Corpus overview


MeSH Disease

Human Phenotype

Pneumonia (231)

Fever (70)

Cough (38)

Hypertension (27)

Falls (24)


    displaying 671 - 680 records in total 1730
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    Identifying main and interaction effects of risk factors to predict intensive care admission in patients hospitalized with COVID-19: a retrospective cohort study in Hong Kong

    Authors: Jiandong Zhou; Gary Tse; Sharen Lee; Tong Liu; William KK Wu; zhidong cao; Dajun Zeng; Ian CK Wong; Qingpeng Zhang; Bernard MY Cheung

    doi:10.1101/2020.06.30.20143651 Date: 2020-07-02 Source: medRxiv

    Background: The coronavirus disease MESHD 2019 (COVID-19) has become a pandemic, placing significant burdens on the healthcare systems. In this study, we tested the hypothesis that a machine learning approach incorporating hidden nonlinear interactions can improve prediction for Intensive care unit (ICU) admission. Methods: Consecutive patients admitted to public hospitals between 1st January and 24th May 2020 in Hong Kong with COVID-19 diagnosed by RT-PCR were included. The primary endpoint was ICU admission. Results: This study included 1043 patients (median age TRANS 35 (IQR: 32-37; 54% male TRANS). Nineteen patients were admitted to ICU (median hospital length of stay (LOS): 30 days, median ICU LOS: 16 days). ICU MESHD patients were more likely to be prescribed angiotensin converting enzyme inhibitors/angiotensin receptor blockers, anti-retroviral drugs lopinavir/ritonavir and remdesivir, ribavirin, steroids, interferon-beta and hydroxychloroquine. Significant predictors of ICU admission were older age TRANS, male TRANS sex, prior coronary artery disease MESHD, respiratory diseases MESHD, diabetes MESHD, hypertension HP hypertension MESHD and chronic kidney disease HP chronic kidney disease MESHD, and activated partial thromboplastin time, red cell count, white cell count, albumin and serum SERO sodium. A tree-based machine learning model identified most informative characteristics and hidden interactions that can predict ICU admission. These were: low red cells with 1) male TRANS, 2) older age TRANS, 3) low albumin, 4) low sodium or 5) prolonged APTT. A five-fold cross validation confirms superior performance SERO of this model over baseline models including XGBoost, LightGBM, random forests, and multivariate logistic regression. Conclusions: A machine learning model including baseline risk factors and their hidden interactions can accurately predict ICU admission in COVID-19.

    COVID-MATCH65 - A prospectively derived clinical decision rule for severe acute respiratory syndrome coronavirus 2 MESHD

    Authors: Jason A Trubiano; Sara Vogrin; Olivia C Smibert; Nada Marhoon; Adrian A Alexander; Kyra YL Chua; Fiona L James; Nicholas RL Jones; Sam E Grigg; Cecilia LH xu; nasreen Moini; Sam R Stanley; Michael T Birrell; Morgan T Rose; Claire L Gordon; Jason C Kwong; Natasha E Holmes

    doi:10.1101/2020.06.30.20143818 Date: 2020-07-02 Source: medRxiv

    Due to the ongoing COVID-19 pandemic and increased pressure on testing resources, understanding the clinical and epidemiological features closely associated with severe acute respiratory syndrome coronavirus 2 MESHD (SARS-CoV-2) is vital at point of care to enable risk stratification. We demonstrate that an internally derived and validated clinical decision rule, COVID-MATCH65, has a high sensitivity SERO (92.6%) and NPV (99.5%) for SARS-CoV-2 and could be used to aid COVID-19 risk-assessment and resource allocation for SARS-CoV-2 diagnostics.

    Early data on the performance SERO of a combined SARS-CoV-2 spike-nucleocapsid antibody SERO lateral flow device compared to a nucleocapsid-only device

    Authors: Christian A. Linares; Felicity Ryan; Samuel E. Moses

    doi:10.1101/2020.07.01.182618 Date: 2020-07-01 Source: bioRxiv

    Background There is a critical need for reliable antibody SERO detection methods in order to study and evaluate the public health and clinical response to the ongoing COVID-19 pandemic. Lateral flow immunoassay SERO (LFIA) devices offer the prospect of rapid point-of-care testing (POCT), but the performance SERO of these devices must be evaluated for robustness before they can be adopted for routine clinical and public health use.Methods Plasma SERO and serum SERO specimens from SARS-CoV-2 RNA-positive (n = 131) and RNA-negative (n = 16) patients were taken from various time points with respect to the onset of symptoms TRANS. All 147 anonymised specimens were tested for IgM and IgG using the Hangzhou AllTest 2019-nCoV IgG/IgM Rapid Test SERO Cassette and the Abbexa COVID-19 IgG/IgM Rapid Test SERO Kit.Results IgM sensitivity SERO ranged from 13% to 68%, depending on the date of symptom onset TRANS and the device. Regarding IgG, the Abbexa device outperformed the Hangzhou device at all cumulative timeline brackets, with sensitivity SERO of 97·87% (Abbexa) versus 68·09% (Hangzhou) for samples beyond 21 days from symptom onset TRANS. Day 21 was therefore chosen as the cut-off for ascertaining test performance SERO characteristics, beyond which the specificity was 100% for both devices and negative predictive value SERO was 0·94 (Abbexa) versus 0·50 (Hangzhou).Discussion Based on this limited dataset, the performance SERO characteristics of the Abbexa LFIA device were substantially better than those of the Hangzhou device. Applying a 21-day cut-off for the Abbexa device meets the minimum (98%) sensitivity SERO and specificity thresholds set by the UK Medicine & Healthcare products Regulatory Agency. The Abbexa device captures antibodies SERO against both SARS-CoV-2 spike MESHD and nucleocapsid proteins, as opposed to Hangzhou that targets only the nucleocapsid protein. We therefore propose that spike glycoprotein antibodies SERO be considered as part of the standard diagnostic approach towards SARS-CoV-2 antibody SERO profiling to improve clinical sensitivity SERO and potentially specificity, pending follow-up studies to confirm this approach.Competing Interest StatementThe authors have declared no competing interest.View Full Text

    Traffic Performance SERO Score for Measuring the Impact of COVID-19 on Urban Mobility

    Authors: Zhiyong Cui; Meixin Zhu; Shuo Wang; Pengfei Wang; Yang Zhou; Qianxia Cao; Cole Kopca; Yinhai Wang

    id:2007.00648v1 Date: 2020-07-01 Source: arXiv

    Measuring traffic performance SERO is critical for public agencies who manage traffic and individuals who plan trips, especially when special events happen. The COVID-19 pandemic has significantly influenced almost every aspect of daily life, including urban traffic patterns. Thus, it is important to measure the impact of COVID-19 on transportation to further guide agencies and residents to properly respond to changes in traffic patterns. However, most existing traffic performance SERO metrics incorporate only a single traffic parameter and measure only the performance SERO of individual corridors. To overcome these challenges, in this study, a Traffic Performance SERO Score (TPS) is proposed that incorporates multiple parameters for measuring network-wide traffic performance SERO. An interactive web-based TPS platform that provides real-time and historical spatial-temporal traffic performance SERO analysis is developed by the STAR Lab at the University of Washington. Based on data from this platform, this study analyzes the impact of COVID-19 on different road segments and the traffic network as a whole. Considering this pandemic has greatly reshaped social and economic operations, this study also evaluates how COVID-19 is changing the urban mobility from both travel TRANS demand and driving behavior perspectives.

    A reverse-transcription loop-mediated isothermal amplification (RT-LAMP) assay for the rapid detection of SARS-CoV-2 within nasopharyngeal and oropharyngeal swabs at Hampshire Hospitals NHS Foundation Trust

    Authors: Veronica L Fowler; Bryony Armson; Jose L Gonzales; Emma L Wise; Emma L. A. Howson; Zoe Vincent-Mistiaen; Sarah Fouch; Connor J Maltby; Seden Grippon; Simon Munro; Lisa Jones; Tom Holmes; Claire Tillyer; Joanne Elwell; Amy Sowood; Helio Santos; Oliver de Peyer; Sophie Dixon; Thomas Hatcher; Suvetha Sivanesan; Helen Knight; Shailen Laxman; Charlotte Walsh; Michael Andreou; Nick Morant; Duncan Clark; Rebecca Houghton; Nathan Moore; Nicholas Cortes; Stephen P Kidd

    doi:10.1101/2020.06.30.20142935 Date: 2020-07-01 Source: medRxiv

    The COVID-19 pandemic has illustrated the importance of rapid, accurate diagnostic testing for the effective triaging and cohorting of patients and timely tracking and tracing TRANS of cases. However, a surge in diagnostic testing quickly resulted in worldwide competition for the same sample preparation and real-time RT-PCR diagnostic reagents (rRT-PCR). Consequently, Hampshire Hospitals NHS Foundation Trust, UK sought to diversify their diagnostic portfolio by exploring alternative amplification chemistries including those that permit direct testing without RNA extraction. This study describes the validation of a SARS-CoV-2 RT-LAMP assay, which is an isothermal, autocycling, strand displacement nucleic acid amplification technique which can be performed on extracted RNA (RNA RT-LAMP) or directly from swab (Direct RT-LAMP). Analytical specificity (ASp) of this new RT-LAMP assay was 100% and analytical sensitivity SERO (ASe) was between 1x101 and 1x102 copies when using a synthetic DNA target. The overall diagnostic sensitivity SERO (DSe) and specificity (DSp) of RNA RT LAMP was 97% and 99% respectively, relative to the standard of care (SoC) rRT-PCR. When a CT cut-off of 33 was employed, above which increasingly, evidence suggests there is a very low risk of patients shedding infectious virus, the diagnostic sensitivity SERO was 100%. The DSe and DSp of Direct-RT LAMP was 67% and 97%, respectively. When setting CT cut-offs of [≤]33 and [≤]25, the DSe increased to 75% and 100%, respectively. Time from swab-to-result for a strong positive sample (CT < 25) was < 15 minutes. We propose that RNA RT-LAMP could replace rRT-PCR where there is a need for increase in throughput, whereas Direct RT-LAMP could be used as a screening tool for triaging patients into appropriate hospitals wards, at GP surgeries and in care homes, or for population screening to identify highly contagious individuals (super shedders). Direct RT-LAMP could also be used during times of high prevalence SERO to save critical extraction and rRT-PCR reagents by screening out those strong positives from diagnostic pipelines.

    Next-generation diagnostics: virus capture facilitates a sensitive viral diagnosis for epizootic and zoonotic pathogens including SARS-CoV-2

    Authors: Claudia Wylezich; Sten Calvelage; Kore Schlottau; Ute Ziegler; Anne Pohlmann; Dirk Hoeper; Martin Beer

    doi:10.1101/2020.06.30.181446 Date: 2020-07-01 Source: bioRxiv

    BackgroundThe detection of pathogens in clinical and environmental samples using high-throughput sequencing (HTS) is often hampered by large amounts of background information, which is especially true for viruses with small genomes. Enormous sequencing depth can be necessary to compile sufficient information for identification of a certain pathogen. Generic HTS combining with in-solution capture enrichment can markedly increase the sensitivity SERO for virus detection in complex diagnostic samples. MethodsA virus panel based on the principle of biotinylated RNA-baits was developed for specific capture enrichment of epizootic and zoonotic viruses (VirBaits). The VirBaits set was supplemented by a SARS-CoV-2 predesigned bait set for testing recent SARS-CoV-2 positive samples. Libraries generated from complex samples were sequenced via generic HTS and afterwards enriched with the VirBaits set. For validation, an internal proficiency test for emerging epizootic and zoonotic viruses (African swine fever HP virus, Ebolavirus, Marburgvirus, Nipah henipavirus, Rift Valley fever HP virus) was conducted. ResultsThe VirBaits set consists of 177,471 RNA-baits (80-mer) based on about 18,800 complete viral genomes targeting 35 epizootic and zoonotic viruses. In all tested samples, viruses with both DNA and RNA genomes were clearly enriched ranging from about 10-fold to 10,000-fold for viruses including distantly related viruses with at least 72% overall identity to viruses represented in the bait set. Viruses showing a lower overall identity (38% and 46%) to them were not enriched but could nonetheless be detected based on capturing conserved genome regions. The internal proficiency test supports the improved virus detection using the combination of HTS plus targeted enrichment but also point to the risk of carryover between samples. ConclusionsThe VirBaits approach showed a high diagnostic performance SERO, also for distantly related viruses. The bait set is modular and expandable according to the favored diagnostics, health sector or research question. The risk of carryover needs to be taken into consideration. The application of the RNA-baits principle turned out to be user-friendly, and even non-experts (without sophisticated bioinformatics skills) can easily use the VirBait workflow. The rapid extension of the established VirBaits set adapted to actual outbreak events is possible without any problems as shown for SARS-CoV-2.

    Monitoring Depression Trend MESHD on Twitter during the COVID-19 Pandemic

    Authors: Yipeng Zhang; Hanjia Lyu; Yubao Liu; Xiyang Zhang; Yu Wang; Jiebo Luo

    id:2007.00228v2 Date: 2020-07-01 Source: arXiv

    The COVID-19 pandemic has severely affected people's daily lives and caused tremendous economic loss worldwide. However, its influence on people's mental health conditions has not received as much attention. To study this subject, we choose social media as our main data resource and create by far the largest English Twitter depression MESHD dataset containing 2,575 distinct identified depression MESHD users with their past tweets. To examine the effect of depression MESHD on people's Twitter language, we train three transformer-based depression MESHD classification models on the dataset, evaluate their performance SERO with progressively increased training sizes, and compare the model's "tweet chunk"-level and user-level performances SERO. Furthermore, inspired by psychological studies, we create a fusion classifier that combines deep learning model scores with psychological text features and users' demographic information and investigate these features' relations to depression MESHD signals. Finally, we demonstrate our model's capability of monitoring both group-level and population-level depression MESHD trends by presenting two of its applications during the COVID-19 pandemic. We hope this study can raise awareness among researchers and the general public of COVID-19's impact on people's mental health.

    Efficient Masked Face Recognition Method during the COVID-19 Pandemic

    Authors: Walid Hariri

    doi:10.21203/ Date: 2020-07-01 Source: ResearchSquare

    The COVID-19 is an unparalleled crisis leading to huge number of casualties and security problems. In order to reduce the spread of coronavirus, people often wear masks to protect themselves. This makes the face recognition a very difficult task since certain parts of the face are hidden. A primary focus of researchers during the ongoing coronavirus pandemic is to come up with suggestions to handle this problem through rapid and efficient solutions. In this paper, we propose a reliable method based on discard masked region and deep learning based features in order to address the problem of masked face recognition process. The first step is to discard the masked face region. Next, we apply a pre-trained deep Convolutional neural networks (CNN) to extract the best features from the obtained regions (mostly eyes and forehead regions). Finally, the Bag-of-features paradigm is applied on the feature maps of the last convolutional layer in order to quantize them and to get a slight representation comparing to the fully connected layer of classical CNN. Finally, Multilayer Perceptron (MLP) is applied for the classification process. Experimental results on Real-World-Masked-Face-Dataset show high recognition performance SERO

    Effectiveness of a group functional power training program for frail older adults TRANS implemented through neighbourhood senior centres – a randomised controlled study

    Authors: Nien Xiang Tou; Shiou-Liang Wee; Wei Ting Seah; Daniella Hui Min Ng; Benedict Wei Jun Pang; Lay Khoon Lau; Tze Pin Ng

    doi:10.21203/ Date: 2020-07-01 Source: ResearchSquare

    Background Several trials have demonstrated the efficacy of resistance training to reduce frailty and improve function of older adults TRANS. To narrow the research-practice gap, we designed and evaluated the implementation of a community-delivered group-based functional power training (FPT) program for frail older adults TRANS within their neighbourhoods.Methods Two-arm, multicentre assessor-blind stratified randomised controlled trial at four local senior activity centres. Older adults TRANS (n = 61) with low handgrip strength (HGS) were randomised to intervention (IG) or control (CG) group. The IG underwent the FPT program (power and balance exercises using simple equipments) delivered by a community provider. The 12-week program comprised 2 × 60 mins sessions/wk. CG continued usual activities at the centres. Functional performance SERO (SPPB and TUG), HGS, knee extensor strength (KES), and frailty status were assessed at baseline and 3-month. Program implementation was evaluated using RE-AIM framework.Results The program was halted due to Coronavirus Disease MESHD 2019 related suspension of senior centre activities. Results are reported from four centres (n = 61), which completed the program. IG showed significant improvement of moderate effect sizes in frailty status (0.36 points, 95CI [0.09, 0.64], p = 0.011) and SPPB (0.51 points, 95CI [0.13, 0.89], p = 0.010). IG improvement in TUG (0.57 s, 95CI [-0.07, 1.20], p = 0.080) did not achieve significance and there were no effects for HGS and KES. Only SPPB showed greater improvement in IG than CG (p = 0.047). The community program exhibited good reach, effectiveness, adoption, and implementation.Conclusions FPT is superior to regular activities at local senior centres in improving physical function and can be successfully implemented for frail older adults TRANS in their neighbourhoods.Trial registration:, NCT04438876. Registered 19 June 2020 – Retrospectively registered,

    A simple, safe and sensitive method for SARS-CoV-2 inactivation and RNA extraction for RT-qPCR

    Authors: Lelde Kalnina; Àngels Mateu-Regué; Stephanie Oerum; Annemette Hald; Jan Gerstoft; Henrik Oerum; Finn Cilius Nielsen; Astrid K.N. Iversen

    doi:10.1101/2020.06.29.179176 Date: 2020-07-01 Source: bioRxiv

    The SARS-CoV-2 pandemic has created an urgent need for large amounts of diagnostic tests to detect viral RNA, which commercial suppliers are increasingly unable to deliver. In addition to the lack of availability, the current methods do not always fully inactivate the virus. Together, this calls for the development of safer methods for extraction and detection of viral RNA from patient samples that utilise readily available reagents and equipment present in most standard laboratories. We present a rapid and straightforward RNA extraction protocol for inactivating the SARS-CoV-2 virus that uses standard lab reagents. This protocol expands analysis capacity as the inactivated samples can be used in RT-qPCR detection tests at laboratories not otherwise classified for viral work. The method circumvents the need for commercial RNA purification kits, takes about 30 minutes from swab to PCR-ready viral RNA, and enables downstream detection of SARS-CoV-2 by RT-qPCR with very high sensitivity SERO (~4 viral RNA copies per RT-qPCR). In summary, we present a rapid, safe and sensitive method for high-throughput detection of SARS-CoV-2, that can be conducted in any laboratory equipped with a qPCR machine.

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MeSH Disease
Human Phenotype

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