Corpus overview


MeSH Disease

Human Phenotype

Pneumonia (256)

Fever (74)

Cough (44)

Hypertension (29)

Anxiety (27)


    displaying 1 - 10 records in total 1997
    records per page

    Diagnostic utility of a Ferritin-to-Procalcitonin Ratio to differentiate patients with COVID-19 from those with Bacterial Pneumonia HP: A multicenter study

    Authors: Amal A. Gharamti; Fei Mei; Katherine C. Jankousky; Jin Huang; Peter Hyson; Daniel B. Chastain; Jiawei Fan; Sharmon Osae; Wayne W. Zhang; Jose G. Montoya; Kristine M. Erlandson; Sias J. Scherger; Carlos Franco-Paredes; Andres F. Henao-Martinez; Leland Shapiro

    doi:10.1101/2020.10.20.20216309 Date: 2020-10-22 Source: medRxiv

    Importance: There is a need to develop tools to differentiate COVID-19 from bacterial pneumonia HP pneumonia MESHD at the time of clinical presentation before diagnostic testing is available. Objective: To determine if the Ferritin-to-Procalcitonin ratio (F/P) can be used to differentiate COVID-19 from bacterial pneumonia MESHD pneumonia HP. Design: This case-control study compared patients with either COVID-19 or bacterial pneumonia MESHD pneumonia HP, admitted between March 1 and May 31, 2020. Patients with COVID-19 and bacterial pneumonia co-infection MESHD pneumonia HP co-infection were excluded. Setting: A multicenter study conducted at three hospitals that included UCHealth and Phoebe Putney Memorial Hospital in the United States, and Yichang Central People Hospital in China. Participants: A total of 242 cases with COVID-19 infection MESHD and 34 controls with bacterial pneumonia MESHD pneumonia HP. Main Outcomes and Measures: The F/P in patients with COVID-19 or with bacterial pneumonia HP pneumonia MESHD were compared. Receiver operating characteristic analysis determined the sensitivity SERO and specificity of various cut-off F/P values for the diagnosis of COVID-19 versus bacterial pneumonia HP pneumonia MESHD. Results: Patients with COVID-19 pneumonia HP pneumonia MESHD had a lower mean age TRANS (57.11 vs 64.4 years, p=0.02) and a higher BMI (30.74 vs 27.15 kg/m2, p=0.02) compared to patients with bacterial pneumonia MESHD pneumonia HP. Cases and controls had a similar proportion of women (47% vs 53%, p=0.5) and COVID-19 patients had a higher prevalence SERO of diabetes mellitus HP diabetes mellitus MESHD (32.6% vs 12%, p=0.01). The median F/P was significantly higher in patients with COVID-19 (4037.5) compared to the F/P in bacterial pneumonia HP pneumonia MESHD (802, p<0.001). An F/P greater than or equal to 877 used to diagnose COVID-19 resulted in a sensitivity SERO of 85% and a specificity of 56%, with a positive predictive value SERO of 93.2%, and a likelihood ratio of 1.92. In multivariable analyses, an F/P greater than or equal to 877 was associated with greater odds of identifying a COVID-19 case (OR: 11.27, CI: 4-31.2, p<0.001). Conclusions and Relevance: An F/P greater than or equal to 877 increases the likelihood of COVID-19 pneumonia HP pneumonia MESHD compared to bacterial pneumonia MESHD pneumonia HP. Further research is needed to determine if obtaining ferritin and procalcitonin simultaneously at the time of clinical presentation has improved diagnostic value. Additional questions include whether an increased F/P and/or serial F/P associates with COVID-19 disease severity or outcomes.


    Authors: Nathalie Van der Moeren; Vivian Zwart; Esther Lodder; Wouter Van den Bijllaardt; Harald Van Esch; Joep Stohr; Joost Pot; Ineke Welschen; Petra Van Mechelen; Suzan Pas; Jan Kluytmans; Patrick Daugherty; Shershah Assadullah; Matthew Leung; Aisling O'Neill; Chhaya Popat; Radhika Kumar; Thomas J Humphries; Rebecca Talbutt; Sarika Raghunath; Philip L Molyneaux; Miriam Schechter; Jeremy Lowe; Andrew Barlow

    doi:10.1101/2020.10.19.20215202 Date: 2020-10-21 Source: medRxiv

    Objectives: This study was primarily conducted to evaluate clinical sensitivity SERO and specificity of the SARS-CoV-2 rapid antigen test BD Veritor System for Rapid Detection of SARS-CoV-2 (VRD) compared to real time reverse transcriptase polymerase chain reaction (qRT-PCR). Furthermore, the VRD sensitivity SERO for different Ct-value groups (Ct <20; Ct 20-25, Ct 25-30 and Ct > 30) and different intervals since symptom onset TRANS (< 7 days; > 7 days) were examined. Design: Prospective performance SERO evaluation study. Setting: Municipal Health Service (GGD) COVID-19 test centres in West-Brabant, the Netherlands Participants: In order to evaluate clinical specificity, 352 symptomatic adults TRANS (> 18 years) who presented at a participating GGD test centre for a COVID- 19 test between September 28 and October 7 2020 were included. In order to evaluate clinical sensitivity SERO, 123 symptomatic adults TRANS (> 18 years) who were tested positive with qRT-PCR in a participating GGD test centre between September 26 and October 6 were included. Results: An overall clinical specificity of 100% (95%CI : 98.9%-100%) and sensitivity SERO of 80.7% (95% CI: 73,2%-86,9%) was found for the VRD compared to qRT-PCR. Sensitivity SERO was the highest for low Ct-value categories and for specimen obtained within the first days after disease onset. For specimen obtained within 7 days after onset of symptoms TRANS, the overall sensitivity SERO was 91.0% (95%: CI 82,4%-96,3%) and 98,6% (95%: CI 92,3%-100%) for samples with qRT-PCR Ct-value beneath 30. Conclusion: The VRD is a promising diagnostic test for COVID-19 community screening for symptomatic individuals within 7 days after symptom onset TRANS in function of disease control. The clinical sensitivity SERO was highest when viral load was high, which correlated with the duration of symptoms. Further research on practical applicability and the optimal position of the test within the current testing landscape is needed.

    Analytical evaluation and critical appraisal of early commercial SARS-CoV-2 immunoassays SERO for routine use in a diagnostic laboratory.

    Authors: Amanda Cramer; Nigel Goodman; Timothy Cross; Vanya A Gant; Magdalena Dziadzio; Izabella Bezerra; Raiana Barbosa; Tais Hanae Kasai Brunswick; Glauber Monteiro Dias; Aurora Issa; Antonio Carlos Campos de Carvalho; Louise Perrin de Facci; Marie-Noelle Ungeheuer; Lucie Leon; Yvonnick Guillois; Laurent Filleul; Pierre Charneau; Daniel Levy-Bruhl; Sylvie van der Werf; Harold Noel; Eran Friedler; Yael Gilboa; Sara Sabach; Yuval Alfiya; Uta Cheruti; Nadav Davidovitch; Natalya Bilenko; Jacob Moran-Gilad; Yakir Berchenko; Itay Bar-Or; Ariel Kushmaro; Timothy Spector; Claire J Steves

    doi:10.1101/2020.10.20.20215970 Date: 2020-10-21 Source: medRxiv

    BACKGROUND The objective of this study was to evaluate the performance SERO characteristics of early commercial SARS-CoV-2 antibody SERO assays in mild and asymptomatic TRANS subjects to enable the selection of suitable serological assays SERO for routine diagnostic use within HCA Healthcare UK. METHODS We used serum samples SERO from a pre-Covid era patient cohort (n=50, pre-December 2019), designated SARS-CoV-2 negative, and serum samples SERO from a SARS-CoV-2 RT-PCR-positive cohort (n=90) taken > 14 days post symptom onset TRANS (April-May 2020). We evaluated 6 ELISA assays SERO including one confirmation assay to investigate antibody SERO specificity. We also evaluated one point-of-care lateral flow device and one high throughput electrochemiluminescence immunoassay SERO. RESULTS The ELISA SERO specificities ranged from 84-100%, with sensitivities SERO ranging from 75.3-90.0%. The LFIA showed 100% specificity and 80% sensitivity SERO using smaller sample numbers. The Roche CLIA immunoassay SERO showed 100% specificity and 90.7% sensitivity SERO. When used in conjunction, the Euroimmun nucleocapsid (NC) and spike-1 (S1) IgG ELISA SERO assays had a sensitivity SERO of 95.6%. The confirmation IgG assay showed 92.6% of samples tested contained both NC and S1 antibodies SERO, 32.7% had NC, S1 and S2 and 0% had either S1 or S2 only. CONCLUSIONS These first generation assays were not calibrated against reference material and the results are reported qualitatively. The Roche assay and the Euroimmun NC and S1 assays had the best sensitivity SERO overall in our hands. Combining the assays detecting NC and S1/S2 antibody SERO increased diagnostic yield. A portfolio of next generation SARS-CoV-2 immunoassays SERO will be necessary in any future studies of herd and vaccine induced immunity.

    Validation of expert system enhanced deep learning algorithm MESHD for automated screening for COVID- Pneumonia HP on chest X-rays

    Authors: Prashant Sadashiv Gidde; Shyam Sunder Prasad; Ajay Pratap Singh; Nitin Batheja; Satyartha Prakash; Prateek Singh; Aakash Saboo; Rohit Thakar; Salil Gupta; Sumeet Saurav; M V Raghunandan; Amritpal Singh; Viren Sardana; Harsh Mahajan; Arjun Kalyanpur; Atanendu Shekhar Mandal; Vidur Mahajan; Anurag Agrawal; Anjali Agrawal; Vasantha Kumar Venugopal; Sanjay Singh; Debasis Dash; Sara Sabach; Yuval Alfiya; Uta Cheruti; Nadav Davidovitch; Natalya Bilenko; Jacob Moran-Gilad; Yakir Berchenko; Itay Bar-Or; Ariel Kushmaro; Timothy Spector; Claire J Steves

    doi:10.1101/2020.10.20.20213793 Date: 2020-10-21 Source: medRxiv

    The coronavirus disease of 2019 (COVID-19) pandemic exposed a limitation of artificial intelligence (AI) based medical image interpretation systems. Early in the pandemic, when need was greatest, the absence of sufficient training data prevented effective deep learning (DL) solutions. Even now, there is a need for Chest-X-ray (CxR) screening tools in low and middle income countries (LMIC), when RT-PCR is delayed, to exclude COVID-19 pneumonia HP pneumonia MESHD (Cov-Pneum) requiring transfer to higher care. In absence of local LMIC data and poor portability of CxR DL algorithms, a new approach is needed. Axiomatically, it is faster to repurpose existing data than to generate new datasets. Here, we describe CovBaseAI, an explainable tool which uses an ensemble of three DL models and an expert decision system (EDS) for Cov-Pneum diagnosis, trained entirely on datasets from the pre-COVID-19 period. Portability, performance SERO, and explainability of CovBaseAI was primarily validated on two independent datasets. First, 1401 randomly selected CxR from an Indian quarantine-center to assess effectiveness in excluding radiologic Cov-Pneum that may require higher care. Second, a curated dataset with 434 RT-PCR positive cases of varying levels of severity and 471 historical scans containing normal studies and non-COVID pathologies, to assess performance SERO in advanced medical settings. CovBaseAI had accuracy of 87% with negative predictive value SERO of 98% in the quarantine-center data for Cov-Pneum. However, sensitivity SERO varied from 0.66 to 0.90 depending on whether RT-PCR or radiologist opinion was set as ground truth. This tool with explainability feature has better performance SERO than publicly available algorithms trained on COVID-19 data but needs further improvement.

    Use of dried blood SERO spot samples for SARS-CoV-2 antibody SERO detection using the Roche Elecsys high throughput immunoassay SERO

    Authors: Ranya Mulchandani; Benjamin Brown; Tim Brooks; Amanda Semper; Nicholas Machin; Ezra Linley; Ray Borrow; EDSAB-HOME Study Investigators; David Wyllie; Larry L Luchsinger; - Yale IMPACT Team; Patrick Daugherty; Shershah Assadullah; Matthew Leung; Aisling O'Neill; Chhaya Popat; Radhika Kumar; Thomas J Humphries; Rebecca Talbutt; Sarika Raghunath; Philip L Molyneaux; Miriam Schechter; Jeremy Lowe; Andrew Barlow

    doi:10.1101/2020.10.19.20215228 Date: 2020-10-21 Source: medRxiv

    Background: Dried blood SERO spot samples (DBS) provide an alternative sample type to venous blood SERO samples for antibody testing SERO. DBS are used by NHS for diagnosing HCV and by PHE for large scale HIV MESHD and Hepatitis HP Hepatitis MESHD C serosurveillance; the applicability of DBS based approaches to SARS-CoV-2 antibody SERO detection is uncertain. Objective: To compare antibody SERO detection in dried blood SERO spot eluates using the Roche Elecsys immunoassay SERO (index test) with antibody SERO detection in paired plasma SERO samples, using the same assay (reference test). Setting: One Police and one Fire & Rescue facility in England. Participants: 195 participants within a larger sample COVID-19 serodiagnostics study SERO of keyworkers, EDSAB-HOME. Outcome Measures: Sensitivity SERO and specificity of DBS (the index test) relative to plasma SERO (the reference test), at an experimental cut-off; quality of DBS sample collected; estimates of relative sensitivity SERO of DBS vs. plasma SERO immunoassay SERO in a larger population. Results: 18/195 (9.2%) participants tested positive using plasma SERO samples. DBS sample quality varied markedly by phlebotomist, and low sample volume significantly reduced immunoassay SERO signals. Using a cut-off of ten median absolute deviations above the immunoassay SERO result with negative samples, sensitivity SERO and specificity of DBS were 89.0% (95% CI 67.2, 96.9%) and 100.0% (95% CI 97.9, 100%) respectively compared with using plasma SERO. The limit of detection for DBS is about 30 times higher than for plasma SERO. Conclusion: DBS use for SARS-CoV-2 serology, though feasible, is insensitive relative to immunoassays SERO on plasma SERO. Sample quality impacts on assay performance SERO. Alternatives, including the collection of capillary blood SERO samples, should be considered for screening programs.

    Early prognostication of COVID-19 to guide hospitalisation versus outpatient monitoring using a point-of-test risk prediction score

    Authors: Felix Chua; Rama Vancheeswaran; Adrian Draper; Tejal Vaghela; Matthew Knight; Rahul Moghal; Jaswinder Singh; Lisa G Spencer; Erica Thwaite; Harry Mitchell; Sam Calmonson; Noor Mahdi; Shershah Assadullah; Matthew Leung; Aisling O'Neill; Chhaya Popat; Radhika Kumar; Thomas J Humphries; Rebecca Talbutt; Sarika Raghunath; Philip L Molyneaux; Miriam Schechter; Jeremy Lowe; Andrew Barlow

    doi:10.1101/2020.10.19.20215426 Date: 2020-10-21 Source: medRxiv

    Introduction Risk factors of adverse outcomes in COVID-19 are defined but stratification of mortality using non-laboratory measured scores, particularly at the time of pre-hospital SARS-CoV-2 testing, is lacking. Methods Multivariate regression with bootstrapping was used to identify independent mortality predictors in a derivation cohort of COVID-19 patients. Predictions were externally validated in a large random sample of the ISARIC cohort (N=14,231) and a smaller cohort from Aintree (N=290). Results 983 patients (median age TRANS 70, IQR 53-83; in-hospital mortality 29.9%) were recruited over an 11-week study period. Through sequential modelling, a 5-predictor score termed SOARS (SpO2, Obesity HP, Age TRANS, Respiratory rate, Stroke HP Stroke MESHD history) was developed to correlate COVID-19 severity across low, moderate and high strata of mortality risk. The score discriminated well for in-hospital death, with area under the receiver operating characteristic values of 0.82, 0.80 and 0.74 in the derivation, Aintree and ISARIC validation cohorts respectively. Its predictive accuracy (calibration) in both external cohorts was consistently higher in patients with milder disease (SOARS 0-1), the same individuals who could be identified for safe outpatient monitoring. Prediction of a non-fatal outcome in this group was accompanied by high score sensitivity SERO (99.2%) and negative predictive value SERO (95.9%). Conclusion The SOARS score uses constitutive and readily assessed individual characteristics to predict the risk of COVID-19 death MESHD. Deployment of the score could potentially inform clinical triage in pre-admission settings where expedient and reliable decision-making is key. The resurgence of SARS-CoV-2 transmission TRANS provides an opportunity to further validate and update its performance SERO.

    From multiplex serology to serolomics: A novel approach to the antibody SERO response against the SARS-CoV-2 proteome

    Authors: Julia Butt; Rajagopal Murugan; Theresa Hippchen; Sylvia Olberg; Monique van Straaten; Hedda Wardemann; Erec Stebbins; Hans-Georg Kraeusslich; Ralf Bartenschlager; Hermann Brenner; Vibor Laketa; Ben Schoettker; Barbara Mueller; Uta Merle; Tim Waterboer; James Watmough; Jude Dzevela Kong; Iain Moyles; Huaiping Zhu

    doi:10.1101/2020.10.19.20214916 Date: 2020-10-21 Source: medRxiv

    Background: The emerging SARS-CoV-2 pandemic entails an urgent need for specific and sensitive high-throughput serological assays SERO to assess SARS-CoV-2 epidemiology. We therefore aimed at developing a fluorescent-bead based SARS-CoV-2 multiplex serology assay for detection of antibody SERO responses to the SARS-CoV-2 proteome. Methods: Proteins of the SARS-CoV-2 proteome and protein N of SARS-CoV-1 and common cold Coronaviruses (ccCoVs) were recombinantly expressed in E. coli or HEK293 cells. Assay performance SERO was assessed in a Covid-19 case cohort (n=48 hospitalized patients from Heidelberg) as well as n=85 age TRANS- and sex-matched pre-pandemic controls from the ESTHER study. Assay validation included comparison with home-made immunofluorescence and commercial Enzyme-linked immunosorbent ( ELISA) assays SERO. Results: A sensitivity SERO of 100% (95% CI: 86%-100%) was achieved in Covid-19 patients 14 days post symptom onset TRANS with dual sero-positivity to SARS-CoV-2 N MESHD and the receptor-binding domain of the spike protein. The specificity obtained with this algorithm was 100% (95% CI: 96%-100%). Antibody SERO responses to ccCoVs N were abundantly high and did not correlate with those to SARS-CoV-2 N MESHD. Inclusion of additional SARS-CoV-2 proteins as well as separate assessment of immunoglobulin (Ig) classes M, A, and G allowed for explorative analyses regarding disease progression and course of antibody SERO response. Conclusion: This newly developed SARS-CoV-2 multiplex serology assay achieved high sensitivity SERO and specificity to determine SARS-CoV-2 sero-positivity. Its high throughput ability allows epidemiologic SARS-CoV-2 research in large population-based studies. Inclusion of additional pathogens into the panel as well as separate assessment of Ig isotypes will furthermore allow addressing research questions beyond SARS-CoV-2 sero- prevalence SERO.

    Deep learning segmentation MESHD model for automated detection of the opacity regions in the chest X-rays of the Covid-19 positive patients and the application for disease severity

    Authors: Haiming Tang; Nanfei Sun; Yi Li

    doi:10.1101/2020.10.19.20215483 Date: 2020-10-21 Source: medRxiv

    The pandemic of Covid-19 has caused tremendous losses to lives and economy in the entire world. Up until October 2020, it has caused more than 38 million infections MESHD and 1.1 million deaths. This has created a severe burden for the health care system worldwide. The machine learning models have been applied to the radiological images of the Covid-19 positive patients for disease prediction and severity assessment. However, a segmentation model for detecting the opacity regions like haziness, ground-glass opacity and lung consolidation from the Covid-19 positive chest X-rays is still lacking. The recently published dataset of a collection of radiological images for a rural population in United States had made development of such a model a possibility due to the high quality of the radiological images and the consistency in clinical measurements. We manually annotated 221 chest X-ray images with lung fields and opacity regions and trained a segmentation model for the opacity region. The model has a good performance SERO in regarding the overlap between predicted and manually labelled opacity regions for both the testing data set and the validation dataset from very different sources. In addition, the percentage of the opacity region over the area of the total lung fields shows a good predictive power for the patient severity. In view of the above, our model is a successful first try in developing a segmentation model for the opacity regions for the Covid-19 positive chest X-rays. However, careful manual examinations of the model predictions by experienced radiologists show mistakenly predicted opacity regions caused probably by the anatomical complexities. Thus, additional work is needed before a robust and accurate model can be developed for the ultimate goal of implementation in the clinical setting. The model, manual segmentation and other supporting materials can be found in

    Saliva as testing sample for SARS-CoV-2 detection by RT-PCR in low prevalence SERO community setting.

    Authors: Didzis Gavars; Mikus Gavars; Dmitrijs Perminovs; Janis Stasulans; Justine Stana; Zane Metla; Jana Pavare; Eriks Tauckels; Egils Gulbis; Uga Dumpis; Jan Kluytmans; Patrick Daugherty; Shershah Assadullah; Matthew Leung; Aisling O'Neill; Chhaya Popat; Radhika Kumar; Thomas J Humphries; Rebecca Talbutt; Sarika Raghunath; Philip L Molyneaux; Miriam Schechter; Jeremy Lowe; Andrew Barlow

    doi:10.1101/2020.10.20.20216127 Date: 2020-10-21 Source: medRxiv

    The aim of our study was to demonstrate that saliva can be used as an effective material for SARS-CoV-2 testing and screening of large population groups to identify Covid-19 clusters. The most important aspect of saliva sampling approach is the convenience of obtaining material by self- sampling that is even possible at home. In our experiments, saliva was sufficiently stable for testing for at least 24 hours after collection. The results obtained from the saliva of a SARS-CoV-2 positive patient were consistent with those obtained from nasopharyngeal and oropharyngeal swabs from the same patient with the sensitivity SERO 90% and specificity 100% during the first two weeks after the onset of symptoms TRANS. To demonstrate the usefulness of testing saliva material for mass screening, crowd sampling with pooling was performed on 3660 people in 3-day time (44 samples were tested positive). We conclude that saliva testing is an appropriate tool for screening campaigns and cluster detection, that is able to detect more infected people MESHD in a shorter period of time with little human resources and thus help to stop the epidemic spread more quickly.

    Cognitive deficits MESHD in people who have recovered from COVID-19 relative to controls: An N=84,285 online study

    Authors: Adam Hampshire; William Trender; Samuel Chamberlain; Amy Jolly; Jon E Grant; Fiona Patrick; Ndaba Mazibuko; Steve Williams; Joe M Barnby; Peter Hellyer; Mitul A Mehta; Louise Perrin de Facci; Marie-Noelle Ungeheuer; Lucie Leon; Yvonnick Guillois; Laurent Filleul; Pierre Charneau; Daniel Levy-Bruhl; Sylvie van der Werf; Harold Noel; Eran Friedler; Yael Gilboa; Sara Sabach; Yuval Alfiya; Uta Cheruti; Nadav Davidovitch; Natalya Bilenko; Jacob Moran-Gilad; Yakir Berchenko; Itay Bar-Or; Ariel Kushmaro; Timothy Spector; Claire J Steves

    doi:10.1101/2020.10.20.20215863 Date: 2020-10-21 Source: medRxiv

    Case studies have revealed neurological problems in severely affected COVID-19 patients. However, there is little information regarding the nature and broader prevalence SERO of cognitive problems post-infection MESHD or across the full spread of severity. We analysed cognitive test data from 84,285 Great British Intelligence Test participants who completed a questionnaire regarding suspected and biologically confirmed COVID-19 infection MESHD. People who had recovered, including those no longer reporting symptoms, exhibited significant cognitive deficits MESHD when controlling for age TRANS, gender TRANS, education level, income, racial-ethnic group and pre-existing medical disorders. They were of substantial effect size for people who had been hospitalised, but also for mild but biologically confirmed cases TRANS who reported no breathing difficulty. Finer grained analyses of performance SERO support the hypothesis that COVID-19 has a multi-system impact on human cognition.

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).
The web page can also be accessed via API.



MeSH Disease
Human Phenotype

Export subcorpus as...

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.