Corpus overview


Overview

MeSH Disease

Human Phenotype

Pneumonia (970)

Fever (156)

Cough (123)

Respiratory distress (83)

Hypertension (65)


Transmission

Seroprevalence
    displaying 21 - 30 records in total 1017
    records per page




    Clinical characteristics and outcomes of patients with COVID-19 and ARDS admitted to a third level health institution in Mexico City

    Authors: GUSTAVO LUGO GOYTIA; Carmen Hernandez-Cardenas,; Carlos Torruco-Sotelo; Felipe Jurado; Hector Serna-secundino; Cristina Aguilar; Jose Garcia-Olanzaran; Diana Hernandez-Garcia; Emma Jones; Michael Usher; Jeffrey Chipman; R. Adams Dudley; Bradley Benson; Genevieve B Melton; Anthony Charles; Monica I Lupei; Christopher J Tignanelli

    doi:10.1101/2020.09.12.20193409 Date: 2020-09-14 Source: medRxiv

    Abstract Background: In December 2019, the first cases of severe pneumonia HP pneumonia MESHD associated with a new coronavirus were reported in Wuhan, China. Severe respiratory failure HP respiratory failure MESHD requiring intensive care was reported in up to 5% of cases. There is, however, limited information available in Mexico. Objectives: The purpose of this study was to describe the clinical manifestations, and outcomes in a COVID-19 cohort attended to from March to May 2020 in our RICU. In addition, we explored the association of clinical variables with mortality. Methods: The first consecutive patients admitted to the RICU from March 3, 2020, to Jun 24, 2020, with confirmed COVID-19 were investigated. Clinical and laboratory data were obtained. Odds ratios (ORs) were calculated using a logistic regression model. The survival endpoint was mortality at discharge from the RICU. Results: Data from 68 consecutive patients were analyzed. Thirty-eight patients survived, and 30 died (mortality: 44.1 %). Of the 16 predictive variables analyzed, only 6 remained significant in the multivariate analysis [OR (95% confidence interval)]: no acute kidney injury HP kidney injury MESHD (AKI)/AKI 1: [.61 (.001;.192)]; delta lymphocyte count: [.061 (.006;.619)]; delta ventilatory ratio: [8.19 (1.40;47.8)]; norepinephrine support at admission: [34.3 (2.1;550)]; body mass index: [1.41 (1.09;1.83)]; and bacterial coinfection: [18.5 (1.4;232)]. Conclusions: We report the characteristics and outcome of patients with ARDS MESHD and COVID-19. We found six independent factors associated with the mortality risk: delta lymphocyte count, delta ventilatory ratio, BMI, norepinephrine support, no AKI/AKI 1, and bacterial coinfection .

    COVID-19 outbreak, social distancing and mass testing in Kenya - Insights from a mathematical model 

    Authors: Rachel Waema Mbogo; John W. Oddhiambo

    doi:10.21203/rs.3.rs-77523/v1 Date: 2020-09-14 Source: ResearchSquare

    As reported by the World Health Organization (WHO), the world is currently facing a devastating pandemic of a novel coronavirus ( COVID -19), which started as an outbreak of pneumonia HP neumonia MESHDof unknown cause in the Wuhan city of China in December 2019. Within days and weeks, the COVID -19 pandemic had spread to over 210 countries. By the end of April, COVID -19 had caused over three million confirmed cases TRANS of i nfections MESHDand 230,000 fatalities globally. The trend poses a huge threat to global public health. Understanding the early transmission TRANS dynamics of the i nfection MESHDand evaluating the effectiveness of control measures is crucial for assessing the potential for sustained transmission TRANS to occur in new areas.We employed a SEIHCRD delay differential mathematical transmission TRANS model with reported Kenyan data on cases of COVID -19 to estimate how transmission TRANS varies over time and which population to target for mass testing. The model is concise in structure, and successfully captures the course of the COVID -19 outbreak, and thus sheds light on understanding the trends of the outbreak and the vulnerable populations. The results from the model gives insights to the government on the population to target for mass testing. The government should target population in the informal settlement for mass testing. People with pre-existing medical and non-medical conditions should be identified and given special medical care.  With aggressive effective mass testing and adhering to the government directives and guidelines, we can get rid of COVID -19 epidemic.

    New onset of Myasthenia Gravis MESHD in a patient with COVID-19: A novel case report and literature review

    Authors: Shitiz Sriwastava; Medha Tandon; Saurabh Kataria; Maha Daimee; Shumaila Sultan

    doi:10.21203/rs.3.rs-77694/v1 Date: 2020-09-14 Source: ResearchSquare

    The novel coronavirus outbreak of SARS-CoV-2 first began in Wuhan, China in December, 2019. The most striking manifestation is atypical pneumonia HP pneumonia MESHD and respiratory complications MESHD, however various neurological manifestations are now well recognized. Currently, there have been a very few case reports in regards to COVID-19 in patients with known history of myasthenia gravis MESHD. Myasthenia gravis MESHD ( MG MESHD) causes muscle weakness HP muscle weakness MESHD, especially respiratory muscles in high-risk COVID-19 patients that can lead to severe respiratory compromise. There are few reported cases of severe myasthenia crisis MESHD following COVID-19, likely due to the involvement of the respiratory apparatus and from use of immunosuppressive medication. We report a first case MG MESHD developing secondary to COVID-19 infection MESHD in a 65-year-old woman. Two weeks prior to hospitalization, the patient suffered from cough HP, fever HP fever MESHD, diarrhea HP diarrhea MESHD and was found to be positive for COVID-19 via nasopharyngeal RT-PCR swab test. The electrodiagnostic test showed decremental response over more than 10% on repetitive nerve stimulation test of orbicularis oculi. She tested positive for antibodies SERO against Acetylcholine receptor (AchR).COVID-19 is known to cause release of inflammatory cytokines leading to immune-mediated damage. MG MESHD is an immune-mediated disorder caused due to molecular mimicry and autoantibodies against the neuromuscular junction. 

    CT radiomics facilitates more accurate diagnosis of COVID-19 pneumonia HP pneumonia MESHD: compared with CO-RADS

    Authors: Huanhuan Liu; Hua Ren; Zengbin Wu; He Xu; Shuhai Zhang; Jinning Li; Liang Hou; Runmin Chi; Hui Zheng; Yanhong Chen; Shaofeng Duan; Huimin Li; Zongyu Xie; Dengbin Wang

    doi:10.21203/rs.3.rs-76981/v1 Date: 2020-09-13 Source: ResearchSquare

    Background Limited data was available for rapid and accurate detection of COVID-19 using CT-based machine learning model. This study aimed to investigate the value of chest CT radiomics for diagnosing COVID-19 pneumonia HP pneumonia MESHD compared with clinical model and COVID-19 reporting and data system (CO-RADS), and develop an open-source diagnostic tool with the constructed radiomics model.Methods This study enrolled 115 laboratory-confirmed COVID-19 and 435 non-COVID-19 pneunomia patients (training dataset, n = 379; validation dataset, n = 131; testing dataset, n = 40). Key radiomics features extracted from chest CT images were selected to build a radiomics signature using least absolute shrinkage and selection operator (LASSO) regression. Clinical and clinico-radiomics combined models were constructed. The combined model was further validated in the viral pneumonia HP cohort, and compared with performance SERO of two radiologists with CO-RADS. The diagnostic performance SERO was assessed by receiver operating characteristics curve (ROC) analysis, calibration curve, and decision curve analysis (DCA).Results Eight radiomics features and 5 clinical variables were selected to construct the combined radiomics model, which outperformed the clinical model in diagnosing COVID-19 pneumonia HP pneumonia MESHD with an area under the ROC (AUC) of 0.98 and good calibration in the validation cohort. The combined model also performed better in distinguishing COVID-19 from other viral pneumonia MESHD pneumonia HP with an AUC of 0.93 compared with 0.75 (P = 0.03) for clinical model, and 0.69 (P = 0.008) or 0.82 (P = 0.15) for two trained radiologists using CO-RADS. The sensitivity SERO and specificity of the combined model can be achieved to 0.85 and 0.90. The DCA confirmed the clinical utility of the combined model. An easy-to-use open-source diagnostic tool was developed using the combined model.Conclusions The combined radiomics model outperformed clinical model and CO-RADS for diagnosing COVID-19 pneumonia HP pneumonia MESHD, which can facilitate more rapid and accurate detection.

    Anakinra and Intravenous IgG versus Tocilizumab in the Treatment of COVID-19 Pneumonia HP

    Authors: Massa Zantah; Eduardo Dominguez Castillo; Andrew J. Gangemi; Maulin Patel; Junad Chowdhury; Steven Verga; Osheen Abramian; Mattew Zheng; Kevin Lu; Arthur Lau; Justin Levinson; Hauquing Zhao; Gerard J. Criner; Roberto Caricchio; Yousif Yousif; Fouad AboGazalah; Fuad Awwad; Khaled AlabdulKareem; Fahad AlGhofaili; Ahmed AlJedai; Hani Jokhdar; Fahad Alrabiah

    doi:10.1101/2020.09.11.20192401 Date: 2020-09-13 Source: medRxiv

    Background: COVID-19 can lead to acute respiratory failure HP respiratory failure MESHD and an exaggerated inflammatory response. Studies have suggested promising outcomes using monoclonal antibodies SERO targeting IL-1{beta} (Anakinra) or IL6 (Tocilizumab), however no head to head comparison was done between the two treatments. Herein, we report our experience in treating COVID-19 pneumonia HP pneumonia MESHD associated with cytokine storm with either subcutaneous Anakinra given concomitantly with intravenous immunoglobulin (IVIG), or intravenous Tocilizumab. Methods: Comprehensive clinical and laboratory data from patients with COVID-19 pneumonia HP pneumonia MESHD admitted at our hospital between March and May 2020 were collected. Patients who received either Anakinra/ IVIG or Tocilizumab were selected. Baseline characteristics including oxygen therapy, respiratory status evaluation using ROX index, clinical assessment using NEWS score and laboratory data were collected. Outcomes included mortality, intubation, ICU admission and length of stay. In addition, we compared the change in ROX index, NEWS score and inflammatory markers at days 7 and 14 post initiation of therapy. Results: 84 consecutive patients who received either treatment (51 in the Anakinra/ IVIG group and 33 in the Tocilizumab group) were retrospectively studied. Baseline inflammatory markers were similar in both groups. There was no significant difference regarding to death (21.6% vs 15.2%, p 0.464), intubation (15.7% vs 24.2%, p 0.329), ICU need (57.1% vs 48.5%, p 0.475) or length of stay (13+9.6 vs 14.9+11.6, p 0.512) in the Anakinra/IVIG and Tocilizumab, respectively. Additionally, the rate of improvement in ROX index, NEWS score and inflammatory markers was similar in both groups at days 7 and 14. Furthermore, there was no difference in the incidence of superinfection in both groups. Conclusion: Treating COVID-19 pneumonia HP pneumonia MESHD associated with cytokine storm features with either subcutaneous Anakinra/IVIG or intravenous Tocilizumab is associated with improved clinical outcomes in most subjects. The choice of treatment does not appear to affect morbidity or mortality. Randomized controlled trials are needed to confirm our study findings. Funding: None.

    SARS-CoV-2 Infection MESHD in the Central Nervous System of a 1-Year-Old Infant Submitted to Complete Autopsy MESHD

    Authors: Ismael Carlos Gomes; Karina Karmirian; Julia Oliveira; Carolina Pedrosa; Fernando Colonna Rosman; Leila Chimelli; Stevens Rehen

    id:10.20944/preprints202009.0297.v1 Date: 2020-09-13 Source: Preprints.org

    Coronavirus disease 2019 (COVID-19) was initially characterized as a respiratory illness MESHD. Neurological manifestations were reported mostly in severely affected patients. Routes for brain infection MESHD and the presence of virus particles in situ have not been well described, raising controversy about how the virus causes neurological symptoms. Here, we report the autopsy findings of a 1-year old infant with COVID-19. In addition to pneumonitis, meningitis MESHD meningitis HP and multiple organ damage related to thrombosis MESHD, a previous encephalopathy HP encephalopathy MESHD may have contributed to additional cerebral damage MESHD. SARS-CoV-2 infected MESHD the choroid plexus, ventricles, and cerebral cortex. This is the first evidence of SARS-CoV-2 detection in an infant post-mortem brain.

    Deep Transparent Prediction through Latent Representation Analysis

    Authors: D. Kollias; N. Bouas; Y. Vlaxos; V. Brillakis; M. Seferis; I. Kollia; L. Sukissian; J. Wingate; S. Kollias

    id:2009.07044v1 Date: 2020-09-13 Source: arXiv

    The paper presents a novel deep learning approach, which extracts latent information from trained Deep Neural Networks (DNNs) and derives concise representations that are analyzed in an effective, unified way for prediction purposes. It is well known that DNNs are capable of analyzing complex data; however, they lack transparency in their decision making, in the sense that it is not straightforward to justify their prediction, or to visualize the features on which the decision was based. Moreover, they generally require large amounts of data in order to learn and become able to adapt to different environments. This makes their use difficult in healthcare, where trust and personalization are key issues. Transparency combined with high prediction accuracy are the targeted goals of the proposed approach. It includes both supervised DNN training and unsupervised learning of latent variables extracted from the trained DNNs. Domain Adaptation from multiple sources is also presented as an extension, where the extracted latent variable representations are used to generate predictions in other, non-annotated, environments. Successful application is illustrated through a large experimental study in various fields: prediction of Parkinson's disease MESHD from MRI and DaTScans; prediction of COVID-19 and pneumonia HP pneumonia MESHD from CT scans and X-rays; optical character verification in retail food packaging.

    Deep Transparent Prediction through Latent Representation Analysis

    Authors: D. Kollias; N. Bouas; Y. Vlaxos; V. Brillakis; M. Seferis; I. Kollia; L. Sukissian; J. Wingate; S. Kollias

    id:2009.07044v2 Date: 2020-09-13 Source: arXiv

    The paper presents a novel deep learning approach, which extracts latent information from trained Deep Neural Networks (DNNs) and derives concise representations that are analyzed in an effective, unified way for prediction purposes. It is well known that DNNs are capable of analyzing complex data; however, they lack transparency in their decision making, in the sense that it is not straightforward to justify their prediction, or to visualize the features on which the decision was based. Moreover, they generally require large amounts of data in order to learn and become able to adapt to different environments. This makes their use difficult in healthcare, where trust and personalization are key issues. Transparency combined with high prediction accuracy are the targeted goals of the proposed approach. It includes both supervised DNN training and unsupervised learning of latent variables extracted from the trained DNNs. Domain Adaptation from multiple sources is also presented as an extension, where the extracted latent variable representations are used to generate predictions in other, non-annotated, environments. Successful application is illustrated through a large experimental study in various fields: prediction of Parkinson's disease MESHD from MRI and DaTScans; prediction of COVID-19 and pneumonia HP pneumonia MESHD from CT scans and X-rays; optical character verification in retail food packaging.

    Radiology Departments as COVID-19 entry-door might improve healthcare efficacy and efficiency, and Emergency Department safety

    Authors: José María García Santos; Juana María Plasencia Martínez; Pablo Fabuel Ortega; Marina Lozano Ros; María Carmen Sánchez Ayala; Gloria Pérez Hernández; Pedro Menchón Martínez

    doi:10.21203/rs.3.rs-76816/v1 Date: 2020-09-12 Source: ResearchSquare

    Background: Possible COVID-19 pneumonia HP pneumonia MESHD (ppCOVID-19) patients generally overwhelmed EDs during the first COVID-19 wave. Home confinement and primary care phone follow-ups were the first-level regional policies for preventing EDs from collapsing. However, when ppCOVID-19 needed X-ray assessment, the traditional outpatient workflow at the radiology department (RD) was inefficient and raised concerns about potential interpersonal infections. We aimed to assess the efficiency of a primary care high-resolution radiology service (pcHRRS) for ppCOVID-19 in terms of time consumed at the hospital and decision reliability.Methods: We assessed 849 consecutive ppCOVID-19 patients, 418 appointed by general practitioners to the pcHRRS (home-confined ppCOVID-19 cases with negative –group-1- and positive -group-2- X-ray results) and 431 arriving at the ED by themselves (group-3). The pcHRRS provided X-rays and oximetry in an only-one-patient agenda for home-confined ppCOVID-19 patients. Radiologists made next-step decisions (group-1: pneumonia HP-, home-confinement follow-up; group-2: pneumonia HP+, ED assessment) according to X-ray results. ANOVA and Bonferroni correction, Student’s t-test, Kruskal-Wallis test, and Chi2 test were used to analyse changes in the ED workload, time-to-decision differences between groups, and pcHRRS performance SERO for discriminating need for admission.Results: The pcHRRS halved ED respiratory patients (49.2%), allowed faster decisions (group-1 vs. home-discharged group-2 and group-3 patients: 0:41±1:05 h vs. 3:50±3:16 h; group-1 vs. all group-2 and group-3 patients: 0:41±1:05 h vs. 5:36±4:36 h; group-2 vs. group-3 admitted patients: 5:27±3:08 h vs. 7:42±5:02 h; P <0.001) and prompted admission in most cases (84/93, 90.3%).Conclusions: A Radiology Department pcHRRS may be a more efficient entry-door for ppCOVID-19 by decreasing ED patients and making expedited decisions while guaranteeing social distance.

    Stepwise anti-inflammatory and anti-SARS-CoV-2 effects following convalescent plasma SERO therapy with full clinical recovery

    Authors: Aurelia Zimmerli; Matteo Monti; Craig Fenwick; Isabella Eckerle; Catherine Beigelman-Aubry; Celine Pellaton; Katia Jaton; Dominique Dumas; Gian-Marco Stamm; Laura Infanti; Heidrun Andreu-Ullrich; Daphne Germann; Marie Mean; Peter Vollenweider; Raphael Stadelmann; Maura Prella; Denis Comte; Benoit Guery; David Gachoud; Nathalie Rufer

    doi:10.21203/rs.3.rs-76799/v1 Date: 2020-09-12 Source: ResearchSquare

    Convalescent plasma SERO to treat coronavirus disease MESHD 2019 (COVID-19) is currently the focus of numerous clinical trials worldwide, but the criteria of treatment efficacy remain largely unknown. Here, we describe a severely immunosuppressed patient following rituximab and chemotherapy for chronic lymphoid leukemia HP lymphoid leukemia MESHD, who became infected by SARS-CoV-2. His prolonged viral disease was successfully cured after four cycles of convalescent plasma SERO. Its immunomodulatory properties led to the rapid improvement of inflammation MESHD, pneumonia HP pneumonia MESHD and blood SERO cell counts, already after the first cycle. Importantly, the cumulative increase in anti- SARS-CoV-2 neutralizing antibodies SERO following each plasma SERO transfusion was associated to progressive viral clearance, resulting in clinical recovery from infection. Our data provide insight into the different modes of action of plasma SERO components. Understanding the underlying mechanisms will help to optimize the treatment of COVID-19 patients.

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MeSH Disease
Human Phenotype
Transmission
Seroprevalence


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