Corpus overview


MeSH Disease

HGNC Genes

SARS-CoV-2 proteins

There are no SARS-CoV-2 protein terms in the subcorpus


SARS-CoV-2 Proteins
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    Constructing and Evaluating an Explainable Model for COVID-19 MESHD Diagnosis from Chest X-rays

    Authors: Rishab Khincha; Soundarya Krishnan; Tirtharaj Dash; Lovekesh Vig; Ashwin Srinivasan

    id:2012.10787v2 Date: 2020-12-19 Source: arXiv

    In this paper, our focus is on constructing models to assist a clinician in the diagnosis of COVID-19 MESHD patients in situations where it is easier and cheaper to obtain X-ray data than to obtain high-quality images like those from CT scans. Deep neural networks have repeatedly been shown to be capable of constructing highly predictive models for disease detection directly from image data. However, their use in assisting clinicians has repeatedly hit a stumbling block due to their black-box nature. Some of this difficulty can be alleviated if predictions were accompanied by explanations expressed in clinically relevant terms. In this paper, deep neural networks are used to extract domain-specific features(morphological features like ground-glass opacity MESHD and disease indications like pneumonia MESHD) directly from the image data. Predictions about these features are then used to construct a symbolic model (a decision tree) for the diagnosis of COVID-19 MESHD from chest X-rays, accompanied with two kinds of explanations: visual (saliency maps, derived from the neural stage), and textual (logical descriptions, derived from the symbolic stage). A radiologist rates the usefulness of the visual and textual explanations. Our results demonstrate that neural models can be employed usefully in identifying domain-specific features from low-level image data; that textual explanations in terms of clinically relevant features may be useful; and that visual explanations will need to be clinically meaningful to be useful.

    Characterization of Confirmed and Suspected COVID-19 MESHD Pneumonia Patients in a Retrospective Cohort Study in Wuhan

    Authors: Maomao Xi; Dan Cui; Qiaomei Liu; Lili Li; Yilin Yin; Fang Dong; Di Xiong; Yuwei Wu; Hongrong Guo; Min Bao; Zhanghua Li; Man Luo; Juan Wu; Weiguo Xie; Qingming Wu; Anlin Peng; Jinhu Wu; Yiqing Tan; Jianbin Sun; Pengcheng Luo; Zan Huang; Xiaodong Huang

    doi:10.21203/ Date: 2020-10-13 Source: ResearchSquare

    Background: A methodical comparison of confirmed and suspected COVID-19 MESHD patients has not been previously reported. Therefore, we thoroughly analyzed the demographic and clinical characteristics between these groups to identify mortality risk factors.Methods: A retrospective cohort of 1,276 hospitalized COVID-19 MESHD pneumonia MESHD patients at Tongren Hospital (Wuhan, China; January 27 to March 3, 2020) was studied. Cox regression analyses were performed to evaluate multiple mortality risk factors. Results: Both cohorts of confirmed (n=797) and suspected (n=479) patients exhibited typical demographic, clinical, and radiological characteristics. Treatment methods were consistent and both groups shared similarities in many demographic and clinical characteristics: age (≥65, 45.9% vs 41.8%, P=0.378) and lung disease MESHD (12.5% vs 14.6%, P=0.293). However, confirmed patients exhibited more severe disease manifestations than those in suspected patients: a higher incidence of fever MESHD (65.4% vs 58.0%, P<0.01), lower lymphocyte count (1.12×109/L vs 1.22×109/L, P=0.022), higher C-reactive protein HGNC ( CRP HGNC) (11.60 mg/L vs 7.61mg/L, P=0.021), and more severe radiographic manifestations ( lung infection MESHD incidence, 3.8% vs 3.0%, P=0.014; ground-glass opacity lesion incidence, 2.3% vs 2.0%, P=0.033). The dynamic profiles of lymphocytes, monocytes, D-dimer, and CRP HGNC, clearly delineated confirmed patients from suspected patients exhibiting critical illness. Cox regression analysis demonstrated that lung disease MESHD (adjusted hazard ratio 8.972, 95% CI: 3.782-21.283), cardiovascular disease MESHD (3.083, 1.347-7.059), neutrophil count (1.189, 1.081-1.307), age (1.068, 1.027-1.110), and ground-glass opacity lesions MESHD (1.039, 95% 1.013-1.065), were the main risk factors for mortality in confirmed patients; lung disease MESHD (14.725, 2.187-99.147), age (1.076, 1.004-1.153), and CRP HGNC level (1.012, 95% CI 1.004-1.020) were the primary factors in suspected patients.Conclusions: Suspected patients with serious illness should seek medical attention to reduce mortality. Multiple factors must be assessed to determine the mortality risk and the appropriate treatment. 

    Deep Learning-based Four-region Lung Segmentation in Chest Radiography for COVID-19 MESHD Diagnosis

    Authors: Young-Gon Kim; Kyungsang Kim; Dufan Wu; Hui Ren; Won Young Tak; Soo Young Park; Yu Rim Lee; Min Kyu Kang; Jung Gil Park; Byung Seok Kim; Woo Jin Chung; Mannudeep K. Kalra; Quanzheng Li

    id:2009.12610v1 Date: 2020-09-26 Source: arXiv

    Purpose. Imaging plays an important role in assessing severity of COVID 19 pneumonia MESHD. However, semantic interpretation of chest radiography (CXR) findings does not include quantitative description of radiographic opacities. Most current AI assisted CXR image analysis framework do not quantify for regional variations of disease. To address these, we proposed a four region lung segmentation method to assist accurate quantification of COVID 19 pneumonia MESHD. Methods. A segmentation model to separate left and right lung is firstly applied, and then a carina and left hilum detection network is used, which are the clinical landmarks to separate the upper and lower lungs. To improve the segmentation performance of COVID 19 images, ensemble strategy incorporating five models is exploited. Using each region, we evaluated the clinical relevance of the proposed method with the Radiographic Assessment of the Quality of Lung Edema MESHD (RALE). Results. The proposed ensemble strategy showed dice score of 0.900, which is significantly higher than conventional methods (0.854 0.889). Mean intensities of segmented four regions indicate positive correlation to the extent and density scores of pulmonary opacities under the RALE framework. Conclusion. A deep learning based model in CXR can accurately segment and quantify regional distribution of pulmonary opacities MESHD in patients with COVID 19 pneumonia MESHD.

    Humoral response to SARS-CoV-2 by healthy and sick dogs during COVID-19 pandemic MESHD COVID-19 pandemic MESHD in Spain.

    Authors: Ana Judith Perise-Barrios; Beatriz Davinia Tomeo-Martin; Pablo Gomez-Ochoa; Pablo Delgado-Bonet; Pedro Plaza; Paula Palau-Concejo; Jorge Gonzalez; Gustavo Ortiz-Diez; Antonio Melendez-Lazo; Michaela Gentil; Javier Garcia-Castro; Alicia Barbero-Fernandez

    doi:10.1101/2020.09.22.308023 Date: 2020-09-22 Source: bioRxiv

    COVID-19 MESHD is a zoonotic disease MESHD originated by SARS-CoV-2. Infection of animals with SARS-CoV-2 are being reported during last months, and also an increase of severe lung pathologies in domestic dogs has been detected by veterinarians in Spain. Therefore it is necessary to describe the pathological processes in those animals that show symptoms similar to those described in humans affected by COVID-19 MESHD. The potential for companion animals contributing to the continued human-to-human disease, infectivity, and community spread is an urgent issue to be considered. Forty animals with pulmonary pathologies were studied by chest X-ray, ultrasound study, and computed tomography. Nasopharyngeal and rectal swab were analyzed to detect canine pathogens, including SARS-CoV-2. Twenty healthy dogs living in SARS-CoV-2 positive households were included. Immunoglobulin detection by different immunoassays was performed. Our findings show that sick dogs presented severe alveolar MESHD or interstitial pattern, with pulmonary opacity MESHD, parenchymal abnormalities MESHD, and bilateral lesions. Forty dogs were negative for SARS-CoV-2 but Mycoplasma spp. was detected in 26 of 33 dogs. Five healthy and one pathological dog presented IgG against SARS-CoV-2. Here we report that despite detecting dogs with IgG -SARS-CoV-2, we never obtained a positive RT-qPCR, not even in dogs with severe pulmonary disease MESHD; suggesting that even in the case of a canine infection transmission would be unlikely. Moreover, dogs living in COVID-19 MESHD positive households could have been more exposed to be infected during outbreaks.

    UMLS-ChestNet: A deep convolutional neural network for radiological findings, differential diagnoses and localizations of COVID-19 MESHD in chest x-rays

    Authors: Germán González; Aurelia Bustos; José María Salinas; María de la Iglesia-Vaya; Joaquín Galant; Carlos Cano-Espinosa; Xavier Barber; Domingo Orozco-Beltrán; Miguel Cazorla; Antonio Pertusa

    id:2006.05274v1 Date: 2020-06-06 Source: arXiv

    In this work we present a method for the detection of radiological findings, their location and differential diagnoses from chest x-rays. Unlike prior works that focus on the detection of few pathologies, we use a hierarchical taxonomy mapped to the Unified Medical Language System (UMLS) terminology to identify 189 radiological findings, 22 differential diagnosis and 122 anatomic locations, including ground glass opacities MESHD, infiltrates, consolidations and other radiological findings compatible with COVID-19 MESHD. We train the system on one large database of 92,594 frontal chest x-rays (AP or PA, standing, supine or decubitus) and a second database of 2,065 frontal images of COVID-19 MESHD patients identified by at least one positive Polymerase Chain Reaction (PCR) test. The reference labels are obtained through natural language processing of the radiological reports. On 23,159 test images, the proposed neural network obtains an AUC of 0.94 for the diagnosis of COVID-19 MESHD. To our knowledge, this work uses the largest chest x-ray dataset of COVID-19 MESHD positive cases to date and is the first one to use a hierarchical labeling schema and to provide interpretability of the results, not only by using network attention methods, but also by indicating the radiological findings that have led to the diagnosis.

    Clinical analysis of 207 patients with coronavirus disease 2019 MESHD ( COVID-19 MESHD) in Shanghai, China

    Authors: Lin Wang; Yuan Zhang; Fei Shan; Renyin Zhang; Nannan Shi; Fengjun Liu; J Shi; Yuxin Shi

    doi:10.21203/ Date: 2020-05-08 Source: ResearchSquare

    Objectives: To investigate clinical features and the chest computed tomography (CT) findings in patients with confirmed cases of coronavirus disease 2019 MESHD ( COVID-19 MESHD) in Shanghai. Materials and Methods: Two hundred seven patients (102 men and 105 women, 15-84 years old) with COVID-19 MESHD from 23 January 2020 to 8 February 2020 were retrospectively reviewed. The imaging findings, clinical and laboratory data of the patients were evaluated and analyzed. The CT score was determined by totaling the lobes of lungs affected ranging from 0-25. Results: The median time from onset of symptoms to first hospital admission was 5.3±3.9 days.After being tested positive, the hospital stay of patients with onset of symptoms within one week is longer than that of patients with onset of symptoms over one week (15.7 vs. 11.5 respectively, p<0.01). The initial lung findings of patients with COVID-19 MESHD on chest CT were small subpleural ground glass opacities MESHD (GGO) that grew larger with crazy-paving pattern and consolidation with or without interstitial opacity. The mean CT scores peaked at 8-10 days of illness, with a slow decline thereafter and substantial scores after the 10 days. Both age and CD4 HGNC+ cell counts had a remarkable prognostic effect on imaging outcomes (p<0.05). Conclusion: For patients in mild-to-moderatecondition, the disease began to improve after 10 days from the initiation of the symptoms. Both age and baseline CD4 HGNC+ cell count were pivotal predictor of the outcome of imaging of the patients with COVID-19 MESHD.

    Can Nebulised Heparin Reduce Time to Extubation in SARS CoV 2 The CHARTER Study Protocol

    Authors: Barry Dixon; Roger Smith; Antonio Artigas; John Laffey; Bairbre McNicholas; Eric Schmidt; Quentin Nunes; Mark Andrew Skidmore; Marcelo Andrade de Lome; John Moran; Frank Van Haren; Gordon Doig; Sachin Gupta; Angajendra Ghosh; Simone Said; John Santamaria

    doi:10.1101/2020.04.28.20082552 Date: 2020-05-01 Source: medRxiv

    Introduction: COVID 19 is associated with the development of ARDS displaying the typical features of diffuse alveolar damage MESHD with extensive pulmonary coagulation MESHD activation resulting in fibrin deposition in the microvasculature and formation of hyaline membranes in the air sacs. The anticoagulant actions of nebulised heparin limit fibrin deposition and progression of lung injury MESHD. Serendipitously, unfractionated heparin also inactivates the SARS CoV 2 virus and prevents its entry into mammalian cells. Nebulisation of heparin may therefore limit both fibrin mediated lung injury MESHD and inhibit pulmonary infection MESHD by SARS CoV 2. For these reasons we have initiated a multicentre international trial of nebulised heparin in patients with COVID 19. Methods and intervention: Mechanically ventilated patients with confirmed or strongly suspected SARS CoV 2 infection, hypoxaemia MESHD and an acute pulmonary opacity MESHD in at least one lung quadrant on chest Xray, will be randomised to nebulised heparin 25,000 Units every 6 hours or standard care for up to 10 days while mechanically ventilated. The primary outcome is the time to separation from invasive ventilation to day 28, where non survivors to day 28 are treated as though not separated from invasive ventilation. Ethics and dissemination: The study protocol has been submitted to the human research and ethics committee of St Vincents Hospital, Melbourne, Australia. Submission is pending in other jurisdictions. Results of this study will be published in scientific journals and presented at scientific meetings.

    Temporal radiographic changes in COVID-19 MESHD patients: relationship to disease severity and viral clearance

    Authors: Xiaofan Liu; Hong Zhou; Yilu Zhou; Xiaojun Wu; Yang Zhao; Yang Lu; Weijun Tan; Mingli Yuan; Xuhong Ding; Jinjing Zou; Ruiyun Li; Hailing Liu; Rob M. Ewing; Yi Hu; Hanxiang Nie; Yihua Wang

    doi:10.21203/ Date: 2020-04-28 Source: ResearchSquare

    Background: COVID-19 MESHD is “public enemy number one” and has placed an enormous burden on health authorities across the world. Given the wide clinical spectrum of COVID-19 MESHD, understanding the factors that can predict disease severity will be essential since this will help frontline clinical staff to stratify patients with increased confidence.Purpose: To investigate the diagnostic value of the temporal radiographic changes, and the relationship to disease severity and viral clearance in COVID-19 MESHD patients.Methods: In this retrospective cohort study, we included 99 patients admitted to the Renmin Hospital of Wuhan University, with laboratory confirmed moderate or severe COVID-19 MESHD. Temporal radiographic changes and viral clearance were explored using appropriate statistical methods.Results: Radiographic features from HRCT scans included ground-glass opacity, consolidation, air bronchogram, nodular opacities MESHD and pleural effusion MESHD. The HRCT scores (peak) during disease course in COVID-19 MESHD patients with severe pneumonia MESHD (median: 24.5) were higher compared to those with pneumonia MESHD (median: 10) (p=3.56×10-12), with more frequency of consolidation (p=0.025) and air bronchogram (p=7.50×10-6). The median values of days when the peak HRCT scores were reached in pneumonia MESHD or severe pneumonia MESHD patients were 12 vs. 14, respectively (p=0.048). Log-rank test and Spearman's Rank-Order correlation suggested temporal radiographic changes as a valuable predictor for viral clearance. In addition, follow up CT scans from 11 pneumonia MESHD patients showed full recovery.Conclusion: Given the values of HRCT scores for both disease severity and viral clearance, a standardised HRCT score system for COVID-19 MESHD is highly demanded.

    Clinical characteristics and risk factors of patients with severe COVID-19 MESHD in Jiangsu province, China: a retrospective multicentre cohort study

    Authors: Songqiao Liu; Huanyuan Luo; Yuancheng Wang; Luis E. Cuevas; Duolao Wang; Shenghong Ju; Yi Yang

    doi:10.21203/ Date: 2020-04-20 Source: ResearchSquare

    Background: Coronavirus Disease-2019 ( COVID-19 MESHD) has become a major health event that endangers people health throughout China and the world. Understanding the factors associated with COVID-19 MESHD disease severity could support the early identification of patients with high risk for disease progression, inform prevention and control activities, and potentially reduce mortality. This study aims to describe the characteristics of patients with COVID-19 MESHD and factors associated with severe or critically ill MESHD presentation.Methods: Multicentre retrospective cohort study of all individuals with confirmed Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) infections MESHD diagnosed at 24 COVID-19 MESHD-designated hospitals in Jiangsu province between the 10th January and 15th March 2020. Demographic, clinical, laboratory, and radiological data were collected at hospital admission and data on disease severity were collected at from admission. Patients were categorised as asymptomatic/mild/moderate, and severe/critically ill according to the worst level of COVID-19 MESHD recorded during hospitalisation.Results: A total of 625 patients, 64 (10.2%) were severe/ critically ill MESHD and 561 (89.8%) were asymptomatic/mild/moderate. All patients were discharged and no patients died. Patients with severe/critically ill COVID-19 MESHD were more likely to be older, to be single onset (i.e. not to a cluster of cases in family/community), to have a medical history of hypertension MESHD and diabetes MESHD; had higher temperature, faster respiratory rates, lower peripheral capillary oxygen saturation (SpO2), and higher CT image quadrant scores and pulmonary opacity MESHD percentage; had increased C-reactive protein HGNC, fibrinogen HGNC, and D-dimer on admission; and had lower white blood cells, lymphocyte, and platelet counts and albumin on admission than asymptomatic/mild/moderate cases. Multivariable regression showed that odds of being a severe/critically ill case were associated with age (year) (OR 1.06, 95%CI 1.03-1.09), lymphocyte count (109/L) (OR 0.25, 95%CI 0.08-0.74), and pulmonary opacity MESHD in CT (per 5%) on admission (OR 1.31, 95%CI 1.15-1.51).Conclusions: Severe or critically ill MESHD patients with COVID-19 MESHD is about one-tenths of patients in Jiangsu. Age, lymphocyte count, and pulmonary opacity MESHD in CT on admission were associated with risk of severe or critically ill COVID-19 MESHD.

    A COVID-19 MESHD patient with multiple negative results for PCR assays outside Wuhan, China: a case report

    Authors: Li-Da Chen; Hao Li; Yu-Ming Ye; Zhi Wu; Ya-Ping Huang; Wei-Liang Zhang; Li Lin

    doi:10.21203/ Date: 2020-04-06 Source: ResearchSquare

    Background: The outbreak of coronavirus disease 2019 MESHD ( COVID-19 MESHD) caused by severe acute respiratory syndrome coronavirus 2 MESHD (SARS-CoV-2) has become a public health emergency of major international concern. Real-time RT-PCR assays are recommended for diagnosis of COVID-19 MESHD. Here we report a rare case of COVID-19 MESHD with multiple negative results for PCR assays outside Wuhan, China. Case presentation: A 32-year old male was admitted to our hospital because of 6 days of unexplained fever MESHD on January 29, 2020. He had come from Wuhan city 10 days before admission. 5 days before admission, no abnormality was noted in laboratory test, chest radiography, and nasopharyngeal swab test for the SARS-CoV-2 nucleic acid. The patient was treated with ibuprofen for  alleviating fever MESHD. On admission, chest computed tomography showed multiple ground- glass opacities MESHD in right lower lung field. COVID-19 MESHD was suspected. 3 times of nasopharyngeal swab specimens were collected after admission. However, none of the specimens were positive. The patient was confirmed with COVID-19 MESHD after fifth SARS-CoV-2 nucleic acid test. He was treated with lopinavir/ritonavir, recombinant human interferon alfa-2b inhalation, methylprednisolone. After 18 days of treatment, he was discharged with improved symptoms, lung lesions MESHD and negative results of nasopharyngeal swab. Conclusion: This case reminds clinician that a patient with high clinical suspicion of COVID-19 MESHD but multiple negative RT-PCR result should not be taken out of isolation. A combination of patient’s exposure history, clinical manifestations, laboratory tests, and typical imaging findings plays a vital role in making preliminary diagnosis and guide early isolation and treatment. Repeat swab tests are helpful in diagnosis for this kind of patients. 

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MeSH Disease
HGNC Genes
SARS-CoV-2 Proteins

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