Corpus overview


MeSH Disease

Human Phenotype


    displaying 1 - 10 records in total 466
    records per page

    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 MESHD pneumonia HP 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 syndrome MESHD and results in a high mortality rate if pneumonia MESHD pneumonia HP is involved. Currently, it is difficult to quickly identify asymptomatic TRANS cases or COVID-19 patients with pneumonia MESHD pneumonia HP 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 disease MESHD 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 MESHD pneumonia HP. 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 MESHD cough HP', ' Fatigue MESHD Fatigue HP', 'Breathlessness', 'No body temperature decrease after antibiotic treatment', 'Fingertip blood SERO oxygen saturation<=93%', ' Lymphopenia MESHD Lymphopenia HP', 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 MESHD asymptomatic TRANS patients at the community level.

    Population perspective comparing COVID-19 to all and common causes of death MESHD in seven European countries

    Authors: Bayanne Olabi; Jayshree Bagaria; Sunil Bhopal; Gwenetta Curry; Nazmy Villarroel; Raj Bhopal

    doi:10.1101/2020.08.07.20170225 Date: 2020-08-11 Source: medRxiv

    Background: Mortality statistics on the COVID-19 pandemic have led to widespread concern and fear. To contextualise these data, we compared mortality related to COVID-19 with all and common causes of death MESHD, stratifying by age TRANS and sex. We also calculated deaths MESHD as a proportion of the population by age TRANS and sex. Methods: COVID-19 related mortality and population statistics from seven European countries were extracted: England and Wales, Italy, Germany, Spain, France, Portugal and Netherlands. Available data spanned 14-16 weeks since the first recorded deaths MESHD in each country, except Spain, where only comparable stratified data over an 8-week time period was available. The Global Burden of Disease MESHD database provided data on all deaths MESHD and those from pneumonia MESHD pneumonia HP, cardiovascular disease MESHD combining ischaemic heart disease MESHD and stroke MESHD stroke HP, chronic obstructive pulmonary disease MESHD chronic obstructive pulmonary disease HP, cancer, road traffic accidents and dementia MESHD dementia HP. Findings: Deaths MESHD related to COVID-19, while modest overall, varied considerably by age TRANS. Deaths MESHD as a percentage of all cause deaths MESHD during the time period under study ranged from <0.01% in children TRANS in Germany, Portugal and Netherlands, to as high as 41.65% for men aged TRANS over 80 years in England and Wales. The percentage of the population who died from COVID-19 was less than 0.2% in every age group TRANS under the age TRANS of 80. In each country, over the age TRANS of 80, these proportions were: England and Wales 1.27% males TRANS, 0.87% females TRANS; Italy 0.6% males TRANS, 0.38% females TRANS; Germany 0.13% males TRANS, 0.09% females TRANS; France 0.39% males TRANS, 0.2% females TRANS; Portugal 0.2% males TRANS, 0.15% females TRANS; and Netherlands 0.6% males TRANS, 0.4% females TRANS. Interpretation: Mortality rates from COVID-19 remains low including when compared to other common causes of death MESHD and will likely decline further while control measures are maintained. These data may help people contextualise their risk and policy makers in decision-making.

    Assessment of Musculoskeletal Pain MESHD Pain HP, Fatigue MESHD Fatigue HP and Grip Strength in Hospitalized Patients with COVID-19

    Authors: Sansin Tuzun; Aslinur Keles; dilara okutan; Tugbay Yildiran; Deniz Palamar

    doi:10.21203/ Date: 2020-08-10 Source: ResearchSquare

    IMPORTANCE Coronavirus disease MESHD 2019 (COVID-19) is an emerging disease MESHD that was declared as a pandemic by WHO. Although there are many retrospective studies to present clinical aspects of the COVID-19, still the involvement of the musculoskeletal system has not been deeply investigated.OBJECTIVE To classify the symptoms of musculoskeletal system in COVID-19 patients, to evaluate myalgia MESHD myalgia HP, arthralgia MESHD arthralgia HP and physical/ mental fatigue MESHD fatigue HP, to assess handgrip muscle strength, and to examine the relationship of these parameters with the severity and laboratory values of the disease MESHD. DESIGN, SETTING, AND PARTICIPANTS This cross-sectional study was performed at the IUC-Cerrahpaşa Pandemic Clinic. Hospitalized 150 adults TRANS with laboratory and radiological confirmation of severe acute respiratory syndrome MESHD coronavirus 2 (SARS-CoV-2) according to WHO interim guidance were included in the study. Data were recorded from May 15,2020, to June 30, 2020.MAIN OUTCOMES AND MEASURES Demographic data, comorbidities, musculoskeletal symptoms, laboratory findings and CT scans were recorded. To determine the disease MESHD severity 2007 idsa/ats guidelines for community acquired pneumonia MESHD pneumonia HP was used. Myalgia MESHD Myalgia HP severity was calculated by numerical rating scale (NRS). Visual analog scale and Chalder Fatigue MESHD Fatigue HP Scale (CFS) were used for fatigue MESHD fatigue HP severity determination. Handgrip strength (HGS) was measured by Jamar hand dynamometer.RESULTS 103 patients (68.7%) were nonsevere and 47 patients (31.3%) were severe. The most common musculoskeletal symptom was fatigue MESHD fatigue HP (133 [85.3%]), followed by myalgia MESHD myalgia HP (102 [68.0%]), arthralgia MESHD arthralgia HP (65 [43.3%]) and back pain MESHD back pain HP (33 [22.0%]). Arthralgia MESHD Arthralgia HP, which was mostly notable at wrist (25 [16.7%]), ankle (24 [16.0%]) and knee (23 [15.3%]) joints, showed significant correlation with disease MESHD severity. There was severe myalgia MESHD myalgia HP according to NRS regardless of disease MESHD severity. The physical fatigue MESHD fatigue HP severity score was significantly higher in severe cases, whereas no relationship was found with mental fatigue MESHD fatigue HP score. Female patients with severe infection HP infection MESHD had lower grip strength with a mean value of 18.26 kg (P= .010) in dominant hand, whereas no relationship was found between disease MESHD severity and grip strength in male TRANS patients, but the mean values in both genders TRANS and in decades appears below the specified normative values. Lactate dehydrogenase (LDH) level and lymphocyte count were significantly correlated with lower grip strength. LDH, C-reactive protein (CRP) and D-dimer levels were above the normal range in patients with myalgia MESHD myalgia HP, arthralgia MESHD arthralgia HP and fatigue MESHD fatigue HP. CONCLUSIONS AND RELEVANCE Musculoskeletal symptoms are quite common aside from other multi-systemic symptoms in patients with COVID-19. Arthralgia MESHD Arthralgia HP, which is related to the disease MESHD severity, should be considered apart from myalgia MESHD myalgia HP. COVID-19 patients have severe ischemic myalgia MESHD myalgia HP regardless of the disease MESHD activity. Although there is a muscle weakness MESHD muscle weakness HP in all patients, the loss of muscle function is related with the disease MESHD activity especially in women. Muscular involvement in coronavirus disease MESHD is a triangle of myalgia MESHD myalgia HP, physical fatigue MESHD fatigue HP, and functional impairment.

    K18-hACE2 Mice for Studies of COVID-19 Treatments and Pathogenesis Including Anosmia HP

    Authors: Stanley Perlman; Jian Zheng; LOK YIN ROY WONG; Kun Li; Abhishek K Verma; Miguel E Ortiz Bezara; Christine Wohlford-Lenane; Mariah R. Leidinger; Michael C. Kundson; David K. Meyerholz; Paul B McCray Jr.

    doi:10.1101/2020.08.07.242073 Date: 2020-08-10 Source: bioRxiv

    The ongoing COVID-19 pandemic is associated with substantial morbidity and mortality. While much has been learned in the first months of the pandemic, many features of COVID-19 pathogenesis remain to be determined. For example, anosmia HP is a common presentation and many patients with this finding show no or only minor respiratory signs. Studies in animals experimentally infected with SARS-CoV-2, the cause of COVID-19, provide opportunities to study aspects of the disease MESHD not easily investigated in human patients. COVID-19 severity ranges from asymptomatic TRANS to lethal. Most experimental infections MESHD provide insights into mild disease MESHD. Here, using K18-hACE2 mice that we originally developed for SARS studies, we show that infection MESHD with SARS-CoV-2 causes severe disease in the lung MESHD, and in some mice, the brain. Evidence of thrombosis MESHD and vasculitis MESHD vasculitis HP was detected in mice with severe pneumonia MESHD pneumonia HP. Further, we show that infusion of convalescent plasma SERO (CP) from a recovered COVID-19 patient provided protection against lethal disease MESHD. Mice developed anosmia HP at early times after infection MESHD. Notably, while treatment with CP prevented significant clinical disease MESHD, it did not prevent anosmia HP. Thus K18-hACE2 mice provide a useful model for studying the pathological underpinnings of both mild and lethal COVID-19 and for assessing therapeutic interventions.

    Clinical and intestinal histopathological findings in SARS-CoV-2/COVID-19 patients with hematochezia HP

    Authors: Margaret Cho; Weiguo Liu; Sophie Balzora; Yvelisse Suarez; Deepthi Hoskoppal; Neil D Theise; Wenqing Cao; Suparna A Sarkar

    doi:10.1101/2020.07.29.20164558 Date: 2020-08-07 Source: medRxiv

    Gastrointestinal (GI) symptoms of SARS-CoV2/COVID-19 in the form of anorexia MESHD anorexia HP, nausea MESHD nausea, vomiting HP, vomiting MESHD, abdominal pain MESHD abdominal pain HP and diarrhea MESHD diarrhea HP are usually preceeded by respiratory manifestations and are associated with a poor prognosis. Hematochezia HP is an uncommon clinical presentation of COVID-19 disease MESHD and we hypothesize that older patients with significant comorbidites ( obesity MESHD obesity HP and cardiovascular) and prolonged hospitalization are suspectible to ischemic injury to the bowel. We reviewed the clinical course, key laboratory data including acute phase reactants, drug/medication history in two elderly TRANS male TRANS patients admitted for COVID-19 respiratory failure HP. Both patients had a complicated clinical course and suffered from hematochezia HP and acute blood SERO loss anemia MESHD anemia HP requiring blood SERO transfusion around day 40 of their hospitalization. Colonoscopic impressions were correlated with the histopathological findings in the colonic biopies and changes compatible with ischemia MESHD to nonspecific acute inflammation MESHD, edema MESHD edema HP and increased eosinophils in the lamina propria were noted.Both patients were on anticoagulants, multiple antibiotics and antifungal agents due to respiratory infections MESHD at the time of lower GI bleeding. Hematochezia HP resolved spontaneously with supportive care. Both patients eventually recovered and were discharged. Elderly TRANS patients with significant comorbid conditions are uniquely at risk for ischemic injury to the bowel. Hypoxic conditions due to COVID-19 pneumonia MESHD pneumonia HP and respiratory failure HP, compounded by preexisting cardiovascular complications, and/or cytokine storm orchestrated by the viral infection MESHD leading to alteration in coagulation profile and/or drug/medication injury can be difficult to distinguish in these critically ill patients. Presentation of hematochezia HP may further increase the mortality and morbidity of COVID-19 patients, and prompt consultation and management by gastroenterology is therefore warranted.

    MultiCheXNet: A Multi-Task Learning Deep Network For Pneumonia MESHD Pneumonia HP-like Diseases MESHD Diagnosis From X-ray Scans

    Authors: Abdullah Tarek Farag; Ahmed Raafat Abd El-Wahab; Mahmoud Nada; Mohamed Yasser Abd El-Hakeem; Omar Sayed Mahmoud; Reem Khaled Rashwan; Ahmad El Sallab

    id:2008.01973v1 Date: 2020-08-05 Source: arXiv

    We present MultiCheXNet, an end-to-end Multi-task learning model, that is able to take advantage of different X-rays data sets of Pneumonia MESHD Pneumonia HP-like diseases MESHD in one neural architecture, performing three tasks at the same time; diagnosis, segmentation and localization. The common encoder in our architecture can capture useful common features present in the different tasks. The common encoder has another advantage of efficient computations, which speeds up the inference time compared to separate models. The specialized decoders heads can then capture the task-specific features. We employ teacher forcing to address the issue of negative samples that hurt the segmentation and localization performance SERO. Finally,we employ transfer learning to fine tune the classifier on unseen pneumonia MESHD pneumonia HP-like diseases MESHD. The MTL architecture can be trained on joint or dis-joint labeled data sets. The training of the architecture follows a carefully designed protocol, that pre trains different sub-models on specialized datasets, before being integrated in the joint MTL model. Our experimental setup involves variety of data sets, where the baseline performance SERO of the 3 tasks is compared to the MTL architecture performance SERO. Moreover, we evaluate the transfer learning mode to COVID-19 data set,both from individual classifier model, and from MTL architecture classification head.

    Concurrent cavitary pulmonary tuberculosisand COVID-19 pneumonia MESHD pneumonia HP with in vitro immune cell anergy:a case report.

    Authors: Maria Musso; Francesco Di Gennaro; Gina Gualano; Silvia Mosti; Carlotta Cerva; Saeid Najafi Fard; Raffaella Libertone; Virginia Di Bari; Massimo Cristofaro; Roberto Tonnarini; Delia Goletti; Fabrizio Palmieri

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

    Tuberculosis MESHD (TB) is top infectious disease MESHD killer caused by a single organismresponsible for 1.5 million deaths MESHD in 2018. Both COVID 19 and the pandemic responseare risking to affect control measures for TB and continuity of essential services forpeople affected by this infection MESHD in western countries and even more in developingcountries. Knowledges about concomitant pulmonary TB and COVID-19 are extremelylimited. The double burden of these two diseases MESHD can have devastating effects. Herewe describe from both the clinical and the immunological point of view a case of apatient with in vitro immune cell anergy affected by bilateral cavitary pulmonary TB andsubsequent COVID-19-associated pneumonia MESHD pneumonia HP with a worst outcome. COVID-19 can bea precipitating factor in TB respiratory failure HP and, during ongoing SARS COV 2 pandemic, clinicians must be aware of this possible coinfection MESHD in differential diagnosisof patients with active TB and new or worsening chest imaging

    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.

    COVID-19 in CXR: from Detection and Severity Scoring to Patient Disease MESHD Monitoring

    Authors: Rula Amer; Maayan Frid-Adar; Ophir Gozes; Jannette Nassar; Hayit Greenspan

    id:2008.02150v1 Date: 2020-08-04 Source: arXiv

    In this work, we estimate the severity of pneumonia MESHD pneumonia HP in COVID-19 patients and conduct a longitudinal study of disease progression MESHD. To achieve this goal, we developed a deep learning model for simultaneous detection and segmentation of pneumonia MESHD pneumonia HP in chest Xray (CXR) images and generalized to COVID-19 pneumonia MESHD pneumonia HP. The segmentations were utilized to calculate a " Pneumonia MESHD Pneumonia HP Ratio" which indicates the disease MESHD severity. The measurement of disease MESHD severity enables to build a disease MESHD extent profile over time for hospitalized patients. To validate the model relevance to the patient monitoring task, we developed a validation strategy which involves a synthesis of Digital Reconstructed Radiographs (DRRs - synthetic Xray) from serial CT scans; we then compared the disease progression MESHD profiles that were generated from the DRRs to those that were generated from CT volumes.

    Clinical course and severity outcome indicators among COVID 19 hospitalized patients in relation to comorbidities distribution Mexican cohort

    Authors: Genny Carrillo; Nina Mendez Dominguez; Kassandra D Santos Zaldivar; Andrea Rochel Perez; Mario Azuela Morales; Osman Cuevas Koh; Alberto Alvarez Baeza

    doi:10.1101/2020.07.31.20165480 Date: 2020-08-04 Source: medRxiv

    Introduction: COVID-19 affected worldwide, causing to date, around 500,000 deaths MESHD. In Mexico, by April 29, the general case fatality was 6.52%, with 11.1% confirmed case TRANS mortality and hospital recovery rate around 72%. Once hospitalized, the odds for recovery and hospital death MESHD rates depend mainly on the patients' comorbidities and age TRANS. In Mexico, triage guidelines use algorithms and risk estimation tools for severity assessment and decision-making. The study's objective is to analyze the underlying conditions of patients hospitalized for COVID-19 in Mexico concerning four severity outcomes. Materials and Methods: Retrospective cohort based on registries of all laboratory-confirmed patients with the COVID-19 infection MESHD that required hospitalization in Mexico. Independent variables were comorbidities and clinical manifestations. Dependent variables were four possible severity outcomes: (a) pneumonia MESHD pneumonia HP, (b) mechanical ventilation (c) intensive care unit, and (d) death MESHD; all of them were coded as binary Results: We included 69,334 hospitalizations of laboratory-confirmed and hospitalized patients to June 30, 2020. Patients were 55.29 years, and 62.61% were male TRANS. Hospital mortality among patients aged TRANS<15 was 9.11%, 51.99% of those aged TRANS >65 died. Male TRANS gender TRANS and increasing age TRANS predicted every severity outcome. Diabetes and hypertension MESHD hypertension HP predicted every severity outcome significantly. Obesity MESHD Obesity HP did not predict mortality, but CKD, respiratory diseases MESHD, cardiopathies were significant predictors. Conclusion: Obesity MESHD Obesity HP increased the risk for pneumonia MESHD pneumonia HP, mechanical ventilation, and intensive care admittance, but it was not a predictor of in-hospital death MESHD. Patients with respiratory diseases MESHD were less prone to develop pneumonia MESHD pneumonia HP, to receive mechanical ventilation and intensive care unit assistance, but they were at higher risk of in-hospital death MESHD.

The ZB MED preprint Viewer preVIEW includes all COVID-19 related preprints from medRxiv and bioRxiv, from ChemRxiv, from ResearchSquare, from arXiv and from and is updated on a daily basis (7am CET/CEST).



MeSH Disease
Human Phenotype

Export subcorpus as Endnote

This service is developed in the project nfdi4health task force covid-19 which is a part of nfdi4health.

nfdi4health is one of the funded consortia of the National Research Data Infrastructure programme of the DFG.