV-2 MESHD; n=38 and 57 samples) at two different disease stages compared with healthy individuals (n=16) and patients with other infections (n=144). We applied inferential statistics/machine-learning approaches (the COVID-engine platform) to RNA profiles derived from peripheral blood SERO mononuclear cells (PBMCs). Compared to healthy individuals, an integrated blood SERO-based gene signatures distinguished acute-like (mimicking coronavirus-infected MESHD patients with prolonged hospitalisation) from recovering-like patients. These signatures also hierarchically represented systems-level parameters associated with PBMC including dysregulated cytokines, genes, pathways, networks of pathways/concepts, immune status, and cell types. Proof-of-principle confirmatory observations included PBMC-associated increases in ACE2, cytokine storm-associated IL6, enhanced innate immunity (macrophages and neutrophils), and lower adaptive T and B cell immunity in patients with acute-like disease compared to those with recovery-like disease. Patients in the recovery-like stage had significantly enhanced TNF, IFN-g, anti-viral, HLA-DQA1, and HLA-F gene expression and cytolytic activity, and reduced pro-viral gene expression compared to those in the acute-like stage in PBMC. Besides, PBMC-derived surrogate-based approach revealed overlapping genes associated with comorbidities (associated diabetes MESHD), and disease-like symptoms (associated with thromboembolism HP thromboembolism MESHD, pneumonia HP pneumonia MESHD, lung disease MESHD and septicaemia MESHD). Overall, our study involving PBMC-based RNA profiling may further help understand complex and variable systems-wide responses displayed by coronavirus-infected MESHD patients.

    Identification and Analysis of Shared Risk Factors in Sepsis HP Sepsis MESHD and High Mortality Risk COVID-19 Patients

    Authors: Sayoni Das; Krystyna Taylor; Matthew Pearson; James Kozubek; Marcin Pawlowski; Claus Erik Jensen; Zbigniew Skowron; Gert Lykke Møller; Mark Strivens; Steve Gardner

    doi:10.1101/2020.05.05.20091918 Date: 2020-05-09 Source: medRxiv

    BACKGROUND Coronavirus disease MESHD 2019 (COVID-19) is a novel coronavirus strain disease MESHD caused by severe acute respiratory syndrome coronavirus 2 MESHD (SARS-CoV-2). The disease is highly transmissible and severe disease including viral sepsis MESHD sepsis HP has been reported in up to 16% of hospitalized cases. The admission characteristics associated with increased odds of hospital mortality among confirmed cases TRANS of COVID-19 include severe hypoxia MESHD, low platelet count, elevated bilirubin, hypoalbuminemia HP hypoalbuminemia MESHD and reduced glomerular filtration rate. These symptoms correlate highly with severe sepsis HP sepsis MESHD cases. The diseases also share similar co-morbidity risks including dementia HP dementia MESHD, type 2 diabetes mellitus HP, coronary heart disease MESHD, hypertension HP hypertension MESHD and chronic renal failure MESHD. Sepsis HP Sepsis MESHD has been observed in up to 59% of hospitalized COVID-19 patients. It is highly desirable to identify risk factors and novel therapy/drug repurposing avenues for late-stage severe COVID-19 patients. This would enable better protection of at-risk populations and clinical stratification of COVID-19 patients according to their risk for developing life threatening disease. METHODS As there is currently insufficient data available for confirmed COVID-19 patients correlating their genomic profile, disease severity and outcome, co-morbidities and treatments as well as epidemiological risk factors (such as ethnicity, blood SERO group, smoking, BMI etc.), a direct study of the impact of host genomics on disease severity and outcomes is not yet possible. We therefore ran a study on the UK Biobank sepsis cohort MESHD sepsis HP cohort as a surrogate to identify sepsis HP sepsis MESHD associated signatures and genes, and correlated these with COVID-19 patients. Sepsis HP Sepsis MESHD is itself a life-threatening inflammatory health condition with a mortality rate of approximately 20%. Like the initial studies for COVID-19 patients, standard genome wide association studies (GWAS) have previously failed to identify more than a handful of genetic variants that predispose individuals to developing sepsis HP sepsis MESHD. RESULTS We used a combinatorial association approach to analyze a sepsis HP sepsis MESHD population derived from UK Biobank. We identified 70 sepsis HP sepsis MESHD risk-associated genes, which provide insights into the disease mechanisms underlying sepsis HP sepsis MESHD pathogenesis. Many of these targets can be grouped by common mechanisms of action such as endothelial cell dysfunction, PI3K/mTOR pathway signaling, immune response regulation, aberrant GABA and neurogenic signaling. CONCLUSION This study has identified 70 sepsis HP sepsis MESHD related genes, many of them for the first time, that can reasonably be considered to be potentially relevant to severe COVID-19 patients. We have further identified 59 drug repurposing candidates for 13 of these targets that can be used for the development of novel therapeutic strategies to increase the survival rate of patients who develop sepsis HP sepsis MESHD and potentially severe COVID-19.

    Examining the effector mechanisms of Xuebijing Injection on COVID-19 based on network pharmacology.

    Authors: Wenjiang Zheng; Qian Yan; Yongshi Ni; Shaofeng Zhan; Liuliu Yang; Hongfa Zhuang; Xiaohong Liu; Yong Jiang

    doi:10.21203/rs.3.rs-26834/v2 Date: 2020-05-03 Source: ResearchSquare

    Objective: To examine the potential effector mechanisms of Xuebijing (XBJ) on coronavirus disease MESHD 2019 (COVID-19) based on network pharmacology.Methods: We searched Chinese and international papers to obtain the active ingredients of XBJ. Then, we compiled COVID-19 disease targets from the GeneCards gene database and via literature searches. Next, we used the SwissTargetPrediction database to predict XBJ’s effector targets and map them to the abovementioned COVID-19 disease targets in order to obtain potential therapeutic targets of XBJ. Cytoscape software version 3.7.0 was used to construct a “XBJ active-compound-potential-effector target” network and protein-protein interaction (PPI) network, and then to carry out network topology analysis of potential targets. We used the ClueGO and CluePedia plugins in Cytoscape to conduct gene ontology (GO) biological process (BP) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway enrichment analysis of XBJ’s effector targets. Results: We obtained 144 potential COVID-19 effector targets of XBJ. Fourteen of these targets—glyceraldehyde 3-phosphate dehydrogenase (GAPDH), albumin (ALB), tumor MESHD necrosis MESHD factor (TNF), epidermal growth factor receptor (EGFR), mitogen-activated protein kinase 1 (MAPK1), Caspase-3 (CASP3), signal transducer and activator of transcription 3 (STAT3), MAPK8, prostaglandin-endoperoxide synthase 2 (PTGS2), JUN, interleukin-2 (IL-2), estrogen receptor 1 (ESR1), and MAPK14—had degree values >40 and therefore could be considered key targets. They participated in extracellular signal–regulated kinase 1 and 2 (ERK1, ERK2) cascade, the T-cell receptor signaling pathway, activation of MAPK activity, cellular response to lipopolysaccharide, and other inflammation MESHD- and immune-related BPs. XBJ exerted its therapeutic effects through the renin–angiotensin system (RAS), nuclear factor κ-light-chain-enhancer of activated B cells (NF-κB), MAPK, phosphatidylinositol-4, 5-bisphosphate 3-kinase (PI3K)–protein kinase B (Akt)–vascular endothelial growth factor (VEGF), toll-like receptor (TLR), TNF, and inflammatory-mediator regulation of transient receptor potential (TRP) signaling pathways to ultimately construct a “ingredient-target-pathway” effector network. Conclusion: The active ingredients of XBJ regulated different genes, acted on different pathways, and synergistically produced anti-inflammatory and immune-regulatory effects, which fully demonstrated the synergistic effects of different components on multiple targets and pathways. Our study demonstrated that existing studies on the pharmacological mechanisms of XBJ in the treatment of sepsis HP sepsis MESHD and severe pneumonia HP pneumonia MESHD, could explain the effector mechanism of XBJ in COVID-19 treatment, and those provided a preliminary examination of the potential effector mechanism in this disease.

    Examining the effector mechanisms of Xuebijing Injection on COVID-19 based on network pharmacology

    Authors: Wenjiang Zheng; Qian Yan; Yongshi Ni; Shaofeng Zhan; Liuliu Yang; Hongfa Zhuang; Xiaohong Liu; Yong Jiang

    doi:10.21203/rs.3.rs-26834/v3 Date: 2020-05-03 Source: ResearchSquare

    Background: Chinese medicine Xuebijing (XBJ) has proven to be effective in the treatment of mild coronavirus disease MESHD 2019 (COVID-19) cases. But the bioactive compounds and potential mechanisms of XBJ for COVID-19 prevention and treatment are unclear. This study aimed to examine the potential effector mechanisms of XBJ onCOVID-19 based on network pharmacology.Methods: We searched Chinese and international papers to obtain the active ingredients of XBJ. Then, we compiled COVID-19 disease targets from the GeneCards gene database and via literature searches. Next, we used the SwissTargetPrediction database to predict XBJ’s effector targets and map them to the abovementioned COVID-19 disease targets in order to obtain potential therapeutic targets of XBJ. Cytoscape software version 3.7.0 was used to construct a “XBJ active-compound-potential-effector target” network and protein-protein interaction (PPI) network, and then to carry out network topology analysis of potential targets. We used the ClueGO and CluePedia plugins in Cytoscape to conduct gene ontology (GO) biological process (BP) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway enrichment analysis of XBJ’s effector targets. We used AutoDock vina and PyMOL software for molecular docking. Results: We obtained 144 potential COVID-19 effector targets of XBJ. Fourteen of these targets-glyceraldehyde 3-phosphate dehydrogenase (GAPDH), albumin (ALB), tumor MESHD necrosis MESHD factor (TNF), epidermal growth factor receptor (EGFR), mitogen-activated protein kinase 1 (MAPK1), Caspase-3 (CASP3), signal transducer and activator of transcription 3 (STAT3), MAPK8, prostaglandin-endoperoxide synthase 2 (PTGS2), JUN, interleukin-2 (IL-2), estrogen receptor 1 (ESR1), and MAPK14 had degree values >40 and therefore could be considered key targets. They participated in extracellular signal–regulated kinase 1 and 2 (ERK1, ERK2) cascade, the T-cell receptor signaling pathway, activation of MAPK activity, cellular response to lipopolysaccharide, and other inflammation MESHD- and immune-related BPs. XBJ exerted its therapeutic effects through the renin-angiotensin system (RAS), nuclear factor κ-light-chain-enhancer of activated B cells (NF-κB), MAPK, phosphatidylinositol-4, 5-bisphosphate 3-kinase (PI3K)-protein kinase B (Akt)-vascular endothelial growth factor (VEGF), toll-like receptor (TLR), TNF, and inflammatory-mediator regulation of transient receptor potential (TRP) signaling pathways to ultimately construct a “drug-ingredient-target-pathway” effector network. The molecular docking results showed that the core 18 effective ingredients had a docking score of less than -4.0 with those top 10 targets. Conclusion: The active ingredients of XBJ regulated different genes, acted on different pathways, and synergistically produced anti-inflammatory and immune-regulatory effects, which fully demonstrated the synergistic effects of different components on multiple targets and pathways. Our study demonstrated that key ingredients and their targets have potential binding activity, the existing studies on the pharmacological mechanisms of XBJ in the treatment of sepsis HP sepsis MESHD and severe pneumonia HP pneumonia MESHD, could explain the effector mechanism of XBJ in COVID-19 treatment, and those provided a preliminary examination of the potential effector mechanism in this disease.

    Performing risk stratification for COVID-19 when individual level data is not available, the experience of a large healthcare organization

    Authors: Noam Barda; Dan Riesel; Amichay Akriv; Joseph Levi; Uriah Finkel; Gal Yona; Daniel Greenfeld; Shimon Sheiba; Jonathan Somer; Eitan Bachmat; Guy N Rothblum; Uri Shalit; Doron Netzer; Ran Balicer; Noa Dagan

    doi:10.1101/2020.04.23.20076976 Date: 2020-04-28 Source: medRxiv

    With the global coronavirus disease MESHD 2019 (COVID-19) pandemic, there is an urgent need for risk stratification tools to support prevention and treatment decisions. The Centers for Disease Control and Prevention (CDC) listed several criteria that define high-risk individuals, but multivariable prediction models may allow for a more accurate and granular risk evaluation. In the early days of the pandemic, when individual level data required for training prediction models was not available, a large healthcare organization developed a prediction model for supporting its COVID-19 policy using a hybrid strategy. The model was constructed on a baseline predictor to rank patients according to their risk for severe respiratory infection MESHD or sepsis HP sepsis MESHD (trained using over one-million patient records) and was then post-processed to calibrate the predictions to reported COVID-19 case fatality rates. Since its deployment in mid-March, this predictor was integrated into many decision-processes in the organization that involved allocating limited resources. With the accumulation of enough COVID-19 patients, the predictor was validated for its accuracy in predicting COVID-19 mortality among all COVID-19 cases in the organization (3,176, 3.1% death rate). The predictor was found to have good discrimination, with an area under the receiver-operating characteristics curve of 0.942. Calibration was also good, with a marked improvement compared to the calibration of the baseline model when evaluated for the COVID-19 mortality outcome. While the CDC criteria identify 41% of the population as high-risk with a resulting sensitivity SERO of 97%, a 5% absolute risk cutoff by the model tags only 14% to be at high-risk while still achieving a sensitivity SERO of 90%. To summarize, we found that even in the midst of a pandemic, shrouded in epidemiologic "fog of war" and with no individual level data, it was possible to provide a useful predictor with good discrimination and calibration.

    Analysis of the Clinical Characteristics of 77 COVID-19 Deaths

    Authors: Kaige Wang; Zhixin Qiu; Dan Liu; Jianfei Luo; Jiasheng Liu; Tao Fan; Chunrong Liu; Panwen Tian; Ye Wang; Zhong Ni; Shumin Zhang; Weimin Li

    doi:10.21203/rs.3.rs-23960/v1 Date: 2020-04-20 Source: ResearchSquare

    Purpose: For the emerging pandemic Coronavirus Disease MESHD 2019 (COVID-19), no clear description on its deaths’ clinical characteristics and causes of death MESHD is available. Hence, this study analyzed clinical characteristics of 77 COVID-19 deaths, providing data support to further understand this disease.Method: A retrospective analysis of 77 COVID-19 deaths in East Branch, Renmin Hospital of Wuhan University from February 1 to March 7, 2020 was performed in clinical characteristics, laboratory results, causes of death MESHD, and subgroup comparison. Results: Totally 72.7% of the deaths ( male TRANS- female TRANS ratio: 51:26, average age TRANS at death: 71, mean survival time: 17.4 days) had hypertension HP hypertension MESHD, heart disease MESHD, diabetes MESHD, chronic lung disease HP chronic lung disease MESHD, and other comorbidities. Acute respiratory distress HP respiratory distress MESHD syndrome ( ARDS MESHD) and sepsis HP sepsis MESHD were the main causes of death MESHD. Increases in C-reactive protein (CRP), lactate dehydrogenase (LDH), D-dimer and lactic acid (LAC), and decreases in lymphocyte, cluster of differentiation (CD) 4+ and CD8+ cells were common in laboratory results. Subgroup analysis showed: 1) Most female TRANS deaths had cough HP cough MESHD and diabetes MESHD. 2) The male TRANS proportion in young and middle- aged TRANS deaths was higher; while elderly TRANS deaths were more prone to myocardial injury MESHD and elevated CRP. 3) There was no statistical difference between short-term and non-short-term survival subgroups. 4) CRP and LDH increased and CD4+ and CD8+ cells decreased significantly in patients with hypertension HP hypertension MESHD.Conclusions: The majority of COVID-19 deaths are males TRANS, especially the elderly TRANS with underlying diseases. The main causes of death include ARDS MESHD and sepsis HP sepsis MESHD. Most female TRANS deaths have cough HP cough MESHD and diabetes MESHD. Myocardial injury MESHD is common in elderly TRANS deaths. Patients with hypertension HP hypertension MESHD are prone to increased inflammatory index, tissue hypoxia MESHD and cellular immune injury.Authors Kaige Wang and Zhixin Qiu contributed equally to this work.

    Survival After In-Hospital Cardiac Arrest HP Cardiac Arrest MESHD In Critically MESHD Ill Patients: Implications For The Covid-19 Pandemic?

    Authors: Saket Girotra; Yuanyuan Tang; Paul Chan; Brahmajee K Nallamothu

    doi:10.1101/2020.04.11.20060749 Date: 2020-04-17 Source: medRxiv

    The coronavirus disease MESHD 2019 (COVID-19) outbreak is placing a considerable strain on U.S. healthcare systems. Due to presumptions of poor outcomes in such critically ill MESHD patients, many hospitals have started considering a universal do-not-resuscitate order in patients with confirmed Covid-19 given a limited supply of intensive care unit (ICU) beds and the potential risk of transmission TRANS of infection MESHD to healthcare workers during resuscitation. However, empirical data on survival of cardiac arrest HP cardiac arrest MESHD in Covid-19 patients are unavailable at this time. To inform this debate, we report survival outcomes following cardiopulmonary resuscitation in a cohort of similar critically ill patients with pneumonia HP pneumonia MESHD or sepsis HP sepsis MESHD who were receiving mechanical ventilation in an ICU at the time of arrest. The probability of survival without severe neurological disability MESHD (CPC of 1 or 2) ranged from less than 3% to over 22% across key patient subgroups, For patients with an initial rhythm of asystole MESHD or PEA, who were also receiving vasopressors at the time of arrest, fewer than 10% were discharged without severe neurological disability MESHD (CPC of 1 or 2), and this number dropped to less than 3% in patients over 80 years old. In contrast, survival rates were much higher in younger patients, patients with an initial rhythm of VF or pulseless VT MESHD, and in patients receiving ventilatory support without vasopressors. Our findings suggest caution in universal resuscitation policies. Even in a cohort of critically ill MESHD patients on mechanical ventilation, survival outcomes following in-hospital resuscitation were not uniformly poor and varied markedly depending on age TRANS, co-morbidities and illness severity. We believe that these data can help inform discussions among patients, providers and hospital leaders regarding resuscitation policies and goals of care in the context of the COVID-19 pandemic.

The ZB MED preprint Viewer preVIEW includes all COVID-19 related preprints from medRxiv and bioRxiv, from ChemRxiv, from ResearchSquare, from arXiv and from Preprints.org and is updated on a daily basis (7am CET/CEST).
The web page can also be accessed via API.

Sources


Annotations

All
None
MeSH Disease
Human Phenotype
Transmission
Seroprevalence


Export subcorpus as...

This service is developed in the project nfdi4health task force covid-19 which is a part of nfdi4health.

nfdi4health is one of the funded consortia of the National Research Data Infrastructure programme of the DFG.