Corpus overview


MeSH Disease

Human Phenotype


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    Automatic analysis system of COVID-19 radiographic lung images (XrayCoviDetector)

    Authors: Juan Nicolas Schlotterbeck; Carlos E Montoya; Patricia Bitar; Jorge A Fuentes; Victor Dinamarca; Gonzalo M Rojas; Marcelo Galvez; Andreas Limmer; Jia Liu; Xin Zheng; Thorsten Brenner; Marc M. Berger; Oliver Witzke; Mirko Trilling; Mengji Lu; Dongliang Yang; Nina Babel; Timm Westhoff; Ulf Dittmer; Gennadiy Zelinskyy; Kelly M Schiabor Barrett; Stephen Riffle; Alexandre Bolze; Simon White; Francisco Tanudjaja; Xueqing Wang; Jimmy M Ramirez III; Yan Wei Lim; James T Lu; Nicole L Washington; Eco JC de Geus; Patrick Deelen; H Marike Boezen; Lude H Franke

    doi:10.1101/2020.08.20.20178723 Date: 2020-08-23 Source: medRxiv

    COVID-19 is a pandemic infectious disease MESHD caused by the SARS-CoV-2 virus, having reached more than 210 countries and territories. It produces symptoms such as fever HP fever MESHD, dry cough MESHD cough HP, dyspnea HP dyspnea MESHD, fatigue HP fatigue MESHD, pneumonia HP pneumonia MESHD, and radiological manifestations. The most common reported RX and CT findings include lung consolidation and ground-glass opacities. In this paper, we describe a machine learning-based system (XrayCoviDetector;, that detects automatically, the probability that a thorax radiological image includes COVID-19 lung patterns. XrayCoviDetector has an accuracy of 0.93, a sensitivity SERO of 0.96, and a specificity of 0.90.

    A Large-Scale Clinical Validation Study Using nCapp Cloud Plus Terminal by Frontline Doctors for the Rapid Diagnosis of COVID-19 and COVID-19 pneumonia HP pneumonia MESHD in China

    Authors: Dawei Yang; Tao Xu; Xun Wang; Deng Chen; Ziqiang Zhang; Lichuan Zhang; Jie Liu; Kui Xiao; Li Bai; Yong Zhang; Lin Zhao; Lin Tong; Chaomin Wu; Yaoli Wang; Chunling Dong; Maosong Ye; Yu Xu; Zhenju Song; Hong Chen; Jing Li; Jiwei Wang; Fei Tan; Hai Yu; Jian Zhou; Jinming Yu; Chunhua Du; Hongqing Zhao; Yu Shang; Linian Huang; Jianping Zhao; Yang Jin; Charles A. Powell; Yuanlin Song; Chunxue Bai

    doi:10.1101/2020.08.07.20163402 Date: 2020-08-11 Source: medRxiv

    Background The outbreak of coronavirus disease MESHD 2019 (COVID-19) has become a global pandemic acute infectious disease MESHD, especially with the features of possible asymptomatic TRANS carriers TRANS and high contagiousness. It causes acute respiratory distress HP respiratory distress MESHD syndrome and results in a high mortality rate if pneumonia HP is involved. Currently, it is difficult to quickly identify asymptomatic TRANS cases or COVID-19 patients with pneumonia HP pneumonia MESHD due to limited access to reverse transcription-polymerase chain reaction (RT-PCR) nucleic acid tests and CT scans, which facilitates the spread of the disease TRANS at the community level, and contributes to the overwhelming of medical resources in intensive care units. Goal This study aimed to develop a scientific and rigorous clinical diagnostic tool for the rapid prediction of COVID-19 cases based on a COVID-19 clinical case database in China, and to assist global frontline doctors to efficiently and precisely diagnose asymptomatic TRANS COVID-19 patients and cases who had a false-negative RT-PCR test result. Methods With online consent, and the approval of the ethics committee of Zhongshan Hospital Fudan Unversity (approval number B2020-032R) to ensure that patient privacy is protected, clinical information has been uploaded in real-time through the New Coronavirus Intelligent Auto-diagnostic Assistant Application of cloud plus terminal (nCapp) by doctors from different cities (Wuhan, Shanghai, Harbin, Dalian, Wuxi, Qingdao, Rizhao, and Bengbu) during the COVID-19 outbreak in China. By quality control and data anonymization on the platform, a total of 3,249 cases from COVID-19 high-risk groups were collected. These patients had SARS-CoV-2 RT-PCR test results and chest CT scans, both of which were used as the gold standard for the diagnosis of COVID-19 and COVID-19 pneumonia HP pneumonia MESHD. In particular, the dataset included 137 indeterminate cases who initially did not have RT-PCR tests and subsequently had positive RT-PCR results, 62 suspected cases who initially had false-negative RT-PCR test results and subsequently had positive RT-PCR results, and 122 asymptomatic TRANS cases who had positive RT-PCR test results, amongst whom 31 cases were diagnosed. We also integrated the function of a survey in nCapp to collect user feedback from frontline doctors. Findings We applied the statistical method of a multi-factor regression model to the training dataset (1,624 cases) and developed a prediction model for COVID-19 with 9 clinical indicators that are fast and accessible: 'Residing or visiting history in epidemic regions', 'Exposure history to COVID-19 patient', 'Dry cough HP', ' Fatigue HP', 'Breathlessness', 'No body temperature decrease after antibiotic treatment', 'Fingertip blood SERO oxygen saturation<=93%', ' Lymphopenia HP Lymphopenia MESHD', and 'C-reactive protein (CRP) increased'. The area under the receiver operating characteristic (ROC) curve (AUC) for the model was 0.88 (95% CI: 0.86, 0.89) in the training dataset and 0.84 (95% CI: 0.82, 0.86) in the validation dataset (1,625 cases). To ensure the sensitivity SERO of the model, we used a cutoff value of 0.09. The sensitivity SERO and specificity of the model were 98.0% (95% CI: 96.9%, 99.1%) and 17.3% (95% CI: 15.0%, 19.6%), respectively, in the training dataset, and 96.5% (95% CI: 95.1%, 98.0%) and 18.8% (95% CI: 16.4%, 21.2%), respectively, in the validation dataset. In the subset of the 137 indeterminate cases who initially did not have RT-PCR tests and subsequently had positive RT-PCR results, the model predicted 132 cases, accounting for 96.4% (95% CI: 91.7%, 98.8%) of the cases. In the subset of the 62 suspected cases who initially had false-negative RT-PCR test results and subsequently had positive RT-PCR results, the model predicted 59 cases, accounting for 95.2% (95% CI: 86.5%, 99.0%) of the cases. Considering the specificity of the model, we used a cutoff value of 0.32. The sensitivity SERO and specificity of the model were 83.5% (95% CI: 80.5%, 86.4%) and 83.2% (95% CI: 80.9%, 85.5%), respectively, in the training dataset, and 79.6% (95% CI: 76.4%, 82.8%) and 81.3% (95% CI: 78.9%, 83.7%), respectively, in the validation dataset, which is very close to the published AI model. The results of the online survey 'Questionnaire Star' showed that 90.9% of nCapp users in WeChat mini programs were 'satisfied' or 'very satisfied' with the tool. The WeChat mini program received a significantly higher satisfaction rate than other platforms, especially for 'availability and sharing convenience of the App' and 'fast speed of log-in and data entry'. Discussion With the assistance of nCapp, a mobile-based diagnostic tool developed from a large database that we collected from COVID-19 high-risk groups in China, frontline doctors can rapidly identify asymptomatic TRANS patients and avoid misdiagnoses of cases with false-negative RT-PCR results. These patients require timely isolation or close medical supervision. By applying the model, medical resources can be allocated more reasonably, and missed diagnoses can be reduced. In addition, further education and interaction among medical professionals can improve the diagnostic efficiency for COVID-19, thus avoiding the transmission TRANS of the disease from asymptomatic TRANS patients at the community level.

    Fighting COVID-19 spread among nursing home residents even in absence of molecular diagnosis: a retrospective cohort study.

    Authors: Alessio Strazzulla; Paul Tarteret; Maria Concetta Postorino; Marie Picque; Astrid de Pontfarcy; Nicolas Vignier; Catherine Chakvetadze; Coralie Noel; Cecile Drouin; Zine Eddine Benguerdi; Sylvain Diamantis

    doi:10.21203/ Date: 2020-07-30 Source: ResearchSquare

    Background Access to molecular diagnosis was limited out-of-hospital in France during the 2020 coronavirus disease 2019 (COVID-19) epidemic. This study describes the evolution of COVID-19 outbreak in a nursing home in absence of molecular diagnosis. Methods A monocentric prospective study was conducted in a French nursing home from March 17th, 2020 to June 11th, 2020. Because of lack of molecular tests for severe acute respiratory syndrome 2 (SARS-Cov2) infection MESHD, probable COVID-19 cases were early identified considering only respiratory and not-respiratory symptoms and therefore preventing measures and treatments were enforced. Once available, serology tests were performed at the end of the study.A chronologic description of new cases and deaths MESHD was made together with a description of COVID-19 symptoms. Data about personal characteristics and treatments were collected and the following comparisons were performed: i) probable COVID-19 cases vs asymptomatic TRANS residents; ii) SARS-Cov2 seropositive residents vs seronegative residents. Results Overall, 32/66 (48.5%) residents and 19/39 (48.7%) members of health-care personnel were classified as probable COVID-19 cases. A total of 34/61 (55.7%) tested residents resulted seropositive. Death occurred in 4/66 (6%) residents. Diagnosis according to symptoms had 65% of sensitivity SERO, 78% of specificity, 79% of positive predictive value SERO and 64% of negative predictive value SERO.In resident population, the following symptoms were registered: 15/32 (46.8%) lymphopenia HP lymphopenia MESHD, 15/32 (46.8%) fever HP fever MESHD, 8/32 (25%) fatigue HP fatigue MESHD, 8/32 (25%) cough HP, 6/32 (18.8%) diarrhoea MESHD, 4/32 (12.5%) severe respiratory distress HP requiring oxygen therapy, 4/32 (12.5%) fall HP, 3/32 (9.4%) conjunctivitis HP conjunctivitis MESHD, 2/32 (6.3%) abnormal pulmonary noise at chest examination and 2/32 (6,25%) abdominal pain HP abdominal pain MESHD. Probable COVID-19 cases were older (81.3 vs 74.9; p=0.007) and they had higher prevalence SERO of atrial fibrillation HP atrial fibrillation MESHD (8/32, 25% vs 2/34, 12%; p=0.030); insulin treatment (4/34, 12% vs 0, 0%; p=0.033) and positive SARS-Cov2 serology (22/32, 69% vs 12/34, 35%; p=0.001) than asymptomatic TRANS residents. Seropositive residents had lower prevalence SERO of diabetes MESHD (4/34, 12% vs 9/27, 33%; p=0.041) and angiotensin-converting-enzyme inhibitors’ intake (1/34, 1% vs 5/27, 19%; p=0.042). Conclusions During SARS-Cov2 epidemic, early detection of respiratory and not-respiratory symptoms allowed to enforce extraordinary measures. They achieved limiting contagion and deaths among nursing home residents, even in absence of molecular diagnosis.

    Type and frequency of ocular and other known symptoms experienced by people who self diagnosed as suffering from COVID-19 in the UK

    Authors: Shahina Pardhan; Megan Vaughan; Jufen Zhang; Lee Smith; Havovi Chichger

    doi:10.1101/2020.06.20.20134817 Date: 2020-06-22 Source: medRxiv

    Background: Recent literature suggests that ocular manifestations present in people suffering from COVID-19. However, the prevalence SERO and the type of ocular symptoms varies substantially, and most studies report retrospective data from patients suffering from more serious versions of the disease. Little is known of exactly which ocular symptoms manifest in people with milder forms of COVID-19. Methods: An online questionnaire obtained self-report data from people in the community, who reported to be inflicted with COVID-19. The type and frequency of different symptoms suffered during COVID-19 were obtained. Details of any pre-existing ocular conditions and the duration of symptoms of COVID-19 were ascertained. Results: Data from 132 participants showed that the four most reported COVID-19 symptoms were Dry Cough HP (63%), Fever HP Fever MESHD (67%), Fatigue HP (83%), and loss of Smell/Taste (63%). 56% of the participants reported to having experienced an eye symptom, 46% reported to having a new or different eye symptom compared to pre-COVID-19 state. Three ocular symptoms (watery eyes, sore eyes, sensitivity SERO to light) were significantly different from Pre-COVID-19 state (p<0.05). Logistic regression showed a significant association of eye symptoms with Fever HP Fever MESHD (p=0.035). Conclusion: Nearly half of the sample of people studied experienced ocular symptoms. The significant ocular symptoms, indicative of viral conjunctivitis MESHD conjunctivitis HP, might have been missed in patients with more serious manifestations of the disease. It is also important to differentiate between the types of ocular manifestation, as symptoms of bacterial conjunctivitis MESHD conjunctivitis HP (i.e. mucous discharge, gritty eyes) were not significant. Possible mechanisms for SARS-CoV-2 infection MESHD within the eye are discussed.

    COVID-19 in Great Britain: epidemiological and clinical characteristics of the first few hundred (FF100) cases: a descriptive case series and case control analysis

    Authors: Nicola L Boddington; Andre Charlett; Suzanne Elgohari; Jemma L Walker; Helen Mcdonald; Chloe Byers; Laura Coughlan; Tatiana Garcia Vilaplana; Rosie Whillock; Mary Sinnathamby; Nikolaos Panagiotopoulos; Louise Letley; Pauline MacDonald; Roberto Vivancos; Obaghe Edeghere; Joseph Shingleton; Emma Bennett; Daniel J Grint; Helen Strongman; Kathryn E Mansfield; Christopher Rentsch; Caroline Minassian; Ian J Douglas; Rohini Mathur; Maria Peppa; Simon Cottrell; Jim McMenamin; Maria Zambon; Mary Ramsay; Gavin Dabrera; Vanessa Saliba; Jamie Lopez Bernal

    doi:10.1101/2020.05.18.20086157 Date: 2020-05-22 Source: medRxiv

    Objectives: Following detection of the first virologically- confirmed cases TRANS of COVID-19 in Great Britain, an enhanced surveillance study was initiated by Public Health England to describe the clinical presentation, course of disease and identify risk factors for infection of the first few hundred cases. Methods: Information was collected on the first COVID-19 cases according to the First Few X WHO protocol. Case-control analyses of the sensitivity SERO, specificity and predictive value of symptoms and risk factors for infection MESHD were conducted. Point prevalences SERO of underlying health conditions among the UK general population were presented. Findings: The majority of FF100 cases were imported (51.4%), of which the majority had recent travel TRANS to Italy (71.4%). 24.7% were secondary cases TRANS acquired mainly through household contact TRANS (40.4%). Children TRANS had lower odds of COVID-19 infection MESHD compared with the general population. The clinical presentation of cases was dominated by cough HP, fever HP fever MESHD and fatigue HP fatigue MESHD. Non-linear relationships with age TRANS were observed for fever HP fever MESHD, and sensitivity SERO and specificity of symptoms varied by age TRANS. Conditions associated with higher odds of COVID-19 infection MESHD (after adjusting for age TRANS and sex) were chronic heart disease MESHD, immunosuppression and multimorbidity. Conclusion: This study presents the first epidemiological and clinical summary of COVID-19 cases in Great Britain. The FFX study design enabled systematic data collection. The study was able to characterize the risk factors for infection MESHD with population prevalence SERO estimates setting these relative risks into a public health context. It also provides important evidence for generating case definitions to support public health risk assessment, clinical triage and diagnostic algorithms.

    An emerging marker predicting the severity of COVID-19: Neutrophil-Lymphocyte Count Ratio

    Authors: Minping Zhang; Enhua Xiao; Jiayi Liu; Yeyu Cai; Qizhi Yu

    doi:10.21203/ Date: 2020-05-14 Source: ResearchSquare

    Background: To analyze clinical features and laboratory indicators and identify the markers of exacerbation in COVID-19. Methods: We reviewed clinical histories of 177 patients with confirmed COVID-19. The patients were categorized into mild group (153 patients) and severe group (24 patients). The baseline demographic and laboratory indicators of all patients were collected, including the neutrophil-lymphocyte count ratio (NLCR) and C-reactive protein to albumin ratio (CAR). Receiver operating characteristic curve (ROC) analysis was performed to search for indicators predicting exacerbation in COVID-19 patients, and acquiring the area under the curves (AUCs), sensitivity SERO, specificity and cut-off value. Results: The age TRANS of the severe group were significantly older than those of the mild group (P <0.01). Fever HP was the typical symptom in all COVID-19 patients. Cough HP and fatigue HP were manifested in mild group, yet severe patients were more prominent in dyspnea HP. The laboratory indicators showing that the mild group mainly had an elevated C-reactive protein; the severe group had a decreased lymphocyte count and lymphocyte ratio. WBC, neutrophil count, neutrophil ratio, D-dimer, AST, ALT, LDH,  BUN, CRP levels increased. Furthermore, compared to mild group, WBC, neutrophil count, neutrophil ratio (Neut%), D-dimer, total bilirubin, albumin, AST, ALT, LDH, BUN, creatine kinase, CRP, CAR, NLCR were significantly higher, the lymphocyte count, lymphocyte ratio, and APTT were significantly lower  in  severe group (P<0.05). The ROC indicating that NLCR, Neut%, CAR, CRP, and LDH were better at distinguishing mild and severe patients. The AUCs of NLCR was larger than others (NLCR>Neut%>CAR>CRP>LDH: 0.939>0.925>0.908>0.895>0.873), which suggested that NLCR was the optimal maker; a cut-off value for NLCR of  6.15  had 87.5% sensitivity SERO and 97.6% specificity for predicting exacerbation in COVID-19 patients. Conclusions: The different types of COVID-19 had significant differences in age TRANS, clinical symptoms and laboratory indicators, and severe patients might be easier to suffer from the multiple organ damage. An elevated NLCR may indicate that the disease was progressing towards exacerbation. It was essential to dynamically monitor the serum SERO NLCR levels which contributed to evaluate the patient's condition and efficacy. NLCR could be used as a novel, highly specific and sensitive marker for predicting severity of COVID-19 patients.

    Loss of smell and taste in combination with other symptoms is a strong predictor of COVID-19 infection MESHD

    Authors: Cristina Menni; Ana Valdes; Maxim B Freydin; Sajaysurya Ganesh; Julia El-Sayed Moustafa; Alessia Visconti; Pirro Hysi; Ruth C E Bowyer; Massimo Mangino; Mario Falchi; Jonathan Wolf; Claire Steves; Tim Spector

    doi:10.1101/2020.04.05.20048421 Date: 2020-04-07 Source: medRxiv

    Importance: A strategy for preventing further spread of the ongoing COVID-19 epidemic is to detect infections MESHD and isolate infected individuals without the need of extensive bio-specimen testing. Objectives: Here we investigate the prevalence SERO of loss of smell and taste among COVID-19 diagnosed individuals and we identify the combination of symptoms, besides loss of smell and taste, most likely to correspond to a positive COVID-19 diagnosis in non-severe cases. Design: Community survey. Setting and Participants: Subscribers of RADAR COVID-19, an app that was launched for use among the UK general population asking about COVID-19 symptoms. Main Exposure: Loss of smell and taste. Main Outcome Measures: COVID-19. Results: Between 24 and 29 March 2020, 1,573,103 individuals reported their symptoms via the app; 26% reported suffering from one or more symptoms of COVID-19. Of those, n=1702 reported having had a RT-PCR COVID-19 test and gave full report on symptoms including loss of smell and taste; 579 were positive and 1123 negative. In this subset, we find that loss of smell and taste were present in 59% of COVID-19 positive individuals compared to 18% of those negative to the test, yielding an odds ratio (OR) of COVID-19 diagnosis of OR[95%CI]=6.59[5.25; 8.27], P= 1.90x10-59 . We also find that a combination of loss of smell and taste, fever HP fever MESHD, persistent cough HP, fatigue HP fatigue MESHD, diarrhoea MESHD, abdominal pain HP abdominal pain MESHD and loss of appetite is predictive of COVID-19 positive test with sensitivity SERO 0.54[0.44; 0.63], specificity 0.86[0.80; 0.90], ROC-AUC 0.77[0.72; 0.82] in the test set, and cross-validation ROC-AUC 0.75[0.72; 0.77]. When applied to the 410,598 individuals reporting symptoms but not formally tested, our model predicted that 13.06%[12.97%;13.15] of these might have been already infected by the virus. Conclusions and Relevance: Our study suggests that loss of taste and smell is a strong predictor of having been infected by the COVID-19 virus. Also, the combination of symptoms that could be used to identify and isolate individuals includes anosmia HP anosmia MESHD, fever HP fever MESHD, persistent cough HP, diarrhoea MESHD, fatigue HP fatigue MESHD, abdominal pain HP abdominal pain MESHD and loss of appetite. This is particularly relevant to healthcare and other key workers in constant contact with the public who have not yet been tested for COVID-19.

    Clinical and immunologic features in severe and moderate forms of Coronavirus Disease MESHD 2019

    Authors: Guang Chen; Di Wu; Wei Guo; Yong Cao; Da Huang; Hongwu Wang; Tao Wang; Xiaoyun Zhang; Huilong Chen; Haijing Yu; Xiaoping Zhang; Minxia Zhang; Shiji Wu; Jianxin Song; Tao Chen; Meifang Han; Shusheng Li; Xiaoping Luo; Jianping Zhao; Qin Ning

    doi:10.1101/2020.02.16.20023903 Date: 2020-02-19 Source: medRxiv

    Background Since late December, 2019, an outbreak of pneumonia HP pneumonia MESHD cases caused by the severe acute respiratory syndrome coronavirus 2 MESHD (SARS-CoV-2) emerged in Wuhan, and continued to spread throughout China and across the globe. To date, few data on immunologic features of Coronavirus Disease MESHD 2019 (COVID-19) have been reported. Methods In this single-centre retrospective study, a total of 21 patients with pneumonia HP pneumonia MESHD who were laboratory-confirmed to be infected with SARS-CoV-2 in Wuhan Tongji hospital were included from Dec 19, 2019 to Jan 27, 2020. The immunologic characteristics as well as their clinical, laboratory, radiological features were compared between 11 severe cases and 10 moderate cases. Results Of the 21 patients with COVID-19, only 4 (19%) had a history of exposure to the Huanan seafood market. 7 (33.3%) patients had underlying conditions. The average age TRANS of severe and moderate cases was 63.9 and 51.4 years, 10 (90.9%) severe cases and 7 (70.0%) moderate cases were male TRANS. Common clinical manifestations including fever HP fever MESHD (100%, 100%), cough HP (70%, 90%), fatigue HP fatigue MESHD (100%, 70%) and myalgia HP myalgia MESHD (50%, 30%) in severe cases and moderate cases. PaO2/FiO2 ratio was significantly lower in severe cases (122.9) than moderate cases (366.2). Lymphocyte counts were significantly lower in severe cases (7000 million/L) than moderate cases (11000 million/L). Alanine aminotransferase, lactate dehydrogenase levels, high- sensitivity SERO C-reactive protein and ferritin were significantly higher in severe cases (41.4 U/L, 567.2 U/L, 135.2 mg/L and 1734.4 ug/L) than moderate cases (17.6 U/L, 234.4 U/L, 51.4 mg/L and 880.2 ug /L). IL-2R, TNF- and IL-10 concentrations on admission were significantly higher in severe cases (1202.4 pg/mL, 10.9 pg/mL and 10.9 pg/mL) than moderate cases (441.7 pg/mL, 7.5 pg/mL and 6.6 pg/mL). Absolute number of total T lymphocytes, CD4+T cells and CD8+T cells decreased in nearly all the patients, and were significantly lower in severe cases (332.5, 185.6 and 124.3 million/L) than moderate cases (676.5, 359.2 and 272.0 million/L). The expressions of IFN-{gamma} by CD4+T cells tended to be lower in severe cases (14.6%) than moderate cases (23.6%). Conclusion The SARS-CoV-2 infection MESHD may affect primarily T lymphocytes, particularly CD4+T cells, resulting in significant decrease in number as well as IFN-{gamma} production, which may be associated with disease severity. Together with clinical characteristics, early immunologic indicators including diminished T lymphocytes and elevated cytokines may serve as potential markers for prognosis in COVID-19.

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MeSH Disease
Human Phenotype

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