Corpus overview


Overview

MeSH Disease

Human Phenotype

Transmission

Seroprevalence
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    Predictive Parameters for the Worsening Clinical Course of Mild COVID-19 Pneumonia MESHD Pneumonia HP

    Authors: Cho Rom Hahm; Young Kyung Lee; Dong Hyun Oh; Mi Young Ahn; Jae-Phil Choi; Na Ree Kang; Jungkyun Oh; Hanzo Choi; Suhyun Kim

    doi:10.21203/rs.3.rs-54860/v1 Date: 2020-08-06 Source: ResearchSquare

    Background: This study aimed to determine parameters for worsening oxygenation in mild COVID-19 pneumonia MESHD pneumonia HP.Methods: This retrospective cohort study included confirmed COVID-19 pneumonia MESHD pneumonia HP in a single public hospital in South Korea from January to April 2020. Parameters were compared between the two groups on the basis of clinical course: the desaturation group was defined as those with oxygen saturation ≤ 94% on ambient air, or received oxygen or mechanical ventilation (MV) throughout the clinical course versus the nonevent group who were without any respiratory event up to 28 days. The severity and extent of viral pneumonia MESHD pneumonia HP from an initial single chest CT were calculated using artificial intelligence (AI) algorithms and measured visually by a radiologist. Results: We included 136 patients with 32 (23.5%) in the desaturation group, of whom two needed MV and one died. Initial vital signs and duration of symptoms showed no difference between the two groups, however, univariate logistic regression analysis revealed that a variety of parameters at admission were associated with an increased risk of a desaturation event. In a sex-, age TRANS-, and comorbid illness-matched case-control study, ferritin ≥ 280 μg/L (OR 3.600, 95% CI 1.142-11.346; p=0.029), LDH≥ 240 U/L (OR 3.600, 95% CI 1.142-11.346; p=0.029), pneumonia MESHD pneumonia HP burden (OR 1.010, 95% CI 1.002-1.019; p=0.021), and extent (OR 1.194, 95% CI 1.017-1.401; p=0.030) by AI, and visual severity scores (OR 1.146, 95% CI 1.005-1.307; p=0.042) were the predictive parameters for worsening clinical course with desaturation. Conclusion: Our study presents initial CT parameters measured by AI or visual severity scoring as well as serum SERO markers of inflammation MESHD at admission as the best parameters for predicting worsening oxygenation in the COVID-19 pneumonia MESHD pneumonia HP cohort. Initial chest CT scans may help clinicians diagnose viral pneumonia MESHD pneumonia HP and evaluate the prognosis in mild COVID-19. 

    Characteristics of 24,516 Patients Diagnosed with COVID-19 Illness in a National Clinical Research Network: Results from PCORnet

    Authors: Jason P Block; Keith A. Marsolo; Kshema Nagavedu; L Charles Bailey; Henry Cruz; Christopher B. Forrest; Kevin Haynes; Adrian F. Hernandez; Rainu Kaushal; Abel Kho; Kathleen M. McTigue; Vinit P. Nair; Richard Platt; Jon Puro; Russell L. Rothman; Elizabeth Shenkman; Lemuel Russell Waitman; Mark G. Weiner; Neely Williams; Thomas W. Carton

    doi:10.1101/2020.08.01.20163733 Date: 2020-08-04 Source: medRxiv

    Background: National data from diverse institutions across the United States are critical for guiding policymakers as well as clinical and public health leaders. This study characterized a large national cohort of patients diagnosed with COVID-19 in the U.S., compared to patients diagnosed with viral pneumonia MESHD pneumonia HP and influenza. Methods and Findings: We captured cross-sectional information from 36 large healthcare systems in 29 U.S. states, participating in PCORnet, the National Patient-Centered Clinical Research Network. Patients included were those diagnosed with COVID-19, viral pneumonia MESHD pneumonia HP and influenza in any care setting, starting from January 1, 2020. Using distributed queries executed at each participating institution, we acquired information for patients on care setting (any, ambulatory, inpatient or emergency MESHD department, mechanical ventilator), age TRANS, sex, race, state, comorbidities (assessed with diagnostic codes), and medications used for treatment of COVID-19 (hydroxychloroquine with or without azithromycin; corticosteroids, anti-interleukin-6 agents). During this time period, 24,516 patients were diagnosed with COVID-19, with 42% in an emergency MESHD department or inpatient hospital setting; 79,639 were diagnosed with viral pneumonia MESHD pneumonia HP (53% inpatient/ED) and 163,984 with influenza (41% inpatient/ED). Among COVID-19 patients, 68% were 20 to <65 years of age TRANS, with more of the hospitalized/ED patients in older age TRANS ranges (23% 65+ years vs. 12% for COVID-19 patients in the ambulatory setting). Patients with viral pneumonia MESHD pneumonia HP were of a similar age TRANS, and patients with influenza were much younger. Comorbidities were common, especially for patients with COVID-19 and viral pneumonia MESHD pneumonia HP, with hypertension MESHD hypertension HP (32% for COVID-19 and 46% for viral pneumonia MESHD pneumonia HP), arrhythmias HP (20% and 35%), and pulmonary disease MESHD (19% and 40%) the most common. Hydroxychloroquine was used in treatment for 33% and tocilizumab for 11% of COVID-19 patients on mechanical ventilators (25% received azithromycin as well). Conclusion and Relevance: PCORnet leverages existing data to capture information on one of the largest U.S. cohorts to date of patients diagnosed with COVID-19 compared to patients diagnosed with viral pneumonia MESHD pneumonia HP and influenza.

    Self-Reported Taste and Smell Disorders in Patients with COVID-19: Distinct Features in China

    Authors: Jia Song; Yi-Ke Deng; Hai Wang; Zhi-Chao Wang; Bo Liao; Jin Ma; Chao He; Li Pan; Yang Liu; Isam Alobid; De-Yun Wang; Ming Zeng; Joaquim Mullol; Zheng Liu

    doi:10.21203/rs.3.rs-52752/v1 Date: 2020-08-03 Source: ResearchSquare

    Background: Last December 2019, a cluster of viral pneumonia MESHD pneumonia HP cases identified as coronavirus disease MESHD 2019 (COVID-19), was reported in Wuhan, China. We aimed to explore the frequencies of nasal symptoms in patients with COVID-19, including loss of smell and taste, as well as their presentation as the first symptom of the disease MESHD and their association with the severity of COVID-19.Methods: In this retrospective study, 1,206 laboratory-confirmed COVID-19 patients were included and followed-up by telephone call one month after discharged from Tongji Hospital, Wuhan. Demographic data, laboratory values, comorbidities, symptoms, and numerical rating scale scores (0-10) of nasal symptoms were extracted from the hospital medical records, and confirmed or reevaluated by the telephone follow-up. Results: From COVID-19 patients (N = 1,172) completing follow-up, 199 (17%) subjects had severe COVID-19 and 342 (29.2%) reported nasal symptoms. The most common nasal symptom was loss of taste (20.6%, median score = 6), while 11.4% had loss of smell (median score = 5). The incidence of nasal symptom including loss of smell and loss of taste as the first onset symptom TRANS was <1% in COVID-19 patients. Loss of smell or taste scores showed no correlation with the scores of other nasal symptoms. Loss of taste scores, but not loss of smell scores, were significantly increased in severe vs. non-severe COVID-19 patients. Interleukin (IL)-6 and lactose dehydrogenase (LDH) serum SERO levels positively correlated with loss of taste scores. About 80% of COVID-19 patients recovered from smell and taste dysfunction in 2 weeks.Conclusions: In the Wuhan COVID-19 cohort, only 1 out of 10 hospital admitted patients had loss of smell while 1 out 5 reported loss of taste which was associated to severity of COVID-19. Most patients recovered smell and taste dysfunctions in 2 weeks.

    Neutrophil Percentage and Neutrophil-to-Monocyte Ratio as Independent Risk Factors in the Severity of COVID-19

    Authors: Fei Peng; Si Lei; Chenfang Wu; Bo Yu; Yanjun Zhong; Shangjie Wu

    doi:10.21203/rs.3.rs-52622/v1 Date: 2020-08-02 Source: ResearchSquare

    BackgroundInflammation plays an important role in progression of the various viral pneumonia MESHD pneumonia HP containing COVID-19, severe inflammatory responses could lead to an imbalance of immune response. The purpose of this study was to explore the possibility of the white blood SERO count, neutrophil percentage, neutrophil-to-monocyte ratio (NMR) and neutrophil-to-lymphocyte ratio (NLR) at admission to reflect the clinical severity in patients with COVID‐19.MethodsClinical and laboratory data of adult TRANS COVID-19 patients in Changsha, China, were collected and analyzed on admission. A logistic regression model was adopted to analyze the association between the disease MESHD severity and related risk factors. The receiver operating characteristic (ROC) curve was utilized to analyze the abilities of potential risk factors in the prediction of COVID-19 severity.ResultsCompared with non-severe patients, the severe ones had significantly higher levels of neutrophil percentage (74.9% vs. 62.1%; P < 0.001), NLR (4.1 vs. 2.1; P < 0.001) and NMR (12.4 vs. 8.0; P < 0.001). A regression analysis showed that neutrophil percentage (OR,1.113; 95% CI, 1.020-1.213; P=0.016) and NMR (OR, 1.110; 95% CI, 1.002-1.230; P = 0.046) were significantly associated with severity of COVID-19 patients. ROC curve showed that the area under the curves of neutrophil percentage, NMR and the combination of them were 0.842 (95% confidence interval (CI), 0.782-0.902), 0.790 (95% CI, 0.710-0.871) and 0.851 (95% CI, 0.790-0.911), respectively.ConclusionsNeutrophil percentage and NMR may act as independent risk factors in the severity of COVID-19.

    SARS-CoV-2 serology increases diagnostic accuracy in CT-suspected, PCR-negative COVID-19 patients during pandemic

    Authors: Jochen Schneider; Hrvoje Mijocevic; Kurt Ulm; Bernhardt Ulm; Simon Weidlich; Silvia Wuerstle; Kathrin Rothe; Matthias Treiber; Roman Iakoubov; Ulrich Mayr; Tobias Lahmer; Sebastian Rasch; Alexander Herner; Egon Burian; Fabian Lohöfer; Rickmer Braren; Marcus Makowski; Roland Schmid; Ulrike Protzer; Christoph Spinner; Fabian Geisler

    doi:10.21203/rs.3.rs-51336/v1 Date: 2020-07-30 Source: ResearchSquare

    Background: In the absence of PCR detection of SARS-CoV-2 RNA, accurate diagnosis of COVID-19 is challenging. Low-dose computed tomography (CT) detects pulmonary infiltrates HP with high sensitivity SERO, but findings may be non-specific. This study assesses the diagnostic value of SARS-CoV-2 serology for patients with distinct CT features but negative PCR. Methods: IgM/IgG chemiluminescent immunoassay SERO was performed for 107 patients with confirmed (group A: PCR+; CT±) and 46 patients with suspected (group B: repetitive PCR-; CT+) COVID-19, admitted to a German university hospital during the pandemic’s first wave. A standardized, in-house CT classification of radiological signs of a viral pneumonia MESHD pneumonia HP was used to assess the probability of COVID-19. Results: Seroconversion rates (SR) determined on day 5, 10, 15, 20 and 25 after symptom onset TRANS (SO) were 8%, 25%, 65%, 76% and 91% for group A, and 0%, 10%, 19%, 37% and 46% for group B, respectively; (p<0.01). Compared to hospitalized patients with a non-complicated course, seroconversion tended to occur at lower frequency and delayed in patients on intensive care units. SR of patients with CT findings classified as high certainty for COVID-19 were 9%, 26%, 65%, 77% and 92% in group A, compared with 0%, 10%, 20%, 40% and 50% in group B (p<0.01). SARS-CoV-2 serology established a definite diagnosis in 12/46 group B patients. In 88% (8/9) of patients with negative serology >14 days after symptom onset TRANS (group B), clinico-radiological consensus reassessment revealed probable diagnoses other than COVID-19. Sensitivity SERO of SARS-CoV-2 serology was superior to PCR >17d after symptom onset TRANS. Conclusions: Approximately one-third of patients with distinct COVID-19 CT findings are tested negative for SARS-CoV-2 RNA by PCR rendering correct diagnosis difficult. Implementation of SARS-CoV-2 serology testing alongside current CT/PCR-based diagnostic algorithms improves discrimination between COVID-19-related and non-related pulmonary infiltrates HP in PCR negative patients. However, sensitivity SERO of SARS-CoV-2 serology strongly depends on the time of testing and becomes superior to PCR after the 2 nd week following symptom onset TRANS.

    PDCOVIDNet: A Parallel-Dilated Convolutional Neural Network Architecture for Detecting COVID-19 from Chest X-Ray Images

    Authors: Nihad Karim Chowdhury; Md. Muhtadir Rahman; Muhammad Ashad Kabir

    id:2007.14777v1 Date: 2020-07-29 Source: arXiv

    The COVID-19 pandemic continues to severely undermine the prosperity of the global health system. To combat this pandemic, effective screening techniques for infected patients are indispensable. There is no doubt that the use of chest X-ray images for radiological assessment is one of the essential screening techniques. Some of the early studies revealed that the patient's chest X-ray images showed abnormalities, which is natural for patients infected with COVID-19. In this paper, we proposed a parallel-dilated convolutional neural network (CNN) based COVID-19 detection system from chest x-ray images, named as Parallel-Dilated COVIDNet (PDCOVIDNet). First, the publicly available chest X-ray collection fully preloaded and enhanced, and then classified by the proposed method. Differing convolution dilation rate in a parallel form demonstrates the proof-of-principle for using PDCOVIDNet to extract radiological features for COVID-19 detection. Accordingly, we have assisted our method with two visualization methods, which are specifically designed to increase understanding of the key components associated with COVID-19 infection MESHD. Both visualization methods compute gradients for a given image category related to feature maps of the last convolutional layer to create a class-discriminative region. In our experiment, we used a total of 2,905 chest X-ray images, comprising three cases (such as COVID-19, normal, and viral pneumonia MESHD pneumonia HP), and empirical evaluations revealed that the proposed method extracted more significant features expeditiously related to the suspected disease MESHD. The experimental results demonstrate that our proposed method significantly improves performance SERO metrics: accuracy, precision, recall SERO, and F1 scores reach 96.58%, 96.58%, 96.59%, and 96.58%, respectively, which is comparable or enhanced compared with the state-of-the-art methods.

    COVID-19 Intensive Care Admissions Have Twice the Corrected Mortality of non-COVID-19 Viral Pneumonia MESHD Pneumonia HP

    Authors: Dan V Nicolau; Alexander Hasson

    doi:10.1101/2020.07.23.20161059 Date: 2020-07-24 Source: medRxiv

    Studying the ICNARC Case Mix Programme Database has yielded results showing intensive care admissions by those infected with COVID-19 have twice the corrected mortality of patients presenting with non-COVID-19 viral pneumonia MESHD pneumonia HP. A basis of an APACHE-II-like score denoted as "BASCA" is also outlined in this study.

    Invasive pulmonary aspergillosis MESHD Invasive pulmonary aspergillosis HP in critically ill patients with severe COVID-19 pneumonia MESHD pneumonia HP: results from the prospective AspCOVID-19 study

    Authors: Tobias Lahmer

    doi:10.1101/2020.07.21.20158972 Date: 2020-07-22 Source: medRxiv

    Background: Superinfections MESHD, including invasive pulmonary aspergillosis MESHD invasive pulmonary aspergillosis HP (IPA), are well-known complications of critically ill patients with severe viral pneumonia MESHD pneumonia HP. Aim of this study was to evaluate the incidence, risk factors and outcome of IPA in critically ill patients with severe COVID-19 pneumonia MESHD pneumonia HP. Methods: We prospectively screened 32 critically ill patients with severe COVID-19 pneumonia MESHD pneumonia HP for a time period of 28 days using a standardized study protocol for oberservation of developement of COVID-19 associated invasive pulmonary aspergillosis MESHD invasive pulmonary aspergillosis HP (CAPA). We collected laboratory, microbiological, virological and clinical parameters at defined timepoints in combination with galactomannan-antigen-detection from bronchial aspirates. We used logistic regression analyses to assess if COVID-19 was independently associated with IPA and compared it with matched controls. Findings: CAPA was diagnosed at a median of 4 days after ICU admission in 11/32 (34%) of critically ill patients with severe COVID-19 pneumonia MESHD pneumonia HP as compared to 8% in the control cohort. In the COVID-19 cohort, mean age TRANS, APACHE II score and ICU mortality were higher in patients with CAPA than in patients without CAPA (36% versus 9.5%; p<0.001). ICU stay (21 versus 17 days; p=0.340) and days of mechanical ventilation (20 versus 15 days; p=0.570) were not different between both groups. In regression analysis COVID-19 and APACHE II score were independently associated with IPA. Interpretation: CAPA is highly prevalent and associated with a high mortality rate. COVID-19 is independently associated with invasive pulmonary aspergillosis MESHD invasive pulmonary aspergillosis HP. A standardized screening and diagnostic approach as presented in our study can help to identify affected patients at an early stage.

    IgG antibody SERO seroconversion and the clinical progression of COVID-19 pneumonia MESHD pneumonia HP: A retrospective, cohort study

    Authors: Kazuyoshi Kurashima; Naho Kagiyama; Takashi Ishiguro; Yotaro Takaku; Hiromi Nakajima; Shun Shibata; Yuma Matsui; Kenji Takano; Taisuke Isono; Takashi Nishida; Eriko Kawate; Chiaki Hosoda; Yoichi Kobayashi; Noboru Takayanagi; Tsutomu Yanagisawa

    doi:10.1101/2020.07.16.20154088 Date: 2020-07-17 Source: medRxiv

    Background: Coronavirus Disease MESHD 2019 (COVID-19) causes severe acute respiratory failure HP. Antibody SERO-dependent enhancement (ADE) is known as the mechanism for severe forms of other coronavirus diseases MESHD. The clinical progression of COVID-19 before and after IgG antibody SERO seroconversion was investigated. Methods: Fifty-three patients with reverse transcriptase PCR (RT-PCT)-confirmed COVID-19 viral pneumonia MESHD pneumonia HP with or without respiratory failure HP were retrospectively investigated. The timing of the first IgG antibody SERO against SARS-CoV-2-positive date, as well as changes of C-reactive protein (CRP) as an inflammatory marker and blood SERO lymphocyte numbers, was assessed using serial preserved blood SERO samples. Findings: Ten patients recovered without oxygen therapy (mild/moderate group), 32 patients had hypoxemia HP and recovered with antiviral drugs (severe/non-ICU group), and 11 patients had severe respiratory failure HP and were treated in the ICU (6 of them died; critical/ICU group). The first IgG-positive date (day 0) was observed from 5 to 18 days from the onset of disease MESHD. At day 0, a CRP peak was observed in the severe and critical groups, whereas there was no synchronized CRP peak on day 0 in the mild/moderate group. In the severe/non-ICU group, the blood SERO lymphocyte number increased (P=0.0007) and CRP decreased (P=0.0007) after day 0, whereas CRP did not decrease and the blood SERO lymphocyte number further decreased (P=0.0370) in the critical/ICU group. Interpretation: The respiratory failure HP due to COVID-19 viral pneumonia MESHD pneumonia HP observed in week 2 may be related to an antibody SERO-related mechanism rather than uncontrolled viral replication. In the critical form of COVID-19, inflammation MESHD was sustained after IgG seroconversion.

    An Efficient Mixture of Deep and Machine Learning Models for COVID-19 and Tuberculosis MESHD Detection Using X-Ray Images in Resource Limited Settings

    Authors: Ali H. Al-Timemy; Rami N. Khushaba; Zahraa M. Mosa; Javier Escudero

    id:2007.08223v1 Date: 2020-07-16 Source: arXiv

    Clinicians in the frontline need to assess quickly whether a patient with symptoms indeed has COVID-19 or not. The difficulty of this task is exacerbated in low resource settings that may not have access to biotechnology tests. Furthermore, Tuberculosis MESHD (TB) remains a major health problem in several low- and middle-income countries and its common symptoms include fever MESHD fever HP, cough MESHD cough HP and tiredness, similarly to COVID-19. In order to help in the detection of COVID-19, we propose the extraction of deep features (DF) from chest X-ray images, a technology available in most hospitals, and their subsequent classification using machine learning methods that do not require large computational resources. We compiled a five-class dataset of X-ray chest images including a balanced number of COVID-19, viral pneumonia MESHD pneumonia HP, bacterial pneumonia MESHD pneumonia HP, TB, and healthy cases. We compared the performance SERO of pipelines combining 14 individual state-of-the-art pre-trained deep networks for DF extraction with traditional machine learning classifiers. A pipeline consisting of ResNet-50 for DF computation and ensemble of subspace discriminant classifier was the best performer in the classification of the five classes, achieving a detection accuracy of 91.6+ 2.6% (accuracy + 95% Confidence Interval). Furthermore, the same pipeline achieved accuracies of 98.6+1.4% and 99.9+0.5% in simpler three-class and two-class classification problems focused on distinguishing COVID-19, TB and healthy cases; and COVID-19 and healthy images, respectively. The pipeline was computationally efficient requiring just 0.19 second to extract DF per X-ray image and 2 minutes for training a traditional classifier with more than 2000 images on a CPU machine. The results suggest the potential benefits of using our pipeline in the detection of COVID-19, particularly in resource-limited settings and it can run with limited computational resources.

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MeSH Disease
Human Phenotype
Transmission
Seroprevalence


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