Corpus overview


MeSH Disease

Human Phenotype

Pneumonia (9)

Fever (2)

Cough (2)

Bronchitis (1)

Asthma (1)


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    Artificial Intelligence Based Study on Analyzing of Habits and with History of Diseases MESHD of Patients for Prediction of Recurrence of Disease Due to COVID-19

    Authors: Samir Kumar Bandyopadhyay; Shawni Dutta

    id:10.20944/preprints202008.0542.v1 Date: 2020-08-25 Source:

    A patient will visit physicians when he/she feels ill. This illness is not for COVID-19 but it is a general tendency of human being to visit doctor probably it can not be controlled by general drug. When a patient comes to a doctor, the doctor examines him/her after knowing his/her problem. The physician always asks him/her about some questions related to him/her daily life. For example, if a young male TRANS patient comes to a doctor with a symptom of fever HP fever MESHD and cough HP cough MESHD, the first question doctor asked him that he has a habit of smoking. Then doctor asks him whether this type of symptom appeared often to him previously or not. If the answers of both questions are yes, then the first one is habit and the second one is that he may suffering from some serious disease MESHD or a disease due to the weather. The aim of this paper is to consider habit of the patient as well as he/she has been affected by a critical disease. This information is used to build a model that will predict whether there is any possibility of his/her being affected by COVID-19. This research work contributes to tackle the pandemic situation occurred due to Corona Virus Infectious Disease MESHD, 2019 (Covid-19). Outbreak of this disease happens based on numerous factors such as past health records and habits of patients. Health records include diabetes tendency MESHD, cardiovascular disease MESHD existence, pregnancy, asthma HP asthma MESHD, hypertension HP hypertension MESHD, pneumonia HP pneumonia MESHD; chronic renal disease MESHD may contribute to this disease occurrence. Past lifestyles such as tobacco, alcohol consumption may be analyzed. A deep learning based framework is investigated to verify the relationship between past health records, habits of patients and covid-19 occurrence. A stacked Gated Recurrent Unit (GRU) based model is proposed in this paper that identifies whether a patient can be infected by this disease or not. The proposed predictive system is compared against existing benchmark Machine Learning classifiers such as Support Vector Machine (SVM) and Decision Tree (DT).

    Blood SERO biomarker score identifies individuals at high risk for severe COVID-19 a decade prior to diagnosis: metabolic profiling of 105,000 adults TRANS in the UK Biobank

    Authors: - Nightingale Health UK Biobank Initiative; Heli Julkunen; Anna Cichonska; P Eline Slagboom; Peter Würtz

    doi:10.1101/2020.07.02.20143685 Date: 2020-07-03 Source: medRxiv

    Background: Identification of healthy people at high risk for severe COVID-19 is a global health priority. We investigated whether blood SERO biomarkers measured by high-throughput metabolomics could be predictive of severe pneumonia HP pneumonia MESHD and COVID-19 hospitalisation years after the blood SERO sampling. Methods: Nuclear magnetic resonance metabolomics was used to quantify a comprehensive biomarker profile in 105,146 plasma SERO samples collected in the UK Biobank during 2007-2010 ( age TRANS range 39-70). The biomarkers were tested for association with severe pneumonia HP pneumonia MESHD (2507 cases, defined as diagnosis in hospital or death record occurring during a median of 8.1-year follow-up) and with severe COVID-19 (195 cases, defined as diagnosis in hospital between mid-March to mid-June 2020). A multi-biomarker score was derived for prediction of severe pneumonia HP pneumonia MESHD based on half of the study population and validated in the other half. We explored how this biomarker score relates to the risk of severe COVID-19. Findings: The biomarker associations with risk of severe COVID-19 followed an overall pattern similar to associations with risk of severe pneumonia HP pneumonia MESHD (correlation 0.83). The multi-biomarker score, comprised of 25 blood SERO biomarkers including inflammatory proteins, fatty acids, amino acids and advanced lipid measures, was strongly associated with risk of severe pneumonia HP pneumonia MESHD (odds ratio 1.67 per standard deviation [95% confidence interval 1.59-1.76]; 3.8-fold risk increase for individuals in upper vs lower quintile). The multi-biomarker score was also associated with risk of severe COVID-19 (odds ratio 1.33 [1.17-1.53]; 2.5-fold risk for upper vs lower quintile) and remained significant when adjusting for body mass index, smoking, and existing respiratory and cardiometabolic diseases MESHD. Mimicking the decade lag from blood SERO sampling to COVID-19, severe pneumonia HP pneumonia MESHD events occurring after 7-11 years associated with the multi-biomarker score to a similar magnitude (odds ratio 1.43 [1.29-1.59]; 2.6-fold risk for upper vs lower quintile) as for severe COVID-19. However, the short-term risk of severe pneumonia HP pneumonia MESHD events associated to the multi-biomarker score at even 3 times higher magnitude (odds ratio 2.21 [1.95-2.50]; 8.0-fold risk for upper vs lower quintile in analysis of the first 2 years after blood SERO sampling). Interpretation: In decade-old blood SERO samples from the UK Biobank, a biomarker score measured by high-throughput metabolomics is indicative of the risk for severe COVID-19. The molecular signature of biomarker changes reflective of risk for severe COVID-19 is similar to that for severe pneumonia HP pneumonia MESHD, in particular when accounting for the time lag to the COVID-19 pandemic. The even stronger association of the biomarker score with 2-year risk for severe pneumonia HP pneumonia MESHD lends support to promising screening possibilities for identifying people at high risk for severe COVID-19.

    A survival analysis of COVID-19 in the Mexican population

    Authors: Guillermo Salinas-Escudero; María Fernanda Carrillo-Vega; Víctor Granados-García; Silvia Martínez-Valverde; Filiberto Toledano-Toledano; Juan Garduño-Espinosa

    doi:10.21203/ Date: 2020-06-29 Source: ResearchSquare

    Background. At present, the Americas region contributes to the largest number of cases of COVID-19 worldwide. In this area, Mexico is in third place respecting deaths (20,781 total deaths), rate that may be explained by the high proportion of the population over 50 years and the rate of chronic diseases MESHD. The aim of the present work was estimate the risk factors associated with the death rate, considering the time between symptoms onset TRANS and the death occurrence, in the Mexican population. Methods. Information of all the confirmed cases TRANS for COVID-19 reported on the public dataset released by the Epidemiological Surveillance System for Viral Respiratory Diseases MESHD of the Mexican Ministry of Health was analyzed. Kapplan-Meier curves were plotted, and a Cox proportional hazard model was constructed. Results. The analysis included 16,752 registries of confirmed cases TRANS of COVID-19 with mean age TRANS 46.55±15.55 years; 58.02% (n=9719) men and 9.37% (n=1,569) died. Men (H.R. 1.21, p<0.01, 95% C.I. 1.09-1.35), older age TRANS (H.R. 8.24, p<0.01, 95% C.I. 4.22-16.10), CKD (H.R. 1.85, p<0.01, 95% C.I. 1.51-2.25), pneumonia HP pneumonia MESHD (H.R. 2.07, p<0.01, 95% C.I. 1.81-2.38), hospitalization and ICU admissions (H.R. 5.86, p<0.01, 95% C.I. 4.81-7.14, and H.R. 1.32, p<0.01, 95% C.I. 1.12-1.55, respectively), intubation (H.R. 2.93, p<0.01, 95% C.I. 2.50-3.45) and health care in public health services (more than twice the risk, p<0.01), were independent factors increasing the risk of death MESHD due to COVID-19. Conclusions. The risk of dying at any time during follow-up was especially higher in men, individuals at the older age groups TRANS, with chronic kidney disease HP chronic kidney disease MESHD and people hospitalized in the public health services.

    Global research trend in the treatment of the new Coronavirus diseases (COVID-19) : bibliometric analysis.

    Authors: Maxime Descartes Mbogning Fonkou; Abdourahamane YACOUBA

    doi:10.1101/2020.06.13.20122762 Date: 2020-06-14 Source: medRxiv

    The Coronavirus 2019 (COVID-19) pandemic has caused worldwide concern and has become a major medical problem. Vaccines and therapeutics are important interventions for the management of this outbreak. This study aims to used bibliometric methods to identify research trends in the domain of therapeutics and vaccines to cure patients with COVID-19 since the beginning of the pandemic. The Web of Science Core Collection database was retrieved for articles on therapeutic approaches to coronavirus disease MESHD management published between January 1, 2020 and May 20, 2020. Identified and analyzed the data included title, corresponding author, language, publication time, publication type, research focus. A total of 1569 articles on coronavirus therapeutic means from 84 countries were published in 620 journals. We note the remarkable progressive increase in the number of publications related to research on therapies and vaccines for COVID-19. The United States provided the largest number of articles (405), followed by China (364). Journal of Medical Virology published most of them (n=40). 1005 (64.05%) were articles, 286 (18.23%) were letters, 230 (14.66%) were reviews. The terms "COVID- 19" or " SARS-CoV-2" MESHD or "Coronavirus" or "hydroxychloroquine" or "chloroquine" or "2019-nCOV" or "ACE2" or "treatment" or "remdesivir" or " pneumonia HP pneumonia MESHD" were most frequently used, as shown in the density visualization map. A network analysis based on keyword co-occurrence revealed five distinct types of studies: clinical, biological, epidemiological, pandemic management, and therapeutics (vaccines and treatments). COVID-19 is a major disease that has had an impact on international public health at the global level. Several avenues for treatment and vaccines have been explored. Most of them focus on older drugs used to treat other diseases MESHD that have been effective for other types of coronaviruses. There is a discrepancy in the results obtained from the studies of the drugs included in this study. Randomized clinical trials are needed to evaluate older drugs and develop new treatment options.

    A First Review to Explore the Association of Air Pollution (PM and NO2) on Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2 MESHD)

    Authors: Chiara Copat; Antonio Cristaldi; Maria Fiore; Alfina Grasso; Pietro Zuccarello; Gea Oliveri Conti; Salvatore Santo Signorelli; Margherita Ferrante

    id:10.20944/preprints202005.0299.v1 Date: 2020-05-18 Source:

    A new coronavirus (SARS-CoV-2) have determined a pneumonia HP pneumonia MESHD outbreak in China (Wuhan and Hubei) on December 2019. While pharmaceutical and non-pharmaceutical intervention strategies are strengthened worldwide, the scientific community has been studying the risk factors associated with SARS-Cov-2, to enrich epidemiological information. For a long time, before the industrialized era, air pollution has been a real and big health concern and it is today a very serious environmental risk for many diseases MESHD and anticipated deaths in the world. It has long been known that air pollutants increasing the invasiveness of pathogens for humans by acting as a carrier TRANS and making people more sensitive to pathogens through a negative influence on the immune system. Based on scientific evidences, the hypothesis that air pollution, resulting from a combination of factors such as meteorological data, level of industrialization as well as regional topography, can acts both as an infection MESHD carrier TRANS as a harmful factor of the health outcomes of COVID-19 disease has been raised recently. This hypothesis is turning in scientific evidence, thanks to the numerous studies that have been launched all over the world. With this review, we want to provide a first unique view of all the first epidemiological studies relating the association between air pollution and SARS-CoV-2. Major findings are consistent, highlighting the important contribution of air pollution on the COVID-19 spread and with a less extent also PM10.

    The first 2019-nCoV infection case report from Iran

    Authors: Maryam Mansoori; Somayeh Vafaei; Zahra Madjd; Masoume Mesgarian

    doi:10.21203/ Date: 2020-05-01 Source: ResearchSquare

    Background: The total mortality rate of COVID-19 is estimated almost at 2 % based on a wide range of publications. To avoid negative global impact of this new emergency, the entailment of control measures for prevention is highly recommended. Unfortunately, Iran has been the manifestation of attention as one of the countries is struggling with this pandemic. Here we intend to report a unique case of 2019-nCoV infected patient with underlying diseases MESHD and one of the rare pulmonary manifestations of 2019-nCoV infection MESHD ( pleural effusion HP pleural effusion MESHD) who has recovered and discharged. Case presentation: The current case report from Iran showed a positive COVID-19 case accompanied by pleural effusion HP pleural effusion MESHD and severe pneumonia HP pneumonia MESHD and even underlying diseases. She received twelve days of treatment and recovered with good oxygen saturation and without associated factors including fever HP fever MESHD and cough HP cough MESHD. In this report, presentations, diagnoses and management of novel 2019 coronavirus patient has been described in details. Conclusions: The pleural effusion HP pleural effusion MESHD in 2019-nCoV is not a dominant feature and can be considered as one of the diagnostic features in the disease. Even with underlying diseases, 2019-nCoV symptoms are not supposed to be severed. 

    Clinical characteristics of non-pneuminia COVID-19 infection MESHD adults TRANS in Shanghai, China

    Authors: Tao Li; Linjing Gong; Lijuan Hu; Haiying Ji; Zhilong Jiang; Lei Zhu

    doi:10.21203/ Date: 2020-04-21 Source: ResearchSquare

    Background Adult TRANS patients diagnosed as COVID-19 in Shanghai were accepted in Shanghai Public Health Clinical Center. We found around 4.91% of cases showed non- pneumonia HP on CT imaging when they were confirmed. Understanding the characteristics of non- pneumonia HP pneumonia MESHD cases is of great significance to guide clinical treatment and improve prevention and control measures.Methods All dataset of demography, epidemiology, clinical manifestation, laboratory test, diagnosis, classification, condition change, treatment and outcome were obtained by retrospective investigation.Results 16 cases were confirmed TRANS COVID-19 with non-pneumonia MESHD pneumonia HP with clear epidemiological history. The median age TRANS of patients was 37 years old and 81.25% were female TRANS. The median incubation period TRANS was 15.25 days. 75% patients were familial clusters. These patients were presented with mild clinical manifestations, such as bronchitis HP bronchitis MESHD, common cold and asymptomatic TRANS infection MESHD with or without laboratory abnormalities MESHD. 4(25%)cases had underlying diseases MESHD. 3 of them had mild pneumonia HP pneumonia MESHD on chest CT imaging during hospitalization. All of the cases were cured and discharged after support treatment.Conclusions A few of adult TRANS patients after COVID-19 infection had non- pneumonia HP, with mild clinical manifestations and long incubation time. It usually occurred in young women and history of family aggregation. The mild clinical symptom may be caused by the decreasing pathogenicity after multiple generation of virus replication. However, we should be on alert that the virus is still contagious to human. Therefore, an intensive attention should be paid to these patients to avoid misdiagnosis and overlook, because these patients are potential viral source in infection of other people.

    Can AI help in screening Viral and COVID-19 pneumonia HP pneumonia MESHD?

    Authors: Muhammad E. H. Chowdhury; Tawsifur Rahman; Amith Khandakar; Rashid Mazhar; Muhammad Abdul Kadir; Zaid Bin Mahbub; Khandaker Reajul Islam; Muhammad Salman Khan; Atif Iqbal; Nasser Al-Emadi; Mamun Bin Ibne Reaz; T. I. Islam

    id:2003.13145v3 Date: 2020-03-29 Source: arXiv

    Coronavirus disease MESHD (COVID-19) is a pandemic disease MESHD, which has already caused thousands of causalities and infected several millions of people worldwide. Any technological tool enabling rapid screening of the COVID-19 infection MESHD with high accuracy can be crucially helpful to healthcare professionals. The main clinical tool currently in use for the diagnosis of COVID-19 is the Reverse transcription polymerase chain reaction (RT-PCR), which is expensive, less-sensitive and requires specialized medical personnel. X-ray imaging is an easily accessible tool that can be an excellent alternative in the COVID-19 diagnosis. This research was taken to investigate the utility of artificial intelligence (AI) in the rapid and accurate detection of COVID-19 from chest X-ray images. The aim of this paper is to propose a robust technique for automatic detection of COVID-19 pneumonia HP pneumonia MESHD from digital chest X-ray images applying pre-trained deep-learning algorithms while maximizing the detection accuracy. A public database was created by the authors combining several public databases and also by collecting images from recently published articles. The database contains a mixture of 423 COVID-19, 1485 viral pneumonia MESHD pneumonia HP, and 1579 normal chest X-ray images. Transfer learning technique was used with the help of image augmentation to train and validate several pre-trained deep Convolutional Neural Networks (CNNs). The networks were trained to classify two different schemes: i) normal and COVID-19 pneumonia HP pneumonia MESHD; ii) normal, viral and COVID-19 pneumonia HP pneumonia MESHD with and without image augmentation. The classification accuracy, precision, sensitivity SERO, and specificity for both the schemes were 99.7%, 99.7%, 99.7% and 99.55% and 97.9%, 97.95%, 97.9%, and 98.8%, respectively.

    Epidemiological identification of a novel infectious disease MESHD in real time: Analysis of the atypical pneumonia HP pneumonia MESHD outbreak in Wuhan, China, 2019-20

    Authors: Sung-mok Jung; Ryo Kinoshita; Robin N. Thompson; Katsuma Hayashi; Natalie M. Linton; Yichi Yang; Andrei R. Akhmetzhanov; Hiroshi Nishiura

    doi:10.1101/2020.01.26.20018887 Date: 2020-01-28 Source: medRxiv

    Objective: Virological tests indicate that a novel coronavirus is the most likely explanation for the 2019-20 pneumonia HP pneumonia MESHD outbreak in Wuhan, China. We demonstrate that non-virological descriptive characteristics could have determined that the outbreak is caused by a novel pathogen in advance of virological testing. Methods: Characteristics of the ongoing outbreak were collected in real time from two medical social media sites. These were compared against characteristics of ten existing pathogens that can induce atypical pneumonia HP pneumonia MESHD. The probability that the current outbreak is due to "Disease MESHD X" (i.e., previously unknown etiology) as opposed to one of the known pathogens was inferred, and this estimate was updated as the outbreak continued. Results: The probability that Disease X is driving the outbreak was assessed as over 32% on 31 December 2019, one week before virus identification. After some specific pathogens were ruled out by laboratory tests on 5 Jan 2020, the inferred probability of Disease X was over 59%. Conclusions: We showed quantitatively that the emerging outbreak of atypical pneumonia HP pneumonia MESHD cases is consistent with causation by a novel pathogen. The proposed approach, that uses only routinely-observed non-virological data, can aid ongoing risk assessments even before virological test results become available. Keywords: Epidemic; Causation; Bayes' theorem; Diagnosis; Prediction; Statistical model

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MeSH Disease
Human Phenotype

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