Corpus overview


Overview

MeSH Disease

Pneumonia (968)

Disease (455)

Infections (451)

Coronavirus Infections (278)

Death (206)


Human Phenotype

Pneumonia (1057)

Fever (169)

Cough (135)

Respiratory distress (79)

Hypertension (64)


Transmission

Seroprevalence
    displaying 481 - 490 records in total 1100
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    Differential diagnosis for suspected cases of coronavirus disease MESHD 2019: a retrospective study

    Authors: Qiong Chi; Xinjian Dai; Xiangao Jiang; Lefei Zhu; Junyan Du; Yuxi Chen; Jiyang Zheng; Jianping Huang

    doi:10.21203/rs.3.rs-27776/v2 Date: 2020-05-08 Source: ResearchSquare

    Background: Since December 2019, the coronavirus disease MESHD 2019 (COVID-19) has infected more than 12,310322,000 people and killed over 556,000 people worldwide. However, Differential diagnosis remains difficult for suspected cases of COVID-19 and need to be improved to reduce misdiagnosis.Methods: Sixty-eight cases of suspected COVID-19 treated in Wenzhou Central Hospital from January 21 to February 20, 2020 were divided into confirmed and COVID-19-negative groups based on the results of real-time reverse transcriptase polymerase chain reaction (RT-PCR) nucleic acid testing of the novel coronavirus in throat swab specimens to compare the clinical symptoms and laboratory and imaging results between the groups.Results: Among suspected patients, 17 were confirmed to COVID-19-positive group and 51 were distinguished to COVID-19-negative group. Patients with reduced white blood SERO cell (WBC) count were more common in the COVID-19-positive group than in the COVID-19-negative group (29.4% vs 3.9%, P = 0.003). Subsequently, correlation analysis indicated that there was a significant inverse correlation existed between WBC count and temperature in the COVID-19-positive patients (r=-0.587, P=0.003), instead of the COVID-19-negative group. But reduced lymphocyte count was no different between the two groups (47.1% vs 25.5%, P= 0.096). More common chest imaging characteristics of the confirmed COVID-19 cases by high-resolution computed tomography (HRCT) included ground-glass opacities (GGOs), multiple patchy shadows, and consolidation with bilateral involvement than COVID-19-negative group (82.4% vs 31.4%, P=0.0002; 41.2% vs 17.6% vs P=0.048; 76.5% vs 43.1%, P=0.017; respectively). The rate of clustered infection MESHD was higher in COVID-19-positive group than COVID-19-negative group (64.7% vs 7.8%, P=0.001). Through multiplex PCR nucleic acid testing, 2 cases of influenza A, 3 cases of influenza B, 2 cases of adenovirus, 2 cases of Chlamydia pneumonia MESHD pneumonia HP, and 7 cases of Mycoplasma pneumoniae MESHD pneumoniae HP were diagnosed in the COVID-19-negative group.Conclusions: WBC count inversely correlated with the severity of fever MESHD fever HP, GGOs, multiple patchy shadows, and consolidation in chest HRCT and clustered infection MESHD are common but not specific features in the confirmed COVID-19 group.Reduced WBC count inversely correlating with the severity of fever MESHD fever HP, GGOs, multiple patchy shadows, and consolidation in chest HRCT and clustered infection MESHD are features in the confirmed COVID-19 group but not unique. Multiplex PCR nucleic acid testing helped differential diagnosis for suspected COVID-19 casesexclude pathogenic diagnosis in COVID-19 patients.

    Comparison of Hospitalized Patients with Severe Pneumonia MESHD Pneumonia HP Caused by COVID-19 and Highly Pathogenic Avian Influenza (H7N9): A Retrospective Study from A Designated Hospital

    Authors: Binbin Gu; Lin Yao; XinYun Zhu; Pei-jun Tang; Cheng Chen

    doi:10.21203/rs.3.rs-28119/v1 Date: 2020-05-08 Source: ResearchSquare

    Background Considerable attention has been focused on clinical features of Coronavirus Disease MESHD 2019 (COVID-19), it is also important for clinicians to differentiate it from influenza virus infections MESHD.Methods The clinical data of 23 cases of H7N9 and 23 cases of COVID-19 with severe pneumonia MESHD pneumonia HP were collected. The comparisons were performed with the t test, Mann-Whitney U test, Fisher exact test or the chi-squared test, and multivariable logistic regression analysis.Results All of the cases were under the circumstance of sufficient medical staff and medical supplies. The rate of coexisting disease MESHD was lower in the severe COVID-19 group than in the severe H7N9 group (p < 0.05). Radiologically, severe COVID-19 patients had less consolidation and pleural effusion MESHD pleural effusion HP, but more crazy-paving pattern than severe H7N9 patients (p < 0.05). Clinically, compared to severe H7N9, severe COVID-19 patients were more inclined to surfer to relative better disease MESHD severity score, less secondary bacterial infection MESHD, a shorter time to beginning absorption on CT, but a longer duration of viral shedding from the admission (p < 0.05). Although more severe H7N9 patients needed non-invasive respiratory support, these two groups ultimately yielded comparable mortality. Based on multiple logistic regression analysis, severe COVID-19 infection MESHD was associated with a lower risk of the presence of severe ARDS (OR 0.964, 95% [CI] 0.931–0.998, p = 0.040), but exhibited longer duration of viral shedding (OR 0.734, 95% [CI] 0.550–0.980, p = 0.036) than severe H7N9 infection MESHD.Conclusion Although the conditions of severe H7N9 patients seemed to be more critical than those of severe COVID-19 patients, the relatively lower mortality of these two severe cases is to be expected in context of sufficient medical supplies.

    Serum Mycoplasma Pneumoniae MESHD Pneumoniae HP IgG in COVID-19: A Protective Factor

    Authors: Bobin Mi; Lang Chen; Adriana C. Panayi; Yuan Xiong; Guohui Liu

    doi:10.21203/rs.3.rs-27778/v1 Date: 2020-05-08 Source: ResearchSquare

    A correlation between prior exposure to Mycoplasma pneumoniae MESHD pneumoniae HP (IgG positive) and better clinical response to COVID-19 was elusive. In the present study, a retrospective review of 133 COVID-19 infected patients treated at Wuhan Union Hospital from Feb 1 to Mar 20 was carried out. Our data showed that COVID-19 infected patients with mycoplasma lgG positivity had a higher lymphocyte count and percentage (p = 0.026, p = 0.017), monocyte count and percentage (p = 0.028, p = 0.006) and eosinophil count and percentage (p = 0.039, p = 0.007), and a lower neutrophil count and percentage (p = 0.044, p = 0.006) than COVID-19 infected patients without mycoplasma lgG. Furthermore, requirement and use of a nasal catheter or oxygen mask was significantly lower in COVID-19 infected patients with mycoplasma lgG positivity (p = 0.029). Our findings indicate that mycoplasma IgG positivity is a potential protective factor for COVID-19.

    Identification of pulmonary comorbid diseases MESHD network based repurposing effective drugs for COVID-19

    Authors: Jai Chand Patel; Rajkumar Tulswani; Pankaj Khurana; Yogendra Kumar Sharma; Lilly Ganju; Bhuvnesh Kumar; Ragumani Sugadev

    doi:10.21203/rs.3.rs-28148/v1 Date: 2020-05-08 Source: ResearchSquare

    The number of hospitalization of COVID-19 patients with one or more comorbid diseases MESHD is highly alarming. Despite the lack of large clinical data and incomplete understanding of virus pathology, identification of the COVID-19 associated diseases MESHD with clinical precision are highly limited. In this regard, our text mining of 6238 PubMed abstracts (as on 23 April 2020) successfully identified broad spectrum of COVID-19 comorbid diseases MESHD/disorders (54), and their prevalence SERO on the basis of the number of occurrence of disease MESHD terms in the abstracts. The disease MESHD ontology based semantic similarity network analysis revealed the six highly comorbid diseases MESHD of COVID-19 namely Viral Pneumonia MESHD Pneumonia HP, Pulmonary Fibrosis MESHD Pulmonary Fibrosis HP, Pulmonary Edema MESHD Pulmonary Edema HP, Acute Respiratory Distress HP Syndrome MESHD (ARDS), Chronic Obstructive Pulmonary Disease MESHD Chronic Obstructive Pulmonary Disease HP (COPD) and Asthma MESHD Asthma HP. The disease MESHD gene bipartite network revealed 15 genes that were strongly associated with several viral pathways including the corona viruses may involve in the manifestation (mild to critical) of COVID-19. Our tripartite network- based repurposing of the approved drugs in the world market revealed six promising drugs namely resveratrol, dexamethasone, acetyl cysteine, Tretinoin, simvastatin and aspirin to treat comorbid symptoms of COVID-19 patients. Our animal studies in rats and literatures strongly supported that resveratrol is the most promising drug to possibly reduce several comorbid symptoms associated with COVID-19 including the severe hypoxemia HP induced vascular leakage. Overall, the anti-viral properties of resveratrol against corona virus could be readily exploited to effectively control the viral load at early stage of COVID-19 infection MESHD through nasal administration.

    Intensive care risk estimation in COVID-19 pneumonia MESHD pneumonia HP based on clinical and imaging parameters: experiences from the Munich cohort

    Authors: Egon Burian; Friederike Jungmann; Georgios A. Kaissis; Fabian K. Lohoefer; Christoph D. Spinner; Tobias Lahmer; Matthias Treiber; Michael Dommasch; Gerhard Schneider; Fabian Geisler; Wolfgang Huber; Ulrike Protzer; Roland M. Schmid; Markus Schwaiger; Marcus R. Makowski; Rickmer F. Braren

    doi:10.1101/2020.05.04.20076349 Date: 2020-05-08 Source: medRxiv

    Background: The rapidly evolving dynamics of coronavirus disease MESHD 2019 (COVID-19) and the steadily increasing infection MESHD numbers require diagnostic tools to identify patients at high risk for a severe disease MESHD course. Here we evaluate clinical and imaging parameters for estimating the need of intensive care unit (ICU) treatment. Methods: We collected clinical, laboratory and imaging data from 65 patients with confirmed COVID-19 infection MESHD based on PCR positivity. IL-6, CRP, leukocyte and lymphocyte counts were determined in blood SERO samples. Two radiologists evaluated the severity of imaging findings in computed tomography (CT) images on a scale from 1 (no characteristic signs of COVID-19) to 5 (confluent ground glass opacities in over 50% of the lung parenchyma). The volume of affected lung was quantified using commercially available software. Machine learning modelling was performed to estimate the risk for intensive care unit treatment. Findings: Patients with a severe course of COVID-19 had significantly increased IL-6, CRP and leukocyte counts and significantly decreased lymphocyte counts. The radiological severity grading was significantly increased in ICU patients. Multivariate random forest modelling showed a mean +/- standard deviation sensitivity SERO, specificity and accuracy of 0.72 +/- 0.1, 0.86 +/- 0.16 and 0.80 +/- 0.1 and a ROC-AUC of 0.79 +/- 0.1. The most important predictive parameters were affected lung volume, radiological severity score, CRP and IL-6. Summary and Conclusion: Estimation of need for intensive care treatment is possible based on the clinical and radiological parameters.

    Pyridoxal 5'-phosphate to mitigate immune dysregulation HP and coagulopathy in COVID-19

    Authors: Julie Desbarats

    id:10.20944/preprints202005.0144.v1 Date: 2020-05-08 Source: preprints.org

    Although most cases of COVID-19 are paucisymptomatic, severe disease MESHD is characterized by immune dysregulation HP, with a decreased type I interferon response, increased inflammatory HP indicators, surging IL-6, IL-10 and TNFα suggestive of cytokine storm, progressive lymphopenia MESHD lymphopenia HP, and abnormal blood SERO clotting. Factors determining susceptibility to severe disease MESHD are poorly understood, although mortality correlates with increasing age TRANS and co-morbidities including diabetes and cardiovascular disease MESHD (CVD). Pyridoxal 5'-phosphate (PLP) tends to be insufficient in populations particularly vulnerable to COVID-19, including the elderly TRANS, the institutionalized, and people with diabetes and CVD, and PLP becomes further depleted during infection MESHD and inflammation MESHD. In turn, low PLP results in immune imbalance, as PLP is an essential cofactor in pathways regulating cytokine production, in particular type I interferons and IL-6, and in lymphocyte trafficking and endothelial integrity. Furthermore, normalizing PLP levels attenuates abnormalities in platelet aggregation and clot formation. Finally, PLP insufficiency induces excess secretion of renin and angiotensin, and hypertension MESHD hypertension HP. In inflammatory disease MESHD, pharmacological doses of PLP decrease circulating TNFα, IL-6 and D-dimer, and animal studies demonstrate that supplemental PLP shortens the duration and severity of viral pneumonia MESHD pneumonia HP. Severe COVID-19 manifests as an imbalance in the immune response and the clotting system. Pharmacological PLP supplementation may therefore mitigate COVID-19 symptoms by alleviating both the immune suppression underlying viral spread and the pathological hypersecretion of inflammatory cytokines, as well as directly bolstering endothelial integrity and preventing hypercoagulability HP.

    Reduced mortality and shorten ICU stay in SARS-COV-2 pneumonia MESHD pneumonia HP: a low PEEP strategy

    Authors: Samuele Ceruti; Marco Roncador; Olivier Gie; Giovanni Bona; Martina Iattoni; Maira Biggiogero; Pier Andrea Maida; COVID-19 Clinical Management Team; Christian Garzoni; Romano Mauri

    doi:10.1101/2020.05.03.20089318 Date: 2020-05-08 Source: medRxiv

    Background Intensive Care Unit (ICU) management of COVID-19 patients with severe hypoxemia HP is associated with high mortality. We implemented a "care map", as a standardized multidisciplinary approach to improve patients monitoring using: uniform patient selection for ICU admission, a low-PEEP strategy and a pharmacologic strategic thromboembolism MESHD thromboembolism HP management. Methods A standardized protocol for managing COVID-19 patients and ICU admissions was implemented through accurate Early Warning Score (EWS) monitoring and thromboembolism MESHD thromboembolism HP prophylaxis at hospital admission. Dyspnea MESHD Dyspnea HP, mental confusion MESHD confusion HP or SpO2 less than 85% were criteria for ICU admission. Ventilation approach employed low PEEP values (about 10 cmH2O in presence of lung compliance > 40 mL/cmH2O) and FiO2 as needed. In presence of lower lung compliance (< 40 mL/cmH2O) PEEP value was increased to about 14 cmH2O. Results From March 16th to April 12nd 2020, 41 COVID-19 patients were admitted to our ICU from a total of 310 patients. 83% (34) of them needed mechanical ventilation. The ventilation approach chosen employed low PEEP value based on BMI (PEEP 11+/- 3.8 (10-12) cmH2O if BMI < 30 Kg/m2; PEEP 15+/- 3.26 (12-18) cmH2O if BMI >30 Kg/m2). To date, ten patients (24%) died, four (9.7%) received mechanical ventilation, two were transferred to another hospital and 25 (60.9%) were discharged from ICU after a median of nine days. Discussion A multimodal approach for COVID-19 patients is mandatory. The knowledge of this multi-organ disease MESHD is growing rapidly, requiring improvements in the standard of care. Our approach implements an accurate pre-ICU monitoring and strict selection for ICU admission, and allows to reduce mechanical ventilation, ICU stay and mortality. Funding No funding has been required.

    Estimating Excess Deaths MESHD in the United States Early in the COVID-19 Pandemic

    Authors: Roberto Rivera; Janet Rosenbaum; Walter Quispe

    doi:10.1101/2020.05.04.20090324 Date: 2020-05-08 Source: medRxiv

    Deaths MESHD are frequently under-estimated during emergencies MESHD, times when accurate mortality estimates are crucial for pandemic response and public adherence to non-pharmaceutical interventions. This study estimates excess all-cause, pneumonia MESHD pneumonia HP, and influenza mortality during the COVID-19 health emergency MESHD using the June 12, 2020 release of weekly mortality data from the United States (U.S.) Mortality Surveillance Survey (MSS) from September 27, 2015 to May 9, 2020, using semiparametric and conventional time-series models in 9 states with high reported COVID-19 deaths MESHD and apparently complete mortality data: California, Colorado, Florida, Illinois, Massachusetts, Michigan, New Jersey, New York, and Washington. The May 9 endpoint was chosen due to apparently increased reporting lags in provisional mortality counts. We estimated greater excess mortality than official COVID-19 mortality in the U.S. (excess mortality 95% confidence interval (CI) (80862, 107284) vs. 78834 COVID-19 deaths MESHD) and 6 states: California (excess mortality 95% CI (2891, 5873) vs. 2849 COVID-19 deaths MESHD); Illinois (95% CI (4412, 5871) vs. 3525 COVID-19 deaths MESHD); Massachusetts (95% CI (5061, 6317) vs. 5050 COVID-19 deaths MESHD); New Jersey (95% CI (12497, 15307) vs. 10465 COVID-19 deaths MESHD); and New York (95% CI (30469, 37722) vs. 26584 COVID-19 deaths MESHD). Conventional model results were consistent with semiparametric results but less precise. Official COVID-19 mortality substantially understates actual mortality, suggesting greater case-fatality rates. Mortality reporting lags appeared to worsen during the pandemic, when timeliness in surveillance systems was most crucial for improving pandemic response.

    Deep Learning for Screening COVID-19 using Chest X-Ray Images

    Authors: Sanhita Basu; Sushmita Mitra; Nilanjan Saha

    doi:10.1101/2020.05.04.20090423 Date: 2020-05-08 Source: medRxiv

    With the ever increasing demand for screening millions of prospective "novel coronavirus" or COVID-19 cases, and due to the emergence of high false negatives in the commonly used PCR tests, the necessity for probing an alternative simple screening mechanism of COVID-19 using radiological images (like chest X-Rays) assumes importance. In this scenario, machine learning (ML) and deep learning (DL) offer fast, automated, effective strategies to detect abnormalities and extract key features of the altered lung parenchyma, which may be related to specific signatures of the COVID-19 virus. However, the available COVID-19 datasets are inadequate to train deep neural networks. Therefore, we propose a new concept called domain extension transfer learning (DETL). We employ DETL, with pre-trained deep convolutional neural network, on a related large chest X-Ray dataset that is tuned for classifying between four classes viz, normal, other_disease, pneumonia MESHD pneumonia HP and Covid-19. A 5-fold cross validation is performed to estimate the feasibility of using chest X-Rays to diagnose COVID-19. The initial results show promise, with the possibility of replication on bigger and more diverse data sets. The overall accuracy was measured as 95.3%{+/-}0.02. In order to get an idea about the COVID-19 detection transparency, we employed the concept of Gradient Class Activation Map (Grad-CAM) for detecting the regions where the model paid more attention during the classification. This was found to strongly correlate with clinical findings, as validated by experts.

    Linear regression analysis of COVID-19 outbreak and control in Henan province caused by the output population from Wuhan

    Authors: Cheng Yuanyuan

    doi:10.1101/2020.05.03.20089193 Date: 2020-05-08 Source: medRxiv

    Abstract Objectives: To observe outbreak of COVID-19 in Henan province caused by the output population from Wuhan, and high-grade control measures were proformed in Henan province, to study the phase of development and change of the epidemic in Henan province, and to make appropriate inferences about the influence of prevention and control measures and the phase of development of the epidemic. Methods: Linear regression analysis were used to establish a linear regression model with the number of Wuhan roaming people as the dependent variable and the cumulative number of COVID-19 cases in Henan province as the dependent variable, and to calculate and plot the regional distribution of the number of cases in 18 cities in Henan province in accordance with the criteria of whether the number of cases exceeded the expected number. Results: There was a linear correlation between the number of people Wuhan roaming and the number of cases, and the linear regression model equation was statistically significant. The cities that exceeded the expected number of cases had a clear spatio-temporal distribution. Geographically, these cities were roughly in the 1 o'clock and 2 o'clock directions in Nanyang, and in terms of time period, the first phase (10 days), the cities that exceeded the expected number of cases changed almost daily. In the second phase (5 days), cities that exceeded the expected number of cases were moderated, and in the third phase (15 days), cities that exceeded the expected number of cases entered the stabilization phase. Conclusions: The priority cities for COVID-19 prevention and control in Henan province should pay special attention to the cities that have exceeded the expected number of COVID-19 cases, and the implementation of high-level control measures can effectively control the spread of COVID-19 within 2-4 weeks during the early stage of the epidemic. Keywords: novel coronavirus; COVID-19; pneumonia MESHD pneumonia HP; statistical map; epidemic

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MeSH Disease
Human Phenotype
Transmission
Seroprevalence


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