Corpus overview


Overview

MeSH Disease

Fever (4)

Myalgia (4)

Arthralgia (4)

Diarrhea (4)

Dysgeusia (2)


Human Phenotype

Anosmia (4)

Chills (4)

Cough (4)

Myalgia (4)

Arthralgia (4)


Transmission

Seroprevalence
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    Symptomatology of Coronavirus Disease MESHD 2019 (COVID-19) - Lessons from A Meta-Analysis Across 13 Countries

    Authors: Champika Saman Kumara Gamakaranage; Dineshani Hettiarachchi; Dileepa Ediriweera; Saroj Jayasinghe

    doi:10.21203/rs.3.rs-39412/v1 Date: 2020-07-01 Source: ResearchSquare

    Background: COVID-19 pandemic has resulted in varying clinical manifestations and mortality rates. There is no consensus on the symptomatology that would guide researchers and clinicians.Objective: The objective of the study was to identify symptoms and their frequencies of coronavirus disease MESHD 2019 with a meta-analysis of studies from several countries. Data sources: A systematic review using PubMed and Google Scholar data sources and reference tracing TRANS were used to identify 7176 relevant articles. Eligibility criteria: Suitable articles were selected manually with selection criteria and 14 original articles included for meta-analysis. Data abstraction analysis: PRISMA guideline was used for abstracting data. Then a table was generated by feeding it with numbers and proportions of each symptom described in original studies. A meta-analysis was carried out using random effect models on each symptom separately across the studies and their prevalence SERO rates and 95% confident intervals calculated.Results: We identified 14 relevant scientific papers, either cross-sectional or cohort studies and analyzed. There were 2,660 cases of COVID-19. he majority were from China (n=2,439, 91.7%) and remainder from the Netherlands, Italy, Korea and India and one article from Europe. There was a total of 32 symptoms (i.e. present in >50% of patients):  fever MESHD (79.56%, 95% CI: 72.17-86.09%), malaise (63.3%, 95% CI: 53.1 – 73.0%), cough HP (56.7. %, 95% CI: 48.6 - 64.6 %) and cold (55.6%, 95% CI: 45.2 – 65.7%). Symptoms of intermediate incidence (5-49%) were; anosmia HP anosmia MESHD, sneezing HP, ocular pain HP ocular pain MESHD, fatigue HP fatigue MESHD, sputum production, arthralgia HP arthralgia MESHD, tachypnea HP tachypnea MESHD, palpitation HP, headache HP headache MESHD, chest tightness HP chest tightness MESHD, shortness of breath MESHD, chills HP, myalgia HP myalgia MESHD, sore throat, anorexia HP anorexia MESHD, weakness MESHD, diarrhea HP diarrhea MESHD, rhinorrhea HP rhinorrhea MESHD, dizziness MESHD, nausea HP nausea MESHD, altered level of consciousness, vomiting HP vomiting MESHD and abdominal pain HP abdominal pain MESHD. Rare symptoms (<5% of patients) were: tonsil swelling, haemoptysis, conjunctival injection, lymphadenopathy HP lymphadenopathy MESHD and rash MESHD were uncommon symptoms of coronavirus disease MESHD (<5%).Conclusion and implications of key findings: We found (25/32) symptoms to be present in =>5% of cases which could be considered as “typical” symptoms of COVID-19. The list of symptoms we identified are different from those documents released by the WHO, CDC, NHS, Chinese CDC, Institute Pasteur and Mayo Clinic. The compiled list would be useful for future researchers to document a comprehensive picture of the illness.

    Symptomatology of Coronavirus Disease MESHD 2019 (COVID-19) - Lessons from a meta-analysis across 13 countries

    Authors: Champika Saman Kumara Gamakaranage; Dineshani Hettiarachchi; Dileepa Ediriweera; Saroj Jayasinghe

    doi:10.21203/rs.3.rs-39412/v2 Date: 2020-07-01 Source: ResearchSquare

    Background: COVID-19 pandemic has resulted in varying clinical manifestations and mortality rates. There is no consensus on the symptomatology that would guide researchers and clinicians. Objective: The objective was to identify symptoms and their frequencies of COVID-19 with a meta-analysis of studies from several countries. Data sources: A systematic review using PubMed and Google Scholar data sources and reference tracing TRANS were used to identify 7176 articles. Eligibility criteria: Suitable articles were selected manually with selection criteria and 14 original articles included in meta-analysis. Data abstraction and analysis: PRISMA guidelines, used for data abstraction and a table was generated by feeding it with numbers and proportions of each symptom described. A meta-analysis was carried out using random effect models on each symptom separately across the studies and their prevalence SERO rates and 95% confident intervals were calculated.Results: Selected 14 studies, either cross-sectional or cohort studies are analyzed. There were 2,660 confirmed cases TRANS of COVID-19. The majority were from China (n=2,439, 91.7%) and remainder from the Netherlands, Italy, Korea and India and one article from Europe. There was a total of 32 symptoms identified from the meta-analysis and additional 7 symptoms were identified from reference searching. The most common symptoms were ( prevalence SERO >50%): fever HP fever MESHD (79.56%, 95% CI: 72.17-86.09%), malaise (63.3%, 95% CI: 53.1 – 73.0%), cough HP (56.7. %, 95% CI: 48.6 - 64.6 %) and cold (55.6%, 95% CI: 45.2 – 65.7%). Symptoms of intermediate incidence (5-49%) were; anosmia HP anosmia MESHD, sneezing HP, ocular pain HP ocular pain MESHD, fatigue HP fatigue MESHD, sputum production, arthralgia HP arthralgia MESHD, tachypnea HP tachypnea MESHD, palpitation HP, headache HP headache MESHD, chest tightness HP chest tightness MESHD, shortness of breath MESHD, chills HP, myalgia HP myalgia MESHD, sore throat, anorexia HP anorexia MESHD, weakness MESHD, diarrhea HP diarrhea MESHD, rhinorrhea HP rhinorrhea MESHD, dizziness MESHD, nausea HP nausea MESHD, altered level of consciousness, vomiting HP vomiting MESHD and abdominal pain HP abdominal pain MESHD. Rare symptoms (<5%): tonsil swelling MESHD, haemoptysis, conjunctival injection, lymphadenopathy HP lymphadenopathy MESHD and rash MESHD. Conclusion and implications of key findings: We found (25/32, from meta-analysis) symptoms to be present in =>5% of cases which could be considered as “typical” symptoms of COVID-19. The list of symptoms we identified is different from those documents released by the WHO, CDC, NHS, Chinese CDC, Institute Pasteur and Mayo Clinic. The compiled list would be useful for future researchers to document a comprehensive picture of the illness.  

    Augmented Curation of Unstructured Clinical Notes from a Massive EHR System Reveals Specific Phenotypic Signature of Impending COVID-19 Diagnosis

    Authors: Tyler Wagner; FNU Shweta; Karthik Murugadoss; Samir Awasthi; AJ Venkatakrishnan; Sairam Bade; Arjun Puranik; Martin Kang; Brian W Pickering; John C O'Horo; Philippe R Bauer; Raymund R Razonable; Paschalis Vergidis; Zelalem Temesgen; Stacey Rizza; Maryam Mahmood; Walter R Wilson; Douglas Challener; Praveen Anand; Matt Liebers; Zainab Doctor; Eli Silvert; Hugo Solomon; Akash Anand; Rakesh Barve; Gregory J Gores; Amy W Williams; William G Morice; John Halamka; Andrew D Badley; Venky Soundararajan

    doi:10.1101/2020.04.19.20067660 Date: 2020-04-23 Source: medRxiv

    Understanding temporal dynamics of COVID-19 patient symptoms could provide fine-grained resolution to guide clinical decision-making. Here, we use deep neural networks over an institution-wide platform for the augmented curation of clinical notes from 77,167 patients subjected to COVID-19 PCR testing. By contrasting Electronic Health Record (EHR)-derived symptoms of COVID-19-positive (COVIDpos; n=2,317) versus COVID-19-negative (COVIDneg; n=74,850) patients for the week preceding the PCR testing date, we identify anosmia HP anosmia MESHD/dysgeusia (27.1-fold), fever HP fever MESHD/ chills HP (2.6-fold), respiratory difficulty (2.2-fold), cough HP (2.2-fold), myalgia HP myalgia MESHD/ arthralgia HP arthralgia MESHD (2-fold), and diarrhea HP diarrhea MESHD (1.4-fold) as significantly amplified in COVIDpos over COVIDneg patients. The combination of cough HP and fever HP fever MESHD/ chills HP has 4.2-fold amplification in COVIDpos patients during the week prior to PCR testing, and along with anosmia HP anosmia MESHD/dysgeusia, constitutes the earliest EHR-derived signature of COVID-19. This study introduces an Augmented Intelligence platform for the real-time synthesis of institutional biomedical knowledge. The platform holds tremendous potential for scaling up curation throughput, thus enabling EHR-powered early disease diagnosis.

    Augmented Curation of Unstructured Clinical Notes from a Massive EHR System Reveals Specific Phenotypic Signature of Impending COVID-19 Diagnosis

    Authors: FNU Shweta; Karthik Murugadoss; Samir Awasthi; AJ Venkatakrishnan; Arjun Puranik; Martin Kang; Brian W. Pickering; John C. O'Horo; Philippe R. Bauer; Raymund R. Razonable; Paschalis Vergidis; Zelalem Temesgen; Stacey Rizza; Maryam Mahmood; Walter R. Wilson; Douglas Challener; Praveen Anand; Matt Liebers; Zainab Doctor; Eli Silvert; Hugo Solomon; Tyler Wagner; Gregory J. Gores; Amy W. Williams; John Halamka; Venky Soundararajan; Andrew D. Badley

    id:2004.09338v2 Date: 2020-04-17 Source: arXiv

    Understanding the temporal dynamics of COVID-19 patient phenotypes is necessary to derive fine-grained resolution of pathophysiology. Here we use state-of-the-art deep neural networks over an institution-wide machine intelligence platform for the augmented curation of 15.8 million clinical notes from 30,494 patients subjected to COVID-19 PCR diagnostic testing. By contrasting the Electronic Health Record (EHR)-derived clinical phenotypes of COVID-19-positive (COVIDpos, n=635) versus COVID-19-negative (COVIDneg, n=29,859) patients over each day of the week preceding the PCR testing date, we identify anosmia HP anosmia MESHD/dysgeusia (37.4-fold), myalgia HP myalgia MESHD/ arthralgia HP arthralgia MESHD (2.6-fold), diarrhea HP diarrhea MESHD (2.2-fold), fever HP fever MESHD/ chills HP (2.1-fold), respiratory difficulty (1.9-fold), and cough HP (1.8-fold) as significantly amplified in COVIDpos over COVIDneg patients. The specific combination of cough HP cough MESHD and diarrhea HP diarrhea MESHD has a 3.2-fold amplification in COVIDpos patients during the week prior to PCR testing, and along with anosmia HP anosmia MESHD/dysgeusia, constitutes the earliest EHR-derived signature of COVID-19 (4-7 days prior to typical PCR testing date). This study introduces an Augmented Intelligence platform for the real-time synthesis of institutional knowledge captured in EHRs. The platform holds tremendous potential for scaling up curation throughput, with minimal need for retraining underlying neural networks, thus promising EHR-powered early diagnosis for a broad spectrum of diseases.

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MeSH Disease
Human Phenotype
Transmission
Seroprevalence


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